Hong Kong Baptist University

DOCTORAL THESIS

Chemical and toxicological characterization of chemical contaminants in airpollution particulate matterBillah, Md Baki

Date of Award:2015

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Chemical and Toxicological Characterization of Chemical

Contaminants in Air Pollution Particulate Matter

BILLAH Md. Baki

Hong Kong Baptist University

August 2015

A thesis submitted in partial fulfillment of the requirements

for the degree of

Doctor of Philosophy

Principal Supervisor: Prof. WONG Chris KC

CHEMICAL AND TOXICOLOGICAL CHARACTERIZATION OF

CHEMICAL CONTAMINANTS IN AIR POLLUTION

PARTICULATE MATTER

BILLAH MD. BAKI

HONG KONG BAPTIST UNIVERSITY

2015

Ph.D. Thesis

i

Declaration

I hereby declare that this thesis represents my own work which has been done

after registration for the degree of Ph.D at Hong Kong Baptist University, and has

not been previously included in a thesis or dissertation submitted to this or any

other institution for a degree, diploma or other qualifications.

Signature:

Date: August 2015

ii

Abstract

In wintertime hazy episodes, the air pollution in northern China has always

reached to an alarming level. In the winter of 2012-13, the trans-boundary air

pollution from China has attracted national and global attention. An elevated

public awareness to the unprecedented pollution levels has prompted much

investigation on the health effects of fine particulate matter (PM), in particular

PM2.5. Since PM-elicited harmful effects primarily depends on the composition of

chemical contaminants adsorbed, in this study we characterized the chemical

compositions of PM2.5 and determined its associated toxicity.

Samples of PM2.5 were collected using high-volume samplers installed in five

northern and southern cities in China. One typical (polycyclic aromatic

hydrocarbons, PAHs) and one emerging (perfluorinated compounds, PFCs) family

of organic pollutants were analyzed using gas chromatography–mass spectrometry

(GC-MS) or liquid chromatography-MS-MS (LC-MS-MS), followed by in-vitro

or/and in vivo studies. In Chapters 2 and 3, sixteen PAH congeners in PM2.5

samples collected from five different cities (Hong Kong (HK), Guangzhou (GZ),

Xiamen (XM), Xi’an (XA) and Beijing (BJ)) in the winter and summer time

2012-13 was analyzed. The biological effects of the sample extracts were

determined using the human bronchial epithelial cells BEAS-2B. The total PAH

concentrations ranged from 3.35 to 80.45 ng/m3 air, leading by BJ, followed by

XA, XM, GZ and HK. In a comparison of the physical and chemical data of the

samples obtained during the winter and summer sampling periods, the amount of

PM collected per unit time and the concentrations of PAHs adsorbed were found

to be remarkably greater in the winter time. In the cell culture study, the

expression levels of the pro-inflammatory cytokine (interleukin-6, IL-6) and

detoxifying enzymes (i.e. cytochrome p450 enzymes, CYP1A1 and CYP1B1)

were found to be stimulated in the treatment. The cells exposed to sample extracts

prepared from XA and BJ demonstrated significant migratory activities, indicating

a sign of increase of tumorigenicity. These data highlighted the risk of getting

lung cancer in local population.

In chapters 4 and 5, we focused on the emerging pollutants PFCs, in particular

PFOS. Chemical characterization was implemented using the winter samples.

iii

Biological effects of PFOS were conducted using omics approach in a maternal-

fetal model. Therefore, in the first part of chapter 4, we measured the

concentrations of nine PFC congeners in PM2.5 samples using LC-MS-MS.

Generally, the eight PFCs, namely PFOS, PFDoA, PFUdA, PFDA, PFNA, PFOA,

PFHxA and PFBA were detected in all the sampling cities, with the exception

PFHxS which was below the limit of detection. The total PFC concentrations

ranged from 121.2 to 192.2pg/m3, leading by GZ, followed by XA, BJ, XM and

HK. The data denoted the risk of inhalation exposure to PFCs through PM2.5,

which enter into blood circulations via lung alveoli, presumably penetrates

through placenta in affecting fetal health. Therefore, in the latter part of chapter

4, the potential adverse effect of prenatal exposure to the prototypical PFC

congener PFOS was used in the maternal-fetal mouse model to determine its

effects on fetal liver and pancreas. Transcriptomic analysis demonstrated that the

in-utero exposure to PFOS affect the expression of genes associated with fatty

acid metabolism, lipid transport, and steroid synthesis in fetal livers. KEGG

pathway analysis showed these changes were primarily associated with

modulations of arachidonic, linoleic acid, retinol metabolism and PPAR signaling

pathways in fetal liver. To identify additional target fetal tissue of PFOS, in

chapter 5, we investigated the effects of PFOS on the protein expression in fetal

pancreas using the technique of “Isobaric tags for relative and absolute

quantitation” (iTRAQ). We identified changes in the protein expressions involved

in pancreatic secretion, protein digestion and absorption, protein processing in

endoplasmic reticulum, fat digestion and absorption, glycerolipid metabolism and

steroid biosynthesis. The perturbations to these targets may increase the risk of

pancreatitis in mouse offspring. Collectively, this study provided a

comprehensive chemical and biological analysis of PM2.5 collected in China and

demonstrated the toxicities, in vitro and in vivo of the adsorbed chemical

contaminants.

iv

Acknowledgement

I have the honor and privilege to thank all the benevolent people that made my

Hong Kong adventure a pleasant one! First of all, I would like to express my

sincere gratitude to my supervisor Prof. Chris KC Wong for his support, effort and

friendship all these years during my post graduate studies in the department of

Biology, Hong Kong Baptist University. I highly acknowledge his support since

the very beginning and during the development and conclusion of this thesis and

for his trust in me, even when I had no idea about the subject particulate matter

toxicity. I am also grateful to my co-supervisor Prof. N. K. MAK for his sincere

moral support.

I speak volume about the superior nature of Dr. Ball KP Lai, Research Assistant

Professor, School of Biological Sciences, The University of Hong Kong, for his

illuminating ideas and scholarly discussion about transcriptomic and proteomic

research, when I was the scared Bangladeshi student trying to pursue my studies

here in Hong Kong Baptist University. Thank you very much Dr. Lai you made it

happens!

Thanks to Dr. WKF Tse for his valuable suggestions, kind help and for

proportionating me shining days every morning with his beautiful smile (even if

feeding Zebrafish).

I would also like to thank my dear classroom teachers, scientific officers,

colleagues, lab-mates and friends and administrative stuff, to name just a few, Dr.

H.T. Wan, Dr. Zhao, Dr. Gu Jie, Dr. Alice Law, Dr. Bonnie, Dr. W.Y. Mo, Becky,

Aman, and Mr. Lo Kam Fai for encouraging, helping, sample analysis and

introducing me to the field of molecular biology with a lot of patience and smiles

and laughs throughout all these years.

I highly acknowledge the Government of Hong Kong for the financial support to

pursue my postgraduate studies under the Hong Kong Ph.D Fellowship Scheme

(HKPFS) and would also like to thank the Department of Biology and Croucher

Institute for Environmental Science for giving me the congenial working

environment and instrumental support.

From the bottom of my heart I would like to thank my family especially my wife

and my son (Yearid) for their endless love, friendship and constructive support

and for being always with me, even if far away.

v

Table of contents

Declaration i

Abstracts ii

Table of contents v

Lists of Figures Viii

CHAPTER 1

LITERATURE REVIEW

1

1. Air pollution 1

1.1 Natural and anthropogenic sources of air pollution 4

1.2 Heath effects associated with air pollution 5

1.3 Global concern of air pollution 10

1.4 Contaminants present in PM 17

1.5 Mechanism of PM toxicity 27

1.6 Research questions and Hypothesis 31

1.7 Objectives of the present study 32

CHAPTER 2

CHEMICAL AND BIOLOGICAL CHARACTERIZATION OF

WINTER TIME FINE PARTICULATE MATTER (PM2.5)

COLLECTED IN FIVE CITIES IN CHINA

33

2.1 Introduction 33

2.2 Materials and Methods 35

2.3 Results and Discussion 43

2.4 Conclusions 55

CHAPTER 3

CHEMICAL AND BIOLOGICAL CHARACTERIZATION OF FINE

PARTICULATE MATTER (PM2.5) COLLECTED IN CHINA IN

SUMMER

56

vi

3.1 Introduction 56

3.2 Materials and Methods 57

3.3 Results and Discussion 58

3.4 A comparison of winter and summer sample data 69

3.5 Conclusions 70

CHAPTER 4

DETERMINATION OF THE CONCENTRATION OF

PERFLUORINATED COMPOUNDS (PFCs) IN FINE

PARTICULATE MATTER (PM2.5) IN CHINA AND THEIR

EFFECTS ON FETAL LIVERS

71

4.1 Introduction 71

4.2 Materials and Methods 72

4.3 Results and Discussion 80

4.4 Conclusions 99

CHAPTER 5

PRENATAL EXPOSURE TO PFOS INDUCED THE RISK OF

PANCREATITIS IN OFFSPRING

100

5.1 Introduction 100

5.2 Materials and Methods 101

5.3 Results and Discussion 105

5.4 Conclusions 133

References 134

Curriculum Vitae 176

vii

Lists of Tables

Table 2.1 List of human primers used in this study 42

Table 2.2 Levels of PAHs and TEQ (ppt) measured in the air samples

from the five cities in China.

44

Table 2.3 Diagnostic ratios of PM-bounded PAHs in different cities of

China.

50

Table 3.1 PM2.5 samples from the four cities in China. 61

Table 3.2 Diagnostic ratios of PM-bounded PAHs in different cities of

China.

64

Table 3.3 Comparison of winter and summer season filters weights and

total PAHs in PM2.5

68

Table 4.1 List of mouse primers used in this study 79

Table 4.2 Total concentrations (pg/m3) of PFCs and the average

concentrations of inhalation exposure (ng/day).

82

Table 4.3 Summary of the sequencing results 90

Table 4.4 Lists of up regulated genes with their gene names and

biological functions

94

Table 5.1 Lists of differentially expressed up regulated proteins in

medium treatment dose

Table 5.2. Lists of differentially expressed down regulated proteins in

medium treatment dose

Table 5.3. Lists of differentially expressed up regulated proteins in high

dose treatment

Table 5.4. Lists of differentially expressed down regulated proteins in

high treatment dose

Table 5.5 Up regulated proteins annotated with name, Uni-port identity

and biological functions.

107

112

115

120

126

viii

Lists of Figures

Fig 1.1. PM2.5 is about 4 and 30 times smaller than PM10 and the width of a

human hair strand respectively which indicates that the smaller the size the

greater the health risks.

3

Fig 1.2. Natural and anthropogenic sources of air pollution and formation

of primary and secondary pollutants in the atmosphere.

3

Fig 1.3. (A) National emission inventory in USA in 1999 found the PM2.5,

PM10 and other gaseous pollutants comes from road dust, wind-blown dust,

and other fugitive source (The figure was prepared by Scheffe et.al., 2003;

Hiddy and Pace 2004; USEPA, 1998; Davidson et.al., 2005). (B) The

inventory for 2001 showed that in the United States the largest source of

PM2.5 was the coal burning for electricity production. (Miller, 2003;

Davidson et. al., 2005). All values were given in Ktons (thousand English

tons).

11

Fig 1.4. The basic structure of a human lung showing the trachea,

secondary bronchus, bronchiole and alveoli in which PM2.5 can be retained

in the alveoli of the lung due to their smaller sizes. Modified from National

Center for Environmental Assessment (Research Triangle Park N. C),

2003.

16

Fig 1.5. The industrial emission of PFOS in the environment in China from

direct and indirect sources (Modified from Ministry of Environmental

Protection of China, 2008).

16

Fig 1.6. Structure of some PAHs and PFCs and PFOS emission trend in

China. (A) Represents some of the high molecular weight (HMW) PAHs

that captured more efficiently on PM (Kanaly and Harayama, 2000). (B)

The C-F structure of mostly studied PFOS and PFOA. (C) The increased

PFOS emission scenario in China from 2001-2011(The figure was adopted

from Xie et. al., 2013).

23

Fig 2.1. Experimental set up of present study. (A) Location of five 37

ix

sampling cities on a China map. (B) The workflow of handling and

processing the air filters. One fourth of the air filter collected underwent

soxhlet extraction and the organic extract was dissolved in n-hexane. Half

of the dissolved extracts performed chemical analysis by GC-MS while the

other half underwent nitrogen dry and reconstituted in 1mL DMSO for

biological analysis using cell line.

Fig 2.2. Weights of PM2.5 dust in air filters and the mean concentrations of

total PAHs in each sampling site.

43

Fig 2.3. Concentrations and distributions of PAH congeners in each

sampling site.

46

Fig 2.4. Calculated excess lifetime cancer risks (per million exposed

individuals) of the five sampling sites.

49

Fig 2.5. Graphic illustration of the diagnostic ratios on the sources of PAHs

emission.

51

Fig 2.6. Gene expression levels of pro-inflammatory cytokines and

xenobiotic metabolic enzymes upon extracts treatment for 24h in BEAS-2B

cells. (A) mRNA levels of interleukin-6 (IL-6) was significantly up-

regulated in all five sampling sites as compared to the blank filter control

(p<0.01). (B) Gene expression levels of cytochrome p450 enzymes were

significantly up-regulated by the extracts exposure of all sampling sites

(p<0.01).

53

Fig 2.7. Exposure to PM extracts increased the migration of BEAS-2B

cells in cell migration assay. (A) The proliferation assay demonstrated the

increase in proliferation in the cells treating with GZ, XM, XA and BJ

extracts in MTT assay (p<0.05). (B) Micrographs showing the

representative pictures of cell migration assay (200x). The percentage of

migration of cells treated with XA and BJ were significantly higher than

that of other cities and the blank filter (p<0.05).

54

Fig 3.1. Locations of four sampling cities on a China map 59

Fig 3.2. The weights of PM2.5 in the air filters and the mean concentrations

of total PAHs in each sampling site.

60

x

Fig 3.3. The concentrations and distributions of PAH congeners in each

sampling site.

62

Fig 3.4. Calculated excess lifetime cancer risks (per million exposed

individuals) of the five sampling sites.

65

Fig 3.5. Cytotoxicity and gene expression levels of pro-inflammatory

cytokines and xenobiotic metabolic enzymes upon summer extracts

treatment for 24h in BEAS-2B cells. (A) The MTT assay showed no

cytotoxicity was found with the summer PM2.5 sample extracts upon

exposure to BEAS-2B cells. (B) Gene expression levels of cytochrome

p450 enzymes (CYP1A1 and CYP1B1) were significantly up-regulated by

the summer extracts exposure of all the sampling sites (*p<0.05). (C)

Relative mRNA expression levels of interleukin-6 (IL-6) was significantly

up-regulated in BJ and XA sampling sites as compared to the blank filter

control (*p<0.05).

67

Fig 4.1. A flow diagram illustrates the experimental procedure for RNA

sequencing, including PFOS exposure, sample collection, library

construction, transcriptome sequencing, global gene expression analysis

and pathway analysis.

75

Fig 4.2. A schematic flowchart shows the working principal of using

Illumina MiSeq platform.

77

Fig 4.3. The weights of PM2.5 dust in air filters and the mean

concentrations of total PFCs in each sampling site.

81

Fig 4.4. The concentrations of PFC congers in different cities. (A) PFOS

and PFBA were the most abundantly PFCs detected in HK samples while

PFHxS, PFDoA, PFUdA, and PFDA were found below the LOD. (B) In

GZ, PFBA and PFOS were found to be the major PFC congeners. (C) In

XM, PFBA exhibited the highest concentration followed by PFOS,

PFHxA, PFOA, and PFNA. (D) In BJ, PFOS was most abundantly found

while other PFCs were detected at relatively low concentrations. (E) In

XA, PFOS, PFHxA, and PFBA were the most abundantly found PFCs.

Error bars represents standard deviation.

84

xi

Fig 4.5. A comparison of the average concentrations and human inhalation

exposure of PFCs. (A) PFOS, PFOA, PFBA and PFHxA were abundantly

found in PM2.5 samples. (B) The inhalation exposure data from different

cities.

86

Fig 4.6. Enrichment analysis of GO Molecular Functions. Top 20 pathways 91

Fig 4.7. Enrichment analysis of GO Biological Process. Top 20 pathways 92

Fig 4.8. (A) Enrichment analysis of KEGG pathways. (B) The schematic

diagram showing the genes altered by prenatal PFOS exposure are related

to fatty acid metabolism.

95

Fig 4.9. (A) Validation of some selected RNAseq-identified genes using

mouse fetal liver samples collected at E=17. (B) Significant ROS

formation was found in AML-12 cultured with PFOS. H2O2 was used as a

positive control. Asterisks (*) indicates the statistical significant (p< 0.05)

difference between the control and treatment groups.

98

Fig 5.1. General work flow and summary of the present study. The study

applied proteomic approaches to identify the differentially expressed

proteins in the mouse pancreas in response to exposure with different

prenatal doses of PFOS (Modified from the model proposed by Tse et. al.,

(2013).

104

Fig 5.2. The diagram showing the number of up and down regulated as

well as overlapped protein expression in mouse pancreas in response to

medium and high doses of PFOS.

106

Fig 5.3. Pie diagram showing the enrichment analysis of gene ontology of

PFOS responsive proteins in mice. (A) Proteolysis (3/10) is the dominant

category in the biological process. (B) Hydrolase activity (4/10) is the

dominant molecular function in GO assignment.

109

Fig 5.4. Enrichment analysis of KEGG pathways showing pancreatic

secretion (4/10) is the dominant pathway followed by protein digestion and

absorption (3/10), protein processing in endoplasmic reticulum (1/10) fat

digestion and absorption (1/10), glycerolipid metabolism (1/10) and steroid

biosynthesis (1/10).

110

xii

Lists of Abbreviations

PM Particulate Matter

PM2.5 Particulate Matter 2.5

PM10 Particulate Matter10

SPM Suspended Particulate Matter

VOC Volatile Organic Compound

ROFA Residual Oil Fly Ash

RR Relative Risk

CI Confidence Interval

EPA Environmental Protection Agency

AQG Air Quality Guidelines

GC-MS Gas Chromatography Mass Spectrometry

LC-MS/MS Liquid Chromatography Mass Spectrometry

iTRAQ Isobaric Tag for Relative and Absolute Quantification

NGS Next Generation Sequencing

LOD Limit of Detection

ANOVA Analysis of Variance

TEF Toxic Equivalent Factors

IL-6 interleukin-6

TNF Tumor Necrosis Factor-alpha

CYP1A1 Cytochrome 4501A1

CYP1B1 Cytochrome 4501B1

PFCs Perfluorinated Compounds

PFOS Perfluorooctane Sulfonate

PFOA Perfluorooctanoic Acid

GD Gestational Day

KEGG Kyoto Encyclopedia for Gene and Genome

ROS Reactive Oxygen Species

GO Gene Ontology

FDR False Discovery Rate

PPAR-α Peroxisome Proliferator Activated Receptor- α

xiii

1

CHAPTER 1

REVIEW OF LITERATURE

1. Air pollution

Air pollution is one of the main concerns in the world today. The whole world is

reverberated with resounding slogans stop pollution, stop pollution. The presence

of chemicals in the atmosphere at concentrations that interfere with or causes

harm to biota is generally regarded as air pollution. Severe air pollution episode

took place globally which elevated more public concern than before. For example,

industrial air pollution episodes took place in the Meuse Valley (Belgium, 1930;

Firket, 1931; Nemery et.al., 2001), Donora Valley, Pennsylvania, United States

(Schrenk et. al., 1949) and in the urban London (December 1952). In Belgium

and Pennsylvania, the extreme air pollution episodes took place due to coal

burning and industrial furnaces. In the London Fog, concentrations of particulate

matters (PM) were in excess of 1000μg/ml and were found to be strongly

associated with increased mortality and cardiovascular conditions among the

elderly (Greenbaum 2003; Krewski et al. 2003). The London incidence happened

due to a temperature inversion, a situation in which cold weather trapped the

pollutants at lower ground level (Krewski et al. 2003). Thus, people were exposed

to relatively high concentrations of PM that caused 4000 people death. PM is

generally a complex mixture of extremely small particles, metals, organic

chemicals, and biological materials (Alfaro-Moreno et al., 2007; Baulig et al.,

2009; Billet et al., 2008; Gualtieri et al., 2010; Osornio-Vargas et al., 2011).

Among the particulate matters, PM2.5 and PM10 pertains for aerodynamic diameter

smaller than 2.5μm and 10μm respectively. PM can also be categorized as coarse,

fine and ultrafine particles with sizes larger than 1, smaller than 1 and smaller than

0.1μm in aerodynamic diameter respectively. But according to US standard the

fine particles having aerodynamic diameter < 2.5μm is referred to as fine PM

(Donaldson et. al., 2001). The comparison of the sizes of fine and coarse particles

is shown in Figure 1.1 .

2

A severe air pollution episode was also experienced by the Los Angeles basin

which emitted a lot of fumes from vehicles leading to severe degradation of the air

quality (Elsom, 1987). It is well-recognized that air pollution is associated with a

wide range of acute and chronic health effects. The nature of health effects

depends on the constituents of pollutants. It was reported that ambient air

pollution could cause cardiopulmonary disease, cancers (trachea, bronchus and

lung) and acute respiratory infections in children worldwide, leading to an

increase of mortality by 1-5%. This health burden occurs predominantly in

developing countries of which 65% is in Asia (Cohen, et. al., 2005). A study in

Mexico City showed that air quality in association with health issues are of grave

concern in megacities (Molina & Molina, 2004). Health problems in megacities

are social problems but its regional and global environmental consequences are

also of great concern.

Air pollution is enormously increasing in megacities (for example Beijing,

Shanghai and Guangzhou) in China (Wang et. al., 2010). China has surpassed

United States in term of total CO2 emission since 2007, although emissions per

head are still at the global average (International Energy Agency, 2009). China‟s

rapid industrial and economic development has brought severe environmental

degradation. Economic expansion is largely driven by the use of fossil fuels which

dramatically increase the ambient air pollution. Realizing the severity of air

pollution, the Chinese government has implemented various environmental

friendly measures to improve the air quality. In recent years, China has been

promoting the use of renewable-energy in the markets and set a target of adding at

least 15% renewable energy in the national energy budget by 2020 (Natural

Resources Defense Council, 2007). China government has also introduced special

loans to upgrade equipment in different industries (Economy, 2007) to reduce

levels of emitted pollution. Nevertheless, air pollution is still a big problem in

China. Thus, in this review, we highlighted some potential natural and

anthropogenic sources of air pollution that greatly influenced the air quality in

China.

3

Fig 1.2. Natural and anthropogenic sources of air pollution and formation of primary and

secondary pollutants in the atmosphere.

Fig 1.1. PM2.5 is about 4 and 30 times smaller than PM10 and the width of a human hair

strand respectively which indicates that the smaller the size the greater the health risks.

4

1.1 Natural and anthropogenic sources of air pollution

Both man-made (anthropogenic) and natural (non-anthropogenic) sources attribute

to an increasing severity of air pollution. An anthropogenic source includes

combustion, traffic emission, coal, lignite, heavy oil and biomass combustion for

energy generation (Kampa and Castanas, 2008) while natural sources are mainly

originated from forest and grassland fires which release secondary sulfates

particles to the atmosphere (Davidson et. al., 2005; Yan et al., 2006).

A large variety of pollutants emitted from the natural and anthropogenic sources

can be divided into primary and secondary pollutants. The primary pollutant

includes those pollutants that coming directly from the natural and anthropogenic

sources (NO, CO) while the secondary pollutant includes those pollutants that are

produced by subsequent reactions undertaken in the environment to produce

secondary compounds (for example H2O2, O3). The primary and secondary

sources of pollutants are shown in Figure 1.2.

(A) Coal combustion

The high energy consumption, the reliance on coal burning, and the rapid increase

of vehicle number, made air pollution the major environmental issue in China

(Millman et. al., 2008; He et.al, 2002). In China, 70-75% of energy supply comes

from coal combustion which is much greater than in Japan (14%), USA (22%)

and India (53%) (Economy, 2003; Zhang et. al., 2002). Nearly half of the coal

biomass is used for heating and cooking purposes. Coal burning in China is

characterized by low thermal efficiency, poor dust collection systems, absence of

sulfur purification method and low smoke stakes. Under unfavorable

meteorological conditions, heavy atmospheric air pollution often occurs in urban

and/or suburban areas. Thus, coal-burning produces a lot of pollutants, among

them suspended particulate matter (SPM), sulfur oxides (SO2) are the main

problems (Zhao and Sun, 1986). It was also reported that iron and steel companies

contributed to 55% of total airborne particulate in Beijing (Zhifang et. al., 1998).

In China, the PM exceeded the concentrations of other major pollutant such as

SO2 and NOx. For example, in 2005, PM concentrations in more than 300 major

5

cities in China were 99μg/m3, while those of SO2 and NOx were only 57 and 35

μg/m3, respectively (State Environmental Protection Administration of China,

2007). A report in the same year, showed that coal power plant emitted a

significant amount of PM which was 3.81 million tonnes per year representing

44.6% of total PM emission (National Bureau of Statistics of China, 2006). In a

study, an average PM10 levels in cities in the United States and Europe ranged

from 20 to 70μg/m3 while Asian cities showed PM10 concentrations of 35–

220μg/m3

(WHO, 2006), of particular interest, Chinese cities belongs to the most

air polluted cities in the world (WHO and UNDP, 2001).

(B) Traffic emission

In 2003, the motor vehicles numbers in China were 59.29 million which expected

to increase up to 192 million by 2020 (World Bank, 1997; Deng, 2006). A study

on the vehicular emissions in China from 1980–2005 showed that the emissions of

CH4, CO, CO2, VOC, NOx, PM10, and SO2 were 5, 1066, 19 893, 169, 174, 26,

and 16 thousand-tons in 1980, whereas in 2005, the figures were increased to 377,

36 197, 674 629, 5911, 4539, 983, and 484 thousand-tons. Respectively the

calculated annual increasing rates were 19%, 15%, 15%, 15%, 14%, 16%, and

15% (Cai & Xie, 2007). Since 1990, motorcycles contributed largely to the

emission of CH4, CO, VOC, and PM10 while heavy-duty vans and passenger cars

contributed largely to the emission of NOx and SO2 (Cai & Xie, 2007).

A study on the children health in China suggested that air pollution is associated

with more than 300000 deaths, 20 million cause of respiratory illness which costs

about 500 billion renminbi and accounts for >3% gross domestic product annually

(Millman et. al., 2008). If the increased rate of vehicular emission and fossil fuel

combustion continues at the present trends, a substantial damage to children‟s

health and future economic development would be anticipated (World Bank,

2007).

1.2 Health effects associated with air pollution

The epidemiological data from studies on both short- and long-term exposures

showed positive correlations among air pollution, mortality and hospital

admission rate (Brunekreef and Holgate, 2002). The health effects can range from

breathing problem, skin irritation to cancer. It may also cause defects in birth,

6

delays in developmental and immune system dysfunction (Kampa and Castanas,

2008). The effects of air pollution on human health depend on many factors such

composition of chemical contaminants, doses and exposure time. Some of the

acute and chronic health effects are discussed below.

(A) Pulmonary diseases

In China, the prevalence of asthma among urban children was increased by 64%

during the 1990s (Watts, 2006). In some bigger cities where the air quality was

worsening, this figure was more than doubled. Investigations in China conducted

by US academic institutions and the US Environmental Protection found that the

risk of respiratory morbidity (such as cough with phlegm, wheeze, asthma, and

bronchitis) was higher in children with high exposure levels to both indoor and

outdoor air pollution derived from coal burning (Qian et.al., 2004a,b; Miller et.al.,

2004). In laboratory studies, the exposure to concentrated ambient particles using

a rat model, showed minute effects on pulmonary functions (Godleski et al., 2000;

Clarke et al., 1999; Gordon et al., 2000). But the exposure effects of residual oil

fly ash (ROFA) on rats via inhalation found direct effects on pulmonary

membranes (Kodavanti, et.al. 1996 and 1997a). A thickening of alveolar and

airway walls was noted that implied the progression of lung fibrosis.

(B) Lung cancer

In 2005, 58 million cancer deaths were reported worldwide in which 1.3 million

were due to lung cancer (World Health Organization, 2002). The relationship

among long-term exposure to ambient PM and lung cancer was first addressed by

three cohort studies in the United States (Pope III, 2002). The first longitudinal

study recruited 6,338 non-smoker adults and followed their health conditions for

15 years. The investigators reported that the long term exposure to PM10 increased

the relative risk (RR) of lung cancer mortality among men. The study showed the

RR value as 3.36 which were associated with an annual average increase of PM

24μg/m3 (average increase of PM per 10μg/m

3 causes the risk of lung cancer).

7

The second study was conducted from 1974–1989 on 8,111 residents in six US

cities. In their study they found PM10 at the concentrations of 24.2, 32.5,31.4,

46.5, 18.2 and 26.4μg/m3 from Watertown, Massachusetts (where study

enrollment was conducted in 1974); Harriman, Tennessee, including Kingston

(1975); specific census tracts of St. Louis (1975); Steubenville, Ohio (1976);

Portage, Wisconsin, including Wyocena and Pardeeville (1976); and Topeka,

Kansas (1977) cities respectively. Among the most and the least polluted cities,

the differences in the average PM10 concentrations were about 28μg/m3. They

found RR value as 1.37, which was estimated as a 19% increase of cancer risk per

10μg/m3 (Dockery et.al., 1993).

The third and largest US investigation was published by Pope et. al., (2002).

This study was conducted for a period of 17 years based on the mortality of

approximately 500,000 adult men and women. Concentrations of PM2.5 were

collected from different data sources for each 50 states in the District of

Columbia. Personal information and other confounders or risk factors were

collected with questionnaires (age, race, marital status, smoking, body mass,

occupational exposures, diet, etc.). They found the RR as 1.14 which was around

14% increase of cancer risk per 10μg/m3. These three studies are remarkable

because they avoided the geographical limitations and considered the various

confounders or risk factors, especially smoking habits (Vineis et. al., 2004;

Katsouyanni and Pershagen, 1997).

In all the three aforementioned studies, the estimated RR value indicated that

PM is associated with the lung cancer risk in the United States. In contrast, the

European cities are more polluted than the United States in term of PM emission.

So, it should be possible that more cancer risk in European is associated with PM

exposure. Therefore, another study regarding the association between lung cancer

and long term exposure to PM10 in Europe was conducted in 1993, covering nine

countries (France, Italy, Spain, UK, The Netherlands, Greece, Germany, Sweden

and Denmark) involving over half a million of volunteers. A total of 271 lung

cancer cases and 737 controls were included in these studies which were taken

from cancer registries. PM10 exposure data for cancer cases and controls were 113

and 312 respectively. They found the RR as 0.91 for an increase in PM10 of

8

10μg/m3

and 0.98 (95% CI: 0.66–1.45) for exposures over 27μg/m3 (Vineis et. al.,

2006). This study also found the risk of lung cancer associated with PM10.

Recently, satellite measurement of haze data in the Chinese city of Guangzhou

showed the association of the air pollution events from 1954 to 2006 with the

increased risk of lung cancer (Tie et. al., 2009).

(C) Mortality and cardio-vascular diseases

Epidemiological evidences suggested that lung cancer, respiratory diseases and

arteriosclerosis are associated with long term exposure to PM while short term

exposure causes respiratory diseases, including bronchitis and asthma (Chiaverini,

2002; Sorensen et. al., 2003). Miller et. al., 2007) carried out investigation

regarding long term exposure of PM on cardiovascular events. This study found

the variations of PM2.5 levels in atmosphere ranged from 3.4 to 28.3μg/m3 (mean,

13.5). Each increase of 10μg/m3 was associated with 76% increase in the risk of

death from cardiovascular disease (hazard ratio, 1.76; 95% CI, 1.25 to 2.47) and

24% increase in the risk of a cardiovascular event (hazard ratio, 1.24; 95%

confidence interval [CI], 1.09 to 1.41). Kodavanti et. al., (1999) carried out

residual oil fly ash (ROFA) effects on monocrotaline treated rat (suitable model

for cardiorespiratory disease) and found the severe effects on the cardiac function.

In 2000, another study related daily mortality and air pollution was carried out

using samples from European cities (for example, London, Paris, Barcelona,

Helsinki, Athens, Lyon) (Touloumi et. al., 1997). The daily deaths and

NO2 and/or O3 levels were investigated. This study found that the daily number of

deaths increased by 1.3% and 2.9% with an average increase of 50μg/m3 in

NO2 (1-hour maximum) or O3 (1-hour maximum) concentrations respectively.

The results of this study suggested that short term effects of air pollutants may

causes mortality.

(D) Neurodevelopmental effects

The combustion of high amount of coal caused enormous amount of mercury

emission in China (Zhang et. al., 2002). Elemental mercury can be transported to a

long distance (Morel et.al., 1998). In aquatic ecosystem, in addition to elemental

9

mercury, ionic and organic mercury especially methyl mercury are also present

which become bio-concentrated in fish tissues (Morel et.al., 1998). Prenatal

mercury exposure from maternal consumption of fish is associated with

developmental deficits in children in the United States and elsewhere (Cohen et.

al., 2005; Trasande et. al., 2005). Besides mercury exposure, a study with children

in New York City showed that the children who had high prenatal exposure to

airborne PAHs had suffered from neurodevelopmental delay (Mead and Brajer,

2006).

(E) Susceptibility of the young

Among the population, the very young groups are of particular risk because their

biological systems are developing and growing. For example, the lung of a child

continues to develop until sixth to eighth years of life (Perera et. al., 2006;

Grandjean and Landrigan, 2006 and Plopper and Fanucci, 2000). Experimental

and human evidences reported that the fetus and neonates are the most likely

affected and sensitive to a wide range of chemicals such as, air pollution, tobacco

smoke, PAHs, nitrosamines, pesticides, and radiation (Mead and Brajer 2006;

Dahl, 2005; Shen et.al., 2010; Luo et.al., 2003; Anderson et.al., 2000; National

Research Council, 1993; Whyatt et. al., 2001). More recent epidemiological

studies have shown that infants are mostly affected by the air pollution related

chronic respiratory effects and mortality (Ha et. al., 2003; Hertz-Picciotto et. al.,

2007).

(F) Adverse birth outcomes

Published studies reported that reduced fetal growth is associated with

combustion-related air pollution (Millman et. al., 2008). A study in New York

City found that during pregnancy, exposure to air borne PAHs could lead to

decreased birth weight and reduced head circumference among black infants

(Perera et. al., 2003). Another study from Poland reported that prenatal PAHs

exposure caused reduction in fetal growth (Choi et. al., 2006). A recent study in

China found that the elevated PAH-DNA adducts in cord-blood associated with a

decrease of head circumference in newborns (Tang et. al., 2006).

10

1.3 Global concern of air pollution particulate matter (PM)

1.3.1 Large scale global emission of PM

Globally the PM increases from 1970s to 1980s in rapid growing cities with huge

population for example, China, Chicago, Mexico City, Lagos, Cairo, Tokyo, and

Athens (Asby and Anderson 1982). The 1999 national emission inventory for the

United States (Hidy and Pace 2004) showed the emission among the six major

categories, of them 70% of the PM2.5 emissions came from road dust, wind-blown

dust, and other fugitive sources (Fig. 1.3A).The inventory for 2001 that focused

on primary anthropogenic sources of PM2.5 shown in Figure 1.3B (U.S. EPA,

2004d). This inventory report showed that in the United States the largest source

of PM2.5 is the coal burning for electricity production. In addition, other sources

such as fuel combustion and metals processing altogether contributed in the

emission of total PM2.5 at the amount of 2550 Ktons/year (Davidson et. al., 2005).

In contrast, in China, the PM10 and PM2.5 emissions in 2005 were 1842 and 994 kt,

and 824 and 1090 kt in 2010 respectively (Zhao et.al., 2008). Adverse effects of

different pollutants in PM on human health have been well documented in Europe

and other parts of the world. Realizing the situation, the United States

Environmental Protection Agency (EPA) instituted the PM2.5 24 h standard as

65μg/m3 and an annual average standard of 15μg/m

3 (Greenbaum 2003). Until

2012, there were no regulatory standard for PM2.5 in China. Recently, the Chinese

government issued a national PM2.5 standard on February 29, 2012, that requires

cities to have concentrations below 35μg/m3

annual average and <75μg/m3 for

24h, beginning in 2016 (Cao et. al., 2012). These standards were adopted owing to

recognized adverse effects of PM2.5, chemical components on human health,

visibility, and materials (Hu et al., 2009; Mauderly and Chow, 2008; Pope and

Dockery, 2006).

11

A

B

Fig 1.3. (A) National emission inventory in USA in 1999 found the PM2.5, PM10 and other

gaseous pollutants comes from road dust, wind-blown dust, and other fugitive source (The

figure was prepared by Scheffe et.al., 2003; Hiddy and Pace 2004; USEPA, 1998;

Davidson et.al., 2005). (B) The inventory for 2001 showed that in the United States the

largest source of PM2.5 was the coal burning for electricity production. (Miller, 2003;

Davidson et. al., 2005). All values was given in Ktons (thousand English tons).

12

A study on PM10 in more than 300 major cities in China from 2002 to 2006

showed that PM10 concentrations increased from 36.8% to 62.8%. (State

Environmental Protection Administration of China, 2007). In contrast, for the

regulation of PM emission, European Union defined a limit value of 40μg/m3 of

PM10. Among 25 countries, the PM10 annual means in Bulgaria, Czech and Poland

(East) were 64.3, 69.8 and 71.8μg/m3 respectively; in Greece, Italy, and Spain

(South) were 68.8, 59.3, 103.3μg/m3, respectively; in Denmark, Norway, and

Sweden (North) were 34.2, 23.1 and 51.1μg/m3, respectively; Belgium, France,

Germany and UK (Western) were 36.8, 43.6, 45.5 and 33.4μg/m3 respectively

(CAFE Working Group on Particulate Matter, 2004). From this data, it was

evident that 60% Chinese major cities reached the increased PM emission level of

the east and south Europe countries.

In China, another study related to PM2.5 was carried out in some cities

(Guangzhou, Wuhan, Lanzhou, Chongqing, Shanghai and Beijing) at different

times from 1995 to 2007 (Duan et al., 2006; Kan et al., 2007; Zhang et al., 2002).

A study reported that in the 2000s, the annual average concentrations of PM2.5

were in the range of 56 to 122μg/m3. In 2001- 204, Beijing exhibited a dramatic

increase in PM2.5 concentration levels to the range of 96.5 to 106.7 μg/m3 (Duan et

al., 2006), which was seven times greater than the ambient air quality standard

prescribed by the US Environmental Protection Agency (15 μg/m3) and ten times

higher than the WHO Global Air Quality Guidelines (AQG) (10μg/m3). In 2005,

the concentration of PM2.5 level in Shanghai was much higher (56μg/m3) (Kan et

al., 2007), as compared with the Global Air Quality Guidelines set by World

Health Organization (10μg/m3 for annual mean) and U.S. National Ambient Air

Quality Standards (15μg/m3 for annual mean). In 2013, the PM2.5 concentration in

Beijing was recorded 950μg/m3 which was by far the highest value ever reported

in this year. In year 2015, the air pollution reading in Beijing showed the higher

levels with 671μg/m3 PM2.5, reaching 26 times the threshold level recommended

by World Health Organization (WHO) and visibility reduced to 500 meters (South

China Morning Post, 2015).

