Nasa Nnc05 Ca90 C Final Report

"fi, sf" RTA P2004#65 NASA Topic No B3.05 CN: NNC05CA09C Phase II Final Report June 2, 2007

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Executive Summary The overall goal of this program (through Phase III) is the development of an analyzer integrated into the International Space Station toilets capable of detecting key chemicals in urine to monitor and assess astronaut health. The analyzer will employ a novel metal-doped sol-gel material to simultaneously extract and quantify these key chemicals using surface-enhanced Raman spectroscopy (SERS). During the Phase I program feasibility was successfully demonstrated by chemically extracting 3-methylhistidine, a muscle-loss indicator, and Raloxifene, a bone-loss inhibitor from reconstituted urine and obtaining their SER spectra in 1-mm glass capillaries. During the Phase II program the following success were achieved:

1) 50 biochemicals (12 biomarkers, 13 drugs, and 25 potential interfering urine components) were successfully measured using these SERS-active capillaries.

2) The biomarkers and drugs were successfully detected at physiological concentrations (1 mg/L, and 0.01 mg/L, respectively).

3) Prototype micro-fluidic chips were fabricated that contained separation and the SERS-active materials. 4) 3-methylhistidine and Risedronate were separated from a real urine sample and detected at these

required concentrations using the chip shown below (Figure E.1). 5) A design is offered that can be integrated into Hamilton Sundstrand’s ISS toilet that would allow automated

extraction, measurement and analysis of each astronaut’s urine every day to monitor and assess health. 6) The success of this program has broad commercial value, considering that 55% of the US population over

age 50 suffer from osteoporosis, and the micro-fluidic chips developed here can identify biomarkers indicative of bone loss as much as 1 year prior to standard X-ray measurements. This would allow administering bisphosphonate-based drugs to potentially avert fractures, which represent a $17 billion annual cost to the US healthcare system.

Figure E.1. Photographs of A) 1) urine sample, 2) syringe, 3) filter, 4) ion-retardation capillary, 5) transfer vial, 6) lab-on-a-chip containing a) flow-control syringe, b) ports, c) ion exchange resin loaded channel, and d) SERS-active sol-gel loaded channels. B) Chip mounted on XY plate reader. C) RTA Raman Analyzer. SERS of D) 1 mg/L 3-methyl histidine and E) 0.01 mg/L Risedronate extracted from actual urine sample using this apparatus and detected in the d) channels. Complete analysis takes less than 10 minutes. This figure is proprietary.

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" On-Demand Urine Analyzer "

Part 1: Table of Contents Project Summary ..........................................................................................................................................................1 Executive Summary.......................................................................................................................................................2 Part 1: Table of Contents ..............................................................................................................................................3 Part 2: Identification and Significance of the Innovation .............................................................................................3 Part 3: Technical Objectives.......................................................................................................................................11 Part 4: Work Plan (Phase II Results) ..........................................................................................................................13 Part 5: Potential Applications .....................................................................................................................................53 Part 6: Contacts...........................................................................................................................................................53 Part 7: Future Technical Activities .............................................................................................................................55 Part 8: Potential Customer and Commercialization Activities ...................................................................................55 Part 9: Resources Status .............................................................................................................................................57 Part 10: References.....................................................................................................................................................58

Part 2: Identification and Significance of the Innovation This part is reproduced verbatim from the Phase I proposal.

This Small Business Innovation Research program will develop a novel surface-enhanced Raman (SER) sensor that will perform real-time chemical analysis of urine. It will provide key physiologic information to monitor astronaut health and indicate appropriate preventative treatment. The Phase I program will demonstrate feasibility by establishing the ability of sol-gel chemistry to both select key chemicals: amino acids, biomarkers, drugs, and metabolites, and enhance their Raman signals. The Phase II program will design and build a prototype “On-Demand Urine Analyzer” for ground-based measurement. This will include interfacing the SER sensor between a sampling system and a Raman instrument. The Phase II program will also design a low mass, low power version of this system (Figure 1) to be used on the International Space Station (ISS) and other vehicles employed during extended space flight missions (e.g. Mars expedition). 2.1. The Problem or Opportunity - Extended weightlessness causes numerous deleterious changes in human physiology, including space motion sickness (SMS), cephalad fluid shifts, reduced immune response, and loss of bone and muscle mass.1-6 The need to monitor and assess these effects is critical to developing exercise programs or drug regimes that would maintain astronaut health.7 Many of these physiological changes are reflected in the chemical composition of urine.8-13 For example, 3-methylhistidine can be used to assess loss of muscle mass, hydroxyproline to assess bone loss, and uric acid to assess renal stone formation,11 while metabolites can be analyzed to regulate dosage of anti-SMS drugs.14 According to the National Research Council Space Studies Board,