13

1.3.2 Relation of PM with climate change, energy use and human welfare

Anthropogenic CO2, CH4 and PM contribute to global warming. Other warming

gases include tropospheric O3, halocarbons, and N2O and warming particle

component includes iron, aluminum, ammonium, polycyclic aromatics, and

nitrated aromatics (Jacobson, 2001). PM exerts both direct and indirect effects on

climate change. The direct effects incudes scattering and absorption of sun‟s

energy. In some cases, the PM may reflect solar radiation back to space which

causes the cooling of the earth. In most other cases, the PM absorbs the solar

radiation results in warming effects. For example, ammonium sulfate have high

reflectance which take part in cooling, while elemental carbon absorb radiation

contributing to global warming. It was reported that elemental carbon may be the

second most important anthropogenic atmospheric constituent responsible for

global warming next to CO2 (Hansen and Sato, 2001; Jacobson, 2000).

Most particulate emissions are black carbon and organic matter (Shauer, et al.,

1999). Black carbon is a component of PM2.5 which warms the earth by absorbing

heat in the atmosphere and by reducing albedo, the ability to reflect sunlight.

According to Jacobson (2002) the reduction of black carbon could slow global

warming more than the strategy to reduce CO2 or CH4. This study also showed

that if all the black carbon and anthropogenic CO2 and CH4 emissions are

eliminated together, within 25-100 years it could be possible to slow down global

warming. They measured the historic net global warming by subtracting the

cooling from warming caused by greenhouse gas and black carbon. This study

also showed that elimination of 20–45% of net warming could be possible from

eliminating all black carbon within 3–5 years, if no further changes occur in the

environment.

Adams et.al, (2003) found that regions with high PM air pollution formed

clouds with tiny droplets that resulted in the formation of brighter clouds. These

clouds could reflect back the solar radiation in space. For example, ammonium

sulfates are efficient cloud condensation nuclei that reflect back the solar energy

into space. Thus, helps the cooling process of the earth. Some other research

postulated that high elemental carbon concentration in Asian countries affected

the local hydrological cycle due to absorption of sun‟s energy (INDOEX, 2003).

14

All these evidences suggested that local as well as global climate change was

linked to PM. Malm et. al., (2003) found that reduced visibility can have a

negative impact on psychological well-being of people. PM may bring PM

scatters light thus reduce the light intensity between distant object and background

sky resulting visibility reduction. Normally people can see objects at a distance of

200km in a clean dry air but PM air pollution may restrict the visibility to less

than a kilometer. In this study, it was also reported that ammonium sulfate,

ammonium nitrate, organic compounds, soil and coarse dust particles may reduce

the visibility.

Recently, the U.S has introduced a complex regulatory standard for reducing the

emission of SOx, NOx and Hg from power plants that used for energy production.

In order to achieve the goal, PM should be reduced below the national ambient air

quality standard. But residual PM may contain a greater fraction of carbons that

will be a big challenge for the prescribed standard to reduce SOx, NOx and Hg,

because this standard does not address the elemental carbon issue (Davidson et.

al., 2005). EPA also recognized the importance of controlling all the major

components in PM2.5. However, formulation of new national rule for the major

anthropogenic carbonaceous sources is a challenge ahead (Bachmann, 2003).

Thus, this study suggested that PM is associated with increasing energy

consumption and economic growth. Therefore, PM should undertake to address a

number of questions that have been raised regarding health issue associated with

PM.

1.3.3 Difficulties in the isolation of the health effects of specific chemical

components in PM2.5

Among the international scientific community, much more emphasis was given on

the smaller size PM for their more adverse health effects (Laden et. al., 2000).

PM2.5 can penetrate into the lung alveoli thus cannot be cleared efficiently. The

human lung and retention mechanism of PM2.5 in alveoli is shown in Figure 1.4).

During a pollution episode, each alveolus on an average could receive 1500 PM in

a 24-h exposure period of which, 50% can be retained in lung parenchyma

(Brown, et.al, 2001). Some studies suggested that the particles that reached the

alveoli included toxic sulfates, nitrates, and bioavailable transition metals

(Kodavanti, et.al., 1997; Pritchard et.al., 1996). Several studies were conducted to

15

isolate the health effects of the specific chemical component of PM2.5 but many of

these studies were not able to address the individual chemical species with a

particular health effect (Harrison and Yin, 2000). Thus, much more study is

needed globally to address the PM2.5 related health issues. Since the health effects

of PM are thought to be strongly associated with particle size, composition and

concentrations at which they prevail in the atmosphere. Therefore, next

appropriate step in the scientific research was to investigate the contaminants

associated with PM.

16

A

B

Fig 1.4. The basic structure of a human lung showing the trachea, secondary bronchus,

bronchiole and alveoli in which PM2.5 can be retained in the alveoli of the lung due to their

smaller sizes. Modified from National Center for Environmental Assessment (Research

Triangle Park N. C), 2003.

Fig 1.5. The industrial emission of PFOS in the environment in China from direct and

indirect sources (Modified from Ministry of Environmental Protection of China, 2008).

17

1.4 Contaminants present in PM

Contaminants in PM vary greatly and depend on the factors such as combustion

sources, climate change and type of urban and industrial sources. No single

compound was identified to explain the effects of PM. So, it is generally accepted

that the composition and sizes of PM are responsible for producing health effects

(Kampa and Castanas, 2008). The nucleus of PM is a carbonaceous core covered

by multiple layers of adsorbed pollutant such as various metals, organic

pollutants, acid salts, and biological contaminants (Spurny, 1996). In this review,

we discussed the biotic and abiotic contaminants with special focus on their

sources, functions and general health effects.

1.4.1 Biotic contaminants

The biological contaminants such as endotoxin, allergens and pollen fragments

(Spurny, 1996) can be adsorbed on the carbon core of PM. The pollen fragments

in PM are associated with the respiratory allergic diseases. Allergens are produced

by plant-derived paucimicronic (few microns) components that elicited allergic

symptoms (D'amato, et. al., 2001). It was also reported that the air pollution PM

caused mucosal damage and hindered the muco-cilliary clearance activities thus

facilitated the biotic compounds such as pollen, allergens to enter the cells and

interfere with the immune system (D'amato, et.al, 2001).

Endotoxins (cell-associated bacterial toxin) associated with gram-negative

bacteria for example, Escherichia coli, Salmonella, Shigella, Pseudomonas,

Neisseria, Haemophilus influenzae, Bordetella pertussis, and Vibrio cholerae.

Endotoxin exerts their effects on the intact and isolated lung cells as well. In

whole animals, the pathological functions of both airways and the pulmonary

circulations are mediated by endotoxins. It was reported that acute lung injury and

chronic changes in lung structure and function can be explained by the

pathogenomic effects of endotoxins (Brigham et.al., 1986). A study in Germany

was conducted to determine the endotoxin concentrations in ambient PM

suggested that the concentration of endotoxin in coarse particles were 10-fold

higher than PM2.5 (Heinrich et. al., 2003). Another study from British Columbia,

Canada from October 2005 to September 2006 was conducted to measure the

outdoor airborne endotoxin concentration on PM (PM2.5 and PM10). This study

18

showed the concentrations were generally highest in the summer and fall and

lowest in the winter and spring which explained relative humidity as the

influential environmental factor for this strong seasonal variation (Allen et. al.,

2011).

1.4.2 Abiotic contaminants

Metals

Heavy metals such as vanadium, lead, cadmium, mercury, silver, nickel,

chromium, manganese and transition metals (iron, nickel, vanadium, copper, etc.)

are the constituents of PM (Huang et al., 2009b). By emitting one quarter of the

world‟s anthropogenic emissions of mercury which was approximately 600 tons,

China is the largest contributor of mercury in the world (Pottinger et. al., 2004). In

contrast, the United States produced 120 tons of atmospheric mercury in1999

(Pottinger et. al., 2004). Some of the China‟s central provinces such as Shaanxi,

Guangzhou, Henan, and Sichuan using high amount of coal in heavy industry,

thus contributing to high emission of mercury in this region (Zhang et. al., 2002).

Some other studies suggested that coal combustion is responsible for an estimated

46% of Chongqing‟s total mercury emissions (Wang et. al., 2006).

In fact, metals penetrate into cellular organelles and finally interfere with the

functions of the organism. Chavez et. al. (1987) observed the effects of lead

accumulation in mitochondria and suggested that it caused the fast release of

accumulated Ca2+ and reduction of membrane potential. Other studies postulated

that metals could bind to DNA and regulate the expression of genes. For example,

tumor suppressor genes are masked by the interaction of nuclear chromatin with

nickel (Costa et. al., 2003).

Redox active and redox inactive metals are associated with PM (Costa and

Dreher, 1997). When redox-active metals such as iron, copper and chromium are

present in PM, they undergo redox cycling whereas redox-inactive metals, such as

lead, cadmium, mercury used up the thiol-containing antioxidants (help defend the

body against ROS) and enzymes. Both of these metals may cause an increase in

production of reactive oxygen species (ROS) such as hydroxyl radical (HO-),

superoxide radical (O2-) or hydrogen peroxide (H2O2) leading to oxidative stress

19

in cardiopulmonary damage (Costa and Dreher, 1997). Oxidative stress is the

disturbance of oxidant and anti-oxidant balance. Cumulative evidences suggested

that PM induced oxidative stress is associated with asthma (Li et.al, 2003).

Polycyclic Aromatic Hydrocarbons (PAHs)

PAHs are semi-volatile organic compounds with several hundred of chemicals of

two or more fused aromatic rings, 16 of them are considered as priority

compounds for estimating health risk. Among the 16 priority compounds,

benzo(a)pyrene, the surrogate PAH which is mostly used in carcinogenic studies

(Deutsch-Wenzel et.al., 1983). Due to the PAHs high volatility, PAHs from

emission sources can be released both supported onto PM or in the gas phase

(Mastral et al., 2000, 2001). The most volatile compounds with two or three

aromatic rings are mainly released in the gas phase, while compounds containing

more than three aromatic rings are associated with the PM emission (Mastral et

al., 2000). The structures of some high molecular weight PAHs are shown in

Figure 1.6 A. Atmospheric photochemical degradation and humidity helps to form

different kinds of derivatives of PAHs, for example nitrated PAH (NPAHs),

hydroxylated PAHs (OH-PAHs), amino PAHs (APAHs). Hydroxy radicles and

the oxygen radicles in the presence of nitrogen oxide (N2O5) in the atmosphere

form the NPAHs. Some studies found that these derivatives are sometimes more

toxic than the parent PAH species (Liu et. al., 2007a). PAHs and their derivatives

are mainly originated from industrial process, coal burning, cigarette smoke,

diesel engine and industrial process (Mohanraj et. al., 2011). PAHs are of grave

concern due to their probable carcinogenic activity (IARC, 1983; IPCS, 1998;

UNECE, 1998; Vestreng and Klein, 2002). PAHs have occupied distinct place on

the Convention on Long-Range Trans boundary Air Pollution Protocol (Zhang et.

al., 2009).

In 2004, the total PAHs emission from China was 114,000 tons (Zhang et. al.,

2009), which represented 29% of the total global emission. The huge emission

aggravated the concentrations of PAHs in ambient air which suggested that many

parts of China have high amount of PAHs concentrations compared to other

developed countries (Zhang et. al., 2009). For instances, winter season exhibited

the highest PAHs concentrations in 2005 with the maximum 346ng/m3 in the

20

North China (Liu et. al., 2007b). This concentration was significantly greater than

PAHs concentrations found in London in 1997 (39ng/m3), Chicago in 2004

(70ng/m3) (Sun et.al., 2006; Dimashki et.al., 2001; Harrison et.al 1996) and

Birmingham, United Kingdom in 1992 (20.3ng/m3).

General health effects of PAHs

Previous studies from experimental and human studies suggested that PAHs,

pesticides, tobacco smoke, air pollution, and radiations are carcinogen and

detrimental to the fetus and neonates growth and survival (Mead et. al., 2006;

Whyatt et. al., 2001and Luo et. al., 2003). PM2.5 with PAH-like characteristics

forms an undesired mutagenic risk (Hamers et. al., 2000). The urban air

containing carcinogenic PAH mixtures were collected from Teplice, Czch

Republic and exposed to 3-day-old chick embryos at a concentration of 49.5ng/m3

showed defects in heart and abdominal wall (Binkova et.al., 1999). In mice,

heritable mutations are associated with high atmospheric PAHs concentration

(Bostrom et. al., 2002).

People exposed to coke oven and aluminum production plants those emitting

high PAHs pollutants were prone to an increased lung cancer risk (Bostrom et. al.,

2002). A recent study in China found air pollution was responsible for an increase

of PAH-DNA adducts in cord bloods and a decrease of head circumference in

newborns (Tang et. al., 2006). This study suggested that in addition to

mutagenicity, PAHs can cross the placental barrier and interfere with the

development process of the fetus.

Dioxin/dioxin-like compounds

Chemicals that persists for a longer period of time in the environment are known

as POPs which includes pesticides as well as dioxins, furans and PCBs. Dioxins

are used to explain polychlorinated dibenzo-dioxins (PCDDs) and polychlorinated

dibenzo-furans (PCDFs) while polychlorinated biphenyls (PCB) are regarded as

dioxin -like compounds because of their similar mode of action in case of dioxin-

type toxicity (Schecter et al., 2006).

21

Incomplete combustion and burning of materials that contains chlorine (for

example plastics) are responsible for the production of dioxins and dioxin-like

compounds in the environment. A study in USA suggested that bituminous coal

subjected to high temperature air oxidation and chlorination resulted in the

formation of chlorinated dibenzo-p-dioxins, some of which was known to be

highly toxic (Mahle and Whiting, 1980). Another study before, during, and after

“bonfire night” at Oxford in England suggested that public bonfire and firework

display could change in ambient levels of dioxins (Dyke et.al., 1997). In China, a

short-term sampling survey to determine dibenzo-p-dioxins and dibenzofurans

(PCDD/Fs) from four districts of Guangzhou revealed that the PCDD/Fs were

derived from small diffuse combustion sources such as domestic burning of fossil

fuels, traffic sources, industrial combustion sources and non-industrial combustion

sources as well. Estimation of inhalation exposure of PCDD/Fs also showed that

the exposure levels by the inhabitants in Liwan district were relatively high (Yu

et. al., 2006).

Inhalation risks of PCDDs and PCDFs and PCBs around a steel plant area in

northeast China was investigated by Li et. al. (2010). The results of this study

indicated that steel plants provided a potential source of PCDD/Fs in ambient air.

Dioxins, due to their bio-magnification (Broman et.al., 1992) potential, move up

through the food chain in a magnified way. It was reported that dioxin are

carcinogenic to humans and might association with other health outcomes,

including cardiovascular- and endocrine-related effects (Bertazzi et. al., 2001).

From this study, it was assumed that China environment is the potential source

of dioxin like compounds. Therefore, to estimate the public health risk assessment

and monitoring of environmental health identifying the presence of other toxic

organic compounds in PM are necessary.

22

Perfluorinated compounds (PFCs)

PFCs are stable compounds with unique fluorine-carbon structure. Due to their

unique chemical resistance and surfactant properties, manufacturers have used

PFCs to repel water and oil from furniture carpeting, clothing and food packaging

such as fast-food containers and paper industries (Lau et. al., 2007; Paul et. al.,

2008 and Prevedouros et. al., 2006).

Among the PFCs, perfluorooctane sulfonate (PFOS) and perflourooctanoic acid

(PFOA) are most widely studied compound. The structure of PFOS and PFOA are

shown in Figure 1.6 B. A study of the PFCs in water samples from the Pearl River

(Guangzhou Province, south China) and the Yangtze River (central China)

suggested that PFOS and PFOA were found with the highest concentrations in

water samples from these areas (So et. al., 2007). In our subsequent review, we

highlighted the uses, production, human exposure and general effects of PFOS.

PFOS

PFOS is a fluorinated compound consists of eight carbons (Fig. 1.6B). PFOS was

used extensively in a variety of industry and consumer products, such as repellant

coatings for carpets, leather and food packing materials, and as surfactants in

diverse cosmetics and fire-fighting foams (Thibodeaux, et. al., 2003; Lau, et. al.,

2003 and Wan, et. al., 2012). In addition to stability and metabolic degradation in

environment, PFOS cannot be easily cleared from the body and has serum

elimination half-lives of months in rats and monkeys (Seacat et al., 2002) to

several years in humans (Olsen et al., 2007). Entering into body, PFOS undergo

biotransformation (Nelson et. al., 2010) process and have been shown to affect

cell to cell communication, membrane transport and process of energy generation,

and proxisome proliferation (Upham et. al., 1998; Sohlenius et. al., 1993). PFOS

and related compounds were listed into the Annex B by Stockholm Convention on

Persistent Organic Pollutants (POPs) in May 2009 due to their properties of

persistence, bioaccumulation and toxicity (UNEP, 2009).

23

PFOS PFOA

(A)

(B)

(C)

Fig 1.6. Structure of some PAHs and PFCs and PFOS emission trend in China. (A)

Represents some of the high molecular weight (HMW) PAHs that captured more

efficiently on PM (Kanaly and Harayama, 2000). (B) The C-F structure of mostly

studied PFOS and PFOA. (C) The increased PFOS emission scenario in China from

2001-2011(The figure was adopted from Xie et. al., 2013).

24

Release of PFOS in the environment

PFOS was banned in 2005, but it is a matter of deep concern that PFOS and PFOS

related compounds are being used in many industries in China. PFOS

manufacturers in China generally used ECF (electro-chemical fluorination)

process that was developed by 3M Company. The environmental release of PFOS

was estimated applying the emission factors of PFOS developed by international

PFOS producers (Sweetman, et. al., 2009) which showed that China‟s largest

PFOS manufacturer located in Hubei Province that emit PFOS in air and water at

the rate of 315.6 kg/y and 525.0 kg/y respectively. In the process of metal plating

PFOS are used to prevent the formation of mists or prevent harmful chemicals

from baths (Mei, 2008). Applying the emission scenario document on metal

finishing (OECD, 2004), an investigation was made on the large metal plant in

China, regarding how much PFOS they are releasing in the local water

compartment. The data showed that about 2.88 kg/y PFOS is released. In contrast,

the fire-fighting foams industry released 1.76 kg/y and 35.3 kg/y of PFOS to local

air and water compartment respectively (European Commission, 2003). As for

sulfluramid formulation, the releases of PFOS to local air, water and soil

compartment were estimated to be 15.0 kg/y, 120 kg/y and 0.60 kg/y respectively

(European Commission, 2003). The sources of PFOS are shown in Figure. 1.5

(Ministry of Environmental Protection of China, 2008). Recently, a study

suggested that the production volume of PFOS is about 100 tons per year (Zhang

et. al., 2012). Figure 1.6 C represents the trends of PFOS production in China

since 2001-2011, which indicated that in last 10 years 1800 tons production

surprisingly adding a huge load to the ecosystem population leading to adverse

health effects (Xie et. al., 2013).

Even though, the huge amount of PFOS was released in the environment, little

data has been reported on the levels of PFOS contamination in wildlife and

humans because of the difficulties in measuring the trace amount of PFOS in

surface water and air borne particulate matter (Sasaki et. al., 2003). Hanseng et.

al., (2001), developed a new method for several low levels (ng/mL or ng/g) of

PFCs in sera and liver tissue using high-performance liquid chromatography with

electro-spray tandem mass spectrometry (HPLC/MS/MS). Later on, for the

determination of the concentrations of PFOS from the surface waters, a simple

and sensitive method that enables the determination of trace concentrations of

25

PFOS at the pg/mL level was developed in Japan using LC/MS (Saito et. al.,

2004). Since then a number of analyses have been conducted.

PFOS in air samples

Published report on PFOS concentrations from Japan air samples suggested that in

urban and rural areas the average PFOS concentrations exhibited 5.3pg/m3, and

0.6pg/m3

respectively (Sasaki et. al., 2003). Another study in 2005 suggested that

in urban areas (5.6pg/m3) the PFOS concentrations are greater than rural area

(0.7pg/m3) (Harada et. al., 2005). However, after one year it was found that the

PFOS concentration in rural areas increased by 3 times (6.8 pg/m3) compared to

urban area (2.9pg/m3) (Harada et. al., 2006). As follow up to this study, Sugita et.

al. (2007) carried out an experiment where the highest average PFOS

concentrations were recorded in the Wako city of Japan with the concentration of

7.3pg/m3. These studies suggested that PFOS is widely distributed with increasing

trend in rural areas.

PFOS in dust samples

A study conducted in Spain found the average daily intakes of ionic PFCs by

toddlers from dust were 4.9ng/day. For adults, the average daily intakes of dust

were 3.6ng/day. The first indoor dust PFOS concentrations were measured in

Japan (Moriwaki et. al., 2003) and the concentration was found 24.5ng/g, while

Zhang et.al (2010a) measured the concentration of PFOS from indoor dust of 17

cities of China that found a range of 1.11-10.7ng/g. Subsequently, the PFOS

concentrations from the outdoor dust in Japan were measured with the range of

<0.2-11ng/g. This study also mentioned that the variation in these data were due

to variations in sources, sampling methods and detection methodologies. The

existence of PFOS in dust sample suggested that air dust inhalation can be a

potent source of human exposure.

26

General health effects of PFOS

Toxicological studies suggested that PFOS is correlated with multiple toxicities

such as hepatotoxicity, carcinogenicity, immunotoxicity as well as reproductive

and developmental toxicity (OECD, 2002; Lau, et. al., 2007; Wan et. al., 2012). It

was reported that prenatal exposure of PFOS causes neonatal rat lung

morphological changes and rat early death (Grasty et al., 2005). Previous studies

postulated that PFOS could induce hepatocellular hypertrophy and lipid

vacuolation and cause loss of body weights in rat (Seacat et al., 2002). A recent

study from our lab demonstrated that PFOS elicit pathological manifestation

resembled one of the most common human liver diseases, nonalcoholic fatty liver

diseases (Wan et. al., 2012).

From this review, it was evident that some of the pollutants embedded on PM

are of global concern and may exert some noxious effects on animal health.

Therefore, in regard to question through which mechanism these metals, organic

and inorganic contaminants associated with PM could induce toxicity, in our

subsequent review, we discussed free radical generating activity, oxidative stress,

mutagenicity, cytotoxicity and genotoxicity potential of PM.

27

1.5 Mechanism of PM toxicity

Combination, composition and daily variations in PM mass are believed to

contribute to the toxicity of PM. In order to study the adverse effects of PM

exposure and to identify valuable information on the toxicology of known

compounds present in PM, the study of the mechanism of the toxicity is the key.

Thus, in this review, we discussed the role of the chemical contaminants of PM in

mediating toxic effects by producing oxidative stress, mutagenicity and

genotoxicity.

1.5.1 Free radical generating activity and oxidative stress

PM pollution is associated with adverse health effects in humans, especially with

the cardiopulmonary system (Sunyer and Basagana, 2001). Respiratory infections,

lung cancer, and chronic cardiopulmonary diseases progressions are associated

with oxidative stress through the generation of ROS (Valavanidis et. al., 2008). In

addition, it was also reported that PM initiate inflammatory damage by up

regulation of pro-inflammatory mediators (cytokines and chemokines), endotoxin

effects, modification of cellular components, cellular mutagenicity, and DNA

damage (Nel et. al., 2006). A strong antioxidant defense (enzymatic and non-

enzymatic) for cellular redox homeostasis exists in all aerobic organisms to avoid

oxidative damage to important biological macromolecules (proteins,

carbohydrates, membrane lipids, and mitochondrial and cellular DNA). It was

believed that intracellular enzymatic mechanisms greatly facilitate the anti-

oxidant process.

Cigarette smoke air pollution are important factors that affected ROS production

and can change the redox status of the cell and subsequently triggered the

cascade of events associated with inflammation (Schafer and Buettner, 2001;

Gonzales-Flecha, 2004). A recent observation showed that diesel exhaust particles

(DEP) play an important role in oxidative cellular damage through the generation

of oxygen-free radicals (e.g., hydroxyl, HO-; superoxide anion, O2

- ) and ROS

(e.g., H2O2) which are the suggestive of the ability of PM to produce ROS in the

cellular environment. Many studies have reported the association of ROS with

membrane lipid peroxidation and oxidative DNA damage (Bai et. al., 2001;

Kumagai et.al., 1997; Knuckles and Dreher, 2007).

28

In order to understand, the cellular damage and adverse health effects associated

with oxidative stress a three phase response model was developed (Valavanidis et.

al., 2008). In first phase, at relatively low level of oxidative stress, various

transcription factors (such as the nuclear factor erythroid-2, Nrf2) stimulate a

series of antioxidant and detoxification enzymes (including catalase, superoxide

dismutase, glutathione S-transferase, known collectively as phase 2 response) to

scavenge or destroy ROS. In this phase, PM exposures might not cause any

adverse biological outcomes (Li et. al., 2002 and Cho et. al., 2006).

In the second phase, when ROS concentration is greater than the anti-oxidant

concentration results is the formation of pro-inflammatory situation and lead to

cytotoxicity of the cells. The cytokine production is regulated by the redox-

sensitive mitogen-activated protein (MAP) kinase and NF-κB pathways which are

involved in the inflammatory processes of the lungs (Xia et. al., 2006; Chan and

Kan, 1999).

In the third phase, when the oxidative stress level is high it overwhelmed the

antioxidant defenses and subsequently induce cytotoxic effects. In this stage,

mitochondria may release pro-apoptotic factors and induce apoptosis of lung cells

(Hiura et. al., 2000). It was reported that oxidative potential of PM2.5 and ultrafine

PM is the result of significant amount of organic carbon compounds such as

quinones and PAHs. A study found the correlation between PM concentration and

redox active compounds and damage in the macrophages and epithelial cells.

Electron microscope found the ultrafine particles are localized inside damaged

mitochondria (Li et. al., 2003). Quinones (oxidized derivatives of aromatic

compounds) interacts with the metal ions and results in the formation of ROS

which through redox cycling reactions induce the carcinogenicity of quinones

(Qui and Cadenas, 1997; Hirakawa et.al., 2002).

The principal pathways of metabolic activation of PAHs are involved in (1) The

catalization of cytochrome p450 produces diol epoxides, leading to DNA adduct

formation, considered to be essential to PAH mechanism of carcinogenesis. (2)

dihydro diol dehydrogenases produces redox-active quinones, contributing to

29

PAH carcinogenesis and tumor promotion (Dannisenko et.al., 1996; Ohnishi and

Kawanishi, et. al., 2002).

In addition, transition metal ions of PM with redox potential can contribute to

ROS overproduction and play an important role in oxidative DNA and protein

damage (Kasprzak, 2002). It was also reported that solvable metals on inhaled

particles for example, Fe, Ni, Cu, Cr, Co were associated with ROS production

which cause oxidative stress in air way epithelial cells (Gotschi, et. al., 2008;

Mazumbar et.al., 1982; Koening, 1980). Some other studies have found the

activity of some metals and antioxidants in producing oxidant effects and

inflammation in laboratory animals (Lawther, 1975; Pearlman, et.al., 1971).

1.5.2 Mutagenicity

For the study of mutagenicity of ambient and indoor PM, short-term Ames test is

widely used (Claxton et.al, 2004; Claxton et. al., 1989). Short-term mutagenicity

assays in general applied to determine the effect of either single chemical or

chemicals in a complex mixture such as ambient PM. Metabolizing enzymes from

rat liver microsomes or S9 is used in mutagenicity assay because some PAH and

other organic molecules require metabolic activation in order to exert their

mutagenic activity. But some nitro-PAH originating from diesel engines (Černá

et. al., 2000) due to their mutagenic activities, do not require metabolic activation.

Thus, to characterize organic extracts of airborne particles, Salmonella

typhimurium tester strains TA98, having high sensitivity and specificity has

frequently been used.

The majority of studies that have used TA98 and TA100, showed an increase in

mutagenicity of PM in the Ames test upon addition of S9 (Squadrito et. al., 2001;

Černá, et.al., 2000; Bronzetti et.al., 1996 and Sato et.al., 1995). A study on the

mutagenicity of PM found some day to day variation of S9 on the mutagenic

potential suggests that the composition of PM can vary considerably and

metabolic activation generally resulted in increased mutagenicity (Bronzetti et.al.,

1996).

30

1.5.3 Genotoxicity

Generally, genotoxicity is characterized by DNA-adduct formation and oxidative

DNA damage. A large number of chemical components are associated with PM.

Among them traffic-related airborne particles contains a large number of

genotoxic/mutagenic chemical substances that can cause DNA damage and

promote malignant neoplasms.

In recent decades, the mutagenic potential of airborne PM has been confirmed

using different short-term assays. DNA damage can be measured by comet assay

or as the formation of 8-oxo-7, 8- dihydro-20-deoxyguanosine (8-oxodG). Most of

the genotoxicity studies were conducted using extractable organic compounds and

mixtures, water-soluble substances (such as metals) and volatile organic

compounds (Knaapen et. al., 2002; de Kok et. al., 2005).

A study with the extractable organic material (especially PAH-containing

mixtures bound onto PM10 particles) on human-derived cell lines (leukocytes,

human alveolar carcinoma, human myeloid leukemia, human trancheobronchial

epithelia, human fibroblasts) have been used to investigate DNA damage. In this

study, they used residual oil fly ash (ROFA), PM10, PM2.5, PM2.5−10 and TSP and

other types of PM and found positive DNA damage, single-strand breaks,

micronuclei sister chromatid exchange, and oxidative DNA damage. The

measurements were analyzed by alkaline single-cell gel electrophoresis and comet

assay. These studies suggest that the mechanisms of genotoxicity of PM are the

result of adduct-forming compounds (through cell particulate interactions) and

oxidizing DNA damage (Poma, et. al., 2002; Karlsson et. al., 2004; Healey et. al.,

2005).

Other research was focused on the water-soluble fractions (mainly transition

metals) and compared their DNA damage potential. In their studies they found

that the constituents of the water-soluble PM extracts are more potent to induce

oxidative DNA damage than the organic compounds (Gutierrez-Castillo et. al.,

2006; Prahalat et.al., 1999). Previous studies suggested that inhalation and

deposition of PM in the lung, alveoli are able to stimulate the formation of ROS

(Knaapen et al. 2002), which can be generated by transition metals and/or quinoid

31

redox cycling and can play an important role in oxidative damage to cellular

membrane lipids, proteins-enzymes, and DNA. In addition, ROS can initiate

pulmonary inflammation which might be able to alter the excision repair

mechanisms of DNA and activates oncogenes (Knaapen et. al., 2004; Sagai et. al.,

2000).

Several studies suggested that transition metal contents and the concentrations

of the total or carcinogenic PAHs in PM2.5 (de Kok et. al., 2005) induced

genotoxicity. But Knaapen et al. (2002) concluded that apart from ROS

generation, a direct „particle‟ effect contributes to the genotoxic potential of

ambient PM. Another study showed that both the organic and inorganic

components of PM contributed to the induction of DNA damage, but the majority

of the damage (approximately 75%) was induced by the organic extract (Healey

et. al., 2005) of PM.

1.6 Research questions and Hypothesis

Epidemiological data indicated that PM2.5 is detrimental to public health but there

still remain many questions pertaining to how PM2.5 exerts harm to cells, the lung

and across body. Thus, assuming the adverse effects of PM2.5 on public health, we

undertook to address a number of questions that have been raised regarding the

toxicology and biological effects associated with PM2.5 exposure. For example,

what are the concentrations of particular organic compounds (for example, PAHs

and PFCs) in PM2.5? Does PM2.5 exert any direct toxic effects on human lung

cells? If it is toxic, what cellular mechanisms lead to cell injury or damage? Is

inflammation the basis of cellular toxicity upon exposure to PM2.5? How the

contaminants do adsorb on PM2.5 cause adverse effects on offspring‟s health?

With the benefit of hindsight, we hypothesized that i) PM2.5 from Chinese cities

may contain the chemical contaminants PAHs and PFCs. Thus inhalation

exposure of PM2.5 may cause risks to develop lung diseases to the local people.

Since lung is the first organ in contact with air PM2.5, inflammatory damage may

be evoked. Once the chemical contaminants got into the circulation, they could

pass through placenta in affecting fetal health.

32

1.7 Objectives of the present study

Our goals were to determine the concentrations of some organic pollutants in

PM2.5 and examine the biological effects of PM2.5 in vitro and to investigate the

possible health effects of the contaminant of PM2.5 using in-vivo study.

i) To determine the concentrations of chemical contaminants in PM2.5

collected from different cities of China using either GC-MS or LC-

MS/MS techniques.

ii) To examine the biological effects of the chemical extracts of PM2.5 on

inflammatory and detoxification responses in cell-line studies.

iii) To explore the transcriptional profile associated with the prenatal

hepatotoxicity of PFOS with the intent of identifying critical target

pathways.

iv) To investigate the toxicity of PFOS on fetal pancreas using high-

throughput iTRAQ quantitative proteomic technique.

33

CHAPTER 2

CHEMICAL AND BIOLOGICAL CHARACTERIZATION OF

WINTER TIME FINE PARTICULATE MATTER (PM2.5)

COLLECTED IN FIVE CITIES IN CHINA

2. 1 Introduction

Air pollution problem in Northern China has reached alarming levels. In the

winter of 2012-13, trans-boundary air pollution from China was reported and

became a global concern. A remarkable increase in the prevalence of lung cancers

in the country in the past decades was found to be related to particulate matter

(PM) with an aerodynamic diameter of less than 2.5m (Chen et al., 2013). The

latest report from World Health Organization (WHO) stated that air pollution has

become the world’s single biggest environmental health risk, linked to around 7

million or nearly one in eight deaths in 2012. The figures suggested that outdoor

pollution from traffic fumes, coal and wood burning may kill more people than

smoking and diabetes combined. Outdoor air pollution came as a result of stroke,

cardiovascular and pulmonary disease and the vast majority was found to be in

Asia and America. The situation worsens with the exponential growth in

population together with the industrialization in this area.

It has been well known that ambient PM suspended in the atmosphere as

aerosol are adversely affecting human health, especially to the respiratory and

cardiovascular systems (Brunekreef et al., 2009; Langrish et al., 2012; Lee et al.,

2007; Park et al., 2011). PM10 and PM2.5 which are differentiated by the

particulate diameters (m) are commonly used in the air quality monitoring

scheme all over the world (USEPA). Of which, PM2.5, as compare to PM10, can

penetrate into the deeper area of the lung, directly affect the respiratory surfaces

34

and dissolve into blood which may cause systemic toxic effects. According to the

Environmental Protection Agency (USEPA), the ambient concentration of PM2.5

was set as 35 g/m3 (24 h mean) and 15g/m

3 (annual mean) for national ambient

air quality standard (USEPA, 2013). The pollutants which attached on the PM2.5,

which can pass all along the respiratory tract to the deeper alveolar sac, are the

disease-causing reason of air pollution. Organic and inorganic pollutants were

adsorbed on PM2.5 found globally (Cachon et al., 2014; Chang et al., 2006).

Polycyclic aromatic compounds (PAHs) had been accepted as a class of

ubiquitous environmental pollutants which are mostly products of energy

production such as coal and petroleum, natural gas and fossil fuels, as well as

cigarette smoking and waste incineration (Bostrom et al., 2002; Kong et al., 2010).

The sources of PAHs production may varies from countries to countries; in

Sweden, phenanthrene is the dominant PAHs found in 1994-2000 (Bostrom et al.,

2002); while fluoranthene being the most abundant PAHs detected in Beijing,

China (Wang et al., 2008). The USEPA has classified 7 PAHs as probable human

carcinogens: benz (a) anthracene, benz (a) pyrene, benzo (b) fluoranthene, benzo

(k) fluoranthene, chrysene, dibenz (a,h) anthracene and indeno (1,2,3-cd) pyrene.

Due to its small size, PM2.5 is able to penetrate to the lower respiratory tract to

alveolar sacs and induce cell damage. There are two major routes of inhaled PAHs

to the blood circulations. The majority of the PAHs deposits on the thinner

alveolar epithelium where they readily absorbed and enter the circulation; while

about 10-20% of PAHs inhaled will deposit on the thicker bronchial epithelium,

slowly absorbed and transport through the epithelium. Due to the lipophilic

properties of most PAHs, a fraction of compounds can be retained in the bronchial

tissues and accumulated to attain a high local dose even at low environmental

35

exposure levels (Bostrom et al., 2002). Industrial development and exponential

growth in population in China raises the needs of energy and subsequent different

kind of pollutions to the environment. On Feb 2014, Beijing recorded dangerously

high level of suspended PM2.5 for over 15 times of the recommended levels of

WHO limits (25 g/m3 24h mean PM2.5) for consecutive 6 days (Chen et al.,

2013). This leads to our concern to the air quality monitoring and its potential

health effects to lung, which is the first organ encountered with the suspended

pollution in air. Thus, in this study, human bronchial epithelial Beas-2b cell line

was used to evaluate the cytotoxicity of PM2.5 collected from the five cities in

China.

2.2 Materials and Methods

Air sample collection

Two northern (BJ and XA) and three southern (GZ, XM and HK) Chinese cities

were selected in the present study (Fig. 2.1A). The samples were taken for six to

eight days during the air pollution episode of haze from the end of January to the

beginning of February in 2013. The PM2.5 samples were collected on quartz fiber

filter (8 inch 10 inch) using a high-volume sampler at a flow rate of 1.05–1.16

m3 min

-1. Seven to eight air filters were collected from each sampling sites. A

sampling period of ~ 24 h was adopted at all sampling sites. The filters were then

wrapped in aluminum foils for further analysis in our laboratory.

36

The weights of filters were measured before and after the sampling procedure and

were stored in desiccator cabinet at room temperature. Field blanks were also

collected at each sampling site by putting the filters in the sampler without

drawing air through. The workflow of the experiment was shown in Fig. 2.1B.

City Location Longitude Latitude Site description

Beijing (BJ) Institute of Atmosphere Physics 116°23′09.25″ 39°59′10.78″ Urban

residential

Xi’an (XA) Institute of Earth Environment 108°52′58.59″ 34°13′49.36″ Commercial

and residential

Guangzhou

(GZ)

South China Institute of

Environmental Sciences

113°21′18.14″ 23°07′26.53″ Urban

residential

Xiamen

(XM)

Hu Li District Power Supply

Bureau

118°06′08.04″ 24°29′11.20″ Coastal

Hong Kong

(HK)

Hong Kong Polytechnic Univ. 114°11′00.17″ 22°18′11.49″ Roadside &

coastal

37

Fig 2.1. Experimental set up of present study. (A) Location of five sampling cities

on a China map. (B) The workflow of handling and processing the air filters.

One fourth of the air filter collected underwent soxhlet extraction and the organic

extract was dissolved in n-hexane. Half of the dissolved extracts performed

chemical analysis by GC-MS while the other half underwent nitrogen dry and

reconstituted in 1mL DMSO for biological analysis using cell line.

38

Measurement of PAHs in air filters

One fourth of the air filters were extracted for 16-18h at 68oC with 60 ml of the

solution mix (acetone: dichloromethane (DCM), n-hexane 1:1:1) in a soxhlet

extractor, as described in the standard method 3540C (USEPA Method 3540C,

1996c). The extracted solution was concentrated to 1 ml by a rotary evaporator,

and was then followed by florisil cleanup (USEPA Method 3620B, 1996b). The

cleaned extract was dried under nitrogen gas and resuspended in 1 ml of n-hexane.

Deuterated PAH internal standards (acenaphthene-d10, phenanthrene-d10,

chrysene-d12 and perylene-d12) were added into the extracts at the concentration of

320 ng/g prior to GC-MSD analysis (Hewlett-Packard (HP) 6890 N gas

chromatograph (GC) coupled with a HP-5973 mass selective detector (MSD) and

a 30 m x 0.25 mm x 0.25 m DB-5 capillary column (J&W Scientific Co. Ltd.,

Folsom, CA), as described in the Standard method 8270C (USEPA Method 8270C,

1996c). The native PAH standards (naphthalene (Nap), acenaphthylene (Acel),

acenaphthene (Ace), fluorine (Flu), phenanthrene (Phe), anthracene (Ant),

fluoranthene (Fla), pyrene (Pyr), benz (a) anthracene (BaA), chrysene (Chr),

benzo (b+k) fluoranthene (BbkF), benzo (a) pyrene (BaP), indeno (1,2,3-cd)

pyrene (Ind), dibenzo (a,h) anthracene (DbA), benzo (g,h,i) pyrelene (BghiP))

were used to obtain the standard curve with the concentrations of 0, 2, 5, 10, 20,

50, 100 and 200 ng/g. QA/QC analysis. The limit of detection (LOD) was

determined as the concentration of an individual PAH detected in a sample with a

signal-to-noise ratio of 3, ranging from 0.05 – 0.15 ng/g. The recoveries of

individual PAHs were from 74 – 108%. For each batch of samples, a method

blank (solvent), a spiked blank, a sample duplicate and a standard reference

material were analyzed.

39

The variation of coefficients of concentrations of PAHs of duplicate samples was

less than 10%. The concentrations of PAHs in the method blank were less than

the LOD. All the results were expressed as per one fourth of air filter.

Risk assessment

The risk assessment methodology advocated by WHO was used for assessing the

excess lifetime cancer risk from exposure to PAHs. The unit risk of lung cancer

suggested by WHO air quality guidelines is 87 x 10-6

per ng BaP per m3 air. The

lifetime cancer risk for lung cancer is then calculated by the equation below. The

cancer risk was expressed as extra cancer cases occur in 100,000 exposed

individuals.

Cancer risk = BaP equivalents (ng/ m3) x 87 x 10

-6

Cell culture and treatment

The human normal bronchial epithelium cell line, Beas-2b (ATCC, CRL-9609)

was grown in DMEM/F12 (HAM’s) medium supplemented with 10% FBS

(HyClone, Perbio, Thermo Fisher Scientific, Carmlington, UK) and antibiotics

(50U/ml penicillin and 50g/ml streptomycin) (Invitrogen, CA, USA). For the

soluble organic extractable matter in the extracts for biological assay, half of the

extracts in n-hexane (0.5 ml) were dried under nitrogen and reconstituted with

dimethyl sulfoxide (DMSO) (Sigma Aldrich, USA.). Filter extracts from same

region were combined to form a mixture for each region and approximately 500

g of extracts were used for cell assay (DMSO <0.005%).

40

MTT assay

Effects of filter extracts on cell viability were determined by MTT assay. Human

Beas-2b cells were plated into 96-well plates (Iwaki, Tokyo, Japan) at a density

reaching 70-80% confluence by the time of adding 500μg of extracts. After

incubation for 24 h with extracts in 5% CO2 at 37°C, the cells were incubated with

100 μl of 10% MTT solution (Sigma Aldrich) for another 4 hours at 37oC for

color development. The medium was then removed and 100μl of DMSO was

added to dissolve the intracellular blue crystalline formazan product for 10 min at

room temperature. Optical density was measured at 540nm by absorbance

microplate reader (BioTek ELx800). The results were presented as a percentage of

the absorbance of control cells.

Cell Migration assay

Cell migration was performed by using trans well chambers with 8m pore size

(Costar) in a 24-well plate (Iwaki, Tokyo, Japan).Cells were seeded at 2x104 in 0.2

ml in the top chambers while the bottom chambers contained 0.7ml of completed

medium with 500g of extracts from different locations. Migration assay was

done in duplicate. After incubation at 37oC and 5% CO2 for 24 hours, the migrated

cells were fixed with ice-cold absolute methanol for 10 min and stained with

crystal violet solution for another 10 min before mounted on glass slide. More

than 10 views were analyzed under light microscope (100X) and number of

migrated cells was scored. The mean value was expressed as percentage from two

or three independent experiments as compared to the blank filter controls.

41

Real-time PCR

BEAS-2B cells were plated at a density of 7 x 104 in a 12-well plate (Iwaki, Tokyo,

japan) and incubated at 37∘C, 5% CO2 for 24 hours until the cells had reached

70-80% confluence. An amount of 500g of extracts were then added and

incubated for 24 hours. Total RNA was then isolated and measured. Total RNA

with A260:A280 ratio between 1.8 and 1.9 was used for real-time PCR analysis.

Complementary DNA was synthesized from 100ng of total RNA using High

Capacity RNA-to-cDNA Master Mix (Applied Biosystems, Foster City, CA).

Primers which are gene-specific were designed from published sequences.

Real-time PCR was carried out with programmed time and temperature: 3min at

95∘C, 40 cycles of 95∘C for 15 sec, 56∘C for 20 sec and 72∘C for 30 sec. The

amplified PCR product from samples were quantified by Step One Real-Time

PCR system using SYBR Green Master mix (Applied Biosystems). Cycle

numbers were then calculated and normalized by the transcript level of actin.

Sequences of primers were listed in Table 2.1.

Statistical analysis

Statistical evaluations were conducted by SigmaStat 3.5. All data were tested to be

normally distributed and independent by using the Normal Plots in SigmaStat

significance were 0.05. Differences among groups were tested for statistical

significance by analysis of variance (ANOVA) followed by Duncan’s Multiple

Range test (significance at p< 0.05). Results are presented as the mean + SD.

Groups were considered significantly different if p< 0.05.

42

Table 2.1 List of human primers used in this study.

Primer Forward primer sequences Reverse primer sequences

CYP1A1 AGCAGCTGGATGAGAACGCC GCCGTGACCTGCCAATCACT

CYP1B1 TTGTGCCTGTCACTATTCCTC ATCAAAGTTCTCCGGGTTAGG

TNF- GGGCCTGTACCTCATCTACT TAGATGGGCTCATACCAGGG

IL-6 AGCCCACCGGGAACGAAAGA TGTGTGGGGCGGCTACATCT

IL-8 AAGCCACCGGAGCACTCCAT CACGGCCAGCTTGGAAGTCA

b-Actin GACTACCTCATGAAGATCCTCACC TCTCCTTAATGTCACGCACGATT

43

2. 3 Results and Discussion

16 USEPA PAHs were detected in PM2.5 of samples from China.

Air filters were collected from the five cities in southern (HK, GZ and XM) and

northern (XA and BJ) China. The one fourth of each air filters collected was

undergo standardized soxhlet extraction for PAHs and performed chemical and

biological analysis. The weights of PM2.5 collected on the filters were measured

(Fig. 2.2 A). The weights of PM2.5 per m3 air collected in the northern cities of

China were approximately 3 times higher than that of the southern cities,

weighted in average of 228g and 50g respectively. The concentrations of 16

USEPA PAHs in PM2.5 per m3 air flow of the five selected cities were shown in

Fig. 2.2 B and details were listed in Table 2.2.

Fig 2.2. Weights of PM2.5 dust in air filters collected from different cities of China

and the mean concentrations of total PAHs in each sampling site.

44

Table 2.2 Levels of PAHs and TEQ* (ppt) measured in the air samples from the

five cities in China.

HK GZ XM XA BJ

PAH Species TEF PAH

(ng/m3)

TEQ

(ppt)

PAH

(ng/m3)

TEQ

(ppt)

PAH

(ng/m3)

TEQ

(ppt)

PAH

(ng/m3)

TEQ

(ppt)

PAH

(ng/m3)

TEQ

(ppt)

Naphthalene

n.d n.d 0.03 0.09 0.08

Acenaphthylene n.d n.d n.d 0.32 0.34

Acenaphthene n.d 0.12 n.d 0.12 0.20

Fluorene 0.1 n.d n.d 0.21 0.43

Phenanthrene 0.13 0.12 0.07 2.45 5.74

Anthracene 0.01 0.02 n.d 0.36 0.93

Fluoranthene 0.23 0.37 0.25 8.56 13.97

Pyrene 0.28 0.38 0.24 8.00 11.35

Benz(a)anthracene 0.1 0.12 0.01 0.19 0.02 0.58 0.06 7.27 0.73 9.74 0.97

Chrysene 0.001 0.26 0.00 0.68 0.001 0.48 0.00 9.37 0.01 11.00 0.01

Benzo(b+k)fluoranthene 0.1 0.52 0.05 1.61 0.16 0.81 0.08 11.63 1.16 12.40 1.24

Benzo(a)pyrene 1 0.28 0.28 0.86 0.86 0.42 0.42 5.16 5.16 4.91 4.91

Indeno(1,2,3-cd)pyrene 0.1 0.53 0.05 1.10 0.11 0.57 0.06 7.13 0.71 5.04 0.50

45

Dibenz(a,h)anthracene 1 0.39 0.39 0.52 0.52 0.39 0.39 1.84 1.84 1.40 1.40

Benzo(g,h,i)perylene 0.49 0.92 0.53 6.06 3.54

Total PAHs 3.35 6.77 4.35 68.05 80.45

Total BaP equivalents(BaPeq) 0.79 1.68 1.00 9.61 9.04

Lifetime excess cancer risk

( cancer cases per million

exposed individuals)

6.8 14.6 8.7 83.6 78.6

*TEF = toxic equivalency factor. TEQ= (Concentrations of PAHs in each sample x corresponding TEF)

All 16 PAHs were detected in the samples from XA and BJ, while PAHs with

shorter carbon chains were undetectable in HK, GZ and XM samples (Fig. 2.3

A-E). Total PAH concentrations were calculated by the summation of all 16

PAHs congeners, the data ranging from 3.35 to 80.45ng/m3, leading by BJ,

followed by XA, GZ, XM and HK. Our results were relatively lower than

previous studies on PAHs contamination in ambient air in China (Okuda et al.,

2010; Sin et al., 2005; Wang et al., 2008).

46

Fig 2.3. Concentrations and distributions of PAH congeners in each sampling site.

Benzo(b+k)fluoranthene (BbkF) was the most abundance species among 15 PAHs

measured with the highest concentrations detected in most sampling sites except

HK and BJ, ranging from 0.52 to 12.40ng/m3. However, its levels were found to

be noticeable higher (> 12.40ng/m3) in the northern cities (XA and BJ) versus in

47

all the three southern cites (< 2ng/m3 air). Fluoranthrene is the most abundance

species found in BJ with the mean concentration of 13.97ng/m3. Similar to a

study conducted in 2006, the most abundant quantified PAHs in PM2.5 in BJ city

was Fla, at which this species of PAHs is closely associated with the increase uses

of natural gas (Wang et al., 2008).

PAHs concentrations of samples from northern China were at least 10 times

higher than that from southern China, showing less severe pollution in the

southern cities. The higher PAHs contaminations in northern cities may be due to

more coal and wood combustions for heat production in the winter, comparing to

the lesser demand on heating in the relatively warmer southern cities. In addition,

contaminations in the southern cities which are closer to the coastal area are

readily dispersed by the sea wind verses inland northern cities which tends to

accumulate the polluted air masses to local areas. Topography and climate

differences may also contributed to the difference in levels of PAHs

contaminations in mainland China. The average temperature and precipitation in

January was much lower in BJ and XA (average temperature below 0oC and 7

inches for average precipitation) than in the three southern cities (average

temperature above 12oC and precipitation above 24 inches). Higher rainfall in

southern China brings ambient air particulate matter to the ground, may contribute

to the lower PAH concentrations in these cities. Furthermore, BJ was

geographically surrounded by three mountains, polluted air mass produced was

difficult to be dispersed and led to a higher chance of smog accumulations, thus

more PM2.5 collected and higher PAHs concentration in our samples. PAHs in

ambient air can be in both gaseous and particulates forms. PAHs in particulates

were of higher molecular weight and greater carcinogenicity (Chang et al., 2006).

48

PAH congeners with carbon chain shorter than 14, noted naphthalene,

acenaphthylene, acenaphthene and fluorene, were found in much lower

concentrations than that with longer carbon chain (highest concentration with 0.43

ng fluorine/m3 air, with most of them were in undetectable level). However, PAHs

with longer carbon chain or higher molecular weight were found in higher

concentrations in all five sampling sites.

Cancer risks via inhalation of PAHs.

Data from a number of health studies suggested that there is an association

between lung cancer and exposure to PAH compounds (Zhang and Smith, 2007;

Zhang et al., 2009). The most important exposure route for lung cancer would

appear to be via inhalation. Most of the PAHs are known to be associated with

airborne particles. According to USEPA, some of the PAHs are classified as

human carcinogens such as BaP, BaA, BbkF, Chr, InP, and DbA. BaP, a

probable human carcinogen found in appreciable concentrations in the atmosphere,

can be used as a marker of the carcinogenic risk of airborne PAH. A previous

study suggested that an average of 6.5 million people in China was diagnosis with

lung cancer due to inhalation of ambient PAHs (Zhang et al., 2009). Total BaP

equivalent measures the relative toxicity of PAHs to BaP. The total BaP

equivalents (BaPeq) determined by toxic equivalent factors (TEF) and the

concentrations of individual PAHs was listed in Table 2.2. The data from XA

(9.61 ppt) show the highest calculated BaPeq among five cities, followed by BJ

(9.04 ppt), GZ (1.68 ppt), XM (1.00 ppt) and HK (0.79 ppt) with the lowest.

Excess lifetime cancer risk calculated based on total BaPeq of each city was

shown in Fig. 2.4. For XA and BJ, the estimated lifetime cancer risk were the

highest, reaching 83.6 and 78.6 extra cancer cases per 100,000 exposed

49

individuals; while HK, GZ and XM were with much lower exposure risk at 6.8,

14.6 and 8.7 extra cancer cases in 100,000 exposed individuals respectively. The

guideline value for ambient BaP was set to be 0.1ng/m3, thus the acceptable risk

of exposure to PAHs via inhalation was 1.0e-05. Our result suggested if the risk is

higher than the maximum acceptable risk level of 1 per 100,000 exposed

individuals, more legislation on the air quality control on PAHs-bound PM

emission is needed to control the pollution.

Fig 2.4. Calculated excess lifetime cancer risks (per million exposed individuals)

of the five sampling sites.

Coal combustion and vehicle emission were the common sources of PAHs in

PM 2.5.

Analyses of the diagnostic ratio were widely used to give an idea on the possible

emission sources of PAHs in environmental monitoring (Akyuz and Cabuk, 2008;

Vasilakos et al., 2007). Five diagnostic ratios were calculated and shown in Table

2.3. For Hong Kong, the ratio BaP/BghiP (0.55) and Ant/(Ant+Phe) (0.098)

indicated gasoline engine and non-burned fossil fuels contributed to the major

sources of emission. On the other hand, the sources of PAHs in other cities were

50

Table 2.3 Diagnostic ratios of PM-bounded PAHs in different cities of China.

Diagnostic

ratio

Ind/

(Ind+BghiP)

BaP/

BghiP

Flu/

(Flu+Pyr)

Ant/

(Ant+Phe)

BaA/

(BaA+Chr)

Gasoline

engine

>0.18 0.5-0.6 <0.5 >0.5 >0.49

Diesel

engine

0.35-0.7 0.3-0.4 >0.5 >0.35 >0.68

Coal

burning

>0.56 0.9-6.6 >0.57 >0.24 >0.46

Non-burne

d fossil

fuels inputs

- >0.58 - <0.1 -

Natural gas

combustion

>0.32 - >0.49 >0.12 >0.39

HK 0.52 ± 0.009 0.55 ± 0.039 0.30 ± 0.093 0.098 ± 0.013 0.31 ± 0.029

GZ 0.54 ± 0.008 0.95 ± 0.078 - 0.13 ± 0.027 0.19 ± 0.08

XM 0.52 ± 0.025 0.78 ± 0.080 - - 0.55 ± 0.026

XA 0.54 ± 0.011 0.87 ± 0.134 0.03 ± 0.01 0.13 ± 0.022 0.42 ± 0.036

BJ 0.59 ± 0.011 1.37 ± 0.060 0.04 ± 0.005 0.14 ± 0.031 0.46 ± 0.042

51

Fig 2.5. Graphic illustration of the diagnostic ratios on the sources of PAHs

emission.

mainly due to the burning of coal and natural gas combustion. Diagnostic ratios

shown in Fig. 2.5 illustrated the source of PAHs in XM, XA and BJ are mainly

from grass, wood and coal combustion; whereas the source in HK and GZ are

mainly from mixed sources of both combustion and petroleum for vehicles.

Flu

/ F

lu+

Pyr

52

Gene expression levels of pro-inflammatory cytokine and xenobiotic

metabolizing enzymes were altered by PM2.5 exposure.

Human bronchial epithelial cells which were usually used in in vitro study to

determine the pro-inflammatory and cytotoxic effects were exposed to 500g of

PM2.5 extracts for 24h, gene expression levels of pro-inflammatory cytokines and

xenobiotic metabolizing enzymes were investigated. Samples from all locations

were found to significantly induce the gene expression level of interleukin-6

(IL-6), but not IL-8 and tumor necrosis factor-alpha (TNF) (Fig. 2.6A). In

addition, gene expression levels of xenobiotic metabolic enzymes (CYP1A1 and

CYP1B1) were also up-regulated by PM2.5 extract treatment for 24h (Fig. 2.6B).

Recent studies demonstrated the PAHs adsorbed on particulate matter can lead to

cell damage, induce cytotoxicity and pro-inflammatory responses (Cachon et al.,

2014; Osornio-Vargas et al., 2011).

Initiation of inflammatory response involves in the induction of various

cytokines and chemokine. Other studies reported the evaluation of the relationship

between PM exposure and cytokines induction (Cachon et al., 2014; Dergham et

al., 2012; Michael et al., 2013). IL-6 and IL-8 were both critical pro-inflammatory

cytokine produced by epithelial cells to stimulate inflammatory response. In the

present study, IL-6 was significantly induced by PM2.5 extracts, inflammatory

response may be triggered by the exposure of Beas-2b cells to PM extracts from

the five cities.

Xenobiotic metabolic enzymes were also up-regulated upon exposure to PM2.5

extracts (Fig. 2.6B). CYP1A1, a phase I enzyme of xenobiotic metabolic pathway,

was known to be induced by PAHs (Cachon et al., 2014; Dergham et al., 2012; Val

et al., 2011).

53

Fig 2.6. Gene expression levels of pro-inflammatory cytokines and xenobiotic

metabolic enzymes upon extracts treatment for 24h in BEAS-2B cells. (A)

mRNA levels of interleukin-6 (IL-6) was significantly up-regulated in all five

sampling sites as compared to the blank filter control (p<0.01). (B) Gene

expression levels of cytochrome p450 enzymes were significantly up-regulated by

the extracts exposure of all sampling sites (p<0.01).

PM2.5 from XA and BJ induced migration of Beas-2b cells.

Cell proliferation and migration are important biological process found in tumor

metastasis and progression. Treatments of Beas-2b cells with PM2.5 extracts from

BJ, XA, XM or GZ induced cell proliferation (Fig. 2.7A). For the transwell cell

migration assay, PM2.5 extracts from XA and BJ caused significant increases in

cell migration as compared to the filter control, and extracts from HK, GZ and

XM (Fig. 2.7B). Although most of the PM2.5 extracts induced cell proliferation

and the expression levels of IL-6, the extracts from the Northern cities (BJ and

XA) might contain more carcinogenic substances that promoted tumorigenicity.

This observation is consistent with the highest calculated values of the excess

lifetime cancer risks in BJ and XA (Fig 2.4). However it may warrant a further

investigation if there are other unidentified carcinogenic substances in the air of

the Northern cities.

54

Fig 2.7. Exposure to PM extracts increased the migration of BEAS-2B cells in cell

migration assay. (A) The proliferation assay demonstrated the increase in

proliferation in the cells treating with GZ, XM, XA and BJ extracts in MTT assay

(p<0.05). (B) Micrographs showing the representative pictures of cell migration

assay (200x). The percentage of migration of cells treated with XA and BJ were

significantly higher than that of other cities and the blank filter (p<0.05).

55

2.4 Conclusion

Ten priority PAHs were identified in the winter time PM samples in all five cities;

while all 16 PAHs can be detected in samples of XA and BJ. Chemical analysis

results showed the higher levels of PAH contaminations were found in XA and BJ,

indicating the pollution in these two cities were much severe than HK, GZ and

XM. We used TEF to evaluate the possibility of cancer risks in equivalent to

human carcinogen BaP. These analyses suggested that a long term exposure to

such environment may cause adverse health effects, such as a higher risk of

getting lung cancers. Additional new policy measures on PM2.5 emission should

be adopted to protect the deteriorating air quality and public health against the air

pollution, especially in northern cities in China.

56

CHAPTER 3

CHEMICAL AND BIOLOGICAL CHARACTERIZATION OF

FINE PARTICULATE MATTER (PM2.5) COLLECTED IN

CHINA IN SUMMER

3.1 Introduction

In chapter two, we demonstrated that the presence of PAHs in the PM2.5 samples

collected in the winter time, increase risk of lung cancer in local population. In

summer time, the use of coal burning for heat is greatly reduced. Moreover,

summer season is in general characterized by frequent and intense precipitation.

These two factors can attribute to a large reduction of air pollution in the region

(Cao et. al., 2012). Thus, we assumed that the air pollution problem is

comparatively lesser in the summer season. However some studies suggested that

air quality and visibility can be strongly affected by atmospheric photochemistry

in summer which can produce a significant amount of secondary aerosols (Pathak

et. al. 2009). The atmospheric transformation of primary and secondary pollutants

in the presence of sunlight is generally known as photochemical smog, which can

directly affect respiratory tracts and had statistically related to increased mortality

(Motley et.al., 1959). A study using a lung cell-line to test against the effects of

complex urban air mixtures in smog chambers demonstrated that secondary

aerosols contribute significantly to the inflammatory responses (Sexton et. al.,

2004). Another study revealed an association between the formation of DNA

adducts and the exposure to O3, suggesting the role of photochemical smog in an

increased risk of lung cancer in never-smokers (Peluso et. al., 2005). In

considering all these factors, we expected that PM2.5 collected in summer time

could cause negative health effects on the local residences.

In this study, PM2.5 samples were collected from 4 cities in China, including

Guangzhou (GZ), Xiamen (XM), Beijing (BJ) and Xian (XA) from July 2013 –

August 2013. We then determined the concentrations of PAH congers using GC-

MS and estimated excess lifetime cancer risk via inhalation exposure to PAHs. In

57

addition, the potency the PM2.5 samples to induce pro-inflammatory cytokines

(IL-6, IL-8, TNF-alpha) and cytochrome P450 enzymes (CYP1A1, CYP1B1)

were determined using human bronchial epithelial cells, BEAS-2B. Then a

comparison of summer and winter season data was made to provide a better

understand on the chemical characteristics of PM2.5 in association with seasonal

variations.

3. 2 Materials and Methods

Air sample collection

Two northern (BJ and XA) and two southern (GZ and XM) China cities were

selected in the present study (Fig.3.1). Air was sampled for six to eight days from

the end of July to the beginning of August in 2013. The air PM2.5 samples were

collected using quartz fiber filters (8 inch 10 inch) installed in the high-volume

samplers at a flow rate of 1.05–1.16 m3 min

-1. Seven to eight air filters were

collected from each sampling sites for a period of 24 h. The filters were then

wrapped in aluminum foils for further analysis in our laboratory.

Measurement of PAHs in air filters, risk assessment, cell culture and

treatment

The method of chemical analysis and biological experiments were conducted as

described in section 2.2 of chapter 2.

Statistical analysis

Statistical evaluations were conducted by SigmaStat 3.5. All data were tested to be

normally distributed and independent by using the Normal Plots in SigmaStat

significance were 0.05. Differences among groups were tested for statistical

significance by analysis of variance (ANOVA) followed by Duncan’s Multiple

Range test (significance at p< 0.05). Results are presented as the mean ± SD.

Groups were considered significantly different if p< 0.05.

58

3.3 Results and Discussion

Physical and chemical characterization of PM2.5 samples.

The weights of PM2.5 collected from southern (GZ, XM) and northern (BJ and

XA) cities were measured (Fig. 3.2A). Concentrations of the 16 USEPA PAHs

detected in the PM2.5 samples from the four cities were shown in (Fig 3.2B). All

16 PAHs were detected in the samples from all the sampling cities. The total PAH

concentrations were calculated by the summation of all the 16 PAHs congeners,

ranged from 0.81 to 11.2 ng/m3, led by XA, followed by BJ, GZ and XM (Table

3.1). Generally the concentrations of PAHs with shorter carbon chains

(naphthalene, acenaphthylene, acenaphthene and fluorine) were lesser than that of

the longer carbon chain congeners (Fig. 3.3 A-D) which are known to have high

carcinogenicity and may impose greater risk of lung cancer (Ravindra, et.al.,

2008).

The average total weights of the PM2.5 filters collected from the northern cities

(148.73 μg/m3air) were 3.5 times greater than that from the southern cities (41.30

μg/m3air). In contrast, the average total concentrations of PAHs in the northern

cities (15.05 ng/m3) were 4 times greater than that of the southern cities (3.75

ng/m3). These observations indicated the serious air pollution problem in the

Northern cities. In this study, the fewer amounts of PAHs in the PM2.5 samples

collected in the filters indicated the less severe pollution in the southern cities.

The higher PAH contamination in northern cities may be due to reliance on huge

coal and wood combustion for heat production (Cao et. al., 2012), while relatively

warmer southern cities showed lesser demand of heating. In addition,

contaminations in the southern cities those are closer to the coastal area are readily

dispersed by the sea wind verses inland northern cities where PM tends to be

accumulated in the local areas. Topography and climate differences may also

affect the PAH contamination in China. The average temperature and rainfall in

July was much lower in BJ and XA (average temperature 27°C and 4 inches for

precipitation) than the two southern cities (average temperature 29°C and

precipitation above 10 inches) (Weather.org, 2015).

59

The higher precipitation in the southern China might facilitate the dilution of PAH

concentrations in these cities. Moreover, Beijing was geographically surrounded

by three mountains which make difficulty in both horizontal and vertical diffusion

of pollutants, leading to a high chance of smog formation. It was reflected by the

more PM2.5 collected in filters and greater PAHs concentrations detected in our

samples.

Fig 3.1. Locations of four sampling cities on a China map

60

24.32 16.98

62.96

85.77

0

20

40

60

80

100

120

140

GZ XM BJ XA

Wei

gh

t (μ

g/m

3 a

ir)

2.94

0.81

3.85

11.2

0

2

4

6

8

10

12

14

GZ XM BJ XA

Co

nce

ntr

atio

n (

ng/

m3)

(B)

(A)

Fig 3.2. The weights of PM2.5 in the air filters and the mean concentrations of total PAHs in each

sampling site.

61

Table 3.1 PM2.5 samples from the four cities in China.

Sampling cities GZ XM XA BJ

PAH Species TEF PAH

(ng/m3)

TEQ

(ppt)

PAH

(ng/m3)

TEQ

(ppt)

PAH

(ng/m3)

TEQ (ppt) PAH

(ng/m3)

TEQ

(ppt)

Naphthalene

0.09 0.01 0.06 0.13

Acenaphthylene 0.01 0.01 0.03 0.01

Acenaphthene 0.04 n.d 0.08 0.03

Fluorene 0.04 0.02 0.06 0.04

Phenanthrene 0.12 0.06 0.35 0.20

Anthracene 0.17 0.01 0.11 0.10

Fluoranthene 0.12 0.06 0.75 0.35

Pyrene 0.13 0.06 0.66 0.29

Benz(a)anthracene 0.1 0.08 0.00 0.06 0.00 0.77 0.07 0.12 0.01

Chrysene 0.001 0.17 0.00 0.09 9.27 0.86 0.00 0.40 0.00

Benzo(b+k)fluoranthene 0.1 0.36 0.03 0.14 0.01 1.57 0.15 0.52 0.05

Benzo(a)pyrene 1 0.26 0.26 0.02 0.02 1.13 1.13 0.23 0.22

Indeno(1,2,3-cd)pyrene 0.1 0.46 0.04 0.07 0.00 1.85 0.18 0.51 0.05

Dibenz(a,h)anthracene 1 0.12 0.12 0.02 0.02 0.50 0.49 0.14 0.14

Benzo(g,h,i)perylene 0.71 0.12 2.45 0.76

Total PAHs 2.94 0.81 11.2 3.85

Total BaP

equivalents(BaPeq)

0.473 0.077

2.04 0.485

Lifetime excess cancer risk

( cancer cases per million

exposed individuals)

4.12 0.670 17.83 4.22

62

0

0.2

0.4

0.6

0.8

1

1.2

Nap

hth

alen

e

Ace

nap

hth

yle

ne

Ace

nap

hth

ene

Flu

ore

ne

Phen

anth

rene

Anth

race

ne

Flu

ora

nth

ene

Pyre

ne

Ben

z(a)

anth

race

ne

Ch

ryse

ne

Ben

zo(b

+k

)flu

ora

nth

ene

Ben

zo(a

)pyre

ne

Inden

o(1

,2,3

-cd

)py

ren

e

Dib

enz(

a,h)a

nth

race

ne

Ben

zo(g

,h,i

)per

yle

ne

Con

cen

trati

on

s of

tota

l P

AH

s (n

g/m

3 a

ir)

GZ

0

0.05

0.1

0.15

0.2

0.25

Nap

hth

alen

e

Ace

nap

hth

yle

ne

Ace

nap

hth

ene

Flu

ore

ne

Phen

anth

rene

Anth

race

ne

Flu

ora

nth

ene

Pyre

ne

Ben

z(a)

anth

race

ne

Ch

ryse

ne

Ben

zo(b

+k

)flu

ora

nth

ene

Ben

zo(a

)pyre

ne

Inden

o(1

,2,3

-cd

)py

ren

e

Dib

enz(

a,h)a

nth

race

ne

Ben

zo(g

,h,i

)per

yle

ne

Co

nce

ntr

ati

on

s o

f to

tal

PA

Hs

(ng

/m3 a

ir)

XM (B)

0.00

0.20

0.40

0.60

0.80

1.00

1.20

Nap

hth

alen

e

Ace

nap

hth

yle

ne

Ace

nap

hth

ene

Flu

ore

ne

Phen

anth

rene

Anth

race

ne

Flu

ora

nth

ene

Pyre

ne

Ben

z(a)

anth

race

ne

Ch

ryse

ne

Ben

zo(b

+k

)flu

ora

nth

ene

Ben

zo(a

)pyre

ne

Inden

o(1

,2,3

-cd

)py

ren

e

Dib

enz(

a,h)a

nth

race

ne

Ben

zo(g

,h,i

)per

yle

ne

Co

ncen

tra

tio

ns

of

tota

l P

AH

s (n

g/m

3 a

ir)

BJ

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

5.00

Nap

hth

alen

e

Ace

nap

hth

yle

ne

Ace

nap

hth

ene

Flu

ore

ne

Phen

anth

rene

Anth

race

ne

Flu

ora

nth

ene

Pyre

ne

Ben

z(a)

anth

race

ne

Ch

ryse

ne

Ben

zo(b

+k

)flu

ora

nth

ene

Ben

zo(a

)pyre

ne

Inden

o(1

,2,3

-cd

)py

ren

e

Dib

enz(

a,h)a

nth

race

ne

Ben

zo(g

,h,i

)per

yle

ne

Co

ncen

tra

tio

n o

f to

tal

PA

Hs

(ng

/m3 a

ir)

XA (D)

Fig 3.3. The concentrations and distributions of PAH congeners in each sampling site.

(A)

(C)

63

Benzo (g,h,i) perylene was measured in samples from all the sampling cities

ranging from 0.12 to 2.45 ng/m3 (Table 3.1). The concentrations were found

greater (3.21 ng/m3) in the northern (BJ and XA) than the southern cities (0.83

ng/m3). Among the sampling cities, the samples from XA were measured with the

highest level of benzo (g,h,i) perylene concentration (2.45 ng/m3). Similar to a

study conducted in 2008, the most abundant PAHs detected in PM sample from

XA was benzo (g,h,i) perylene, which emission is closely associated with

increased traffic-activities (Shen et. al., 2010).

64

Table 3.2 Diagnostic ratios of PM-bounded PAHs in different cities of China.

Diagnostic

ratio

Ind/

(Ind+BghiP)

BaP/

BghiP

Flu/

(Flu+Pyr)

Ant/

(Ant+Phe)

BaA/

(BaA+Chr)

Gasoline

engine

>0.18 0.5-0.6 <0.5 >0.5 >0.49

Diesel

engine

0.35-0.7 0.3-0.4 >0.5 >0.35 >0.68

Coal

burning

>0.56 0.9-6.6 >0.57 >0.24 >0.46

Non-

burned

fossil fuels

inputs

- >0.58 - <0.1 -

Natural gas

combustion

>0.32 - >0.49 >0.12 >0.39

GZ 0.386±0.03 0.301±0 0.480±0.01

0.577±0.007

0.335±0.02

XM 0.361±0.06 0.225±0.320 0.526±0.017 0.267±0.171 0.350±0.217

XA 0.422±0.028 0.444±0.135 0.521±0.03 0.209±0.129 0.713±0.096

BJ 0.432±0.086 0.354±0.188 0.546±0.012 0.155±0.151 0.235±0.040

65

Cancer risks via inhalation of PAHs.

B[a]P is a surrogate marker to indicate carcinogenic risk of airborne PAHs. Thus,

in our study, the total B[a]P equivalent (B[a]Peq) were determined using toxic

equivalent factors (TEF) and the concentrations of the individual PAHs (Table

3.1). The calculated value of 2.04 ppt from XA showed the highest calculated

B[a]Peq among the four cities, followed by BJ (0.485 ppt), GZ (0.473 ppt) and

XM (0.077 ppt) (Table 3.1). The estimated excess lifetime cancer risk was shown

in Fig. 3.4. For XA, BJ and GZ, the estimated lifetime cancer risk were

comparatively greater, reaching 17.83, 4.22 and 4.12 extra-cancer cases per

100,000 exposed individuals. The relative lower exposure risk was calculated in

XM with 0.670 extra-cancer cases in 100,000. Therefore in the summer season,

the serious lifetime cancer risk was in XA, BJ and GZ. Recent studies on Chinese

population suggested that lung cancer caused by inhaled exposure to PAHs was

1.6%, corresponding to an excess annual lung cancer incidence rate of 0.65x 10-5

(Zhang et. al., 2009). In this context, however, the estimated results of our study

suggested a comparable high cancer risk is associated with PAH exposure.

4.12

0.67

4.22

17.83

0

2

4

6

8

10

12

14

16

18

20

GZ XM BJ XA

Exce

ss li

fe t

ime

can

cer

risk

s (p

er

mill

ion

exp

ose

d in

div

idu

als)

Fig 3.4. Calculated excess lifetime cancer risks (per million exposed individuals) of

the five sampling sites.

66

Coal combustion and vehicle emission were the common sources of PAHs in

PM 2.5.

The ratio of the individual PAH concentration can be calculated and used to trace

possible emission sources (Schauer et al., 2003). Among the PAH compounds,

BkF, Ind, and BghiP are considered as the tracers of vehicle emission (Miguel and

Pereira 1989; Li and Kamens 1993; Harrison et al. 1996), whereas Phe, Ant, Flu,

Pyr, BaA, Chr, BaP, and BghiP are recognized to be the source of coal

combustion and coke production (Duval and Friedlander 1981). Thus, five

diagnostic ratios were calculated and shown in Table 3.2. For GZ, the gasoline

and diesel engine contributed to the major sources of the emission. On the other

hand, the sources of PAHs in other cities were mainly due to coal and diesel

engine combustion.

Biological characterization of the effects of PM2.5 extracts on the expression

levels of pro-inflammatory cytokine and xenobiotic metabolizing enzymes in

human bronchial cells.

Human bronchial epithelial cells (BEAS-2B) were exposed to the PM2.5 extracts

and gene expression levels of pro-inflammatory cytokines and xenobiotic

metabolizing enzymes were measured. For cell cytotoxicity study, no noticeable

effects were observed in the cells exposed to PM2.5 samples extracts (Fig. 3.5A).

For inflammatory responses, the samples from BJ and XA were found to

significantly induce the gene expression levels of interleukin-6 (IL-6), but not IL-

8 and tumor necrosis factor-alpha (TNF-) (Fig.3.5B). Among different

cytokines, IL-6 is an important pro-inflammatory cytokine produced by epithelial

cells. In addition, gene expression levels of xenobiotic metabolic enzymes

(CYP1A1 and CYP1B1) were found to be up-regulated in the treatment with

PM2.5 extracts (Fig. 3.5C). It was reported that CYP1 enzymes actively take part

in detoxifying PAHs (Nebert et. al., 2004). Since CYP enzymes belongs to

xenobiotic metabolizing pathway. The induction of CYP1A1 and CYP1B1

enzymes illustrated the response of the biological system to the presence of PAH

contaminants in the samples.

67

0

50

100

150

Solvent control GZ XM BJ XA

% o

f ce

ll v

iab

ilit

y

MTT assay: BEAS-2B cells were exposed to PM2.5 for 24-h

Fig 3.5. Cytotoxicity and gene expression levels of pro-inflammatory cytokines and

xenobiotic metabolic enzymes upon summer extracts treatment for 24h in BEAS-2B

cells. (A) The MTT assay showed no cytotoxicity was found with the summer PM2.5

sample extracts upon exposure to BEAS-2B cells. (B) Gene expression levels of

cytochrome p450 enzymes (CYP1A1 and CYP1B1) were significantly up-regulated by

the summer extracts exposure of all the sampling sites (*p<0.05). (C) Relative mRNA

expression levels of interleukin-6 (IL-6) was significantly up-regulated in BJ and XA

sampling sites as compared to the blank filter control (*p<0.05).