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Figure 1. Block diagram of surface-enhanced Raman based urinalysis system. A pump or flush mechanism draws the sample from the process through a particle filter into a flow cell and back into the process. Four sol-gel coated discs in the side wall provide polar-positive, polar-negative, weakly polar-positive and weakly polar-negative chemical selectivity and SER-activity. The proposed system will weigh 7.6 kg, occupy a 20x12x10 cm space (0.1 cubic foot), and require 20 watts (pump not included). Expanded view illustrates surface-enhanced Raman scattering from one of the sol-gel coated discs. This Illustration is Confidential and Proprietary.


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"Analysis of in-flight specimens for markers of bone resorption and formation would offer a unique opportunity to determine relative efficacy of these various exercise programs."15 The Board further states that current exercise regimes are ineffective and physiological data is inadequate to properly develop methods to offset the maladies of weightlessness. Furthermore, these physiological changes also influence metabolism of therapeutic drugs used by astronauts during space flight. Unfortunately, current earth based analytical laboratory methods that employ liquid or gas chromatography for separation and fluorescence or mass spectrometry for trace detection are labor intensive, slow, massive, and not cost-effective for operation in space, regardless of the type of bio-fluid sample analyzed.16-20 Therefore, the ability to assess and rapidly diagnose the status of individual bio-fluid samples “on-demand” is a critical and necessary component for monitoring the health and future well being of the crew members during extended flight missions in space. 2.2. The Innovation - We at Real-Time Analyzers (RTA) believe a light-weight, real-time analyzer can be developed based on surface-enhanced Raman spectroscopy (SERS) to provide detection and identification of several key chemicals (amino acids, biomarkers, drugs, and metabolites) in urine at relevant concentrations (from ng/mL to microg/mL) in under 5 minutes. This approach is based on the extreme sensitivity of the SERS technique, which has been demonstrated by detection of single molecules,21,22 and the ability to identify molecular structure of key physiological chemicals and drugs through the abundant vibration information provided by Raman spectroscopy. We proposed this concept in 2001 and received a high score, but not an award. Since that time we have made several significant advances in our SER-active sol-gel technology, two of which address reviewer’s comments. First, the sol-gel process is highly reproducible, and we guarantee SER-activity at 20% RSD for our Simple SERS Sample Vials, now sold commercially for 2 years (Figure 2). Second, we have successfully coated glass capillaries that are capable of measuring analytes in a flowing solution, reversibly (Figure 3) and capable of performing chemical separations.23 Additional important aspects of the technology include: third, we have patented the sol-gel process (NASA sponsored) that incorporates silver and/or gold nanoparticles into a stable porous silica matrix.24,25,26

Fourth, virtually all solvents can be used, including aqueous solutions ranging in pH from 2 to 11. No special reagents or conditions are required. Fifth, we have used these metal-doped sol-gels to measure SER spectra of several hundred chemicals,27,28,29,30,31,32 with typical detection limits of 1 ng/mL using 100 mW of 785 nm and 3-min acquisition time. Sixth, we have measured creatinine, lactic acid, uric acid, and actual urine specimens by simply adding the samples to vials and recording the SER spectra (Figure 4).33-35 Furthermore, in preparation of this proposal, we measured 1 mg of 3-methylhistidine in 1 mL of water and estimate a current detection limit of 60 microg/mL (0.35 mM, 6 ppm, Figure 5). It is worth noting that most drugs contain nitrogen functionalities indicative of SER activity, and we have been able to measure drugs and their metabolites (Figure 6).36 Although physiological measurements require detection limits below 1 microg/mL for biomarkers and as low as 10 ng/mL for drugs and their metabolites, we believe improvements in sol-gel chemistry and instrumentation would allow

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Figure 2. Reproducible SER-intensity response for benzoic acid over entire surface of a Simple SERS Sample Vial. Average = 29.1± 4.26 (14.6%) for 240 points (10 sec per point).