A

B C

* *

*

*

* * *

* * *

68

Table 3.3 Comparison of winter and summer season filters weights and total PAHs

in PM2.5

Sampling

location

Sampling

cities

Winter Average

total

Summer Average

total

Weight

of dust

Filters

(μg/m3)

Southern

cities

HK 42.91 151.15 - 41.3

GZ 68.32 24.32

XM 39.92 16.98

Northern

cities

BJ 223.98 456.41 62.96 148.73

XA 232.43 85.77

Total

PAHs

(ng/m3)

Southern

cities

HK 3.35 14.47 - 3.75

GZ 6.77 2.94

XM 4.35 0.81

Northern

cities

BJ 80.45 148.15 3.85 15.05

XA 68.05 11.2

69

3.4 A comparison of winter and summer sample data

Since the summer samples were collected only from the four cities in China, we

didn’t have the HK summer samples for the comparison.

Comparison of data in the northern and southern cities in winter and

summer.

To compare the effects of seasonal changes on the quantity and chemical

characteristics of PM2.5 collected, our data indicated that the amount of filter

samples collected per unit time in the winter season were notably greater.

Moreover, the concentrations of PAHs detected in the PM2.5 samples were

significantly higher. In the northern cities, the average total PM2.5 filters weights

of the winter samples (456.41 g/m3 air) were more than 3 times greater than the

summer samples (148.73 μg/m3 air) (Table 3.3). In northern cities, the average

total concentrations of PAHs in the winter samples (148.5 ng/m3 air) were about

10 times greater than the summer season (15.05 ng/m3 air) (Table 3.3). In contrast,

in the southern cities, the average total PM2.5 filters weights of the winter samples

(151.15 μg/m3 air) were 3.6 times greater than in the summer season (41.3 μg/m

3

air). The average total PAH concentrations (14.47 ng/m3 air) were found to be

around 4 times greater than the summer season (3.75 ng/m3 air). To compare the

air pollution problem among the cities of the northern or southern region, our data

showed that XA and BJ were found to be seriously polluted in the respective

region in both sampling seasons.

These data suggested that the higher the filter weights the greater the PAHs

concentrations. In a study from Peking University, He et. al., (2006) reported that

PM2.5 concentrations at Shenzhen, China was 34.9μg/m3 in summer and

99.0μg/m3 in winter; while another study carried out by He et.al. (2001) from

Tsinghua University found greater PM2.5 concentrations in Beijing in winter than

the summer. Taken together the levels and contamination profile of PM emission

was influenced by seasonal variations (Feng et. al., 2006; Niu et. al., 2006 and Hu

et. al., 2005).

70

3.5 Conclusion

In summer, fifteen priority PAHs were identified in all the sampling cities. From

the chemical analysis, we understood that the amounts of PAH concentrations in

the northern cities (BJ and XA) were greater than southern cities (GZ and XM)

indicating the pollution in BJ and XA were severe than GZ and XM. A seasonal

comparison suggested that the greater levels PM2.5 were collected in the winter

time. In considering the analytical and biological analysis in term of seasonal

variations, we assumed that a long term exposure to such environment may cause

adverse health effects, such as a higher risk of getting lung cancer. A strict

regulation of criteria standard for PM2.5 at both local and national levels should be

enforced to protect the deteriorating air quality and public health, especially in

northern cities in China.

71

CHAPTER 4

DETERMINATION OF THE CONCENTRATION OF

PERFLUORINATED COMPOUNDS (PFCs) IN FINE

PARTICULATE MATTER (PM2.5) IN CHINA AND THEIR

EFFECTS ON FETAL LIVERS

4.1 Introduction

In the previous chapters 2 and 3, we measured the concentrations of PAHs in

PM2.5 collected from different cities in China during winter and summer. Our

data suggested that a long-term exposure to such environment may cause adverse

health effects, such as a higher risk of lung cancers. Besides PAHs, perfluorinated

compounds (PFCs) are global pollutants that is known to have long environmental

and biological half-life (Ellis et al., 2004; Wallington et al., 2006; Young et al.,

2007; Martin et al., 2005), are widely detected in humans and wildlife (Zhao et.

al., 2011). PFCs can be transported in air and adsorbed on PM. A study in

Keihanshin in Japan suggested that inhalation is a potential source of PFCs

(perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) intake

(Harada et. al., 2005). Despite the worldwide ban on the uses of PFOS, it is still

being produced and used in China. PFOS has a long half-life of 4 years in

humans, suggesting that continuous exposure of PFOS could increase body

burden to levels that may result in adverse health outcomes (ATSDR 2009).

Therefore, in the first part of this chapter, we measured the concentrations of

PFCs in the winter dust samples collected from the northern cities (Beijing, BJ;

Xian, XA) and southern cities (Hong Kong, HK; Guangzhou, GZ; and Xiamen,

XM) in China using LC-MS/MS techniques.

The inhalation of PFCs through PM2.5 dust, subsequently get into our blood

circulation via lung alveoli. Cumulating reports demonstrated the presence of

PFOS in human maternal blood, umbilical cord blood and placenta, suggesting

that human fetus is potentially exposed to PFOS via their mothers' blood (Midasch

et. al., 2007; Inoue et. al., 2004; Kim et. al., 2011). In the second part of this

72

chapter, we used mouse model and high throughput transcriptomic technology, to

determine the potential effects of prenatal exposure to PFOS on fetal livers.

4.2 Materials and Methods

Air samples collection

The method of sample collection and description of sampling cities were

described in section 2.2. of chapter 2.

Measurement of PFCs in air filters

The concentration of PFC in the PM2.5 collected from different cities of China was

determined using high-performance liquid chromatography with an electrospray

tandem mass spectrometer (LC/MS/MS) as previously described (Sasaki et.al.,

2003; Harada et.al., 2005; Zhao et.al., 2011). Briefly, one-quarter of the air filters

were used for the extraction. Deuterated PFCs internal standards at the

concentration of 10 ppb (sodium perfluoro-1-hexane[18

O2] sulfonate, MPFHxS;

sodium perfluoro-1-[1,2,3,4-13

C4 ] octanesulfonate, MPFOS; perfluoro-n- [13

C4]

butanoic acid, MPFBA; perfluoro-n-[1,2-13

C2] hexanoic acid, MPFHxA;

perfluoro-n-[1,2,3,4-13

C4 ] octanoic acid, MPFOA; perfluoro-n-[1,2,3,4,5-13

C5 ]

nonanoic acid, MPFNA; perfluoro-n-[1,2-13

C2] decanoic acid, MPFDA;

perfluoro-n-[1,2-13

C2 ] undecanoic, MPFUdA; perfluoro-n-[1,2-13

C2] dodecanoic

acid, MPFDoA were added into the extracts. The homogenate was extracted by

1mL of 0.5M tetra-N-butyl ammonium hydrogen sulfate (TBA, Sigma-Aldrich,

GmbH, Switzerland) solution and 2mL of 0.25M sodium carbonate buffer in a 15-

mL polypropylene tube. After being thoroughly mixed, 5mL of methyl terta-butyl

ether (MTBE, Sigma-Aldrich, GmbH, Seelze) was added to the solution, and the

mixture was shaken at 280rpm for 40 minutes. After being separated by

centrifugation at 3000 rpm for 10 minutes, adequate volume of MTBE (4 mL) was

removed from the solution, and the process was repeated twice. The solvent was

allowed to evaporate under nitrogen (N-EvapTM

112, MA, USA) and then

reconstituted in 1mL solution of ammonium acetate and acetonitrile (6:4 ratios).

After centrifugation, the supernatants were collected in auto sampler vials (AMB

ram vial 9mm THD, Grace, USA).

73

LC-MS/MS system for determination of PFCs

The PFCs standards (Perfluoro-n- butanoic acid, PFBA; perfluoro-n-hexanoic

acid, PFHxA; perfluoro-n-octanoic acid, PFOA; perfluoro-n-nonanoic acid,

PFNA; perfluoro-n-decanoic acid, PFDA; perfluoro-n-undecanoic acid, PFUdA;

perfluoro-n -dodecanoic acid, PFDoA; sodium perfluoro-1-hexanesulfonate, L-

PFHxS; sodium perfluoro-1-octanesulfonate, L-PFOS) were used to obtain the

standard curve.

Analysis was performed using LC/MS/MS (Agilent 1200 series, Agilent 1200

Series 6410 Triple Quad LC/MS, USA) with a sample volume of 30μL. Sample

separation was achieved in the Zorbax Eclipse plus C8 column (2.1x 100mm, 3.5

micron), using a mobile phase of 10 mM ammonium acetate/water (v/v) at a flow

rate of 0.25 mL/min. The gradient profile was as follows: a linear increase from

40% to 90% acetonitrile (ACN) solution in 0-5.5 min, held at 90% for 4 min, then

held at 100% for 1min. PFCs were quantitatively analyzed by single mass mode

using characteristic ions at m/z.

Quality control/quality assurance

The limit of detection (LOD) was determined as the concentration of an individual

PFCs detected in a sample with a signal-to-noise ratio of 3. The concentrations of

PFCs in the method blank were less than the LOD. All the results were expressed

as per one fourth of air filter.

Risk assessment

Inhalation exposure (Einhal, pg/day) was calculated as publised previously (Shoeib

et. al., 2011). EInhal= Cair x V air x F uptake fraction .Where Cair is the concentrations of

PFCs (pg/m3) in PM2.5, V air is the volume inhaled (m

3/day).

74

Experimental animal and PFOS dosing

ICR mice were purchased and acclimatized for one week before experiment. The

mice were breed and ascertained of mating by the sperm positive vaginal smear of

the females. The mice were divided into 4 groups including a control and 3 PFOS-

treated groups, housed in polypropylene cages with sterilized bedding. The

treatment was started on gestational day 0.5 (GD 0.5) through GD 17. PFOS

(98% purity, sigma Aldrich) was dissolved in DMSO (<0.4%) and the exposed

groups were orally administered with 0, 0.3, 1 and 3 mg/kg/day PFOS. The

animals were maintained in a controlled temperature (24°C) and light (12h/12h

light-dark cycles) and given with standards foods (LabDiet, 5001Roden Diet) and

water ad libitum. On GD 17, pregnant mice were sacrificed by cervical dislocation

and fetal livers were collected. Total RNA was prepared for library construction,

followed by RNA sequencing using the MiSeq platform according to the

manufacturer’s protocols. All experimental animals were maintained according to

the guidelines and regulations of HKBU. The workflow of this study is shown in

Figure 4.1.

75

Fig 4.1. A flow diagram illustrates the experimental procedure for RNA sequencing,

including PFOS exposure, sample collection, library construction, transcriptome

sequencing, global gene expression analysis and pathway analysis.

76

RNA preparation, cDNA synthesis and real-time PCR quantification

RNA isolation was conducted as previously described (Wan et. al., 2012).

Concentration of RNA was measured using a Nanodrop 1000 Spectrophotometer

(Thermo Scientific, USA). The quality of RNA with A260/A280 ratio of between

1.7 and 1.9 was used. For the cDNA synthesis, High Capacity RNA-to-cDNA

Master Mix and 100 ng of total RNA was used in the reaction (Applied

Biosystems, Foster City, CA).

RNA Isolation, cDNA Library Construction and Illumina Deep Sequencing

Total RNA was isolated from GD17 fetal liver using TRIzol reagent (Life

Technologies, CA, USA). The RNA concentration was measured using Qubit®

RNA Assay Kit in Qubit® 2.0 Flurometer (Life Technologies, CA, USA). RNA

samples (300 ng) with RNA Integrity Number (RIN) greater than 8, as determined by

the Agilent 2100 Bioanalyzer system, was used for library construction (Agilent

Technologies, CA, USA). Four independent cDNA libraries were prepared for RNA

sequencing using the TruSeq Stranded mRNA LT Sample Prep Kit (Illumina, San

Diego, USA) following manufacturer’s recommendation. Index codes were ligated

and used as identification for individual samples. Firstly, mRNA was purified from

the total RNA using poly-T oligo-attached magnetic beads (Illumina, San Diego,

USA), followed by fragmentation using divalent cations. First strand cDNAs was

synthesized using random oligonucleotides and SuperScript II. Then second strand

cDNA was synthesized using DNA polymerase I and RNase H. Overhangs were

blunted by using exonuclease/polymerase, followed by 3/ end adenylation and

ligation using Illumina PE adapter oligonucleotides. DNA fragments with adaptor

molecules were enriched by 15 cycles of PCR reaction. The libraries were then

purified using the AMPure XP magnetic bead system and were quantified using the

Agilent Bioanalyzer 2100 system. Before subjected to sequencing, the libraries were

normalized and pooled together in a single lane on an Illumina MiSeq platform.

Working principal of illumine MiSeq platform is illustrated in Figure 4.2.

77

Step1: Sample

preparation

Step2: Library

construction

Step3: Cluster

generation

Step4:

Sequencing

Attach DNA to flow cell

Fig 4.2. A schematic flowchart shows the working principal of using Illumina MiSeq

platform.

Bridge

amplification

Cluster

formation

78

Paired-end reads, each of 151 bp read-length, were sequenced. Adapters, reads

containing poly-N were first trimmed and the sequence-reads were dynamically

trimmed according to BWA's− q algorithm (Li & Durbin, 2009). All the

downstream analyses were based on quality trimmed reads.

Differential expression and GO enrichment analysis

Sequencing reads were mapped to mouse reference genome (GRCm38/mm10)

using Novoalign v3.00.05 with parameter–r to report all multi-mapped reads

(http://www.novocraft.com/). Alignment files were parsed via Samtools. Briefly,

the number of reads mapping to each transcript in each sample were summarized

generate a count table (Li, et. al, 2012). Read count data were then subjected to

differential expression analysis using the edge R package (Robinson et. al., 2010).

Samples with identical treatment were considered as biological replicate. B&H

corrected p-value <0.05 &|log2 (fold change)| >1.5 was set as the threshold for the

determination of significant differential expression. Expression in terms of TMM-

normalized-FPKM of transcripts were obtained independently using RSEM

pipeline (Li & Dewey, 2011). Dysregulated genes were subjected to KEGG

pathway analysis in the Database for Annotation, Visualization and Integrated

Discovery (DAVID) Tools to decipher the deregulated molecular interaction

networks (Huang et. al., 2009a).

Verification of RNA-sequencing data by real time-PCR (RT-PCR)

Based on the results from the RNA-sequencing data, RT-PCR verification of

selected genes was conducted for the independent cohort of sample (n: 6).The

primer list was shown as Table 4.1.

79

Real-time PCR was conducted with a program that consisted of 3 min at 95 °C

followed by 40 cycles of 95 °C for 15 s, 56 °C for 20 s and 72 °C for 30 s.

StepOne Real-time PCR system using SYBR Green Master mix (Applied

Biosystems) was used for the quantification of cDNAs from samples. Data

normalization was performed using the transcript levels of mouse actin.

Cell culture and treatment

Mouse primary liver cells (AML-12) were cultured in DMEM high glucose

medium supplemented with 10% FBS (HyClone, Perbio, Thermo Fisher

Scientific, Carmlington, UK) and antibiotics (50U/ml penicillin and 50μg/ml

streptomycin) (Invitrogen, CA, USA).

Reactive Oxygen Species (ROS) assay

ROS was measured as described previously (Law et. al., 2012). AML-12 cells

were seeded at the density of 0.5 x 104 in triplicate into 96-well plate. After 24h of

an incubation period, the cells were incubated with 10mM H2DCF-DA (Molecular

Probes, Invitrogen) for 1 hour followed by 4 hours incubation with PFOS (100

and 400μM) and H2O2 (200μM) treatment (DMSO <0.005%). DCF fluorescence

was then measured at excitation 495 nm/emission 530 nm using the multi label

reader VICTOR X4.

Table 4.1 List of mouse primers used in this study

Primers Forward sequences Reverse sequences

Cyp2j6 CCCTCTACCCAGAAGTCCAA TTCTGGCCAATCACCCTATC

Cyp4a10 ATCTCCTTAATGACCCTAGACACTG GCCTGGAGGTAGGTCCTGTAA

Cyp2e1 CCAAAGAGAGGCACACTTCC TCAGAAAGGTAGGGTCAAAAGG

Cyp2e40 ATCTGGTTTTTGTGGGACA CATTGTCAATCTCTTCCTGGACT

Cyp4f16 GGATTGTTGACCCTGCATTT GGCTTCAGGAAGCGTAAAAA

Cyp4a31 CAACACATCTCTTTAATGACCCTAGA ATGGCCTGGAGGTAGGTCTT

Cyp4a14 GATGGAGTCAGGGCAGTC AGCCAGAGACAAAAGCAGGTA

80

Statistical analysis

Statistical evaluations were conducted by SPSS 16.0. Student’s t-test was

performed to test the level of significances (p< 0.05) of the tested genes.

4.3 Results and Discussion

PFC concentrations in the PM2.5 samples from China.

Air filters were collected from the five cities in southern (HK, GZ and XM) and

northern (XA and BJ) China. The weights of PM2.5 collected on the filters were

measured (Fig 4.3A). The weights of PM2.5 per m3 air collected in the northern

cities of China were approximately 4 times higher than that of the southern cities,

weighted in average of 228g and 50g respectively. The concentrations of PFCs

in PM2.5 per m3 air flow of the five selected cities were shown in Fig 4.3B and

details were listed in Table 4.2.

Among the 9 measured PFC compounds, the levels of PFHxS in all the samples

were below the limit of detection. The other 8 PFCs (PFOS, PFDoA, PFUdA,

PFDA, PFNA, PFOA, PFHxA and PFBA) were detected in the samples from GZ,

XM, XA and BJ, while PFDoA was not found in the HK samples (Fig. 4.4A-E).

Total PFC concentrations calculated by the summation of all PFC compounds,

ranged from 121.2 to 192.2pg/m3, leading by GZ, followed by XA, BJ, XM and

HK. The levels of PFCs detected in this study, were relatively higher than

previous studies on PFOS contamination in ambient air from Japan (Sugita et.

al.2007; Harada et. al., 2005; Sasaki et. al., 2003).

PFOS was the most abundant species among the 9 PFCs measured with the

highest concentrations detected in most sampling sites ranging from 28.25- 99.4

pg/m3. However, its levels were found to be noticeable higher (> 72pg/m

3) in the

northern cities (XA and BJ) versus in all the three southern cites (< 65pg/m3 air).

In this study PFOS, PFHxA, PFBA and PFOA were predominantly measured in 5

sampling cities reflecting the very low volatility of these compounds. Gewurtz et

al. 2009 reported ionic PFCs in the indoor window film in Toronto with a profile

81

dominated by PFOA, PFDA, PFNA, and PFOS which is consistent with our

findings.

A

B

42.91

68.32

39.92

232.44 223.98

0.00

50.00

100.00

150.00

200.00

250.00

300.00

HK GZ XM BJ XA

Wei

gh

t (μ

g/m

3 a

ir)

121.21

192.28

139.06 156.97

172.41

0

50

100

150

200

250

HK GZ XM BJ XAConce

ntr

atio

ns

of

tota

l P

FC

s

(pg/m

3 a

ir)

Fig 4.3. The weights of PM2.5 dust in air filters and the mean concentrations

of total PFCs in each sampling site.

A

82

Table 4.2 Total concentrations (pg/m3) of PFCs and the average concentrations of

inhalation exposure (ng/day).

PFCs HK GZ XM BJ XA

Con

(pg/m3)

Inhala

tion

expos

ure

(ng/

day)

Con

(pg/m3)

Inhal

ation

expo

sure

(ng/

day)

Con

(pg/m3)

Inhalat

ion

exposu

re(ng/

day

Con

(pg/m3)

Inhala

tion

expos

ure(ng

/day

Con

(pg/m3)

Inhala

tion

expos

ure(ng

/

day

PFOS 99.45 1.59 72.39 1.15 28.25 0 74.77 1 70.78 1

PFHxS 0 0 0 0 0.00 0 0.00 0 0.00 0

PFDoA 0 0 0.36 0.00 0.33 0 1.90 0 0.36 0

PFUdA 0.84 0.01 0.36 0.00 0.41 0 2.00 0 0.43 0

PFDA 0.60 0.00 0.69 0.01 0.79 0 1.31 0 0.42 0

PFNA 2.28 0.03 2.646 0.04 2.78 0 3.96 0 3.21 0

PFOA 3.89 0.06 11.73 0.18 16.81 0 14.05 0 4.52 0

PFHxA 3.01 0.04 16.84 0.26 18.96 0 27.66 0 49.32 1

PFBA 11.12 0.17 87.23 1.39 70.72 1 31.32 1 43.37 1

Total 121.2 1.93 192.28 3.07 139.06 2 156.97 3 172.41 3

83

PFOS exhibited the highest concentration in HK with an average mean of

99.45pg/m3 which comprised 82% of the total PFC content while PFHxA, PFBA

and PFOA exhibited 49, 87 and 16.81pg/m3 respectively for XA, GZ and XM

(Fig.4.5A).

PFCs concentrations of samples from northern China (164.69 pg/m3) were

higher than that from the southern cities (150.8 pg/m3), showing the less severe

pollution in the southern cities. As we do not have any direct evidence in terms of

the sources of PFCs, it is believed that the traffic density (Sasaki et. al., 2003)

might be responsible for the PFC contamination levels in the northern cities. Other

possible sources of PFC emission can be found in fire extinguishers and industrial

products. It was reported that PFOS was one of the ingredients in fire

extinguishing media (Moody et. al., 2003). In addition, Teflon contained PFOA is

widely used in paint sealant coating, oil additives and grease manufacturing

purposes (Harada et. al., 2005).

84

PAHs concentrations of samples from northern China were at least 10 times

Fig 4.4. The concentrations of PFC congers in different cities. (A) PFOS and PFBA were the

most abundantly PFCs detected in HK samples while PFHxS, PFDoA, PFUdA, and PFDA

were found below the LOD. (B) In GZ, PFBA and PFOS were found to be the major PFC

congeners. (C) In XM, PFBA exhibited the highest concentration followed by PFOS, PFHxA,

PFOA, and PFNA. (D) In BJ, PFOS was most abundantly found while other PFCs were

detected at relatively low concentrations. (E) In XA, PFOS, PFHxA, and PFBA were the most

abundantly found PFCs. Error bars represents standard deviation.

0

50

100

150

200

250

Co

nce

ntr

atio

n (

pg/

m3 )

HK

020406080

100120

PFO

S

PFH

xS

PFD

oA

PFU

dA

PFD

A

PFN

A

PFO

A

PFH

xA

PFB

A

Co

nce

ntr

atio

n (

pg/

m3 )

GZ

0.00

20.00

40.00

60.00

80.00

100.00

120.00

Co

nce

ntr

atio

n (

pg/

m3)

XM

0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

160.00

Co

nce

ntr

ati

on

(p

g/m

3)

BJ

0.00

50.00

100.00

150.00

PFOS PFHxS PFDoA PFUdA PFDA PFNA PFOA PFHxA PFBA

Co

nce

ntr

atio

n (

pg/

m3 )

XA

A

C D

E

B

85

PFCs compositions in different cities of China.

HK

PFOS exhibited the highest concentration in HK with an average mean of

99.45pg/m3 which constituted 82% of the total PFC content. Among the other

PFCs, PFBA (11.12 pg/m3), PFHxA (3pg/m

3), PFOA (3.89 pg/m

3) and PFNA

(2.28pg/m3) were also dominant which constituted 9.17, 3.21, 2.48 and 1.88% of

the total PFC content respectively while PFHxS and PFDoA were found below

the limit of detection (LOD) (Table 4.2; Fig. 4.4A).

GZ

In GZ, PM2.5 samples were dominant with PFBA (87.23 pg/m3) which formed

45% of the total PFC content. In contrast, PFOS (72.39 pg/m3), PFHxA (16.84

pg/m3) and PFOA (11.3 pg/m

3) were detected at 37.65, 8.76, 6.10% of total PFC

content respectively (Table 4.2; Fig. 4.4B).

XM

In XM, PFBA (70.71pg/m3) exhibited the highest concentration followed by

PFOS (28.25 pg/m3), PFHxA (18.96 pg/m

3), PFOA (16.81 pg/m

3) and PFNA

(2.77pg/m3) respectively. Among the PFC compounds, PFBA and PFOS

consituted 50.58 and 20.31% of the total PFC content respectively (Table 4.2; Fig.

4.4C).

86

Fig 4.5. A comparison of the average concentrations and human inhalation

exposure of PFCs. (A) PFOS, PFOA, PFBA and PFHxA were abundantly found

in PM2.5 samples. (B) The inhalation exposure data from different cities.

0

50

100

150

200

250

PFOS PFHxS PFDoA PFUdA PFDA PFNA PFOA PFHxA PFBA

Co

nce

ntr

ati

on

(p

g/m

3 a

ir)

Comparison of citywise abundance of PFCs in PM2.5

samples

HK GZ XM BJ XA

0

0.5

1

1.5

2

2.5

3

3.5

HK GZ XM BJ XA

Inh

ala

tion

exp

osu

re (

ng/d

ay)

Inhalation exposure of PFCs in adults based on

concentrations

(A)

(B)

87

BJ

Among the PFCs, PFOS (74.76 pg/m3) was most abundantly found in BJ while

other PFCs were detected at relatively low abundance with PFHxS below the

LOD. Among the PFC compounds, PFOS (74.76 pg/m3), PFBA (31.31pg/m

3),

PFHxA (27.65pg/m3) and PFOA were the dominant congeners contributing to

47.6, 19.9, 17.6 and 12.08 % of the total PFC content respectively (Table 4.2; Fig.

4.4D).

XA

In XA, PFOS exhibited the highest concentration (99.45pg/m3) which constituted

41% of the total PFC content. PFBA (43.36 pg/m3), PFNA (3.21pg/m

3) and PFOA

(4.52 pg/m3) were also detected in the samples with PFHxS below the LOD

(Table 4.2; Fig. 4.4E).

These data altogether suggested that the determination of PFCs in the PM2.5

samples allowed us to estimate human exposure risk (Sasaki et.al. 2003). Recent

studies indicated that men showed a higher exposure risk to PFOS as compared to

women (Yeung et. al., 2008). More importantly the detection of PFOS in

umbilical cord blood suggests fetal exposure risk (Calafat et al., 2006a; Calafat et

al., 2006b) to PFOS via maternal blood circulation.

Human exposure to PFCs by inhalation.

An adult male inhale 20m3 of air daily (Arrieta et al., 2003), thus to estimate the

inhalation exposure, we multiplied the PFCs concentrations with the volume of air

inhaled. Accordingly, the daily intake was estimated to be 1.93, 3.07, 2, 3, and 3

ng/day for HK, GZ, XM, BJ and XA respectively (Fig. 4.5B). Among the PFCs,

PFOS was the dominant inhaled compound representing 1.59, 1.15, 1 and 1ng/day

exposure for HK, GZ, BJ and XA while PFOA was inhaled at 0.06, 0.18ng/day in

HK, GZ respectively (Table 4.2).

A study in Canada reported the dietary intake of 110ng/day for PFOS and

70ng/day for PFOA (Tittlemier et. al., 2007). In our study, we estimated that the

intake of total PFCs by inhalation represented about 91% (HK), 41% (GZ), 37%

88

(BJ) and 37% (XA) for PFOS and for PFOA 2% (HK) and 4% (GZ) of the

Canadian dietary contribution. But another study reported (Shoeib et. al., 2011)

28% of the PFCs intake by inhalation of the Canadian dietary contribution. In this

study, the daily intakes of PFOS in Chinese cities were higher compared to that of

10 and 100 pg/day inhalation exposure of Fukuchiyama city and Oyamazaki town

of Japan (Sasaki et.al. 2003) respectively. Published data suggested that PFOS

through inhalation was little compare to drinking water (Harada et. al., 2003;

Sasaki et. al., 2003). Thus, human exposure to PFCs via inhalation suggests that a

continuous exposure of PFCs could increase body burden to levels that would

result in adverse health outcomes (ATSDR 2009). Therefore, in our subsequent

investigation, we focused on PFOS to determine its adverse health effects in

animal offspring.

89

4.4 RNA-Sequencing Revealed A Disruption Of Hepatic Fatty Acid

Metabolism In Prenatal PFOS-exposed Mouse Fetal Liver.

Illumina RNA-Seq.

We obtained 6.36, 6.01, 7.37, and 6.06 million quality trimmed Illumina reads for

the control and treatment groups 0.3, 1, and 3 mg/kg/day of PFOS respectively, to

give the total clean bases of 0.94 Gb for the control group, 0.89 Gb for the low dose

and 1.09 Gb for the medium dose and 0.90 Gb for the high dose treatment groups

(Table 4. 3).

Gene expression and differential gene expression.

In the comparison of transcriptome data among the control group and PFOS-

treatment groups, a total of 2084 genes were identified to be differentially expressed

(B&H corrected p-value <0.05 & |log2 (fold change)|>1.5). These included 719 up

and 1365 down differentially expressed genes in the PFOS-treatment groups as

compared to the control group (Table 4.3). The differentially expressed genes were

further analysed according to GO functional enrichment analysis. The top five

pathways involved in molecular functions, included metal ion binding, protein

tyrosine kinase activity, protein binding, heme binding and monooxygenase activity

(Fig. 4.6). In “biological process”, it included metabolic process, protein

phosphorylation, oxidation-reduction process, angiogenesis, acyl-CoA metabolic

process (Fig. 4.7).

90

Table 4.3 Summary of the sequencing results

Control Low Medium High

Category Measure Reverse Forward Reverse Forward Reverse Forward Reverse Forward

Raw Reads count 3484717 3484717 3317085 3317085 3935207 3935207 3319617 3319717

Base 5238164

97

5244835

15

4982872

43

4991129

49

5899327

53

5919435

22

4985307

74

4995390

76

Quality

trimmed

Reads count 3180724 3180724 3003986 3003986 3685395 3685395 3028350 3028350

Base 4730711

68

4711959

51

4471037

09

4452170

05

5469249

78

5468620

15

4500951

74

4492179

27

Mapping

GRCm

38

% mapped 99.37 99.44 99.51 99.34

No. uniquely

mapped

77.41 82.64 78.13 77.41

Total genes differentially

expressed

2084

Total up regulated genes 719

Total down regulated genes 1365

91

0 20 40 60 80 100 120

antibiotic transporter activity (MF)

non-membrane spanning protein tyrosine kinase activity (MF)

carboxylesterase activity (MF)

oxidoreductase activity, acting on paired donors, with

incorporation or reduction of molecular oxygen (MF)

electron carrier activity (MF)

heme binding (MF)

protein tyrosine kinase activity (MF)

monooxygenase activity (MF)

transferase activity, transferring phosphorus-containing groups

(MF)

protein kinase activity (MF)

catalytic activity (MF)

oxidoreductase activity (MF)

kinase activity (MF)

nucleic acid binding (MF)

ATP binding (MF)

transferase activity (MF)

hydrolase activity (MF)

nucleotide binding (MF)

protein binding (MF)

metal ion binding (MF)

Fig 4.6. Enrichment analysis of Gene Ontology Molecular Functions

(X-axis indicates the molecular functions of the genes) . Top 20 pathways

92

0 10 20 30 40 50 60 70 80

antibiotic transport (BP)

glomerular filtration (BP)

regulation of systemic arterial blood pressure by renin-

angiotensin (BP)

positive regulation of complement activation (BP)

threonine biosynthetic process (BP)

linoleic acid metabolic process (BP)

cellular response to mechanical stimulus (BP)

oligopeptide transport (BP)

long-chain fatty acid metabolic process (BP)

drug transmembrane transport (BP)

regulation of Rab GTPase activity (BP)

acyl-CoA metabolic process (BP)

protein complex assembly (BP)

positive regulation of angiogenesis (BP)

angiogenesis (BP)

protein phosphorylation (BP)

oxidation-reduction process (BP)

phosphorylation (BP)

transport (BP)

metabolic process (BP)

Fig 4.7. Enrichment analysis of Gene Ontology Biological Process (X-axis

indicates the biological process). Top 20 pathways

93

KEGG pathway analysis.

All the activated genes were subjected to Kyoto Encyclopedia of Genes and

Genomes (KEGG) analysis. Our results highlighted that prenatal exposure to PFOS

caused the deregulation of different metabolic pathways (Fig. 4.8 A). Among those,

we found an induction of a subset of genes involving in fatty acid metabolic

pathways including PPAR signaling pathway, arachidonic acid, retinol and linoleic

acid metabolisms in the fetal livers (Fig. 4.8 B). The genes and their functions in

fatty acid metabolism were highlighted and shown in Table 4.4.

Effects of PFOS on arachidonic acid metabolism.

Cyp2j5, Cyp4a10, Cyp2e1, Cyp2b9, Cyp2c40, Cyp4f16, Cyp4a31 and cyp4a14

associated with arachidonic metabolism, were found to be elevated in the livers of

fetus exposed to PFOS (Fig. 4.8B). Arachidonic metabolism is known to be

responsible for the fatty acid metabolism and the synthesis of prostaglandins

(PGs) and leukotrienes (LTs). LTs and PGs are pro-inflammatory mediators

involved in the inflammatory cascade in asthmatic airways (Wenzel et.al., 1997).

Inflammatory responses can result in the induction of cytokines and chemokines,

leading to the progression of liver fibrosis through actions on hepatic stellate cells

(Marra, 2002). Taken together, our data suggested that the prenatal exposure to

PFOS stimulated arachidonic acid pathways to drive a variety of inflammatory

signals which may result in an initiation of liver fibrosis.

94

Symbol Gene name Biological functions

Cyp2e1 Cytochrome P450, family 2,

subfamily E, polypeptide 1

Fatty acid metabolism; steroid

metabolism

Cyp2j6 Cytochrome P450, family 2,

subfamily b, polypeptide 6

(Cyp2b10)

Fatty acid metabolism; electron

transport

Cyp2c40 Cytochrome P450, family 2,

subfamily E, polypeptide 40

Metabolized arachidonic acid to

signaling molecules

Cyp4a10 Cytochrome P450, family 2,

subfamily A, polypeptide 10

Metabolized arachidonic acid to

signaling molecules

Cyp4a14 Cytochrome P450, family 4,

subfamily A, polypeptide 14

Fatty acid metabolism; omega

hydroxylation and beta oxidation,

marker gene for PPAR-alpha

activation

Ehhadh Enoyl-Coenzyme A,

hydratase (L-bifunctional

protein)

Fatty acid beta-oxidation

Slc27a1 Solute carrier family 27,

member 1 (FATP1)

Fatty acid metabolism, lipid

transport

Fabp1 Fatty acid binding protein 1,

liver

Fatty acid metabolism; steroid

metabolism

Table 4.4 Lists of up regulated genes with their gene names and biological functions

95

0 2 4 6 8 10 12

Pantothenate and CoA biosynthesis

Linoleic acid metabolism

Steroid hormone biosynthesis

Drug metabolism - other enzymes

Peroxisome

PPAR signaling pathway

Arachidonic acid metabolism

Drug metabolism - cytochrome P450

Metabolism of xenobiotics by cytochrome P450

Vascular smooth muscle contraction

Retinol metabolism

Purine metabolism

Enrichment analysis of KEGG pathways

Fig 4.8. (A) Enrichment analysis of KEGG pathways. (B) The schematic diagram showing

the genes altered by prenatal PFOS exposure are related to fatty acid metabolism.

(A)

(B)

96

Effects of PFOS on PPAR signaling pathway.

In our study, genes related to peroxisome proliferator-activated receptor (PPPAR)

signaling pathway including Ehhadh, fabp1, cyp8b1, cyp4a10, cyp4a31, Slc27a1,

cyp4a14 were found to be induced in the livers of fetus exposed to PFOS (Fig.

4.8B). The up-regulated genes included genes associated with peroxisomal beta

oxidation (Ehhadh) and fatty acid transport (Slc27a1and fabp1). Slc27a1 is a

membrane bound fatty acid transporter while Fabp1 is synthesized for the

intracellular transport of fatty acids. In addition, our data demonstrated a

significantly induction of cyp4a14 which is a marker for PPAR-α activation. The

PPAR-α signaling was found to directly regulate the process of inflammation

(Corton et al., 1998; Cuzzocrea et al., 2006).

PPARs belong to nuclear hormone receptor super family and mainly consisted

of three nuclear receptor isoforms, PPAR-α, PPAR-γ and PPAR-δ. PPARs are

ligand-activated transcription factors. PPAR forms a heterodimer with the retinoid

X receptor (RXR) (Tan et.al, 2005; Tien et. al., 2006). The endogenous ligand for

RXR is 9-cis-retinoic acid and RXR is a partner for several other nuclear receptors

(retinoic acid receptor, thyroid hormone receptor, and vitamin D receptor). Upon

ligand binding, conformational changes in the protein structure occurs and

recruitment of co-activators/co-factors to PPAR-RXR heterodimer activates

transcription (Zoete et. al., 2007; Tan et.al, 2005; Tien et. al., 2006). PPAR-α

plays an important role in the peroxisome proliferation, but PPAR-γ and PPAR-δ

are not involved in peroxisome proliferation (Peters et al., 2005). It was reported

that PPARs bind to endogenous ligands to regulate genes involved in different

biological processes including lipid and glucose metabolism and transport. Thus,

the receptors play a pivotal role to maintain metabolic homeostasis. Different

pathogenesis including atherosclerosis, inflammation, cancer, infertility, and

demyelination were found to relate to PPAR-signaling (Berger & Moller, 2002).

Thus, ligands for the PPARs were recognized for the treatment of various diseases

including dyslipidemias and cardiovascular risk (Plutzky, 2000; Linton and Fazio,

2000).

97

Effects of PFOS on retinol metabolism.

The prenatal PFOS exposure also induced a group of genes that are associated

with retinol metabolism including Aldh1a7, cyp3a25, cyp4a10, cyp2b9, Ugt2b36,

cyp2c40, cyp3a44, cyp3a11, cyp4a31 and cyp4a14 (Fig. 4.8B). Our results

demonstrated an induction of Aldh1a7, which is an oxidoreductase that catalyzed

the biosynthesis of the two retinoic acid (RA) receptor ligands, 9-cis-retinoic acid

and all-trans-retinoic acid. Retinols (vitamin A) are fat soluble and is essential for

vision, growth and differentiation of many cell types during embryonic

development as well as in adult tissues (Blomhoff and Wake, 1991). Retinol

regulates metabolism by activating specific nuclear receptors such as retinoic acid

receptor (RAR) and the retinoid X receptor (RXR). 9-cis-retinoic acid is a high-

affinity ligand for RXR (Heyman et.al., 1992; Levin et.al., 1992), its activation

lead to heterodimerization with nuclear receptors including CAR, FXR, LXR,

PPAR (Plutzky, 2011) .

Liver is a major storage site for vitamin A (Blomhoff and Wake, 1991). But

excess vitamins A in liver would initiate a pathologic liver condition including

lysosomal labilization with enzyme release to increase cytolysosomes and

mitochondrial swelling (with “filamentous” inclusions) (Hruban, et.al., 1974;

Hathcock et. al., 1990). Liver fibrosis can be resulted from diverse forms of acute

injury or inflammation. It was reported that the fibrotic lesion in liver may be

derived from a superfluous hepatic storage of retinol (Blomhoff and Wake, 1991).

Moreover a study of hypervitaminosis A (diseases caused by excess vitamin A) in

liver defined an advanced hepatic fibrosis involving intra-acinar, portal and

periportal zones with nodular regeneration (i.e., cirrhosis) in humans (Jacques

et.al., 1979). This observation was further supported by a report from Seifert et al.

(1989) to demonstrate that a high intake of retinol (37.5 mg/kg body weight twice

a week for 4 week) increased liver fibrosis in rats. Therefore, our data suggested

that the prenatal exposure of PFOS induce the over-production of retinol that may

increase the risk of liver fibrosis in fetus.

98

0

50

100

150

200

250

Solvent control PFOS-100uM PFOS-400uM H202 200uM

DC

F f

luore

scen

ce

*

*

* *

0

5

10

15

20

25

CYP4A10 CYP4A14 CYP2j6 CYP4A31 CYP2e1 CYP2e40 CYP4f16

Rel

ati

ve

gen

e ex

pre

ssio

n l

evel

s RT-PCR validation of some selected genes of RNA sequencing using

mouse fetal liver samples collected at GD=17

Control High treatment dose

(A)

Fig 4.9. (A) Validation of some selected RNAseq-identified genes using mouse fetal liver

samples collected at E=17. (B) Significant ROS formation was found in AML-12 cultured

with PFOS. H2O2 was used as a positive control. Asterisks (*) indicates the statistical

significant (p< 0.05) difference between the control and treatment groups.

(B)

99

Verification of some selected RNA-sequencing transcripts.

To investigate the pro-inflammatory responses caused by PFOS in fetal liver, a

number of selected up regulated-genes involved in linoleic acid and arachidonic

acid metabolism were validated by qRT-PCR analysis. The primer sequences were

listed in Table 4.1. The results of qRT-PCR analysis demonstrated an increased in

all the tested genes, although there is no significant difference (Fig. 4.9A).

PFOS induces oxidative stress in in vitro.

Oxidative stress is resulted from the imbalance between antioxidant and reactive

oxygen species (ROS) in cells. In vitro studies on primary culture of tilapia

hepatocytes demonstrated that PFOS and PFOA exposure are able to produce

oxidative stress and induce apoptosis in liver (Liu et. al., 2007c). In an attempt to

test whether PFOS exposure caused oxidative stress in mouse liver mouse primary

cell line, AML-12 was used. We exposed the AML-12 cells to PFOS (100μM -

400μM) for 4 h, followed by the measurement of ROS activity. We found a

significant induction of ROS activity in the PFOS treated cells as compared to the

control group, suggesting PFOS exposure induced oxidative stress in livers (Fig.

4.9B).

4.5 Conclusion

Exposure to PFOS during gestation altered total 2084 genes in fetal livers. This

set of genes was involved in 1) fatty acid metabolism (arachidonic acid, linoleic

acid and retinol metabolism) through the activation of PPAR-α and 2) pro-

inflammation in fetal liver. Taken together, our results indicated that prenatal

exposure of PFOS caused perturbations to fatty liver metabolism and might provoke

lifelong effects on fatty acid metabolism. In future studies, both transcriptomic and

metabolomics profiling are necessary to provide a better understanding on the

adverse effects of prenatal exposure of PFOS on fetal livers.

100

CHAPTER 5

PRENATAL EXPOSURE TO PFOS INDUCED THE RISK OF

PANCREATITIS IN OFFSPRING

5.1 Introduction

In chapter four, we demonstrated the disorder of fatty acid metabolism associated

with prenatal PFOS exposure in the liver of mouse fetus using high throughput

transcriptomic deep sequencing. Besides the liver, pancreas is another major organ

which is important for fatty acid metabolism. In this chapter, we examined the

changes in protein expressions in fetal pancreas using high-throughput isobaric tag

for relative and absolute quantitation (iTRAQ) labeling technique to provide insight

into the molecular mechanisms underlying the adverse effects of the prenatal PFOS

exposure.

Proteins are important functional molecules in different cellular processes. Changes

protein expression induced by environmental pollutants might reveal the clues to the

underlying mechanisms and information about biomarkers to indicate the exposure in

disease susceptibility (Benninghoff, 2007; Colquhoun et. al., 2009) A number of

studies were conducted to unravel the possible mechanisms of PFOS-induced toxicity

in mice. But almost all of them share common objectives to make feasible the protein

expression mechanism. The use of a conventional 2-DE proteomic technique could

capture only a few numbers of proteins. The separation efficiency of 2-DE is low

when the proteins are at high molecular mass, isoelectric point, or hydrophobic

character. In addition, low abundance proteins are difficult to be identified because

of the low sensitivity of 2-DE (Nesatyy et. al., 2007). On the contrary, the

determination of the global protein changes using high-throughput iTRAQ labeling

quantitative proteomic technique coupled with LTQ-Orbitrap can help to perform

reliably quantifiable pathway analysis (Wang and You et. al., 2012).

The working principle of the iTRAQ approach is the use of a set of at least four

isobaric reagents to differentially label the amide linkages of peptides, prepared from

101

different biological samples (Ross, et al., 2004). In LC-MS/MS, differentially labeled

peptides appear as single peaks in MS scans. When iTRAQ-tagged peptides are

subjected to MS/MS analysis, the mass balancing carbonyl moiety is released to

liberate isotope-encoded reporter ions that provide relative quantitative information

on protein levels.

In this study, pregnant mice were orally dosed with PFOS. On gestational day 17

(GD-17), the mice were sacrificed by cervical dislocation and the pancreatic

rudiments were collected to investigate the protein expression profiles using iTRAQ

techniques. The workflow of this study is shown in Fig 5.1. The results of iTRAQ

technique followed by gene ontology analysis suggested that prenatal exposure of

PFOS caused changes in proteins involved in functions of pancreatic secretion,

protein digestion and absorption, protein processing in endoplasmic reticulum, fat

digestion and absorption, glycerolipid metabolism and steroid biosynthesis.

5.2 Materials and Methods

Experimental animals and treatments

ICR mice were purchased and acclimatized for one week before the experiment. The

mice were bred and ascertained of mating by checking the presence of vaginal

smears. The pregnant mice were then divided into 4 groups and housed in

polypropylene cages with sterilized bedding. On gestational 0.5 (GD 0.5), the dams

(one control and 3 PFOS exposed groups) were treated through GD 17.

PFOS (98% purity, sigma Aldrich) was dissolved in DMSO (<0.4%) and the PFOS-

exposed groups were orally administered with 0, 0.3, 1 and 3 mg/kg/day PFOS. The

animals were maintained at a controlled temperature (24°C) and 12 h/12h light-dark

cycles and given with standard foods (LabDiet, 5001Roden Diet) and water ad

libitum. On GD 17, pregnant mice were sacrificed by cervical dislocation and fetal

pancreas were collected for proteomic analysis using the technique “isobaric tag for

relative and absolute quantitation (iTRAQ)” coupled with the LTQ-Orbitrap, a high

102

resolution mass spectrometer. All experimental animals were maintained according to

the guidelines and regulations of HKBU.

Protein extraction

The protein extraction was performed as previously described (Tse et. al., 2013).

Pancreatic tissue from each group was homogenized in an extraction buffer

consisting of 8 M urea and 40 mM HEPES at pH 7.4 respectively. The homogenates

were then sonicated and centrifuged at 15,000 g for 10 min. 2D clean-up kit (Bio-

Rad) and RC-DC Protein Assay Kit (Bio-Rad) were used for purification and

determination of protein concentrations respectively.

iTRAQ labeling

The iTRAQ labeling was performed on the basis of a published protocol (Tse et.al.,

2013; Zhang et. al., 2010b) with slight modifications. Briefly, 5 mM tris carboxyethyl

phosphine hydrochloride (TCEP) was added into 200 μg of protein sample incubated

for 60 min at 37 °C to facilitate the process of chemical reduction, then was followed

by alkylation with 10 mM methyl methane thiosulfonate (MMTS) for 20 min at room

temperature. The samples were then diluted by seven fold with 50 mM

triethylammonium bicarbonate (TEAB). For digestion, the sequencing grade trypsin

(Promega) was added into the protein samples in 1:50 trypsin-to-protein mass-ratio

and kept at 37 °C for 16 h. The digests were desalted and dried using Sep-Pak C18

cartridges (Waters) and SpeedVac (Eppendorf). Peptides from pancreatic samples of

control, low, medium and high dosed groups were labeled with the iTRAQ reporter

114, 115, 116 and 17 respectively. A strong cation exchange fractionation of peptide

mixture was carried out as described (Zhang et. al., 2010b). The collected fractions

were desalted followed by the reconstitution of dried fractions in 30μl of 0.1% formic

acid.

LC-MS/MS analysis

LTQ-Orbitrap (Velos, Thermo Electron, Germany) coupled with an Easy-nLC

(Proxeon, Germany) was used for analysis of the samples. The LC-MS/MS was

103

performed as previously described (Tse et. al., 2013). Briefly, for each analysis, 10 μl

of peptide sample was used for analysis followed by two phases with a different

gradient of solvents in a C18 capillary column (Michrom Bioresources, USA). The

mobile phases A was 0.1% formic acid in water and the mobile phase B was 0.1%

formic acid in acetonitrile. The system was run in a linear gradient: 0-5 minutes of

100% A, after 5 minutes mobile phase was increased from 0-30%, held for 50

minutes. After 50 minutes, mobile phase B was increased from 30-80% and held for

10 minutes, followed by a final run at 100%A for 10 minutes. The full Mass

Spectrometry (MS) scan was obtained in a profile mode with resolution of 30,000 and

ion resolution time 2s. The fragmentation was achieved by ions with multiple charges

in a high-energy collision-induced dissociation (HCD) in C-trap and collision-

induced dissociation (CID) in LTQ. The other parameters were adjusted followed by

Tse et. al. (2013).

Protein identification & quantification

The protein identification and quantification was performed according to a standard

protocol (Tse et.al, 2013). The obtained HCD and CID were subjected to Proteome

Discoverer 1.0 (Thermo Fisher Scientific) to generate the MASCOT generic files

(mgf). The normalized mgf files of three replicates were submitted through

MASCOT (version 2.3.02) to search the protein database. In order to maintain the

false discovery rate, FDR at both peptides and protein levels of less than 1%, cut-off

scores were dynamically assigned to each dataset. Proteins containing at least two

spectra were used for quantification.

According to manufacturer's instructions isotope impurity of iTRAQ, was corrected

and any dissimilar ratios between any two iTRAQ reporters (e.g. 115/114 over 100)

were removed in this analysis. Normalization of the peptide-iTRAQ reporter intensity

was performed to make sure that they were all 1. Based on the total intensity of the

assigned peptides, protein quantification was made using a python script followed by

statistical analysis (Student's t-test).

104

Pancreas samples

from E=17

Protein extraction

followed by

enzymatic digestion

iTRAQ labeling and

MS analysis Control

Control group

(0 mg/kg/day)

Low treatment group

(0.3 mg/kg/day)

Medium treatment group

(1 mg/kg/day)

High treatment group

(3 mg/kg/day)

Low Medium High

Quantification of

Ctrl vs Low

Quantification of Ctrl

vs Medium

Quantification of Ctrl

vs High

Low dose treatment group

showed a highly dissimilar

pattern of protein expressions

as compared to medium and

high dose treatment groups

58 proteins

up

regulated

50 proteins

up

regulated

25 proteins

down

regulated

62 proteins

down

regulated

17 overlapped up-regulated

proteins in mid and high doses

2 overlapped down regulated

proteins in mid and high doses

Enrichment analysis of GO

Biological process, Molecular

function and KEGG pathway

Fig 5.1. General work flow and summary of the present study. The study applied proteomic

approaches to identify the differentially expressed proteins in the mouse pancreas in response to

exposure with different prenatal doses of PFOS. (Modified from the model proposed by Tse et.

al., (2013). In our study, 4-5 pregnant mice were sacrificed from each group.

19 proteins

up

regulated

11 proteins

down

regulated

105

5.3 Results and Discussion

Identification and quantification of pancreas proteome.

In order to investigate the expression changes of pancreatic proteins associated with

prenatal PFOS exposure in mice, high-throughput iTRAQ labeling quantitative

proteomic technology was conducted. After labeling the protein samples with

iTRAQ reagents, the samples were subjected to LCMS/MS analysis. The HCD and

CID data obtained from MASCOT generic files were combined to match the protein

profile identified in each treatment group. We then compared the 3 treatment groups

(low, medium and high) to determine the commonly dysregulated proteins in

response to prenatal PFOS exposure. We found dissimilar patterns of protein profiles

detected from low to high dose treatment (similarity <1%). But, we observed a

number of dysregulated proteins commonly identified in the medium and high dose

treatments (Fig. 5.2). A total of 176 proteins exhibited differential expression in

medium and high dose treatment groups (Table 5.1-5.4). Among them, a total of 91

differentially up-regulated proteins were identified in medium and high dose groups

with 17 proteins overlapped including chymotrypsin-like elastase family members

(Cel A1, Cel 2A & Cel 3B), Serpin I2, PRSS3, bile salt-activated lipase (BAL),

protein disulfide isomerase (PDI) and carboxypeptidases. On the other hand, 85

down-regulated proteins were identified with 2 overlapped proteins, such as Retinol-

binding protein and large neutral amino acids transporter small subunit 1. Then we

focused on the function of the commonly up-regulated proteins using gene

enrichment analysis of GO biological process, molecular function and KEGG

pathway. The list of pathway analysis is summarized in Table 5.5.

106

Fig 5.2. The diagram showing the number of up and down regulated as well as overlapped protein

expression in mouse pancreas in response to medium and high doses of PFOS.

107

Accession Name

1

sp|Q8BP67|RL24_MOUSE

60S ribosomal protein L24 OS=Mus musculus

GN=Rpl24 PE=2 SV=2

2

sp|P62242|RS8_MOUSE

40S ribosomal protein S8 OS=Mus musculus

GN=Rps8 PE=1 SV=2

3

sp|P14148|RL7_MOUSE

60S ribosomal protein L7 OS=Mus musculus

GN=Rpl7 PE=2 SV=2

4

sp|P47963|RL13_MOUSE

60S ribosomal protein L13 OS=Mus musculus

GN=Rpl13 PE=2 SV=3

5

sp|Q9D8E6|RL4_MOUSE

60S ribosomal protein L4 OS=Mus musculus

GN=Rpl4 PE=1 SV=3

6

sp|P47911|RL6_MOUSE

60S ribosomal protein L6 OS=Mus musculus

GN=Rpl6 PE=1 SV=3

7

sp|P61255|RL26_MOUSE

60S ribosomal protein L26 OS=Mus musculus

GN=Rpl26 PE=2 SV=1

8

sp|P62918|RL8_MOUSE

60S ribosomal protein L8 OS=Mus musculus

GN=Rpl8 PE=2 SV=2

9

sp|P19253|RL13A_MOUSE

60S ribosomal protein L13a OS=Mus musculus

GN=Rpl13a PE=1 SV=4

10

sp|Q9D1R9|RL34_MOUSE

60S ribosomal protein L34 OS=Mus musculus

GN=Rpl34 PE=3 SV=2

11

sp|Q9CR57|RL14_MOUSE

60S ribosomal protein L14 OS=Mus musculus

GN=Rpl14 PE=2 SV=3

Table 5.1 Lists of differentially expressed up regulated proteins in medium treatment dose

108

12

sp|P62754|RS6_MOUSE

40S ribosomal protein S6 OS=Mus musculus

GN=Rps6 PE=1 SV=1

13

sp|Q6ZWV3|RL10_MOUSE

60S ribosomal protein L10 OS=Mus musculus

GN=Rpl10 PE=2 SV=3

14

sp|Q6ZWN5|RS9_MOUSE

40S ribosomal protein S9 OS=Mus musculus

GN=Rps9 PE=2 SV=3

15

sp|Q91X79|CELA1_MOUSE

Chymotrypsin-like elastase family member 1

OS=Mus musculus GN=Cela1 PE=2 SV=1

16

sp|Q8K0C5|ZG16_MOUSE

Zymogen granule membrane protein 16

OS=Mus musculus GN=Zg16 PE=2 SV=1

17 tr|Q9CPN9|Q9CPN9_MOUSE Protein 2210010C04Rik OS=Mus musculus

GN=2210010C04Rik PE=2 SV=1

18

sp|Q504N0|CBPA2_MOUSE

Carboxypeptidase A2 OS=Mus musculus

GN=Cpa2 PE=2 SV=1

19

sp|Q7TPZ8|CBPA1_MOUSE

Carboxypeptidase A1 OS=Mus musculus

GN=Cpa1 PE=2 SV=1

20

sp|Q64285|CEL_MOUSE

Bile salt-activated lipase OS=Mus musculus

GN=Cel PE=1 SV=1

21

tr|B2RS76|B2RS76_MOUSE

Carboxypeptidase B1 (Tissue) OS=Mus

musculus GN=Cpb1 PE=2 SV=1

22

sp|P05208|CEL2A_MOUSE

Chymotrypsin-like elastase family member 2A

OS=Mus musculus GN=Cela2a PE=2 SV=1

23

sp|P02089|HBB2_MOUSE

Hemoglobin subunit beta-2 OS=Mus musculus

GN=Hbb-b2 PE=1 SV=2

109

24

sp|P27659|RL3_MOUSE

60S ribosomal protein L3 OS=Mus musculus

GN=Rpl3 PE=2 SV=3

25

sp|P15864|H12_MOUSE

Histone H1.2 OS=Mus musculus GN=Hist1h1c

PE=1 SV=2

26

sp|P62849|RS24_MOUSE

40S ribosomal protein S24 OS=Mus musculus

GN=Rps24 PE=1 SV=1

27

tr|Q792Z0|Q792Z0_MOUSE

Protein Prss3 OS=Mus musculus GN=Prss3

PE=3 SV=1

28

sp|P62717|RL18A_MOUSE

60S ribosomal protein L18a OS=Mus musculus

GN=Rpl18a PE=1 SV=1

29

sp|P62806|H4_MOUSE

Histone H4 OS=Mus musculus GN=Hist1h4a

PE=1 SV=2

30

sp|P14115|RL27A_MOUSE

60S ribosomal protein L27a OS=Mus musculus

GN=Rpl27a PE=2 SV=5

31 tr|Q9CQM8|Q9CQM8_MOUS

E

60S ribosomal protein L21 OS=Mus musculus

GN=Rpl21 PE=2 SV=1

32

sp|Q9D2R4|TMD11_MOUSE

Transmembrane emp24 domain-containing

protein 11 OS=Mus musculus GN=Tmed11

PE=2 SV=1

33

sp|P62900|RL31_MOUSE

60S ribosomal protein L31 OS=Mus musculus

GN=Rpl31 PE=2 SV=1

34

sp|P47962|RL5_MOUSE

60S ribosomal protein L5 OS=Mus musculus

GN=Rpl5 PE=1 SV=3

35 tr|Q4VBW7|Q4VBW7_MOUS

E

Pancreatic lipase-related protein 2 OS=Mus

musculus GN=Pnliprp2 PE=2 SV=1

110

36

sp|P43137|LIT1_MOUSE

Lithostathine-1 OS=Mus musculus GN=Reg1

PE=2 SV=1

37

sp|P61358|RL27_MOUSE

60S ribosomal protein L27 OS=Mus musculus

GN=Rpl27 PE=2 SV=2

38

sp|P35980|RL18_MOUSE

60S ribosomal protein L18 OS=Mus musculus

GN=Rpl18 PE=2 SV=3

39

tr|L7N202|L7N202_MOUSE

Uncharacterized protein OS=Mus musculus

GN=Gm16477 PE=4 SV=1

40

sp|Q9JK88|SPI2_MOUSE

Serpin I2 OS=Mus musculus GN=Serpini2

PE=1 SV=1

41

sp|P06467|HBAZ_MOUSE

Hemoglobin subunit zeta OS=Mus musculus

GN=Hbz PE=2 SV=2

42

sp|D3Z6P0|PDIA2_MOUSE

Protein disulfide-isomerase A2 OS=Mus

musculus GN=Pdia2 PE=1 SV=1

43

sp|Q9CQ52|CEL3B_MOUSE

Chymotrypsin-like elastase family member 3B

OS=Mus musculus GN=Cela3b PE=2 SV=1

44

sp|P43274|H14_MOUSE

Histone H1.4 OS=Mus musculus GN=Hist1h1e

PE=1 SV=2

45

sp|P62281|RS11_MOUSE

40S ribosomal protein S11 OS=Mus musculus

GN=Rps11 PE=2 SV=3

46

tr|G3X8R0|G3X8R0_MOUSE

Receptor accessory protein 5, isoform CRA_a

OS=Mus musculus GN=Reep5 PE=4 SV=1

47

sp|Q9EQU5-2|SET_MOUSE

Isoform 2 of Protein SET OS=Mus musculus

GN=Set

111

48

tr|D3Z6C3|D3Z6C3_MOUSE

40S ribosomal protein S3a OS=Mus musculus

GN=Rps3a2 PE=3 SV=1

49

sp|P04444|HBBZ_MOUSE

Hemoglobin subunit beta-H1 OS=Mus musculus

GN=Hbb-bh1 PE=2 SV=3

50

sp|P09103|PDIA1_MOUSE

Protein disulfide-isomerase OS=Mus musculus

GN=P4hb PE=1 SV=2

51

sp|P02535-3|K1C10_MOUSE

Isoform 3 of Keratin, type I cytoskeletal 10

OS=Mus musculus GN=Krt10

52

tr|Q9D8L3|Q9D8L3_MOUSE

Signal sequence receptor, delta OS=Mus

musculus GN=Ssr4 PE=2 SV=1

53

sp|P62301|RS13_MOUSE

40S ribosomal protein S13 OS=Mus musculus

GN=Rps13 PE=1 SV=2

54

tr|E9QAZ2|E9QAZ2_MOUSE

Ribosomal protein L15 OS=Mus musculus

GN=Gm10020 PE=3 SV=1

55

tr|Q5XJF6|Q5XJF6_MOUSE

Ribosomal protein OS=Mus musculus

GN=Rpl10a PE=2 SV=1

56

sp|P84228|H32_MOUSE

Histone H3.2 OS=Mus musculus GN=Hist1h3b

PE=1 SV=2

57 tr|Q6ZWZ4|Q6ZWZ4_MOUS

E

60S ribosomal protein L36 OS=Mus musculus

GN=Rpl36 PE=3 SV=1

58

sp|P63325|RS10_MOUSE

40S ribosomal protein S10 OS=Mus musculus

GN=Rps10 PE=1 SV=1

112

Accession Name

1

sp|Q6ZWY8|TYB10_MOUSE

Thymosin beta-10 OS=Mus musculus

GN=Tmsb10 PE=2 SV=3

2

sp|Q9Z127|LAT1_MOUSE

Large neutral amino acids transporter small

subunit 1 OS=Mus musculus GN=Slc7a5 PE=1

SV=2

3

sp|P31001|DESM_MOUSE

Desmin OS=Mus musculus GN=Des PE=1

SV=3

4

sp|Q4VAA2|CDV3_MOUSE

Protein CDV3 OS=Mus musculus GN=Cdv3

PE=1 SV=2

5

tr|Q497J0|Q497J0_MOUSE

MCG130175, isoform CRA_b OS=Mus

musculus GN=BC100530 PE=4 SV=1

6

sp|P20152|VIME_MOUSE

Vimentin OS=Mus musculus GN=Vim PE=1

SV=3

7

sp|Q9CY02|AHSP_MOUSE

Alpha-hemoglobin-stabilizing protein OS=Mus

musculus GN=Ahsp PE=2 SV=1

8

sp|Q9CPU0|LGUL_MOUSE

Lactoylglutathione lyase OS=Mus musculus

GN=Glo1 PE=1 SV=3

9

tr|H7BX95|H7BX95_MOUSE

Serine/arginine-rich-splicing factor 1 OS=Mus

musculus GN=Srsf1 PE=2 SV=1

10

sp|Q9CQ60|6PGL_MOUSE

6-phosphogluconolactonase OS=Mus musculus

GN=Pgls PE=2 SV=1

Table 5.2. Lists of differentially expressed down regulated proteins in medium treatment dose

113

11

sp|O70400|PDLI1_MOUSE

PDZ and LIM domain protein 1 OS=Mus

musculus GN=Pdlim1 PE=2 SV=4

12

sp|Q9D3D9|ATPD_MOUSE

ATP synthase subunit delta, mitochondrial

OS=Mus musculus GN=Atp5d PE=1 SV=1

13

sp|Q06770|CBG_MOUSE

Corticosteroid-binding globulin OS=Mus

musculus GN=Serpina6 PE=1 SV=1

14

tr|Q8C6G3|Q8C6G3_MOUSE

Ribonuclease pancreatic OS=Mus musculus

GN=Rnase1 PE=2 SV=1

15

tr|H7BWY6|H7BWY6_MOUSE

Retinol-binding protein 4 OS=Mus musculus

GN=Rbp4 PE=2 SV=1

16

sp|Q60598|SRC8_MOUSE

Src substrate cortactin OS=Mus musculus

GN=Cttn PE=1 SV=2

17

sp|P37889-2|FBLN2_MOUSE

Isoform 2 of Fibulin-2 OS=Mus musculus

GN=Fbln2

18

sp|Q9DAW9|CNN3_MOUSE

Calponin-3 OS=Mus musculus GN=Cnn3 PE=2

SV=1

19

sp|P97825|HN1_MOUSE

Hematological and neurological expressed 1

protein OS=Mus musculus GN=Hn1 PE=1

SV=3

20

sp|P48428|TBCA_MOUSE

Tubulin-specific chaperone A OS=Mus

musculus GN=Tbca PE=2 SV=3

21

sp|Q91XV3|BASP1_MOUSE

Brain acid soluble protein 1 OS=Mus musculus

GN=Basp1 PE=1 SV=3

22

sp|O88207|CO5A1_MOUSE

Collagen alpha-1(V) chain OS=Mus musculus

GN=Col5a1 PE=2 SV=2

114

23

sp|Q3U962|CO5A2_MOUSE

Collagen alpha-2(V) chain OS=Mus musculus

GN=Col5a2 PE=1 SV=1

24

sp|Q9CQ45|NENF_MOUSE

Neudesin OS=Mus musculus GN=Nenf PE=1

SV=1

25

tr|O08692|O08692_MOUSE

Myeloid bactenecin (F1) OS=Mus musculus

GN=Ngp PE=2 SV=1

115

Accession Name

1

sp|Q06890|CLUS_MOUSE

Clusterin OS=Mus musculus GN=Clu PE=1

SV=1

2

tr|E9PZF0|E9PZF0_MOUSE

Nucleoside diphosphate kinase OS=Mus

musculus GN=Gm20390 PE=2 SV=1

3

sp|P15947|KLK1_MOUSE

Kallikrein-1 OS=Mus musculus GN=Klk1 PE=1

SV=3

4

sp|Q93092|TALDO_MOUSE

Transaldolase OS=Mus musculus GN=Taldo1

PE=1 SV=2

5

sp|Q91X79|CELA1_MOUSE

Chymotrypsin-like elastase family member 1

OS=Mus musculus GN=Cela1 PE=2 SV=1

6

tr|G5E8N5|G5E8N5_MOUSE

L-lactate dehydrogenase OS=Mus musculus

GN=Ldha PE=3 SV=1

7

sp|Q9CQC2|COL_MOUSE

Colipase OS=Mus musculus GN=Clps PE=2

SV=1

8

sp|Q6ZWY8|TYB10_MOUSE

Thymosin beta-10 OS=Mus musculus

GN=Tmsb10 PE=2 SV=3

9

sp|Q8K0C5|ZG16_MOUSE

Zymogen granule membrane protein 16

OS=Mus musculus GN=Zg16 PE=2 SV=1

10

sp|Q9JK88|SPI2_MOUSE

Serpin I2 OS=Mus musculus GN=Serpini2 PE=1

SV=1

11 tr|Q9ER05|Q9ER05_MOUSE Chymopasin OS=Mus musculus GN=Ctrl PE=2

Table 5.3. Lists of differentially expressed up regulated proteins in high dose treatment

116

SV=1

12

tr|Q9CPN9|Q9CPN9_MOUSE

Protein 2210010C04Rik OS=Mus musculus

GN=2210010C04Rik PE=2 SV=1

13

sp|Q00623|APOA1_MOUSE

Apolipoprotein A-I OS=Mus musculus

GN=Apoa1 PE=1 SV=2

14

sp|P17742|PPIA_MOUSE

Peptidyl-prolyl cis-trans isomerase A OS=Mus

musculus GN=Ppia PE=1 SV=2

15

sp|Q504N0|CBPA2_MOUSE

Carboxypeptidase A2 OS=Mus musculus

GN=Cpa2 PE=2 SV=1

16

sp|P06728|APOA4_MOUSE

Apolipoprotein A-IV OS=Mus musculus

GN=Apoa4 PE=2 SV=3

17

sp|P06467|HBAZ_MOUSE

Hemoglobin subunit zeta OS=Mus musculus

GN=Hbz PE=2 SV=2

18

tr|Q9CR49|Q9CR49_MOUSE

Hemoglobin Y, beta-like embryonic chain

OS=Mus musculus GN=Hbb-y PE=2 SV=1

19

sp|D3Z6P0|PDIA2_MOUSE

Protein disulfide-isomerase A2 OS=Mus

musculus GN=Pdia2 PE=1 SV=1

20

sp|P08228|SODC_MOUSE

Superoxide dismutase [Cu-Zn] OS=Mus

musculus GN=Sod1 PE=1 SV=2

21

sp|P08226|APOE_MOUSE

Apolipoprotein E OS=Mus musculus GN=Apoe

PE=1 SV=2

22

sp|P07146|TRY2_MOUSE

Anionic trypsin-2 OS=Mus musculus GN=Prss2

PE=2 SV=1

23 sp|Q7TPZ8|CBPA1_MOUSE Carboxypeptidase A1 OS=Mus musculus

117

GN=Cpa1 PE=2 SV=1

24

sp|Q9CQ52|CEL3B_MOUSE

Chymotrypsin-like elastase family member 3B

OS=Mus musculus GN=Cela3b PE=2 SV=1

25

sp|Q64285|CEL_MOUSE

Bile salt-activated lipase OS=Mus musculus

GN=Cel PE=1 SV=1

26

tr|B2RS76|B2RS76_MOUSE

Carboxypeptidase B1 (Tissue) OS=Mus

musculus GN=Cpb1 PE=2 SV=1

27

sp|P02088|HBB1_MOUSE

Hemoglobin subunit beta-1 OS=Mus musculus

GN=Hbb-b1 PE=1 SV=2

28

sp|P05208|CEL2A_MOUSE

Chymotrypsin-like elastase family member 2A

OS=Mus musculus GN=Cela2a PE=2 SV=1

29

sp|Q3SYP2|CTRC_MOUSE

Chymotrypsin-C OS=Mus musculus GN=Ctrc

PE=2 SV=1

30

sp|P02089|HBB2_MOUSE

Hemoglobin subunit beta-2 OS=Mus musculus

GN=Hbb-b2 PE=1 SV=2

31

sp|Q9CQZ1|HSBP1_MOUSE

Heat shock factor-binding protein 1 OS=Mus

musculus GN=Hsbp1 PE=2 SV=1

32

sp|Q9D154|ILEUA_MOUSE

Leukocyte elastase inhibitor A OS=Mus

musculus GN=Serpinb1a PE=1 SV=1

33

sp|Q00915|RET1_MOUSE

Retinol-binding protein 1 OS=Mus musculus

GN=Rbp1 PE=2 SV=2

34

sp|P62082|RS7_MOUSE

40S ribosomal protein S7 OS=Mus musculus

GN=Rps7 PE=2 SV=1

35 sp|P01867|IGG2B_MOUSE Ig gamma-2B chain C region OS=Mus musculus

118

GN=Igh-3 PE=1 SV=3

36

sp|P29595|NEDD8_MOUSE

NEDD8 OS=Mus musculus GN=Nedd8 PE=1

SV=2

37

sp|Q06770|CBG_MOUSE

Corticosteroid-binding globulin OS=Mus

musculus GN=Serpina6 PE=1 SV=1

38

sp|P24369|PPIB_MOUSE

Peptidyl-prolyl cis-trans isomerase B OS=Mus

musculus GN=Ppib PE=2 SV=2

39

tr|Q8C6G3|Q8C6G3_MOUSE

Ribonuclease pancreatic OS=Mus musculus

GN=Rnase1 PE=2 SV=1

40

sp|P56480|ATPB_MOUSE

ATP synthase subunit beta, mitochondrial

OS=Mus musculus GN=Atp5b PE=1 SV=2

41

sp|P20029|GRP78_MOUSE

78 kDa glucose-regulated protein OS=Mus

musculus GN=Hspa5 PE=1 SV=3

42

sp|P55095|GLUC_MOUSE

Glucagon OS=Mus musculus GN=Gcg PE=1

SV=1

43

sp|P04444|HBBZ_MOUSE

Hemoglobin subunit beta-H1 OS=Mus musculus

GN=Hbb-bh1 PE=2 SV=3

44

sp|P09103|PDIA1_MOUSE

Protein disulfide-isomerase OS=Mus musculus

GN=P4hb PE=1 SV=2

45

tr|Q792Z0|Q792Z0_MOUSE

Protein Prss3 OS=Mus musculus GN=Prss3

PE=3 SV=1

46

sp|P02802|MT1_MOUSE

Metallothionein-1 OS=Mus musculus GN=Mt1

PE=1 SV=1

47 sp|P02535-3|K1C10_MOUSE Isoform 3 of Keratin, type I cytoskeletal 10

119

OS=Mus musculus GN=Krt10

48

sp|P21107-2|TPM3_MOUSE

Isoform 2 of Tropomyosin alpha-3 chain

OS=Mus musculus GN=Tpm3

49

sp|P20065|TYB4_MOUSE

Thymosin beta-4 OS=Mus musculus

GN=Tmsb4x PE=1 SV=1

50

sp|P07309|TTHY_MOUSE

Transthyretin OS=Mus musculus GN=Ttr PE=1

SV=1

120

Accession Name

1

sp|P46978|STT3A_MOUSE

Dolichyl-diphosphooligosaccharide--protein

glycosyltransferase subunit STT3A OS=Mus

musculus GN=Stt3a PE=1 SV=1

2

tr|A8DUK4|A8DUK4_MOUSE

Beta-globin OS=Mus musculus GN=Hbbt1

PE=4 SV=1

3

sp|Q8BP67|RL24_MOUSE

60S ribosomal protein L24 OS=Mus musculus

GN=Rpl24 PE=2 SV=2

4

tr|Q6ZWZ7|Q6ZWZ7_MOUSE

60S ribosomal protein L17 OS=Mus musculus

GN=Rpl17 PE=2 SV=1

5

sp|P62242|RS8_MOUSE

40S ribosomal protein S8 OS=Mus musculus

GN=Rps8 PE=1 SV=2

6

sp|P14148|RL7_MOUSE

60S ribosomal protein L7 OS=Mus musculus

GN=Rpl7 PE=2 SV=2

7

sp|P47963|RL13_MOUSE

60S ribosomal protein L13 OS=Mus musculus

GN=Rpl13 PE=2 SV=3

8

sp|Q9D8E6|RL4_MOUSE

60S ribosomal protein L4 OS=Mus musculus

GN=Rpl4 PE=1 SV=3

9

sp|Q9CZS1|AL1B1_MOUSE

Aldehyde dehydrogenase X, mitochondrial

OS=Mus musculus GN=Aldh1b1 PE=2 SV=1

10

sp|P47911|RL6_MOUSE

60S ribosomal protein L6 OS=Mus musculus

GN=Rpl6 PE=1 SV=3

11

sp|P61255|RL26_MOUSE

60S ribosomal protein L26 OS=Mus musculus

GN=Rpl26 PE=2 SV=1

Table 5.4. Lists of differentially expressed down regulated proteins in high treatment dose

121

12

sp|P61358|RL27_MOUSE

60S ribosomal protein L27 OS=Mus musculus

GN=Rpl27 PE=2 SV=2

13

sp|P62918|RL8_MOUSE

60S ribosomal protein L8 OS=Mus musculus

GN=Rpl8 PE=2 SV=2

14

sp|P35980|RL18_MOUSE

60S ribosomal protein L18 OS=Mus musculus

GN=Rpl18 PE=2 SV=3

15

sp|P19253|RL13A_MOUSE

60S ribosomal protein L13a OS=Mus musculus

GN=Rpl13a PE=1 SV=4

16

sp|Q9D1R9|RL34_MOUSE

60S ribosomal protein L34 OS=Mus musculus

GN=Rpl34 PE=3 SV=2

17

sp|P61620|S61A1_MOUSE

Protein transport protein Sec61 subunit alpha

isoform 1 OS=Mus musculus GN=Sec61a1

PE=2 SV=2

18

sp|Q9DCF9|SSRG_MOUSE

Translocon-associated protein subunit gamma

OS=Mus musculus GN=Ssr3 PE=1 SV=1

19

sp|Q9CR57|RL14_MOUSE

60S ribosomal protein L14 OS=Mus musculus

GN=Rpl14 PE=2 SV=3

20

sp|P62754|RS6_MOUSE

40S ribosomal protein S6 OS=Mus musculus

GN=Rps6 PE=1 SV=1

21

sp|P35564|CALX_MOUSE

Calnexin OS=Mus musculus GN=Canx PE=1

SV=1

22

sp|P62301|RS13_MOUSE

40S ribosomal protein S13 OS=Mus musculus

GN=Rps13 PE=1 SV=2

23

sp|Q6ZWV3|RL10_MOUSE

60S ribosomal protein L10 OS=Mus musculus

GN=Rpl10 PE=2 SV=3

122

24

sp|Q6ZWN5|RS9_MOUSE

40S ribosomal protein S9 OS=Mus musculus

GN=Rps9 PE=2 SV=3

25

tr|L7N202|L7N202_MOUSE

Uncharacterized protein OS=Mus musculus

GN=Gm16477 PE=4 SV=1

26

sp|Q9D0F3|LMAN1_MOUSE

Protein ERGIC-53 OS=Mus musculus

GN=Lman1 PE=2 SV=1

27

sp|Q9D1D4|TMEDA_MOUSE

Transmembrane emp24 domain-containing

protein 10 OS=Mus musculus GN=Tmed10

PE=2 SV=1

28

sp|Q80UM7|MOGS_MOUSE

Mannosyl-oligosaccharide glucosidase

OS=Mus musculus GN=Mogs PE=2 SV=1

29

tr|E9PY58|E9PY58_MOUSE

Caseinolytic peptidase B protein homolog

OS=Mus musculus GN=Clpb PE=2 SV=1

30

sp|P70168|IMB1_MOUSE

Importin subunit beta-1 OS=Mus musculus

GN=Kpnb1 PE=1 SV=2

31

sp|O54734|OST48_MOUSE

Dolichyl-diphosphooligosaccharide--protein

glycosyltransferase 48 kDa subunit OS=Mus

musculus GN=Ddost PE=1 SV=2

32

sp|P27659|RL3_MOUSE

60S ribosomal protein L3 OS=Mus musculus

GN=Rpl3 PE=2 SV=3

33

tr|Q7JCZ1|Q7JCZ1_MOUSE

Cytochrome c oxidase subunit 2 OS=Mus

musculus GN=mt-Co2 PE=2 SV=1

34

sp|P12382|K6PL_MOUSE

6-phosphofructokinase, liver type OS=Mus

musculus GN=Pfkl PE=1 SV=4

35 sp|Q8VDN2|AT1A1_MOUSE Sodium/potassium-transporting ATPase subunit

123

alpha-1 OS=Mus musculus GN=Atp1a1 PE=1

SV=1

36

sp|P25206|MCM3_MOUSE

DNA replication licensing factor MCM3

OS=Mus musculus GN=Mcm3 PE=1 SV=2

37

sp|Q68FD5|CLH1_MOUSE

Clathrin heavy chain 1 OS=Mus musculus

GN=Cltc PE=1 SV=3

38

sp|Q9DCN2|NB5R3_MOUSE

NADH-cytochrome b5 reductase 3 OS=Mus

musculus GN=Cyb5r3 PE=1 SV=3

39

sp|P60229|EIF3E_MOUSE

Eukaryotic translation initiation factor 3 subunit

E OS=Mus musculus GN=Eif3e PE=1 SV=1

40

sp|P47915|RL29_MOUSE

60S ribosomal protein L29 OS=Mus musculus

GN=Rpl29 PE=2 SV=2

41

sp|P43274|H14_MOUSE

Histone H1.4 OS=Mus musculus GN=Hist1h1e

PE=1 SV=2

42

sp|P15864|H12_MOUSE

Histone H1.2 OS=Mus musculus GN=Hist1h1c

PE=1 SV=2

43

tr|H7BWY6|H7BWY6_MOUSE

Retinol-binding protein 4 OS=Mus musculus

GN=Rbp4 PE=2 SV=1

44

sp|Q7TPV4|MBB1A_MOUSE

Myb-binding protein 1A OS=Mus musculus

GN=Mybbp1a PE=1 SV=2

45

sp|Q9Z127|LAT1_MOUSE

Large neutral amino acids transporter small

subunit 1 OS=Mus musculus GN=Slc7a5 PE=1

SV=2

46

tr|E9QAZ2|E9QAZ2_MOUSE

Ribosomal protein L15 OS=Mus musculus

GN=Gm10020 PE=3 SV=1

124

47

sp|P43276|H15_MOUSE

Histone H1.5 OS=Mus musculus GN=Hist1h1b

PE=1 SV=2

48

sp|P10922|H10_MOUSE

Histone H1.0 OS=Mus musculus GN=H1f0

PE=2 SV=4

49

sp|Q9D8V0|HM13_MOUSE

Minor histocompatibility antigen H13 OS=Mus

musculus GN=Hm13 PE=1 SV=1

50

sp|Q99PV0|PRP8_MOUSE

Pre-mRNA-processing-splicing factor 8

OS=Mus musculus GN=Prpf8 PE=1 SV=2

51

sp|P62849|RS24_MOUSE

40S ribosomal protein S24 OS=Mus musculus

GN=Rps24 PE=1 SV=1

52

sp|P97449|AMPN_MOUSE

Aminopeptidase N OS=Mus musculus

GN=Anpep PE=1 SV=4

53

sp|Q6ZQI3|MLEC_MOUSE

Malectin OS=Mus musculus GN=Mlec PE=2

SV=2

54

sp|P84228|H32_MOUSE

Histone H3.2 OS=Mus musculus GN=Hist1h3b

PE=1 SV=2

55

sp|P14115|RL27A_MOUSE

60S ribosomal protein L27a OS=Mus musculus

GN=Rpl27a PE=2 SV=5

56

sp|Q7TPR4|ACTN1_MOUSE

Alpha-actinin-1 OS=Mus musculus GN=Actn1

PE=1 SV=1

57

sp|P41105|RL28_MOUSE

60S ribosomal protein L28 OS=Mus musculus

GN=Rpl28 PE=1 SV=2

58

sp|O88508|DNM3A_MOUSE

DNA (cytosine-5)-methyltransferase 3A

OS=Mus musculus GN=Dnmt3a PE=1 SV=2

125

59

tr|Q9CQM8|Q9CQM8_MOUSE

60S ribosomal protein L21 OS=Mus musculus

GN=Rpl21 PE=2 SV=1

60

tr|A2A547|A2A547_MOUSE

Ribosomal protein L19 OS=Mus musculus

GN=Rpl19 PE=2 SV=1

61

sp|P61514|RL37A_MOUSE

60S ribosomal protein L37a OS=Mus musculus

GN=Rpl37a PE=2 SV=2

62

sp|P62911|RL32_MOUSE

60S ribosomal protein L32 OS=Mus musculus

GN=Rpl32 PE=2 SV=2

126

Table 5.5 Up regulated proteins annotated with name, Uni-port identity and

biological functions.

Protein name Uni port ID Functional description

Bile salt activated lipase (BAL) Q64285 Carboxylic ester hydrolase activity,

pancreatic juice secretion

Chymotrypsin like elastase family

member 2A (Cela 2A)

P05208 Serine hydrolase activity, establishment

of skin barrier

Carboxy peptidase A1(cpa1) Q7tpz8 Metallo- carboxypeptidase activity

Carboxy peptidase A2(cpa2) Q504N0 Metallo- carboxypeptidase activity

Protein disulfide isomerase (PDI) P09103 Protein disulfide isomerase activity

Enrichment analysis of Gene Ontology (GO) biological process.

We further examined the biological process enrichment analysis of the up-regulated

proteins based on GO terms using genecodis algorithm (reference cite PMID:

22573175, PMID: 19465387). Seventeen differentially proteins mapped to biological

process, with the majority of them involved in proteolysis (3/10), cell redox

homeostasis (2/10), oxygen transport (2/10), glycerol-ether metabolic process (2/10),

regulation of cell adhesion (1/10), erythrocyte maturation (1/10), cholesterol catabolic

process (1/10), pancreatic juice secretion (1/10), peptidyl-proline hydroxylation to 4-

hydroxy-L-proline (1/10) and ceramide catabolic process (1/10) (Fig 5.3A).

127

Enrichment analysis of GO molecular function.

GO analysis based on molecular functions showed that 17 (4/10) up-regulated

proteins were involved in the activities of hydroxylase (3/10), peptidase (2/10),

carboxypeptidase (2/10), metallocarboxy peptidase (2/10), protein disulfide oxido

reductase (2/10), protein disulfide isomerase (2/10), oxygen binding (2/10), oxygen

transporter (2/10), hemoglobin alpha binding (1/10), retinyl palmitate esterase (1/10),

sterol esterase (1/10) and exopeptidase (1/10) (Fig. 5.3B).

Enrichment analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG)

pathways.

KEGG pathway analysis highlighted that prenatal exposure of PFOS might affect the

functions of the fetal pancreas, including pancreatic secretion (4/10), protein

digestion and absorption (3/10), protein processing in endoplasmic reticulum (1/10),

fat digestion and absorption (1/10), glycerolipid metabolism (1/10) and steroid

biosynthesis (1/10) pathways (Fig. 5.4).

128

A

Fig 5.3. Pie diagram showing the enrichment analysis of gene ontology of PFOS

responsive proteins in mice. (A) Proteolysis (3/10) is the dominant category in the

biological process. (B) Hydrolase activity (4/10) is the dominant molecular function

in GO assignment.

B

129

PFOS exposed fetal

mice pancreas

B

Pancreatic secretion

(BAL, Cpa1, Cpa2)

Protein digestion and

absorption (Cpa1, Cpa2)

Steroid biosynthesis (BAL)

Glycero lipid

metabolism (BAL)

Fat digestion and

absorption (BAL)

Protein processing in

endoplasmic reticulum

(PDI)

Fig 5.4. Enrichment analysis of KEGG pathways showing pancreatic secretion (4/10) is the dominant

pathway followed by protein digestion and absorption (3/10), protein processing in endoplasmic

reticulum (1/10) fat digestion and absorption (1/10), glycerolipid metabolism (1/10) and steroid

biosynthesis (1/10).

A

130

Chymotrypsin-like elastase family members (Elastase-1, Cela2A, Cela3B).

In the KEGG pathways analysis, we found that a number of dysregulated proteins

including Bile salt activated lipase (BAL), Chymotrypsin-like elastase family

member 3B (CELA3B), Carboxypeptidase A1 (Cpa1), and Carboxypeptidase A2

(Cpa2) are involved in pancreatic functions (Fig. 5.4B), such as pancreatic secretion,

fat digestion and absorption and glycerolipid metabolism.

Pancreas involved in secretion of digestive enzymes into small intestines to

hydrolysis protein to be absorbed by intestinal villus. Among the enzymes,

chymotrypsin and elastase are endopeptidases of serine protease family.

Chymotrypsin hydrolyses protein at the peptide (aromatic amino acids for example

tyrosine, tryptophan) level while elastase hydrolyses small amino acids (for example

glycine, serine, alanine) (Schmitz, 2004). Humans have six elastase genes

(Rosenbloom, 1984; Appelt et. al., 1988) which encode the structurally similar

proteins elastase 1, 2, 2A, 2B, 3A, and 3B. Elastase 3B is involved in intestinal

transport and metabolism of cholesterol. Generally elastase 3A and elastase 3B is

referred as elastase-1 (NCBI, 2015). The determination of major elastic like elements

in pancreatic juices may serve as a springboard for understanding the pancreatic

functions. For example, an excretion of elastase-1 protein in fecal materials is

frequently used as a measure of pancreatic function in clinical assays. In order to

measure the elastase concentrations in stool, monoclonal antibodies and an ELISA is

commercially available elsewhere in Europe (Gullo, et.al., 1999; Dominguez-Munoz

et.al., 1995; Amann, et.al., 1996). In the inflammation of the pancreas, pancreatic

elastase-1 (E1) is released into the bloodstream. Thus, the quantification of elastase-1

in serum allows diagnosis or exclusion of acute pancreatitis (Clavien et. al., 1989).

The concentration of elastase-1 was measured in patients with chronic pancreatitis

and those with non-pancreatic digestive diseases (Gullo et.al., 1999). Progressive use

of elastase-1 and its role in distinguishing between cystic fibrosis and pancreatic

inefficiencies is also recognized (Glasbrenner et. al., 2002). A study conducted with

cigarette smoke effects on mouse suggested that a set of pancreatic enzymes

including carboxypeptidase 1 (Cbp1), Chymotrypsin-like elastase (Cela3b) was

131

highly up-regulated in livers of ApoE-/- mice exposure to cigarette smoke (Leon et.

al., 2013), which is consistent with our findings.

Carboxypeptidases A1 and Carboxypeptidases A2.

The enzymes involved in the digestion of C-terminus peptide chains are called

carboxypeptidases. Carboxypeptidases are classified into A1 (Cpa1) and A2 (Cpa2),

A3, B1 and B2 (Whitcomb and Lowe, 2007). Cpa1 acts on terminal amino acid of a

target peptide whereas Cpa2 attack the basic amino acids (serine hydrolase activity).

The carboxypeptidase family and the elastase family are strongly associated with

microvascular endothelial cell dysfunction (Han et. al., 2010).

The carboxypeptidase enzymes are synthesized by proenzymes that are activated by

trypsin (Whitcomb and Lowe, 2007). But it was reported that premature activation of

trypsin in the pancreas causes the risk of acute pancreatitis (Whitcomb, 1999). Some

other studies showed that the proper regulation of protease enzymes can help to

prevent from digesting of body tissue, and activating inflammatory pathways

(Whitcomb and Lowe, 2007). In our iTRAQ results, the carboxypeptidase family

proteins (Cpa1 and Cpa2) were expressed in mouse pancreatic cells that can be used

as potential biomarkers to indicate pancreatic inflammation.

Serine protease inhibitor (Serpin I2).

Serine proteases are enzymes that cleave the peptide bonds in protein. One thousand

five hundred serpin sequences have been identified (Potempa et.al., 1994). Serpins

play important physiological roles in hormone transport, corticosteroid binding,

coagulation, and blood pressure regulation, tumor invasion and inflammation

(Silverman, 2001; Mignatti, and Rifkin, 1993). The use of SERPINs for identification

of diseases was suggested (Heit, 2013). Specifically, SERPINI2, as they have

unknown target may be involved in pancreatic dysfunction (Ozaki et. al., 1998). It is

expressed in the heart, plasma and platelets. But it was reported that serpin I2 is a

protein specific to the pancreas and to breast cancer stroma (Ozaki et.al., 1998; Xiao

et.al., 1999). The function of Serpin I2 is poorly understood, however, sequence

132

analysis suggested its role as a serine protease inhibitor in protein digestion and

absorption. Some other studies suggested that Serpin I2 deficiency directly results in

the apoptosis of acinar cell, mal-absorption, and malnutrition observed in pq/pq mice

(Loftus et. al., 2005).

Bile salt-Activated Lipase (BAL).

For the digestion of fat droplets, pancreas secretes lipase enzyme (Scheele et.al.,

1981) that requires bile salt for the activation Fat digestion by BAL occurs in the

small intestine (Iijima et. al., 1998; Wang and Hartsuck, 1993). BAL brokedown fats

by hydrolysis and make them absorbable by the intestinal lumen. But the activity of

the BAL is solely depended on bile salts released by the pancreas. In the human

infant, BAL is also presence in the breast milk (Alemi et. al., 1981; Wang et.al.,

1989). Thus, the copious supply of BAL in the mother's milk, in fact, show no

activity until it reaches the intestine where the bile salt is secreted. Therefore, these

evidences suggested that BAL is especially important for human infant nutrition

(Wang et. al., 1997).

Like other intestinal lipases BAL facilitated the hydrolytic activity for

triacylglycerol. Some other unique functions, for example hydrolytic activity of

cholesterol and vitamin A esters were reported (Lombardo, and Guy, 1980;

Fredrikzon et.al., 1978), highlighting the importance of BAL in human physiological

functions (Wang et. al., 1997). In laboratory experiment, BAL stimulated cholesterol

uptake in cultured cells (Lepez-Candales et.al., 1993). This observation was

supported by a transgenic mice study, in which reduced reduction of cholesterol

uptake was observed in BAL-knockout mice (Howles et. al., 1996). If pancreas stops

working or fails, the fat droplets cannot be hydrolysed, leading to steatorrhea

(DiMagno et.al., 1973) the presence of excessive fat in faces.

133

5.4 Conclusion

This study postulated that prenatal exposure to PFOS altered fetal pancreatic

functions. A total of 176 proteins exhibited differential expression in medium and

high dose treatment groups. Among them, a total of 91 differentially up-regulated

proteins were identified in the medium and high dose groups with 17 proteins

overlapped, including chymotrypsin-like elastase family members, Serpin I2, PRSS3,

bile salt-activated lipase (BAL), protein disulfide isomerase (PDI) and

carboxypeptidases. In the fetal pancreas, the effects of PFOS were noticeable in

affecting the expression of the proteins associated with hydroxylase activity,

peptidase activity, carboxypeptidase activity, metallocarboxy peptidase activity,

protein disulfide oxido reductase activity, protein disulfide isomerase activity, oxygen

binding, oxygen transporter activity, hemoglobin alpha binding, retinyl palmitate

esterase activity, sterol esterase activity and exopeptidase activity. The KEGG

pathway analysis showed that the differential expressed proteins are mainly involved

in pancreatic functions such as pancreatic secretion, fat digestion and absorption, and

glycerolipid metabolic pathways. From the literatures, we found some of the proteins,

for example, chymotrypsin-like elastase-1 is associated with inflammation, initial

cause for diseases progression. Apparently, we extrapolated that the excessive

secretion of some of the enzymes might provoke the inflammation in pancreas, thus

increased the risk of pancreatitis. Taken together, the results of the iTRAQ analysis

suggested that PFOS affected the expression levels of some pancreatic protein in

mice. The identification of BAL, SERPIN I2, elastase family member proteins

(elastase-1, Cela2A, cela3B) might be helpful for the diagnosis of PFOS exposure in

associated with pancreatitis. However, the possible role of PFOS in the risk of

pancreatitis may warrant further investigation.

134

References

Abbott, B. D. 2009. Review of the expression of peroxisome proliferator-activated

receptors alpha (PPARα), beta (PPARβ), and gamma (PPARγ) in rodent

and human development. Reproductive toxicology, 27(3), 246-257.

Adams, P. 2003. Presentation at the Conference ―Particulate Matter: Atmospheric

Sciences, Exposure, and the Fourth Colloquium on PM and Human

Health,‖ Pittsburgh, PA, March 31–April 4.

Akimoto, H. 2003. Global air quality and pollution. Science, 302(5651), 1716

1719.

Akyuz, M., Cabuk, H., 2008. Particle-associated polycyclic aromatic

hydrocarbons in the atmospheric environment of Zonguldak, Turkey. Sci

Total Environ 405, 62-70.

Alemi, B., Hamosh, M., Scanion, J.W., Salzman-Mann, C. and Hamosh, P. 1981.

Pediatrics 68, 484-489.

Alfaro-Moreno, E., Ponce-de-León, S., Osornio-Vargas, A. R., García-Cuellar,

C., Martínez, L., & Rosas, I. 2007. Potential toxic effects associated to

metals and endotoxin present in PM10: an ancillary study using

multivariate analysis. Inhalation toxicology, 19(S1), 49-53.

Allen, J., Bartlett, K., Graham, M., & Jackson, P. 2011. Ambient concentrations

of airborne endotoxin in two cities in the interior of British Columbia,

Canada. Journal of Environmental Monitoring, 13(3), 631-640.

Amann, S. T., Bishop, M., Curington, C., Toskes, P. P., 1996. Fecal pancreatic

elastase 1 is inaccurate in the diagnosis of chronic pancreatitis. Pancreas

13:226–230

Anderson, L. M., Diwan, B. A., Fear, N. T., Roman E. 2000. Critical windows of

exposure for children‘s health: cancer in human epidemiological studies

and neoplasms in experimental animal models. Environ Health

Perspect.108 (suppl 3):573–594.

135

Appelt, G., Schulze, B., Rogos, R., Kopperschlager, G., 1988. Analysis of human

exocrine pancreatic proteins by means of pore gradient polyacrylamide gel

electrophoresis. Biomed Biochim Acta 47:133–140

Arrieta, D. E., Ontiveros, C. C., Li, W. W., Garcia, J. H., Denison, M. S.,

McDonald, J. D., ... & Washburn, B. S. 2003. Aryl hydrocarbon receptor-

mediated activity of particulate organic matter from the Paso del Norte

airshed along the US-Mexico border. Environmental health perspectives,

111(10), 1299.

Asby, E., Anderson, M. 1982. The Politics of Clean Air, Oxford University Press,

Oxford.

Asian Correspondent, 2013. Record pollution levels reported at Beijing Culture

and Tourism City site. Retrieved on 15 January 2015 from

http://asiancorrespondent.com/95342/highest-pm2-5-level-reported-in-

beijing-culture-and-tourism-city/

ATSDR (Agency for Toxic Substance and Diseases Registry), 2009. Draft

toxicological profile for perfluoroalkyls.www.atsdr.cdc.gov/tox

profiles/tp200.pdf

Bachmann, J. D. 2003. Presentation at the Conference ―Particulate Matter:

Atmospheric Sciences, Exposure, and the Fourth Colloquium on PM and

Human Health,‖ Pittsburgh, PA, March 31–April 4.

Bai, Y., Suzuki, A., Sagai, M. 2001. The cytotoxic effects of diesel exhaust

particles on human pulmonary artery endothelial cells in vitro: role of

reactive oxygen species. Free Radical Biology and Medicine, 30:555–562.

Bascom, R., Bromberg, P. A., Costa, D. L., et al. 1996. Health effects of outdoor

air pollution. Am J Respir Crit Care Med. 153: 477-98.

Baulig, A., Singh, S., Marchand, A., Schins, R., Barouki, R., Garlatti, M.,

Marano, F., Baeza-Squiban,A., 2009. Role of Paris PM2.5 components in

the pro-inflammatory response induced in airway epithelial

cells.Toxicol.261, 126–135.

Beeson, W.L., Abbey, D. E., Knutsen, S. F. 1998. Long-term concentrations of

ambient air pollutants and incident lung cancer in California adults: results

from the AHSMOG study. Adventist Health Study on Smog.

Environmental Health Perspectives; 106:813–823.

136

Benninghoff, A. D. 2007.Toxicoproteomics - The next step in the evolution of

environmental biomarkers? Toxicol. Sci., 95 (1), 1− 4.

Berger, J., & Moller, D. E. 2002. The mechanisms of action of PPARs. Annual

review of medicine, 53(1), 409-435.

Bertazzi, P. A., Consonni, D., Bachetti, S., Rubagotti, M., Baccarelli, A.,

Zocchetti, C., & Pesatori, A. C. 2001. Health effects of dioxin exposure: a

20-year mortality study. American Journal of Epidemiology, 153(11),

1031-1044.

Billet, S., Abbas, I., LeGoff, J.,Verdin, A., Andre,V., Lafargue, P. E., Hachimi,

A., Cazier, F., Sichel, F., Shirali, P., Garcon, G., 2008. Genotoxic potential

of polycyclic aromatic hydrocarbons-coated onto air borne particulate

matter (PM2.5) in human lung epithelial A549cells. Cancer Lett.270, 144–

155.

Binkov , B., Vesel , D., Vesel , D., Jel nek, R., r m, R. J. 1999. enotoxicity

and embryotoxicity of urban air particulate matter collected during winter

and summer period in two different districts of the Czech

Republic.Mutation Research/Genetic Toxicology and Environmental

Mutagenesis, 440(1), 45-58.

Bjork, J. A., Lau, C., Chang, S. C., Butenhoff, J. L., & Wallace, K. B. 2008.

Perfluorooctane sulfonate induced changes in fetal rat liver gene

expression. Toxicology, 251(1), 8-20.

Blankenship, A. L., Kannan, K., Villalobos, A., Falandysz, J., Giesy J. P. 2000.

Relative potencies of halowax mixtures and individual polychlorinated

naphthalenes (PCNs) in H4IIe-Luc cell bioassay Environ. Sci. Technol.,

34, pp. 3153–3158.

Blomhoff, R., Wake, K. 1991. Perisinusoidal stellate cells of the liver: important

roles in retinol metabolism and fibrosis. FASEB J; 5:271–7.

Bostrom, C. E., Gerde, P., Hanberg, A., Jernstrom, B., Johansson, C., Kyrklund,

T., Rannug, A., Tornqvist, M., Victorin, K., Westerholm, R., 2002. Cancer

risk assessment, indicators, and guidelines for polycyclic aromatic

hydrocarbons in the ambient air. Environ Health Perspect 110 Suppl 3,

451-488.

137

Braakman, I., Hoover-Litty, H., Wagner, K. R., & Helenius, A. 1991. Folding of

influenza hemagglutinin in the endoplasmic reticulum. The Journal of cell

biology, 114(3), 401-411.

Brigham, K. L., & Meyrick, R. A. 1986. Endotoxin and lung injury. The

American review of respiratory disease, 133(5), 913-927.)

Brimblecombe, P. 1977. London air pollution 1500–1900. Atmospheric

Environment; 11:1157–1162.

Brody, J. S., & Spira, A. 2006. State of the art. Chronic obstructive pulmonary

disease, inflammation, and lung cancer. Proceedings of the American

Thoracic Society, 3(6), 535-537.

Broman, D., Rolff, C., Näf, C., Zebühr, Y., Fry, B., & Hobbie, J. 1992. Using

ratios of stable nitrogen isotopes to estimate bioaccumulation and flux of

polychlorinated dibenzo‐p‐dioxins (PCDDs) and dibenzofurans (PCDFs)

in two food chains from the Northern Baltic. Environmental Toxicology

and Chemistry, 11(3), 331-345.

Bronzetti, G., Cini, M., Paoli, M., Ciacchini, G., Giaconi, V., & Morichetti, E.

1996. Mutagenicity and chemical analysis of airborne particulate matter

collected in Pisa. Journal of environmental pathology, toxicology and

oncology: official organ of the International Society for Environmental

Toxicology and Cancer, 16(2-3), 147-156.

Brown, D. M., Wilson, M. R., MacNee, W., Stone, V., Donaldson, K. 2001. Size-

dependent pro-inflammatory effects of ultrafine polystyrene particles: the

role of surface area and oxidative stress in the enhanced activity of

ultrafines. Toxicology and Applied Pharmacology, 175:191–199.

Brunekreef, B., Beelen, R., Hoek, G., Schouten, L., Bausch-Goldbohm, S.,

Fischer, P., Armstrong, B., Hughes, E., Jerrett, M., van den Brandt, P.,

2009. Effects of long-term exposure to traffic-related air pollution on

respiratory and cardiovascular mortality in the Netherlands: the NLCS-

AIR study. Res Rep Health Eff Inst, 5-71; discussion 73-89.

Brunekreef, B., Holgate, S.T., 2002. Air pollution and health. Lancet 360, 1233.

Buja, L. M., Eigenbrodt, M. L., & Eigenbrodt, E. H. 1993. Apoptosis and

necrosis. Basic types and mechanisms of cell death. Archives of pathology

& laboratory medicine, 117(12), 1208-1214.

138

Buschini, A., Cassoni, F., Anceschi, E., Pasini, L., Poli, P., & Rossi, C. 2001.

Urban airborne particulate: genotoxicity evaluation of different size

fractions by mutagenesis tests on microorganisms and comet assay.

Chemosphere, 44(8), 1723-1736.

Cachon, B. F., Firmin, S., Verdin, A., Ayi-Fanou, L., Billet, S., Cazier, F., Martin,

P.J., Aissi, F., Courcot, D., Sanni, A., Shirali, P., 2014. Pro-inflammatory

effects and oxidative stress within human bronchial epithelial cells

exposed to atmospheric particulate matter (PM2.5 and PM>2.5) collected

from Cotonou, Benin. Environ Pollut 185, 340-351.

CAFE Working Group on Particulate Matter. 2004. Second position paper on

particulate matter.Brussels: CAFE Working Group on Particulate Matter.

Seealsohttp://ec.europa.eu/environment/air/cafe/pdf/working_groups/2nd_

Cai, H., & Xie, S. 2007. Estimation of vehicular emission inventories in China

from 1980 to 2005. Atmospheric Environment, 41(39), 8963-8979.

Calafat, A. M., Kuklenyik, Z., Caudill, S. P., Reidy, J, A., Needham L. L.,

Perfluorochemicals in pooled serum samples from United States residents

in 2001 and 2002. Environmental Science & Technology 2006a; 40: 2128-

2134.

Calafat, A. M., Needham, L. L., Kuklenyik, Z., Reidy, J. A., Tully, J. S., Aguilar-

Villalobos, M., Naeher L, P. Perfluorinated chemicals in selected

residents of the American continent. Chemosphere 2006b; 63: 490-496.

Campling, B. G., Pym, J., Galbraith, P. R., & Cole, S. P. 1988. Use of the MTT

assay for rapid determination of chemo sensitivity of human leukemic

blast cells. Leukemia research, 12(10), 823-831.

Cao, J. J., Shen, Z. X., Chow, J. C., Watson, J. G., Lee, S. C., Tie, X. X., ... &

Han, Y. M. 2012. Winter and summer PM2.5 chemical compositions in

fourteen Chinese cities. Journal of the Air & Waste Management

Association, 62(10), 1214-1226.

ern , M., Pochmanov , D., Pastorkov , A., Bene , ., en ek, J., Topinka, J., &

Binková, B. 2000. Genotoxicity of urban air pollutants in the Czech

Republic: Part i. bacterial mutagenic potencies of organic compounds

adsorbed on PM10 particulates. Mutation Research/Genetic Toxicology

and Environmental Mutagenesis, 469(1), 71-82.

139

Chan, K., & Kan, Y. W. 1999. Nrf2 is essential for protection against acute

pulmonary injury in mice. Proceedings of the National Academy of

Sciences, 96(22), 12731-12736.

Chang, K.F., Fang, G.C., Chen, J.C., Wu, Y.S., 2006. Atmospheric polycyclic

aromatic hydrocarbons (PAHs) in Asia: a review from 1999 to 2004.

Environ Pollut 142, 388-396.

Chavez, E., Jay, D., Bravo, C.1987. The mechanism of lead-induced

mitochondrial Ca2þ efflux. J. Bioenerg. Biomembr 19, 285.

Chen, Z., Wang, J. N., Ma, G. X., Zhang, Y. S. 2013. China tackles the health

effects of air pollution. Lancet 382, 1959-1960.

Chiaverini, L. 2002. Asthma, particulates, and diesel exhaust, Med. Health RI 85,

140–142.

Cho, H. Y., Reddy, S. P, Kleeberger, S. R. 2006. Nrf2 defends the lung from

oxidative stress. Antioxidant and Redox Signaling, 8: 76–87.

Choi, J. H., Kim, J. S., Kim, Y. C., Kim, Y. S., Chung, N. H., and Cho, M. H.

2006. Comparative study of PM2.5 and PM10 - induced oxidative stress in

rat lung epithelial cells. J Vet Sci 5, 11-8.

Clarke, R. W., Catalano, P. J., Coull, B., Koutrakis, P., Krishna Murthy, G.G.,

Godleski, J.J. 2000. Age-related responses in rats to concentrated urban air

particles (CAPs). In: Proceedings of the third colloquium on particulate air

pollution andhuman health. June 1999; Durham, NC. Inhal. Toxicology.

129 (suppl. 1): 73-84.

Clarke, R. W., Catalano, P. J., Koutrakis, P., Krishna Murthy, G. G., Sioutas, C.,

Paulauskis, J., Coull, B., Ferguson, S., Godleski, J.J. 1999. Urban air

particulate inhalation alters pulmonary function and induces pulmonary

inflammation in a rodent model of chronic bronchitis. Inhal. Toxicology

11:637-656.

Clavien, P. A., Burgan, S., & Moossa, A. R. 1989. Serum enzymes and other

laboratory tests in acute pancreatitis. British journal of surgery, 76(12),

1234-1243.

Claxton, L. D., Matthews, P. P., & Warren, S. H. 2004. The genotoxicity of

ambient outdoor air, a review: Salmonella mutagenicity. Mutation

Research/Reviews in Mutation Research, 567(2), 347-399.

140

Claxton, L. D., Morin, R. S., Hughes, T. J., & Lewtas, J. 1989. A genotoxic

assessment of environmental tobacco smoke using bacterial bioassays.

Mutation Research/Genetic Toxicology, 222(2), 81-99.

Clifton, M., Stuart Harris, C. 1978. Effect of air pollution, Part 1. Air pollution

and health. In: Parker, A. (ed.), Industrial Air Pollution, McGraw Hill,

London, pp. 1931.

Cohen, A. J., Ross Anderson, H., Ostro, B., Pandey, K. D., Krzyzanowski, M.,

Künzli, N., & Smith, K. 2005. The global burden of disease due to outdoor

air pollution. Journal of Toxicology and Environmental Health, Part A,

68(13-14), 1301-1307.

Cohen, J. T, Bellinger, D. C, Shaywitz, B. A. 2005. A quantitative analysis of

prenatal methyl mercury exposure and cognitive development. Am J Prev

Med. 29(4):353–365

Colquhoun, D. R., Goldman, L. R., Cole, R. N., Gucek, M., Mansharamani, M.,

Witter, F. R., Apelberg, B. J., Halden, R. U. 2009. Global Screening of

human cord blood proteomes for biomarkers of toxic exposure and effect.

Environ. Health Perspect, 117 (5), 832−838.

Conner, E. M., & Grisham, M. B. 1996. Inflammation, free radicals, and

antioxidants. Nutrition, 12(4), 274-277.

Corton, J. C., Fan, L. Q., Brown, S., Anderson, S. P., Bocos, C., Cattley, R. C.,

1998. Distribution of perfluorochemicals between sera and milk from the

same mothers and implications for prenatal and postnatal exposures.

Environmental Pollution, 159(1), 169-174.

Corton, J.C., Anderson, S.P., Stauber, A., 2000. Central role of peroxisome

proliferator activated receptors in the actions of peroxisome proliferators.

Annu. Rev. Pharmacol. Toxicol. 40, 491–518.

Costa, D. L., & Dreher, K. L. 1997. Bioavailable transition metals in particulate

matter mediate cardiopulmonary injury in healthy and compromised

animal models. Environmental health perspectives, 105(Suppl 5), 1053.

Costa, M., Yan, Y., Zhao, D., Salnikow, K., 2003. Molecular mechanisms of

nickel carcinogenesis: gene silencing by nickel delivery to the nucleus and

gene activation/inactivation by nickel-induced cell signaling. J. Environ.

Monit. 5, 222.

141

Crutzen, P. J., Heidt, L. E., Krasnec, J. P., Pollock, W. H., & Seiler, W. 1979.

Biomass burning as a source of atmospheric gases CO, H2, N2O, NO,

CH3Cl and CO2. Nature, 282, 253-256.

Cuzzocrea, S., Mazzon, E., Di Paola, R., Peli, A., Bonato, A., Britti, D.,

Genovese, T., Muia, C., Crisafulli, C., Caputi, A. P., 2006. The role of the

peroxisome proliferator activated receptor-alpha (Ppar -alpha) in the

regulation of acute inflammation. J. Leukoc. Biol. 79, 999–1010.

D‘eon, J. C., Mabury, S. A. 2011. s indirect exposure a significant contributor

to the burden of perfluorinated acids observed in humans? Environmental

science & technology, 45(19), 7974-7984.

Dahl, R. 2005. Heavy traffic ahead: car culture accelerates. Environ Health

Perspect.113 (4):A238–A245.

D'amato, G., Liccardi, G., D'amato, M., & Cazzola, M. 2001. The role of outdoor

air pollution and climatic changes on the rising trends in respiratory

allergy. Respiratory medicine, 95(7), 606-611.

Dannisenko, M. F. A., Tang, M. S., Pfeifer G. P. 1996. Preferential formation of

benzo[a]pyrene adducts at lung cancer mutational hotspots in p53.

Carcinogenesis, 14:475–482.

Davidson, C. I., Phalen, R. F., & Solomon, P. A. 2005. Airborne particulate

matter and human health: a review. Aerosol Science and Technology,

39(8), 737 749.

De Kok, T. M., Hogervorst, J. G., Briedé, J. J., van Herwijnen, M. H., Maas, L.

M., Moonen, E. J., & Kleinjans, J. C. 2005. Genotoxicity and

physicochemical characteristics of traffic‐related ambient particulate

matter. Environmental and molecular mutagenesis, 46(2), 71-80.

Deng, X. 2006. Economic costs of motor vehicle emissions in China: a case study.

Transportation Res D Transport Environ,11(3): 216–222

Dergham, M., Lepers, C., Verdin, A., Billet, S., Cazier, F., Courcot, D., Shirali,

P., Garcon, G., 2012. Pro-oxidant and pro-inflammatory potency of air

pollution particulate matter (PM2.5-0.3) produced in rural, urban, or

industrial surroundings in human bronchial epithelial cells (BEAS-2B).

Chem Res Toxicol 25, 904-919.

Desvergne, B., Wahli, W. 1999. Peroxisome proliferator-activated receptors:

nuclear control of metabolism, Endocr. Rev. 20, 649–688.

142

Deutsch-Wenzel, R. P., Brune, H., Grimmer, G., Dettbarn, G., & Misfeld, J.

1983. Experimental studies in rat lungs on the carcinogenicity and dose-

response relationships of eight frequently occurring environmental

polycyclic aromatic hydrocarbons. Journal of the National Cancer

Institute, 71(3), 539-544.

Dietert, R. R., Etzel, R. A., Chen, D., Halonen, M., Holladay, S. D., Jarabek, A.

M., & Zoetis, T. 2000. Workshop to identify critical windows of exposure

for children's health: immune and respiratory systems work group

summary. Environmental health perspectives, 108(Suppl 3), 483.

DiMagno, E. P., Go, V. L., Summerskill, W. H., 1973. Relations between

pancreatic enzyme ouputs and malabsorption in severe pancreatic

insufficiency. N Engl J Med 288:813–815.

Dimashki, M., Lim, L. H., Harrison, R. M., Harrad, S. 2001. Temporal trends,

temperature dependence, and relative reactivity of atmospheric polycyclic

aromatic hydrocarbons. Environ Sci Technol 35:2264–2267.

Dockery, D. W., Pope, C. A III. 1994. Acute respiratory effects of particulate air

pollution. Annu Rev Public Health.15:107-32.

Dockery, D. W., Schwartz, J., and Spengler, J. D. 1993. Air pollution and daily

mortality Association with particulates and acid aerosols. Environ. Res.

59, 362-373.

Dominguez-Munoz, J. E., Hieronymus, C., Sauerbruch, T., Malfertheiner, P.

1995 Fecal elastase test: evaluation of a new noninvasive pancreatic

function test. Am J Gastroenterol 90:1834–1837.

Donaldson, K., Gilmour, M. I., Mac Nee, W., 2001. Asthma and PM10. Respir.

Res. 1, 12–15.

Duan, F. K., He, K. B., Ma, Y. L., Yang, F. M., Yu, X. C., Cadle, S. H., et al.

2006. Concentration and chemical characteristics of PM2.5 in Beijing,

China: 2001–2002. Sci Total Environ, 355: 264–75.

Duan, J., Bi, X., Tan, J., Sheng, G., and Fu, J. 2007. Seasonal variation on size

distribution and concentration of PAHs in Guangzhou city, China.

Chemosphere, 67(3), 614-622.

Duval, M. M., & Friedlander, S. K. 1981. Source resolution of polycyclic

aromatic hydrocarbons in the Los Angeles atmosphere application of a

143

CMB with first-order decay. U.S. EPA report EPA-600/2-81-161.

Washington, DC: US Government Printing Office.

Dyke, P., Coleman, P., & James, R. 1997. Dioxins in ambient air, bonfire night

1994. Chemosphere, 34(5), 1191-1201.

Economy, E. C. 2003. China‘s Environmental Challenge: Political, Social, and

Economic Implications. New York, NY: Council on Foreign Relations.

Economy, E. C. 2007.The great leap backward? Foreign Aff.; 86(5):38–59

Ellis, D. A., Martin, J. W., De Silva, A. O., Mabury, S. A., Hurley, M. D., Sulbaek

Andersen, M. P., Wallington, T. J., 2004. Degradation of fluorotelomer

alcohols: a likely atmospheric source of perfluorinated carboxylic acids.

Environmental Science & Technology 38, 3316-3321.

Elsom, D. Atmospheric Pollution, Blackwell, Oxford, 1987, pp. 156–160.

Environmental Protection Agency, Office of Air Quality Planning and Standards.

1996. Review of the National Ambient Air Quality Standards for

Particulate Matter: policy assessment of scientific and technical

information. OAQPS staff paper no. EPA-452\R-96-013. Washington,

D.C.: Government Printing Office.

EPA, U.S. 2004. Air Quality Criteria for Particulate Matter (vol. I, EPA/600/P-

99/002aF and vol. II, EPA/600/P-99/002bF), Report.

European Commission. 2003. Technical Guidance Document in support of

Commission Directive 93/67/EEC on Risk Assessment for New Notified

Substances, Commission Regulation (EC) No. 1488/94 on Risk

Assessment for Existing Substances and Directive 98/8/EC of the

European Parliament and of the Council Concerning the Placing of

Biocidal Products on the19 Market. Joint Research Centre, European

Chemicals Bureau, Brussels, Belgium.

Feng, J. L., Hu, M., Chan, C. K., Lau. P. S., Fang, M. He., L. Y., et al. 2006. A

comparative study of the organic matter in PM2.5 from three Chinese

megacities in three different climatic zones. Atmos Environ, 40(21):3983–

94.

Fredrikzon, B., Hernell, O., Blackberg, L. and Olivecrona, T. 1978. Pediat. Res.

12, 1048-1052.

144

Gielen, M. H., van der Zee, S. C., van Wijnen, J. H., van Steen, C. J., Brunekreef,

B., 1997. Acute effects of summer air pollution on respiratory health of

asthmatic children. Am. J. Respir. Crit. Care Med. 155, 2105–2108.

Giesy, J. P, Hilscherova, K., Jones, P. D., Kannan, K and Machala, M. 2002. Cell

bio-assays for detection of aryl hydrocarbon (AhR) and estrogen receptor

(ER) mediated activity in environmental samples, Marine pollution

Bulletin 45: 3-16.

Giesy, J. P., & Kannan, K. 2001. Global distribution of perfluorooctane sulfonate

in wildlife. Environmental science & technology, 35(7), 1339-1342.

Gilbert, H. F. 1997. Protein disulfide isomerase and assisted protein

folding.Journal of Biological Chemistry, 272(47), 29399-29402.

Glasbrenner, B., Kahl, S., & Malfertheiner, P. 2002. Modern diagnostics of

chronic pancreatitis. European journal of gastroenterology &

hepatology, 14(9), 935-941.

Glover, J. 1974. Retinol-binding proteins. Vitamins & Hormones, 31, 1-42.

Godleski, J. J., Verier, R. L, Koutrakid, P., Catalano, P. 2000. Mechanisms of

morbidity and mortality from exposure to ambient air particles.

Cambridge, MA: Health Effects Institute; research report no. 91.

Gonzales-Flecha B. 2004. Oxidant mechanisms in response to ambient air

particles. Molecular Aspects of Medicine, 25:169–182.

Gordon, T., Nadziejko, C., Chen, L. C., Schlessinger, R. 2000. Effects of

concentrated ambient particles in rats and hamsters: an exploratory study.

Cambridge, MA: Health Effects Institute; research report no. 93.

Gotschi, T., Heinrich, J., Sunyer, J., Kuzli, N. 2008. Long-term effects of ambient

air pollution on lung function: a review. Epidemiology, 19:690–701.

Grandjean P, Landrigan P. J. 2006. Developmental neurotoxicity of industrial

chemicals. Lancet.368 (9553):2167–2178

Grasty, R. C., Bjork, J. A., Wallace, K. B., Lau, C. S., & Rogers, J. M. 2005.

Effects of prenatal perfluorooctane sulfonate (PFOS) exposure on lung

maturation in the perinatal rat. Birth Defects Research Part B:

Developmental and Reproductive Toxicology, 74(5), 405-416.

145

Grasty, R. C., Grey, B. E., Lau, C. S., Rogers, J. M., 2003a. Prenatal window of

susceptibility to perfluorooctane sulfonate-induced neonatal mortality in

the Sprague–Dawley rat. Birth Defects Res. B Dev. Reprod. Toxicol. 68,

465–471.

Grasty, R. C., Grey, B. E., Lau, C. S., Rogers, J.M., 2003b. Prenatal window of

susceptibility to perfluorooctane sulfonate-induced neonatal mortality in

the Sprague–Dawley rat. Birth Defects Res. (Part B) 68, 465–471.

Greenbaum, D. S. 2003. A historical perspective on the regulation of particles. J

Toxicol Environ Health A 66, 1493-8.

Greenwell, L. L., Moreno, T., Jones, T. P., & Richards, R. J. 2002. Particle-

induced oxidative damage is ameliorated by pulmonary antioxidants. Free

Radical Biology and Medicine, 32(9), 898-905.

Gualtieri, M., Øvrevik, J., Holme, J. A., Perrone, M. G., Bolzacchini, E.,

Schwarze, P. E., Camatini, M., 2010. Differences in cytotoxicity versus

pro-inflammatory potency of different PM fractions in human epithelial

lung cells. Toxicology in Vitro 24, 29–39.

Gullo, L., Ventrucci, M., Tomassetti, P., Migliori, M., & Pezzilli, R. 1999. Fecal

elastase 1 determination in chronic pancreatitis. Digestive diseases and

sciences, 44(1), 210-213.

Gutierrez-Castillo, M., Roubicek, D. A., Cebri´an-Garcia, M. E., De Vizcaya-

Ruiz, A., Sordo-Cedeo, M., Ostrosky-Wegman, P. 2006. Effect of

chemical composition on the induction of DNA damage by urban airborne

particulate matter. Environmental and Molecular Mutagenesis; 47:199–

211.

Gützkow, K. B., Line, S., Haug, C. T., Azemira, S., Georg, B., and Gunnar B.

2012. "Placental transfer of perfluorinated compounds is selective–a

Norwegian Mother and Child sub-cohort study." International journal of

hygiene and environmental health 215, no. 2: 216-219.

Ha, E. H, Lee, J. T, Kim, H., et al. 2003. Infant susceptibility of mortality to air

pollution in Seoul, South Korea. Pediatrics. 111(2): 284–290

Hamers, T., Van Schaardenburg, M. D., Felzel, E. C., Murk, A. J., & Koeman, J.

H. 2000. The application of reporter gene assays for the determination of

the toxic potency of diffuse air pollution. Science of the total environment,

262(1), 159-174.

146

Han, D., Moon, S., Kim, H., Choi, S. E., Lee, S. J., Park, K. S., & Kim, Y. 2010.

Detection of differential proteomes associated with the development of

type 2 diabetes in the Zucker rat model using the iTRAQ

technique. Journal of proteome research, 10(2), 564-577.

Hansen, J. E., & Sato, M. 2001. Trends of measured climate forcing agents.

Proceedings of the National Academy of Sciences, 98 (26), 14778-14783.

Hansen, K. J., Clemen, L. A., Ellefson, M. E., & Johnson, H. O. 2001b.

Compound-specific, quantitative characterization of organic

fluorochemicals in biological matrices. Environmental science &

technology, 35(4), 766-770.

Harada, K. Saito, N., Sasaki, K., Inoue, K., Koizumi, A. 2003. Perfluorooctane

sulfonate contamination of drinking water in the Tama River, Japan:

Estimated effects on resident serum levels. Bull Environ Contam Toxicol

71: 31-36.

Harada, K., Nakanishi, S., Saito, N,. Tsutsui, T., Koizumi, A. 2005. Airborn

Perfluorooctanoate May Be a Substantial Source Contamination in Kyoto

Area, Japan, Bull. Environ. Contam. Toxicol, 74:64–69

Harada, K., Nakanishi, S., Sasaki. K., Furuyama, K., Nakayama, S., Saito, N.,

Yamakawa, K., Koizumi, A. 2006. Particle size distribution and

respiratory deposition estimates of airborne perfluorooctanoate and

perfluorooctane-sulphonate in Kyoto area, Japan. Bulletin of

Environmental Contamination and Toxicology, 76: 306-310.

Harrison, R. M., and Yin, J. 2000. Particulate Matter in the Atmosphere: Which

Particle Properties are Important for its Effects on Health? Sci. Total

Environ. 249:85–101

Harrison, R. M., Smith, D. J. T., Luhana, L. 1996. Source apportionment of

atmospheric polycyclic aromatic hydrocarbons collected from an urban

location in Birmingham, UK. Environ Sci Technol 30:825–832.

Hathcock, J. N., Hattan, D. G., Jenkins, M. Y., McDonald, J. T., Sundaresan. P.

R., Wilkening, V. L. 1990. Evaluation of vitamin A toxicity. Am J Clin

Nutr; 52:183–202.

147

Haywood, J., & Boucher, O. 2000. Estimates of the direct and indirect radioactive

forcing due to tropospheric aerosols: A review. Reviews of geophysics,

38(4), 513-543.

He, K. B., Yang, F. M., Ma, Y. L., Zhang, Q., Yao, X. H., Chan, C. K, et al.

2001.The characteristics of PM2.5 in Beijing, China. Atmos Environ,

35(29):4959–70.

He, K., Hou, H., and Zhang, Q. 2002. Urban air pollution in China: Current status,

characteristics, and progress. Annu. Rev. Energy Environ. 2002. 27:397–

431

He, L. Y., Hu, M., Huang, X. F., Zhang, Y. H., Yu, B. D., & Liu, D. Q. 2006.

Chemical characterization of fine particles from on-road vehicles in the

Wutong tunnel in Shenzhen, China. Chemosphere, 62(10), 1565-1573.

Healey, K., Lingard, J. J. N, Tomlin, A., Hughes, A., White, K. L. M, Wild, C. P,

Roudledge, M. N. 2005. Genotoxicity of size-fractionated samples of

urban particulate matter. Environmental and Molecular Mutagenesis;

45:380–387.

Heinrich, J., Pitz, M., Bischof, W., Krug, N., & Borm, P. J. 2003. Endotoxin in

fine (PM2.5) and coarse (PM2.5–10) particle mass of ambient aerosols. A

temporo-spatial analysis. Atmospheric environment, 37(26), 3659-3667.

Heit, C., Jackson, B. C., McAndrews, M., Wright, M. W., Thompson, D. C.,

Silverman, G. A., & Vasiliou, V. 2013. Update of the human and mouse

SERPIN gene superfamily. Hum Genomics, 7(1), 22.

Hertz-Picciotto, I., Dostal, M., James, R. A., Keller, J., Dejmek, J., Selevan, S. G.,

Kotesovec, F., Nozicka, J., Gomez-Caminero, A., Wegienka, G., Sram, R.

J. 2007. Immunity and childhood morbidity in the Teplice program. In:

Teplice Program: Impact of air pollution on human health. (R.J. Sram, ed.)

Academia, Prague, p. 207-215.

Heyman, R. A., Mangelsdorf, D. J., Dyck, J. A., Stein, R. B., Eichele, G., Evans,

R. M. a Thaller, C. 1992. 9-Cis retinoic acid is a high affinity ligand for

the retinoid X receptor. Cell 68: 397-406.

Hiddy, G. M., and Pace, T. 2004. Emissions Characterization, In Particulate

Matter Science for Policy Makers: A NARSTO Assessment. McMurry, P.,

Shepherd, M., and Vickery, J. eds. Chapter 4 Cambridge University Press,

148

United Kingdom, ISBN 0521842875. (EPRI report version available at

http://www. cgenv. com/Narsto link to PM Science and Assessment).

Hirakawa, K., Oikawa, S., Hiraku, Y., Hirosawa, I., Kawanishi, S. 2002. Catechol

and hydroquinone have different redox properties responsible for their

differential DNAdamaging ability. Chemical Research in Toxicology,

15:76–82.

Hiura, T. S., Li, N., Kaplan, R., Horwitz, M., Seagrave, J. C., Nel, A. 2000. The

role of a mitochondrial pathway in the induction of apoptosis by chemicals

extracted from diesel exhaust particles. Journal of Immunology,

165:2703–2711.

Hogrefe, C., Civerolo, K., Ku, J. Y., Lynn, B., Rosenthal, J., Solecki, B. et al.

2006. Air quality in future decades determining the relative impacts of

changes in climate, anthropogenic and biogenic emissions, global

atmospheric composition, and regional land use. In: Air Pollution

Modeling and Its Application XVII (Borrego C, Norman AL, eds).

Proceedings of the 27th NATO/CCMS international technical meeting on

air pollution modeling and its application, 25–29 October 2004, Banff,

Canada. New York: Springer, 217–226.

Howles, P. N., Carter, C. P., Hui, D. Y. Dietary free and esterified cholesterol

absorption in cholesterol esterase (bile salt-stimulated lipase) gene-

targeted mice. 1996. Biol. Chem, 271, pp. 7196–7202 96215158.

Hruban, Z., Russel, l. R. M., Boyer, J. L., et al. 1974. Ultrastructural changes in

livers of two patients with hypervitaminosis A. Am J Pathol, 76451-468.

Hu, M., Zhao, X. L., He, L. Y., Huang, X. F., Tang, X. Y., Yao, X. H, et al. 2005.

Mass size distribution of Beijing particulate matters and its inorganic

water-soluble ions in winter and summer. Environ Sci, 26(4):1–6.

Hu, T. F. S. C., Lee, J. J., Cao, W. K., Ho, K. F., Ho, J. C., Chow, J. G. 2009.

Watson, B. Rong, and Z.S. Atmospheric deterioration of Qin brick in an

environmental chamber at Emperor Qin‘s Terracotta Museum, China.

Journal of Archaeological Science 36(11):2578–2583.

doi:10.1016/j.jas.2009.07.014

Huang, D. W., Sherman, B. T. & Lempicki, R. A. 2009a. Bioinformatics

enrichment tools: paths toward the comprehensive functional analysis of

large gene lists. Nucleic Acids Res. 37, 1-13.

149

Huang, Y. C., Li, Z., Carter, J. D., Soukup, J. M., Schwartz, D. A., and Yang, I.

V. 2009b. Fine ambient particles induce oxidative stress and metal binding

genes in human alveolar macrophages. Am. J. Respir. Cell Mol. Biol.

41:544–552.

Hwang, C. J. S. A., Sinskey, A. J., & Lodish, H. F. 1992. Oxidized redox state of

glutathione in the endoplasmic reticulum. Science, 257(5076), 1496-1502.

Iijima, N., Tanaka, S., & Ota, Y. 1998. Purification and characterization of bile

salt-activated lipase from the hepatopancreas of red sea bream, Pagrus

major.Fish Physiology and Biochemistry, 18(1), 59-69.

INDOEX, 2003. INDOEX, Indian Ocean Experiment, An International Field

Experiment in the Indian Ocean. Information available at http://www-

indoex. ucsd.edu.

Inoue, K., Okada, F., Ito, R., Kato, S., Sasaki, S., Nakajima, S. & Nakazawa, H.

2004. Perfluorooctane sulfonate (PFOS) and related perfluorinated

compounds in human maternal and cord blood samples: assessment of

PFOS exposure in a susceptible population during pregnancy.

Environmental Health Perspectives, 1204-1207.

International Agency for Research on Cancer (IARC), 1983. Monographs on the

Evaluation of the Carcinogenic Risk of Chemicals to Humans: Polynuclear

Aromatic Hydrocarbons, vol. 32. World Health Organization, Lyon,

France.

International Energy Agency. 2009. CO2 Emissions from Fuel Combustion 2009

Highlights: IEA.

International Programme on Chemical Safety (IPCS), 1998. Environmental Health

Criteria 2002. Selected Non-Heterocyclic Polycyclic Aromatic

Hydrocarbons. World Health Organization, Geneva

Ivanov V. P. and Yakobson, G. A. 1965. Exchange of metabolites in plants via

aerial organs," Fiziologiya Rastenii, 12, (3): 405.

Jacobson, M. Z. 2000. A Physically Based Treatment of Elemental Carbon

receptor alpha target genes. Cell Mol. Life Sci. 61, 393–416.

Jacobson, M. Z. 2002. Control of fossil‐fuel particulate black carbon and organic

matter possibly the most effective method of slowing global warming.

150

Journal of Geophysical Research: Atmospheres (1984–2012), 107(D19),

ACH-16.

Jacobson, M. Z. 2008. On the causal link between carbon dioxide and air

pollution mortality. Geophys. Res. Lett, 35:L03809; doi:

10.1029/2007GL031101. [Online 12 February 2008].

Jacobson, M. Z., 2001. Strong radiative heating due to the mixing state of black

carbon in atmospheric aerosols, Nature, 409, 695– 697.

Jacques, E. A., Buschmann, R. J., Layden, T. J. 1979.The histopathologic

progression of vitamin A-induced hepatic injury. Gastroenterology,

76599-602.

Jaffe, D., Anderson, T., Covert, D., Trost, B., Danielson, J., Simpson, W., &

Streets, D. 2001. Observations of ozone and related species in the

northeast Pacific during the PHOBEA campaigns: 1. Ground‐based

observations at Cheeka Peak. Journal of Geophysical Research:

Atmospheres (1984–2012), 106(D7), 7449-7461.

Jahn, H. J., Schneider, A., Breitner, S., Eibner, R., Wendisch, M., & Krämer, A.

2011. Particulate matter pollution in the megacities of the Pearl River

Delta, China–A systematic literature review and health risk assessment.

International journal of hygiene and environmental health, 214(4), 281-

295.

Jarup, L., 2003. Hazards of heavy metal contamination. Br. Med. Bull. 68, 167.

Jiang, G., Cao, F., Ren, G., Gao, D., Bhakta, V., Zhang, Y., & Wang, Y. 2010.

PRSS3 promotes tumour growth and metastasis of human pancreatic

cancer. Gut, 59(11), 1535-1544.

Jin, Y. H., Liu, X., Li, T., Qin, H. M., Zhang, Y. H., 2004. Status of

perfluorochemicals in adult serum and umbilical blood in Shenyang.

Journal of Hygiene Research 33.

Kampa, M., & Castanas, E. 2008. Human health effects of air

pollution.Environmental pollution, 151(2), 362-367.

Kan, H., Chen, R., & Tong, S. 2012. Ambient air pollution, climate change, and

population health in China. Environment international, 42, 10-19.

151

Kan, H., London, S. J, Chen, G, Zhang, Y, Song, G, Zhao, N, et al. 2007.

Differentiating the effects of fine and coarse particles on daily mortality in

Shanghai, China. Environ Int; 33:376–84.

Kanai, M., Raz, A., & Goodman, D. S. 1968. Retinol-binding protein: the

transport protein for vitamin A in human plasma. Journal of Clinical

Investigation, 47(9), 2025.

Kanaly, R. A., & Harayama, S. 2000. Biodegradation of high-molecular-weight

polycyclic aromatic hydrocarbons by bacteria. Journal of bacteriology,

182(8), 2059-2067.

Karlsson, H. L., Nygren, J., Moller, L. 2004. Genotoxicity of airborne particulate

matter: the role of cell-particle interaction and of substances with adduct-

forming and oxidizing capacity. Mutation Research; 565:1–10.

Kasprzak, K. S. 2002. Oxidative DNA and protein damage in metal-induced

toxicity and carcinogenesis. Review. Free Radical Biology and Medicine,

32:958–967.

Katsouyanni, K., Pershagen, G. 1997. Ambient air pollution exposure and cancer.

Cancer Causes Control 1997; 8:284–291.

Killingsworth, C. R., Alessandrini, F., Krishna Murthy, G. G., Catalano, P. J.,

Paulauskis, J. D., & Godleski, J. J. 1997. Inflammation, chemokine

expression, and death in monocrotaline-treated rats following fuel oil fly

ash inhalation. Inhalation toxicology, 9(6), 541-565.

Kim, S. K., Lee, K. T., Kang, C. S., Tao, L., Kannan, K., Kim, K. R., & Lee, J.

H. 2011. Distribution of perfluorochemicals between sera and milk from

the same mothers and implications for prenatal and postnatal exposures.

Environmental Pollution, 159(1), 169-174.

Knaapen, A. M., Borm, P. J. A., Albercht, C., Schins, R. P. F. 2004. Inhaled

particles and lung cancer. Part A. Mechanisms. International Journal of

Cancer ; 109:799–809.

Knaapen, A. M., Shi, T., Borm, P. J. A., Schins, R. P. F. 2002. Soluble metals as

well as insoluble particle fraction are involved in cellular DNA damage

induced by particulate matter. Molecular and Cell Biochemistry; 234/235:

317–326.

152

Knuckles, T. L, Dreher K. L. 2007. Fine oil combustion particle bioavailable

constituents induce molecular profiles of oxidative stress, altered function,

and cellular injury in cardiomyocytes. Journal of Toxicology and

Environmental Health, 70:1824–1837.

Kodavanti, U. P., Hauser, R., Christiani, D. C., Meng, Z. H., McGee, J.,

Ledbetter, A., Richards, J., Costa, D. L. 1998b. Pulmonary responses to oil

fly ash particles inthe rat differ by virtue of their soluble metals. Toxicol.

Sci. 43:204-212.

Kodavanti, U. P., Jackson, M. C., Ledbetter, A. D., Richards, J. R., Gardner, S.

Y., Watkinson, W. P., Campen, M. J., Costa, D. L. 1999. Lung injury from

intratracheal and inhalation exposures to residual oil fly ash in a rat model

of monocrotoaline induced pulmonary hypertension. J. Toxicolo. Environ.

Health Part A 57: 101-121.

Kodavanti, U. P., Jaskot, R. H., Bonner, J., Badgett, A., Dreher, K. L. 1996.

Eosinophilic lung inflammation in particulate-induced lung injury:

technical consideration in isolating RNA for gene expression studies. Exp.

Lung Res. 22: 541-554.

Kodavanti, U. P., Jaskot, R. H., Su, W.Y., Costa, D. L., Ghio, A. J, Dreher, K. L.

1997. Genetic variability in combustion particle-induced chronic lung

injury. Am. J.Physiol. 272: L521-L532.

Koening, J. Q., Pierson, E., Frank, R. 1980. Acute effects of inhaled sulphur

dioxide plus sodium chloride on pulmonary function in asthmatic

adolescents. Environmental Research; 22:145–147.

Kong, S., Ding, X., Bai, Z., Han, B., Chen, L., Shi, J., Li, Z., 2010. A seasonal

study of polycyclic aromatic hydrocarbons in PM2.5 and PM 2.5-10 in five

typical cities of Liaoning Province, China. J Hazard Mater 183, 70-80.

Krewski, D., Burnett, R. T., Goldberg, M. S., Hoover, B. K., Siemiatycki, J.,

Jerrett, M., Abrahamowicz, M., and White, W. H. 2003. Overview of the

reanalysis of the Harvard Six Cities Study and American Cancer Society

Study of Particulate Air Pollution and Mortality. J Toxicol Environ Health

A 66, 1507-51.

Kultz, D., Fiol, D., Valkova, N., et al. Functional genomics and proteomics of the

cellular osmotic stress response in ‗non-model‘ organisms. J Exp Biol

2007; 210:1593–601.

153

Kumagai, Y., Arimoto, T., Shinyashiki, M., Shimojo, M., Nakai, Y., Yoshikawa,

T., Sagai, M. 1997. Generation of reactive oxygen species during

interaction of diesel exhaust particle components with NADPH-

cytochrome P450 reductase and involvement of the bioactivation in the

DNA damage. Free Radical Biology and Medicine, 22:479–487.

Laden, F., Neas, L. M., Dockery, D. W., & Schwartz, J. 2000. Association of fine

particulate matter from different sources with daily mortality in six US

cities. Environmental health perspectives, 108(10), 941.

LaMantia, M., & Lennarz, W. J. 1993. The essential function of yeast protein

disulfide isomerase does not reside in its isomerase activity. Cell, 74(5),

899-908.

Langrish, J. P., Li, X., Wang, S., Lee, M. M., Barnes, G. D., Miller, M. R.,

Cassee, F. R., Boon, N. A., Donaldson, K., Li, J., Li, L., Mills, N. L.,

Newby, D. E., Jiang, L., 2012. Reducing personal exposure to particulate

air pollution improves cardiovascular health in patients with coronary

heart disease. Environ Health Perspect 120, 367-372.

Lau, C., Anitole, K., Hodes, C., Lai, D., Pfahles-Hutchens, A., Seed, J. 2007.

Perfluoroalkyl acids—a review of monitoring and toxicological findings.

Toxicol Sci. 99:366–94.

Lau, C., Thibodeaux, J. R., Hanson, R. G., Rogers, J. M., Grey, B. E., Stanton, M.

E., Butenhoff, J. L., Stevenson, L. A., 2003. Exposure to perfluorooctane

sulfonate during pregnancy in rat and mouse. II: postnatal evaluation.

Toxicol. Sci. 74, 382–392

Law, A. Y. S., Wei, X., Zhang, X., Mak, N. K., Cheung, K. C., Wong, M. H., ... &

Wong, C. K. C. 2012. Biological analysis of endocrine-disrupting

chemicals in animal meats from the Pearl River Delta, China. Journal of

Exposure Science and Environmental Epidemiology, 22(1), 93-100.

Lawther, P. J. Carbon monoxide. 1975. British Medical Bulletin 1975; 31:256–

260.

Lee, J. T., Son, J. Y., Cho, Y. S., 2007. The adverse effects of fine particle air

pollution on respiratory function in the elderly. Sci Total Environ 385, 28-

36.

154

Lelieveld, J., & Dentener, F. J. 2000. What controls tropospheric ozone? Journal

of Geophysical Research: Atmospheres (1984–2012), 105(D3), 3531-

3551.

León, H. D., Boué, S., Peitsch, M. C., & Hoeng, J. 2013. Modulation of the

hepatic lipidome and transcriptome of Apoe-/-Mice in response to

smoking cessation. J Liver, 2(132), 2167-0889.

Lepez-Candales, A., Bosner, M. S., Spilburg, C. A., Lange, L. G. 1993.

Cholesterol transport function of pancreatic cholesterol esterase: directed

sterol uptake and esterification in enterocytes Biochemistry, 32, pp.

12085–12089 94032342

Levin, A. A., Sturzenbecker, L. J., Kazmer, S., Bosakowski, T., Huselton, C.,

Allenby, G., Speck, J., Kratzeisen, C. I., Rosenberger, M., Lovey, A. &

Grippo, J. F. 1992. 9-Cis retinoic acid stereoisomer binds and activates the

nuclear receptor RXRa. Nature 355: 359-361.

Li, B. & Dewey, C. N. 2011. RSEM: accurate transcript quantification from

RNA-Seq data with or without a reference genome. BMC. Bioinformatics.

12, 323.

Li, C. K., & Kamens, R. M. 1993. The use of polycyclic aromatic hydrocarbons as

source signatures in receptor modeling. Atmospheric Environment, 27A,

523–532.

Li, H., & Durbin, R. 2009. Fast and accurate short read alignment with Burrows-

Wheeler transform. Bioinformatics. 25, 1754-1760.

Li, J. W. et al. 2012. SEQ answers: an open access community for collaboratively

decoding genomes. Bioinformatics. 28, 1272-1273.

Li, J.G., Liu, J.Y., Luan, Y., Zhao, Y.F., Wu, Y.N., 2009. Geographical

distribution of perfluorinated compounds in human blood from Liaoning

Province, China. Environmental Science & Technology 43, 4044e4048.

Li, N., Hao, M., Phalen, R. F., Hinds, W. C., & Nel, A. E. 2003. Particulate air

pollutants and asthma: a paradigm for the role of oxidative stress in PM-

induced adverse health effects. Clinical Immunology, 109(3), 250-265.

Li, N., Kim, S., Wang, M., Froines, J., Sioutas, C., Nel, A. 2002. Use of a

stratified oxidative stress model to study the biological effects of ambient

155

concentrated and diesel exhaust particulate matter. Inhalation Toxicology,

14:459–486.

Li, Y., Wang, P., Ding, L., Li, X., Wang, T., Zhang, Q., & Wei, F. 2010.

Atmospheric distribution of polychlorinated dibenzo-p-dioxins,

dibenzofurans and dioxin-like polychlorinated biphenyls around a steel

plant Area, Northeast China. Chemosphere, 79(3), 253-258.

Linton, M. F., Fazio, S. 2000. Re-emergence of fibrates in the management of

dyslipidemia and cardiovascular risk. Curr. Atheroscler. Rep. 2:29–35.

Lippmann, M., Yeates, D. B., and Albert, R. E. 1980. Deposition, retention, and

clearance of inhaled particles. Br J Ind Med 37, 337-62.

Liu, C., Yu, K., Shi, X., Wang, J., Lam, P. K., Wu, R. S., & Zhou, B. 2007c.

Induction of oxidative stress and apoptosis by PFOS and PFOA in primary

cultured hepatocytes of freshwater tilapia (Oreochromis niloticus). Aquatic

Toxicology, 82(2), 135-143.

Liu, L. B., Hashi, Y., Liu, M., Wei, Y., & Lin, J. M. 2007a. Determination of

particle-associated polycyclic aromatic hydrocarbons in urban air of

Beijing by GC/MS. Analytical sciences, 23(6), 667-671.

Liu, Q; Bengmark, S; Qu, S. 2010. The role of hepatic fat accumulation in

pathogenesis of non-alcoholic fatty liver disease (NAFLD), Lipids Health

Dis. 9 - 42.

Liu, S. Z., et al. 2007b. Atmospheric polycyclic aromatic hydrocarbons in north

China: A wintertime study. Environ Sci Technol 41:8256–8261.

Loftus, S. K., Cannons, J. L., Incao, A., Pak, E., Chen, A., Zerfas, P. M., &

Pavan, W. J. 2005. Acinar cell apoptosis in Serpini2-deficient mice models

pancreatic insufficiency. PLoS genetics, 1(3), e38.

Lombardo, D. and Guy, O. 1980. Biochim. Biophys. Acta 611, 147-155.

uo, W., Zhang, Y., i, H. 2003. Children‘s blood lead levels after the phasing

out of leaded gasoline in Shantou, China. Arch Environ Health.

58(3):184–187

Mahle, N. H., & Whiting, L. F. 1980. The formation of chlorodibenzo-p-dioxins

by air oxidation and chlorination of bituminous coal. Chemosphere, 9(11),

693-699.

156

Malm, W. C. 2003. Fundamentals of Visibility, in Handbook of Weather, Climate,

and Water: Atmospheric Chemistry, Hydrology, and Societal Impacts, T.

D. Potter, T. D. and Colman, B. R., eds, Chapter 16, Wiley Interscience,

John Wiley & Sons, New York, pp. 285–329.

Marra, F. 2002. Chemokines in liver inflammation and fibrosis. Frontiers in

bioscience: a journal and virtual library, 7, d1899-914.

Martin, J. W., Mabury, S. A., O‘Brien, P. J., 2005. Metabolic products and

pathways of fluorotelomer alcohols in isolated rat hepatocytes. Chemico-

Biological Interactions 155, 165-180.

Mastral A. M., Callen, M. S, Garcia T, 2000. Poly aromatic environmental impact

in coal-tire blend atmospheric fluidized bed (AFB) combustion[J]. Energ

Fuel, 14: 164-168.

Mastral, A. M., Garcia, T., Callen, M. S et al., 2001. Effects of limestone on

polycyclic aromatic hydrocarbon emissions during coal atmospheric

fluidized bed combustion, J. Energ. Fuel, 15: 1469-1474.

Mauderly, J. L., Chow, J. C., 2008. Health effects of organic aerosols. Inhalation

Toxicology 20, 257–288.

Mazumbar, S., Schimmel, H., Higgins, I. T. T. 1982. Relation of daily mortality to

air pollution: an analysis of 14 London winters, 1958/59–1971/72.

Archives of Environmental Health; 37:213–220.

Mead, R. W., Brajer, V. 2006. Valuing the adult health effects of air pollution in

Chinese cities. Ann N Y Acad Sci.1076: 882–892

Mei, S. F., 2008. Production, uses and status of international and domestic

standards for PFOS/PFOA in China. Organo-Fluorine Industry 1, 21e25.

Michael, S., Montag, M., Dott, W., 2013. Pro-inflammatory effects and oxidative

stress in lung macrophages and epithelial cells induced by ambient

particulate matter. Environ Pollut 183, 19-29.

Midasch, O., Drexler, H., Hart, N., Beckmann, M. W., & Angerer, J. 2007.

Transplacental exposure of neonates to perfluorooctanesulfonate and

perfluorooctanoate: a pilot study. International archives of occupational

and environmental health, 80(7), 643-648.

Mignatti, P., & Rifkin, D. B. 1993. Biology and biochemistry of proteinases in

tumor invasion. Physiological reviews, 73(1), 161-195

157

Miguel, A. H., & Pereira, P. A. P. 1989. Benzo(k)fuoranthene,

benzo(ghi)perylene, and indeno (1,2,3,-cd) pyrene: New tracers of

automotive emissions in receptor modeling. Aerosol Science and

Technology, 10, 292–295. doi:10.1080/02786828908959265.

Miller, A. 2003. Presentation at the Conference ―Particulate Matter: Atmospheric

Sciences, Exposure, and the Fourth Colloquium on PM and Human

Health,‖ Pittsburgh, PA, March 31–April 4.

Miller, K. A., Siscovick, D. S., Sheppard, L., Shepherd, K., Sullivan, J. H.,

Anderson, G. L., & Kaufman, J. D. 2007. Long-term exposure to air

pollution and incidence of cardiovascular events in women. New England

Journal of Medicine, 356(5), 447-458.

Miller, R. L, Garfinkel, R., Horton, M., et al. 2004. Polycyclic aromatic

hydrocarbons, environmental tobacco smoke, and respiratory symptoms in

an inner-city birth cohort. Chest. 126(4): 1071–1078.

Millman, A., Tang, D., & Perera, F. P. 2008. Air pollution threatens the health of

children in China. Pediatrics, 122(3), 620-628.

Ministry of Environmental Protection of China. 2008.

(http://chm.pops.int/Portals/0/Repository/addinfo_2008/UNEP-POPS-

POPRC-SUB-F08-PFOS-ADIN-CHI. English.pdf ).

Mode, A., Gustafsson, J. A., 1998. Down-regulation of cytochrome P450 2c

family members and positive acute-phase response gene expression by

peroxisome proliferator chemicals. Mol. Pharmacol. 54, 463–473.

Mohanraj, R., Solaraj, G., & Dhanakumar, S. 2011. Fine particulate phase PAHs

in ambient atmosphere of Chennai metropolitan city, India. Environmental

Science and Pollution Research, 18(5), 764-771.

Molina, M. J., & Molina, L. T. 2004. Megacities and atmospheric pollution.

Journal of the Air & Waste Management Association, 54(6), 644-680.

Moody, C., Hebert, G., Strauss, S., and Field, J. J. Environ. Monit., 2003, 5(2),

341.

Morel, F. M., Kraepiel, A. M., & Amyot, M. 1998. The chemical cycle and

bioaccumulation of mercury. Annual review of ecology and systematics,

543-566.

Moriwaki, H., Takata Y., and Arakawa R. 2003. Concentrations of

perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) in

158

vacuum cleaner dust collected in Japanese homes. J. Environ. Monit.,

2003, 5, 753–757

Motley, H. L., Smart, R. H., & Leftwich, C. I. 1959. Effect of polluted Los

Angeles air (smog) on lung volume measurements. Journal of the

American Medical Association, 171(11), 1469-1477.

National Bureau of Statistics of China, 2006. China statistical yearbook 2006.

Beijing: China Statistics Press.

National Center for Environmental Assessment [Research Triangle Park N.C.],

2003. Air quality criteria for particulate matter. National Center for

Environmental Assessment-RTP Office, Office of Research and

Development, U.S. Environmental Protection Agency, Research Triangle

Park, NC.

National Research Council, 1993. Pesticides in the Diets of Infants and Children.

Washington, DC: National Academy Press.

Natural Resources Defense Council. China‘s clean energy project. 2007.

Available at: www.nrdc.org/air/energy/china/cleanpower.asp. Accessed

August 8, 2007.

NCBI. 2015. chymotrypsin-like elastase family, member 3B, retrieved on April

17, 2015 from http://www.ncbi.nlm.nih.gov/gene/23436.

Nebert, D. W., Dalton, T. P., Okey, A. B., & Gonzalez, F. J. 2004. Role of aryl

hydrocarbon receptor-mediated induction of the CYP1 enzymes in

environmental toxicity and cancer. Journal of Biological Chemistry,

279(23), 23847-23850.

Nel A, Xia, T., Madler, L., Li, N., 2006.Toxic potential of materials at the

nanolevel. Science, 311:622–627.

Nelson, J. W., Hatch, E. E., & Webster, T. F. 2010. Exposure to polyfluoroalkyl

chemicals and cholesterol, body weight, and insulin resistance in the

general US population. Environmental health perspectives

(Online),118(2), 197.

Nemery, B., Hoet, P. H., Nemmar, A. 2001.The Meuse Valley for of 1930: an air

pollution disaster. Lancet, 357:704–708.

Nesatyy, V. J., Suter, M. J. F. 2007. Proteomics for the analysis of environmental

stress responses in organisms. Environ. Sci. Technol, 41 (20), 6891−6900

159

Niu, Y., He, L., Hu, M., Zhang, J., Zhao, Y. L. 2006. Pollution characteristics of

atmospheric fine particles and their secondary components in the

atmosphere of Shenzhen in summer and in winter. Sci China Ser B Chem,

49(5): 466–74.

OECD (Organisation for Economic Co-operation and Development), 2002.

Emission Scenario Document on Metal Finishing ENV/JM/MONO p. 23.

Ohnishi, S., Kawanishi, S. 2002. Double base lesions of DNA by a metabolite of

carcinogenic benzo[a]pyrene. Biochemical and Biophysical Research

Communications, 290:778–782.

Okuda, T., Okamoto, K., Tanaka, S., Shen, Z., Han, Y., Huo, Z., 2010.

Measurement and source identification of polycyclic aromatic

hydrocarbons (PAHs) in the aerosol in Xi'an, China, by using automated

column chromatography and applying positive matrix factorization (PMF).

Sci Total Environ 408, 1909-1914.

Olsen, G. W., Burris, J. M., Ehresman, D. J., Froehlich, J. W., Seacat, A. M.,

Butenhoff, J. L., Zobel, L. R., 2007. Half-life of serum elimination of

perfluorooctanesulfonate, perfluorohexanesulfonate and

perfluorooctanoate in retired fluorochemical production workers. Environ.

Health Perspect. 115, 1298–1305.

Osornio Vargas, A. R., Serrano, J., Rojas Bracho, ., Miranda, J., arc ´a Cuellar,

C., Reyna, M. A., Flores, G., Zuk, M., Quintero, M., Va´ zquez, I.,

Sa´nchez-Pe´ rez, Y., Lo´ pez, T., Rosas,I., 2011. In vitro biological

effects of airborne PM2.5 and PM10 from a semi-desert city on the Mexico–

US border.Chemosphere83, 618–626.

Ozaki K, Nagata M, Suzuki M, Fujiwara T, Miyoshi Y, Ishikawa O, Ohigashi H,

Imaoka S, Takahashi E, Nakamura Y. 1998. Isolation and characterization

of a novel human pancreas-specific gene, pancpin, that is down-regulated

in pancreatic cancer cells. Genes Chromosomes Cancer, 22:179–185.

Park, E. J., Roh, J., Kim, Y., Park, K., Kim, D. S., Yu, S. D., 2011. PM2.5

collected in a residential area induced Th1-type inflammatory responses

with oxidative stress in mice. Environ Res 111, 348-355.

Pathak, R. K., Wu, W. S., and Wang, T., 2009. Summertime PM2.5 ionic species

in four major cities of China: nitrate formation in an ammonia-deficient

160

atmosphere, Atmos. Chem. Phys., 9, 1711-1722, doi: 10.5194/acp-9-1711-

2009.

Paul A. G, Jones K. C, Sweetman A. J. 2008. A first global production, emission,

and environmental inventory for perfluorooctane sulfonate. Environ Sci

Technol, 43:386–92.

Pearlman, M. E, Finklea, J. F, Creason, J. P, Shy, C. M., Young, M. M, Horton, R.

J. 1971. Nitrogen dioxide and lower respiratory illness. Pediatrics; 47:391–

398.

Peluso, M., Munnia, A., Hoek, G., Krzyzanowski, M., Veglia, F., Airoldi, L., &

Vineis, P. 2005. DNA adducts and lung cancer risk: a prospective study.

Cancer Research, 65(17), 8042-8048.

Perera, F. P., Rauh, V., Tsai, W. Y., et al. 2003. Effects of transplacental

exposure to environmental pollutants on birth outcomes in a multi-ethnic

population. Environ Health Perspect. 111(2): 201–205

Perera, F., Viswanathan, S., Whyatt, R., Tang, D., Miller, R. L, Rauh, V. 2006.

Children‘s environmental health research: highlights from the Columbia

Center for Children‘s Environmental Health. Ann N Y Acad Sci.1076:15–

28

Pershagen, G., Simonato, L. 1990. Epidemiological evidence on air pollution and

cancer. In: Tomatis, L. (ed.), Air Pollution and Human Cancer, Springer-

Verlag, Heidelberg, pp. 63–74.

Peters, J. M., Cheung, C., and Gonzalez, F. J. 2005. Peroxisome proliferator

activated receptor-alpha and liver cancer: Where do we stand? J. Mol.

Med. 83, 774–785.

Pinkerton, K. E. 2002. A critical review of the particulate matter toxicology

literature for senate bill 25, review of the particulate matter standard.

Pinkerton, K. E. and Joad, J. P. 2000. The mammalian respiratory system and

critical windows of exposure for children‘s health. EHP 108(3):457-462.

Plopper, C. G., Fanucci, M. V. 2000. Do urban environmental pollutants

exacerbate childhood lung disease? Environ Health Perspect.

108(6):A252–A253

Plutzky, 2011. The PPAR-RXR transcriptional complex in the vasculature: energy

in the balance, Circ. Res. 108 (8): 1002–16.

161

Plutzky, J., 2000. Emerging concepts in metabolic abnormalities associated with

coronary artery disease. Curr. Opin. Cardiol. 15:416–21.

Poma, A., Arrizza, L., Picozzi, P., Spano, L. 2002. Monitoring urban air

particulate matter (fractions PM2.5 and PM10) genotoxicity by plant

systems and human cells in vitro: a comparative analysis. Teratogenesis,

Carcinogenesis, and Mutagenesis; 22:271–284.

Pope III, C. A., Burnett, R. T., Thun, M. J., Calle, E. E., Krewski, D., Ito, K., &

Thurston, G. D. 2002. Lung cancer, cardiopulmonary mortality, and long-

term exposure to fine particulate air pollution. Jama, 287(9), 1132-1141.

Pope, C. A. III and Dockery, D. W. 2006. Health effects of fine particulate air

pollution: Lines that connect. Journal of the Air & Waste Management

Association, 56(6), pp. 709–742.

Poschl, U., 2005, Atmospheric aerosols: composition, transformation, climate and

health effects, Angew. Chem. Int. Ed. Engl. 44, 7520.

Potempa J, Korzus E, Travis J. 1994. The serpin superfamily of proteinase

inhibitors: structure, function, and regulation. J Biol Chem, 269:15957–

15960.

Pottinger, M., Stecklow, S., & Fialka, J. J. 2004. Invisible export: a hidden cost of

China‘s growth: mercury migration. The Wall Street Journal, 20.

Prahalat, A. K., Soukup, J. M., Inmon, J., Willis, R., Ghio, A. J., Becker S,

Gallagher, J. E. 1999. Ambient air particles: effects on cellular oxidant

radical generation in relation to particulate elemental chemistry.

Toxicology and Applied Pharmacology; 158:81–91.

Prevedouros, K., Cousins, I. T, Buck, R. C. 2006. Sources, fate and transport of

perfluoro carboxylates. Environ Sci Technol, 40:32–45.

Pritchard, R. J., Ghio, A. J., Lehmann, J. R. 1996. Oxidant generation and lung

injury after particulate air pollutant exposure increase with the

concentrations of associated metals. Inhal Toxicol 8:457–477.

Puga, A., Barnes, S. J., Chang, C., Zhu, H., Nephew, K. P., Khan, S. A., Shertzer,

H. G. 2000. Activation of transcription factors activator protein-1 and

nuclear factor kappa B by 2,3,7,8-tetrachlorodibenzo-p-dioxin. Biochem

Pharmacol. 59:997- 1005.

162

Qian, Z., Chapman, R. S, Hu, W., Wei, F., Korn, L. R, Zhang, J. J. 2004b. Using

air pollution based community clusters to explore air pollution health

effects in children. Environ Int.30(5):611–620

Qian, Z., Zhang, J. J., Korn, L. R., Wei, F., Chapman, R. S. 2004a.

Exposureresponse relationships between lifetime exposure to residential

coal smoke and respiratory symptoms and illnesses in Chinese children. J

Expo Anal Environ Epidemiol. 14(suppl 1): S78–S84.

Qui, X. B., Cadenas, E. 1997. The role of NAD(P)H: quinone oxidoredictase in

quinonemediated p21 induction in human colon carcinoma cells. Archives

of Biochemistry and Biophysics, 346:241–251.

Ramanathan, V. C. P. J., Crutzen, P. J., Kiehl, J. T., & Rosenfeld, D. 2001.

Aerosols, climate, and the hydrological cycle. science, 294(5549), 2119-

2124.

Ravindra, K., Sokhi, R., & Van Grieken, R. 2008. Atmospheric polycyclic

aromatic hydrocarbons: source attribution, emission factors and regulation.

Atmospheric Environment, 42(13), 2895-2921.

Ravindra, K., Sokhi, R., & Van Grieken, R. 2008. Atmospheric polycyclic

aromatic hydrocarbons: source attribution, emission factors and regulation.

Atmospheric Environment, 42(13), 2895-2921.

Ray, P. D., Huang, B. W., & Tsuji, Y. 2012. Reactive oxygen species (ROS)

homeostasis and redox regulation in cellular signaling. Cellular signalling,

24(5), 981-990.

Reddy, J. K. 2001. Nonalcoholic steatosis and steatohepatitis. III. Peroxisomal

betaoxidation, PPAR alpha, and steatohepatitis, Am. J. Physiol.

Gastrointest. Liver Physiol. 281, G1333–G1339.

Reichle, H. G., Connors, V. S., Holland, J. A., Hypes, W. D., Wallio, H. A.,

Casas, J. C., & Hesketh, W. D. 1986. Middle and upper tropospheric

carbon monoxide mixing ratios as measured by a satellite‐borne remote

sensor during November 1981. Journal of Geophysical Research:

Atmospheres (1984–2012), 91(D10), 10865-10887.

Robinson, M.D., McCarthy, D.J. & Smyth, G.K. Edge, R., 2012. A bio-conductor

package for differential expression analysis of digital gene expression

data. Bioinformatics. 26, 139-140.

163

Roos, W. P., & Kaina, B. 2006. DNA damage-induced cell death by apoptosis.

Trends in molecular medicine, 12(9), 440-450.

Rosen, M. B., Schmid, J. R., Corton, J. C., Zehr, R. D., Das, K. P., Abbott, B. D.,

Lau, C. 2010. Gene expression profiling in wild-type and PPAR alpha-null

mice exposed to perfluorooctane sulfonate reveals ppar alpha-independent

effects. PPAR Res.

Rosen, M. B., Thibodeaux, J. R., Wood, C. R., Zehr, R. D., Schmid, J. E., & Lau,

C. 2007. Gene expression profiling in the lung and liver of PFOA-exposed

mouse fetuses. Toxicology, 239(1), 15-33.

Rosenbloom, J. 1984. Elastin: relation of protein and gene structure to disease.

Lab Invest 51:605–623

Ross, P. L. et al. 2004. Multiplexed protein quantitation in Saccharomyces

cerevisiae using amine reactive isobaric tagging reagents. Mol. Cell

Proteomics, 3, 1154-1169.

Sagai, M., Lim, M. S. P, Ichinose, T. 2000. Lung carcinogenesis by diesel exhaust

particles and the carcinogenic mechanism via reactive oxygens. Inhalation

Toxicology; 12:215–223.

Saito, N., Harada, K., Inoue, K., Sasaki, K., Yoshinaga, T., & Koizumi, A. 2004.

Perfluorooctanoate and perfluorooctane sulfonate concentrations in surface

water in Japan. Journal of occupational health, 46(1), 49-59.

Sasaki, K., Harada, K., Saito, N., Tsutsui, T,. Nakanishi, S., Tsuzuki, H., and

Koizumi A. 2003. Impact of Airborne Perfluorooctane Sulfonate on the

Human Body Burden and the Ecological System. Bull. Environ. Contam.

Toxicol. 71:408–413.

Sato, M. I. Z., Valent, G. U., Coimbrão, C. A., Coelho, M. C. L., Sanchez, P. S.,

Alonso, C. D., & Martins, M. T. 1995. Mutagenicity of airborne

particulate organic material from urban and industrial areas of São Paulo,

Brazil. Mutation Research/Environmental Mutagenesis and Related

Subjects, 335(3), 317-330.

Schafer, F. Q, Buettner, G. R. 2001. Redox environment of the cell as viewed

through the redox state of the glutathione disulfite/glutathione couple. Free

Radical Biology and Medicine, 30:1191–1212.

164

Schauer, C., Niessner, R., Poschl, U., 2003. Polycyclic aromatic hydrocarbons in

urban air particulate matter: decadal and seasonal trends, chemical

degradation, and sampling artifacts. Environmental Science and

Technology 37, 2861–2868.

Schecter, A., Birnbaum, L., Ryan, J. J., Constable, J. D. 2006. Dioxins: an

overview. Environ. Res. 101, 419.

Scheele, G., Bartelt, D., Bieger W. 1981. Characterization of human exocrine

pancreatic proteins by two-dimensional isoelectric focusing/sodium

dodecyl sulfate gel electrophoresis. Gastroenterology 80:461–473.

Scheffe, R. 2003. Presentation at the Conference ―Particulate Matter: Atmospheric

Sciences, Exposure, and the Fourth Colloquium on PM and Human

Health,‖ Pittsburgh, PA, March 31–April 4.

Schins, R. P., Lightbody, J. H., Borm, P. J., Shi, T., Donaldson, K., & Stone, V.

2004. Inflammatory effects of coarse and fine particulate matter in relation

to chemical and biological constituents. Toxicology and applied

pharmacology, 195(1), 1-11.

Schlesinger, R. 1995. Deposition and clearance of inhaled particles. In Concepts

in inhalation toxicology (O. a. H. McClellan R, R., F., ed., pp. 191-224.

Taylor and Francis, Washington, DC.

Schmitz, J. 2004. Maldigestion and malabsorption. In: Walker WA, Goulet O,

Kleinman RE, Sherman PM, Shneider BL, Sanderson IR (eds) Pediatric

Gastrointestinal Disease: Pathophysiology, Diagnosis, Management.

Decker, Hamilton, Canada, pp 8–20

Schrenk, H. H., Heimann, H., Clayton, G. D., Wexler, H., Gafafer, W. M. 1949.

Air pollution in Donora, Pa., USA. Us Public Health Bulletin, 306,

Washington DC.

Schwarze, P. E., Ovrevik, J., Hetland, R. B., Becher, R.,Cassee, F. R.,Lag, M.,

Lovik, M., Dybing, E., Refsnes, M., 2007. Importance of size and

composition of particles for effects on cells in vitro. InhalationToxicol.19,

17–22.

Seacat, A. M., Thomford, P. J., Hansen, K. J., Olsen, G. W., Case, M. T.,

Butenhoff, J. L., 2002. Sub chronic toxicity studies on

perfluoroctanesulfonate potassium salt in cynomolgus monkeys. Toxicol.

Sci. 68, 249–264.

165

Seifert, W. F., Bosma, A., Hendriks, H. F J., de Ruiter, G. C. F, van Leeuwen, R.

E. W., Knook, D. L., and Brouwer, A. 1989. Dual role of vitamin A in

experimentally induced liver fibrosis. In Cells of the Hepatic Sinusoid

(Wisse, E., Knook, D. L., and Decker, K.) pp. 43-48, Kupffer Cell

Foundation, Rijswijk, Netherlands.

Sexton, K. G., Jeffries, H. E., Jang, M., Kamens, R. M., Doyle, M., Voicu, I., &

Jaspers, I. 2004. Photochemical products in urban mixtures enhance

inflammatory responses in lung cells. Inhalation toxicology, 16(s1), 107-

114.

Shang, Q., Ren, X., Li, J. 2002. Estimation of arsenic accumulative intake and

residents‘ health effects in an air pollution area: relationship between

arsenic accumulative intake level and arsenicism prevalence [in Chinese].

Wei Sheng Yan Jiu. 31(5):349–351

Shauer, J. J., Kleeman, M. J., Cass, G. R., and Simoneit, B. R. T. 1999.

Measurement of emissions from air pollution sources C1 through C30

compounds from medium duty trucks, Environ. Sci. Technol., 33, 1578–

1587, 1999.

Shen, Z., Han, Y., Cao, J., Tian, J., Zhu, C., Liu, S., & Wang, Y. 2010.

Characteristics of traffic-related emissions: a case study in roadside

ambient air over Xi‘an, China. Aerosol Air Qual. Res, 10(3), 292-300.

Shipley, J. M., Hurst, C. H., Tanaka, S. S., DeRoos, F. L., Butenhoff, J. L., Seacat,

A. M., Waxman, D. J. 2004. Trans-activation of PPAR alpha and

induction of PPAR alpha target genes by perfluorooctane-based chemicals.

Toxicol. Sci. 80 (1), 151−160.

Shoeib, M., Harner, T., Webster, G. M., and Lee, S. C. 2011. Indoor Sources of

Poly- and Perfluorinated Compounds (PFCS) in Vancouver, Canada:

Implications for Human Exposure Environ. Sci. Technol. 45, 7999–8005.

Shoeib, M., Vlahos, P., Harner, T., Peters, A., Graustein, M., & Narayan, J. 2010.

Survey of polyfluorinated chemicals (PFCs) in the atmosphere over the

northeast Atlantic Ocean. Atmospheric Environment, 44(24), 2887-2893.

Shukla, A., Timblin, C., BeruBe, K., Gordon, T., Mckinney,, W., Driscoll, K.,

Vacek, P., Mossman, B. T. 2000. Inhaled particulate matter causes

expression of nuclearfactor (NF)-kappaB-related geres and oxidant-

166

dependent NF-kappaB activationin vitro. AM. J. Respri. Cell Mol. Biol.

23:182-7.

Silverman, G. A, Bird, P. I, Carrell, R. W, Church, F. C, Coughlin, P. B, Gettins,

P. G, Irving, J. A, Lomas, D. A, Luke, C. J, Moyer, R. W, Pemberton, P.

A, Remold-O'Donnell, E., Salvesen, G. S, Travis, J., Whisstock, J. C.

2001.The serpins are an expanding superfamily of structurally similar but

functionally diverse proteins: evolution, mechanism of inhibition, novel

functions, and a revised nomenclature. J. Biol. Chem, 276: 33293–33296.

Sin, D. W., Fung, W. H., Choi, Y. Y., Lam, C. H., Louie, P. K., Chow, J .C.,

Watson, J. G., 2005. Seasonal and spatial variation of solvent extractable

organic compounds in fine suspended particulate matter in Hong Kong. J

Air Waste Manag Assoc 55, 291-301.

Smith, M. T., Jones, R. M., Smith, A. H. 2007. Benzene exposure and risk of non-

Hodgkin lymphoma. Cancer Epidemiol Biomarkers Prev.16(3):385–391

So, M. K., Miyake, Y., Yeung, W. Y., Ho, Y. M., Taniyasu, S., Rostkowski, P. &

Lam, P. K. S. 2007. Perfluorinated compounds in the Pearl River and

Yangtze river of China. Chemosphere, 68(11), 2085-2095.

Sohlenius, A. K., Eriksson, A. M., Ho gstrom, C., Kimland, M., DePierre, J. W.

1993. Pharmacol. Toxicol,72:90- 93

Sorensen, M., Autrup, H., Moller, P., Hertel, O., Jensen, S. S., Vinzents, P.,

Knudsen, L. E., Loft, S. 2003. Linking exposure to environmental

pollutants with biological effects, Mutat. Res. 544, 255–271.

Sørensen, M., Daneshvar, B., Hansen, M., Dragsted, L. O., Hertel, O., Knudsen,

L., & Loft, S. 2003. Personal PM2.5 exposure and markers of oxidative

stress in blood. Environmental Health Perspectives, 111(2), 161.

South China Morning Post, 2015. Blanket of smog in Beijing hits start of Lunar

New Year getaway. Retrieved on 15 January 2015 from

http://www.scmp.com/news/china-insider/article/1406793/beijing-hit-first-

bout-charts-air-pollution-new-year

Speizer, F. E., Samet, J. M., 1994. Air pollution and lung cancer. In: Samet, J.M.

(Ed.), Epidemiology and Lung Cancer. Dekker, New York.

Spurny, K. R., 1996. Chemical mixtures in atmospheric aerosols and their

correlation to lung diseases and lung cancer occurrence in the general

population. Toxicol. Lett. 88, 271–277.

167

Squadrito, G. L., Cueto, R., Dellinger, B., & Pryor, W. A. 2001. Quinoid redox

cycling as a mechanism for sustained free radical generation by inhaled

airborne particulate matter. Free Radical Biology and Medicine, 31(9),

1132-1138.

Squadrito, G. L., Cueto, R., Dellinger, B., & Pryor, W. A. 2001. Quinoid redox

cycling as a mechanism for sustained free radical generation by inhaled

airborne particulate matter. Free Radical Biology and Medicine, 31(9),

1132-1138.

Squadrito, G. L., Cueto, R., Dellinger, B., & Pryor, W. A. 2001. Quinoid redox

cycling as a mechanism for sustained free radical generation by inhaled

airborne particulate matter. Free Radical Biology and Medicine, 31(9),

1132-1138.

State Environmental Protection Administration of China, 2007. The 2006 report

on the State of the environment in China. Beijing: State Environmental

Protection Administration. See also:

http://www.sepa.gov.cn/ztbd/sjhjr/2007hjr/tpbd56/200706/P02007060532

3023573963.pdf.

Stewart, G. S., Wang, B., Bignell, C. R., Taylor, A. M. R., & Elledge, S. J. 2003.

MDC1 is a mediator of the mammalian DNA damage checkpoint. Nature,

421(6926), 961-966.

Su, X. T., Wang, H. J., Song, S., & Zhang, Z. B. 2011. Radiative Force and

Temperature Response of Dust Aerosol over East Asia in Recent Decade

J. Plateau Meteorology, 5, 018.

Sugita, K., Koyano, M., Endo, O., Watanabe, T., Yamashita, N., Ushiyama, A., &

Suzuki, G. 2007. Perfluorinated compound levels in urban airborne

particles–recent aspects in Tokyo area. Organohalogen. Compd, 69, 2885-

2888.

Sun, P., Blanchard, P., Brice, K. A, Hites, R. A 2006. Trends in polycyclic

aromatic hydrocarbon concentrations in the Great Lakes atmosphere.

Environ Sci Technol 40:6221–6227.

Sunyer, J., Basagana X. 2001.Particles, and not gases, are associated with risk of

death in patients with chronic obstructive pulmonary disease. International

Journal of Epidemiology; 30:1138–1140.

168

Sweetman, A. J., Paul, A. G., Jones, K. C., 2009. A first global production,

emission, and environmental inventory for perfluorooctane sulfonate.

Environmental Science & Technology 43, 386e392

Tachibana, C. H. R. I. S. T. I. N. E., & Stevens, T. H. 1992. The yeast EUG1 gene

encodes an endoplasmic reticulum protein that is functionally related to

protein disulfide isomerase. Molecular and cellular biology, 12(10), 4601-

4611.

Tan, F., Jin, Y., Liu, W., Quan, X., Chen, J., & Liang, Z. 2012. Global liver

proteome analysis using iTRAQ labeling quantitative proteomic

technology to reveal biomarkers in mice exposed to perfluorooctane

sulfonate (PFOS).Environmental science & technology, 46(21), 12170-

12177.

Tan, N. S., Michalik, L., Desvergne, B., Wahli, W. 2005. Multiple expression

control mechanisms of peroxisome proliferator-activated receptors and

their target genes. J Steroid Biochem Mol Biol, 93(2–5):99–105.

Tang. D., Li, T. Y., Liu, J. J., Chen, Y. H., Qu, L., Perera, F. P. 2006. PAH-DNA

adducts in cord blood and fetal and child development in a Chinese cohort.

Environ Health Perspect. 114(8): 1297–1300

Tao, F., Gonzalez-Flecha, B., & Kobzik, L. 2003. Reactive oxygen species in

pulmonary inflammation by ambient particulates. Free Radical Biology

and Medicine, 35(4), 327-340.

Thibodeaux, J. R., Hanson, R. G., Rogers, J. M., Grey, B. E., Barbee, B. D.,

Richards, J. H, et al. 2003. Exposure to perfluorooctane sulfonate during

pregnancy in rat and mouse. I: maternal and prenatal evaluations. Toxicol

Sci.74:369–81.

Tie, X., Wu, D., & Brasseur, G. 2009. Lung cancer mortality and exposure to

atmospheric aerosol particles in Guangzhou, China. Atmospheric

Environment, 43(14), 2375-2377.

Tien, E. S., Hannon, D. B., Thompson, J. T., Vanden Heuvel, J. P. 2006.

Examination of liganddependent coactivator recruitment by peroxisome

proliferator-activated receptor-alpha (PPARalpha). PPAR

Res;2006:69612.

169

Tittlemier, S. A., Pepper, K., Seymour, C., Moisey, J., Bronsson, R., Cao, X. L.,

Dabeka, R. W. 2007. Dietary exposure of Canadians to perfluorinated

carboxylates and perfluorooctane sulfonate via consumption of meat, fish

and fast food items prepared in their packaging. J. Agric. Food Chem. 55,

3203–3210.

Touloumi, G., Katsouyanni, K., Zmirou, D., Schwartz, J., Spix, C., de Leon, A. P.,

& Ponka, A. 1997. Short-term effects of ambient oxidant exposure on

mortality: a combined analysis within the APHEA project. American

journal of epidemiology, 146(2), 177-185.

Trasande, L, Landrigan, P. J, Schechter, C. 2005. Public health and economic

consequences of methyl mercury toxicity to the developing brain. Environ

Health Perspect.113(5):590–596

Tse, W. K. F., Sun, J., Zhang, H., Law, A. Y. S., Yeung, B. H. Y., Chow, S. C., &

Wong, C. K. C. 2013. Transcriptomic and iTRAQ proteomic approaches

reveal novel short-term hyperosmotic stress responsive proteins in the gill

of the Japanese eel (Anguilla japonica). Journal of proteomics, 89, 81-94.

Tseng, W. P. 1977. Effects and dose-response relationships of skin cancer and

black foot disease with arsenic. Environ Health Perspect.19:109–119

UNEP, 2009. The conference of the parties 4 of the Stockholm Convention (COP

4) in Geneva placed perfluorooctane sulfonate and perfluorooctane

sulfonyl fluoride (PFOS and PFOSF) in Annex B. Available from:

http://chm.pops.int/.

United Nations Economic Commission for Europe (UNECE), 1998. ECE/EB[Z].

Air/60.

Upham, B. L., Deocampo, N. D., Wurl, B., Trosko. 1998. J. E. Int. J. Cancer, 78,

491-495.

USEPA, 1996b. Method 3620B: Florisil Cleanup.US Environmental Protection

Agency, Washington, DC.

USEPA, 1996c. Method 8270C: Semivolatile Organic Compounds by Gas

Chroma- tography/Mass Spectrometry (GC/MS). US Environmental

Protection Agency, Washington, DC.

USEPA, 2013. National Ambient Air Quality Standards for Particulate Matter.

http:// www.gpo.gov/fdsys/pkg/FR-2013-01-15/pdf/2012-30946.pdf.

170

USEPA. 1998. Particulate Matter Research Needs for Human Health Risk

Assessment to Support Future Reviews of the National Ambient Air

Quality Standards for Particulate Matter, January 15, EPA Report

EPA/600/R-97/132F, Office of Research and Development, Research

Triangle Park, NC.

USEPA. 2004. Air Quality Criteria for Particulate Matter. Fourth External Review

Draft, EPA Report, EPA/600/P-99/002. Office of Research and

Development, Research Triangle Park, NC.

Val, S., Martinon, L., Cachier, H., Yahyaoui, A., Marfaing, H., Baeza-Squiban,

A., 2011. Role of size and composition of traffic and agricultural aerosols

in the molecular responses triggered in airway epithelial cells. Inhal

Toxicol 23, 627-640.

Valavanidis, A., Fiotakis, K., & Vlachogianni, T. 2008. Airborne particulate

matter and human health: toxicological assessment and importance of size

and composition of particles for oxidative damage and carcinogenic

mechanisms. Journal of Environmental Science and Health, Part C, 26(4),

339-362.

Vasilakos, C., Levi, N., Maggos, T., Hatzianestis, J., Michopoulos, J., Helmis, C.,

2007. Gas-particle concentration and characterization of sources of PAHs

in the atmosphere of a suburban area in Athens, Greece. J Hazard Mater

140, 45-51.

Vestreng, V., Klein, H. 2002. Emission data reported to UNECE/ EMEP: Quality

Assurance and Trend Analysis and Presentation of WebDab. MSC-W

Status Report 2002[C]. EMEP-MSC-W Note 1/ 2002. Meteorological

Synthesizing Centre-West. Oslo, Norway

Villeneuve, A. L., Blankenship, J. P., Giesy M. S., Denison, W. G. Helferich

(Eds.). 1998. Interactions between environmental xenobiotics and estrogen

receptor-mediated responses Toxicant–Receptor Interactions, Taylor and

Francis, Philadelphia, PA, USA , pp. 69–99

Vineis, P., Forastier,e F., Hoer. G., Lipsett, M. 2004. Outdoor air pollution and

lung cancer: recent epidemiological evidence. International Journal on

Cancer; 111:647–652.

Vineis, P., Hoek, G., Krzyzanowski, M., Vigna‐Taglianti, F., Veglia, F., Airoldi,

L., & Riboli, E. 2006. Air pollution and risk of lung cancer in a

171

prospective study in Europe. International journal of cancer, 119(1), 169-

174.

Wallington, T. J., Hurley, M. D., Xia, J., Wuebbles, D. J., Sillman, S., Ito, A.,

Penner, J. E., Ellis, D. A., Martin, J., Mabury, S. A., Nielsen, O. J.,

Sulbaek Andersen, M. P., 2006. Formation of C7F15COOH (PFOA) and

other perfluorocarboxylic acids during the atmospheric oxidation of 8:2

fluorotelomer alcohol. Environmental Science & Technology 40, 924e930.

Wan, H. T., Zhao, Y. G., Wei, X., Hui, K. Y., Giesy, J. P., & Wong, C. K. 2012.

PFOS-induced hepatic steatosis, the mechanistic actions on β-oxidation

and lipid transport. Biochimica et Biophysica Acta (BBA)-General

Subjects, 1820(7), 1092-1101.

Wan, Y., Yuan-yuan, L., Wei, X., Jun, C., Zi-quan, L., Huai-cai Zeng, L., Zhang

et al. 2010. "Alterations in tumor biomarker GSTP gene methylation

patterns induced by prenatal exposure to PFOS." Toxicology 274, no. 1:

57-64.

Wang, C. S., Hartsuck, J. A. 1993. Bile salt-activated lipase. A multiple function

lipolytic enzyme Biochim. Biophys. Acta, 166, pp. 1–19

Wang, C. S., Martindale, M. E., King, M. M., Tang, J. 1989. Bile-saltactivated

lipase: effect on kitten growth rate Am. J. Clin. Nutr, 49, pp. 457–463

Wang, D., He, L., Wei, S., Feng, X. 2006. Estimation of mercury emission from

different sources to atmosphere in Chongqing, China. Sci Total Environ.

366(2 3):722–728

Wang, H., Fu, L., Zhou, Y., Du, X., & Ge, W. 2010. Trends in vehicular

emissions in China's mega cities from 1995 to 2005. Environmental

Pollution, 158(2), 394-400.

Wang, M. and You, J. 2012. Mass spectrometry for protein quantification in

biomarker discovery. Methods Mol Biol, 815:199–225.

Wang, X., Cheng, H., Xu, X., Zhuang, G., Zhao, C., 2008. A wintertime study of

polycyclic aromatic hydrocarbons in PM (2.5) and PM (2.5-10) in Beijing:

assessment of energy structure conversion. J Hazard Mater 157, 47-56.

Wang, X., Wang, C. S., Tang, J., Dyda, F., & Zhang, X. C. 1997. The crystal

structure of bovine bile salt activated lipase: insights into the bile salt

activation mechanism. Structure, 5(9), 1209-1218.

172

Watkinson, W. P., Campen, M. J., Dreher, K. L., Su, W.Y., Kodavanti, U. P.,

Highfill, J. W. Costa, D. L. 2000. Thermoregulatory effects following

exposure to particulate matter in healthy and cardiopulmonary-

compromised rats. J. Therm. Biol. 25:131-137.

Watts, J. 2006. Doctors blame air pollution for China‘s asthma increases.

Lancet.368 (9537):719–720

Weather. org, 2015. Weather history, climate records and average. Retrieved on 4

May2015fromhttp://www.weather.org/weatherorg_records_and_averages.

htm.

Wenzel, S. E. 1997. Arachidonic acid metabolites: mediators of inflammation in

asthma. Pharmacotherapy: The Journal of Human Pharmacology and Drug

Therapy, 17(1P2), 3S-12S.

Whitcomb, D. C., & Lowe, M. E. 2007. Human pancreatic digestive

enzymes.Digestive diseases and sciences, 52(1), 1-17.

Whitcomb, D. C., 1999. Early trypsinogen activation in acute pancreatitis.

Gastroenterology 116:770–773.

WHO, UNDP, 2001. Environment and People‘s Health in China. WHO, UNDP,

Geneva/New York.

Whyatt, R. M., Jedrychowski, W., Hemminki, K., et al. 2001. Biomarkers of

polycyclic aromatic hydrocarbon-DNA damage and cigarette smoke

exposures in paired maternal and newborn blood samples as a measure of

differential susceptibility. Cancer Epidemiol Biomarkers Prev.10(6):581–

588

World Bank. 1997.China: Air, Land, and Water. Washington, DC: World Bank.

World Bank. 2007. Cost of Pollution in China. Washington, DC: World Bank.

World Health Organization, & World Health Organization. Regional Office for

Europe. 2006. Air quality guidelines: global update 2005: particulate

matter, ozone, nitrogen dioxide, and sulfur dioxide.World Health

Organization.

World Health Organization. 2002. The World Health Report – Reducing Risks to

Health, Promoting Healthy Life, Report, ISBN-13 9789241562072.

Wouters, E. F. 2005. Local and systemic inflammation in chronic obstructive

pulmonary disease. Proceedings of the American Thoracic Society, 2(1),

26-33.

173

Wright, H. T. 1993. Introns and higher-order structure in the evolution of serpins.

J. Mol. Evol, 36:136–143.

Xia, T., Kovochich, M., Nel, A. 2006. The role of reactive oxygen species and

oxidative stress in mediating particulate matter injury. Clinical,

Occupational and Environmental Medicine 2006; 5:817–836.

Xiao, G., Liu, Y. E, Gentz, R, et al. 1999. Suppression of breast cancer growth

and metastasis by a serpin myoepithelium-derived serine proteinase

inhibitor expressed in the mammary myoepithelial cells. Proc Natl Acad

Sci USA. 96(7):3700–3705. [PubMed: 10097100]

Xie, S., Wang, T., Liu, S., Jones, K. C., Sweetman, A. J., & Lu, Y. 2013.

Industrial source identification and emission estimation of perfluorooctane

sulfonate in China. Environment international, 52, 1-8.

Yamashita, N., So, M. K., Miyake, Y., Yeung, W. Y., Ho, Y. M., Taniyasu, S.,

Rostkowski, P., Zhou, B. S., Shi, X. J., Wang, J. X., Giesy, J. P., Yu, H.,

Lam, P. K. S., 2007. Perfluorinated compounds in the Pearl River and

Yangtze River of China. Chemosphere 68, 2085e2095.

Yamashita, N., Yeung, L. W. Y., Miyake, Y., Taniyasu, S., Wang, Y., Yu, H. X.,

So, M. K., Jiang, G.B., Wu, Y. N., Li, J. G., Giesy, J. P., Lam, P. K. S.,

2007. Perfluorinated compounds and total and extractable organic fluorine

in human blood samples from China. Environmental Science &

Technology 42, 8140e8145.

Yan, X.Y., T. Ohara, and H. Akimoto. 2006. Bottom-up estimate of biomass

burning in mainland China. Atmos. Environ. 40(27):5262–5273.

doi:10.1016/ j.atmosenv.2006.04.040

Yeung, L. W., Miyake, Y., Taniyasu, S., Wang, Y., Yu, H., So, M. K., & Lam, P.

K. 2008. Perfluorinated compounds and total and extractable organic

fluorine in human blood samples from China. Environmental science &

technology, 42(21), 8140-8145.

Young, C. J., Furdui, V. I., Franklin, J., Koerner, R. M., Muir, D. C. G., Mabury,

S. A., 2007. Perfluorinated acids in arctic snow: new evidence for

atmospheric formation. Environmental Science & Technology 41,

3455e3461.

174

Yu, L., Mai, B., Meng, X., Bi, X., Sheng, G., Fu, J., & Peng, P. A. 2006. Particle-

bound polychlorinated dibenzo-p-dioxins and dibenzofurans in the

atmosphere of Guangzhou, China. Atmospheric Environment, 40(1), 96-

108.

Zhang, H., Zhao, C., Li, X., et al. 2010b. Study of monocyte membrane proteome

perturbation during lipopolysaccharide-induced tolerance using iTRAQ-

based quantitative proteomic approach. Proteomics, 10:2780–9.

Zhang, J. J., Hu, W., Wei, F., Wu, G., Korn, L. R., Chapman R. S. 2002.

Children's respiratory morbidity prevalence in relation to air pollution in

four Chinese cities. Environ Health Perspect, 110:961–7.

Zhang, J. J., Smith, K. R., 2007. Household air pollution from coal and biomass

fuels in China: measurements, health impacts, and interventions. Environ

Health Perspect 115, 848-855.

Zhang, J. J., Smith, K. R., 2007. Household air pollution from coal and biomass

fuels in China: measurements, health impacts, and interventions. Environ

Health Perspect 115, 848-855.

Zhang, L., Liu, J., Hu, J., Liu, C., Guo, W., Wang, Q., & Wang, H. 2012. The

inventory of sources, environmental releases and risk assessment for

perfluorooctane sulfonate in China. Environmental Pollution, 165, 193-

198.

Zhang, M. Q, Zhu, Y. C, Deng, R. W. 2002. Evaluation of mercury emissions to

the atmosphere from coal combustion, China. Ambio.31(6):482–484.

Zhang, T., Sun, H. W., Wu, Q., Zhang, X. Z., Yun, S. H., & Kannan, K. 2010a.

Perfluorochemicals in meat, eggs and indoor dust in China: assessment of

sources and pathways of human exposure to perfluorochemicals.

Environmental science & technology, 44(9), 3572-3579.

Zhang, Y., Tao, S., Shen, H., & Ma, J. 2009. Inhalation exposure to ambient

polycyclic aromatic hydrocarbons and lung cancer risk of Chinese

population. Proceedings of the National Academy of Sciences, 106(50),

21063-21067.

Zhao, D., & Sun, B. 1986. Atmospheric pollution from coal combustion in China.

Journal of the Air Pollution Control Association, 36(4), 371-374.

175

Zhao, X., Wan. Z., Chen, G., Zhu, H., Jiang, S., Yao. J. 2002. Genotoxic activity

of extractable organic matter from urban airborne particles in Shanghai,

China. Mutat Res.514(1–2):177–192

Zhao, Y. G., Wan, H. T., Law, A. Y., Wei, X., Huang, Y. Q., Giesy, J. P., &

Wong, C. K. 2011. Risk assessment for human consumption of

perfluorinated compound-contaminated freshwater and marine fish from

Hong Kong and Xiamen. Chemosphere, 85(2), 277-283.

Zhao, Y. G., Wan, H. T., Law, A. Y., Wei, X., Huang, Y. Q., Giesy, J. P., ... &

Wong, C. K. 2011. Risk assessment for human consumption of

perfluorinated compound-contaminated freshwater and marine fish from

Hong Kong and Xiamen. Chemosphere, 85(2), 277-283.

Zhao, Y., Wang, S., Duan, L., Lei, Y., Cao, P., & Hao, J. 2008. Primary air

pollutant emissions of coal-fired power plants in China: Current status and

future prediction. Atmospheric Environment, 42(36), 8442-8452.

Zheng, M., Salmon, L. G., Schauer, J. J., Zeng, L., Kiang, C. S., Zhang, Y., &

Cass, G. R. 2005. Seasonal trends in PM2. 5 source contributions in

Beijing, China. Atmospheric Environment, 39(22), 3967-3976.

Zhifang, C., Qinfang, Q., & Xiangqian, F. 1998. A study on environmental

pollution monitoring and occupational health in the capital iron and steel

company, Beijing, China, using nuclear and related analytical techniques.

Zhou, J., Wang, T., Huang, Y., Mao, T., & Zhong, N. 2005. Size distribution of

polycyclic aromatic hydrocarbons in urban and suburban sites of Beijing,

China. Chemosphere, 61(6), 792-799.

Zoete, V., Grosdidier, A., Michielin, O. 2007. Peroxisome proliferator-activated

receptor structures: ligand specificity, molecular switch and interactions

with regulators. Biochim Biophys Acta 1771: 915–25.

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CURRICULUM VITAE

Academic qualifications of the thesis author, BILLAH Md. Baki

- Received the Bachelor of Science in Zoology from Jahangirnagar

University, Savar, Dhaka, Bangladesh, 2006.

- Received the degree of Master of Science (M.Sc) in Zoology from

Jahangirnagar University, Savar, Dhaka, Bangladesh, 2007.

August 2015