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Figure 3. Reversible SER spectra of 30-sec “plug” of benzoic acid flowing through a sol-gel coated capillary. A) Spectra from time 0 to 2.4 min (bottom to top) and B) plot of corresponding 1000 cm-1 band intensity. Spectra are each 8-sec, using 100 mW of 785 nm.

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achieving these detection limits. Seventh, the choice of metal and alkoxide can be used to develop chemically selective sensors. We have successfully developed sol-gels that select for polar-positive, polar-negative, weakly polar-positive, and weakly polar-negative chemical species.37 This will allow discriminative enhancement of the biomarkers or drugs in favor of urine components. Finally, it is worth noting that RTA has developed an extremely rugged, compact Raman instrument that employs interferometry for absolute wavelength accuracy and an avalanche Si detector that improves sensitivity by ~100 times.38 And we are currently developing a hand portable, battery powered version of the system for the Navy, which will weigh 9.8 kg, occupy 13,500 cc (0.5 cubic foot), require 23.5 W, and will be capable of wireless communication.39

2.3. The Proposal - The overall objective of the proposed program (through Phase III) is the development of an analyzer integrated into the ISS toilets capable of immediate detection of key chemicals in urine to monitor and assess astronaut health (complete analysis within 5 minutes of flush). The focus of Phase I will be to establish the ability of the sol-gel chemistry to both select these key chemicals and enhance their Raman signals. These key chemicals, listed in Table 1, include: urine products, hormones, muscle loss, bone loss and stone forming indicators (biomarkers), drugs and their metabolites. This will be achieved in three tasks. The first task will employ combinatorial chemistry to synthesize 36 libraries of metal-doped sol-gel coated micro-plates varying in alkoxide composition (Si:Si = 1:0 or 1:1 v/v) to be screened for analyte specific SER activity in Task 2. This will be

Urine Products (g/L):* Muscle Loss Indicators (<mg/L):** creatinine (1.4) 3-methyl histidine glucose (0.1) glutamic acid (0.3) Bone Loss Indicators(<mg/L): hippuric acid (0.9) hydroxyproline hydroxyproline (0.9) deoxypyridinoline lactic acid (0.2) nicotinic acid (0.25) Stone Formation Indicators (<mg/L): PABA (0.2) calcium oxalate uric acid (0.2) calcium phosphate thiamine (0.2) uric acid histidine (0.2) pyridoxamine (0.1) Drugs (~microg/L): Hormones (g/L): alendronate - for Anti bone loss pregnanediol (0.9) scopolamine - for Anti motion sickness pregnanetriol (2.2) D-penicilamine - for Anti stone formation raloxifene - for Anti bone loss estradiol lovastatin - for Anti bone loss

Table 1. Partial list of chemicals in urine, muscle loss, bone loss, and stone formation indicators, and administered drugs. *To be measured in Task 3. **Chemicals in italics to be measured in Task 2.

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Wavenumbers (∆cm-1) Figure 6. SER spectra of A) amobarbital, B) barbital, C) phenobarbital, and D) secobarbital. Conditions: 1 mg/ml (analyte/methanol) in sol-gel coated sample vials, 80 mW of 1064 nm, 50 averaged scans.

Confidential Proprietary Information

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Wavenumbers (∆cm-1) Figure 4. SERS of A) female and B) male urine specimens. Both samples were pH of 6.5 and diluted to 50% with water. Bands attributed to uric acid occur at 502, 650, 815, 1134, and 1616 cm-1. Conditions: 120 mW of 1064 nm, 50 scans at 8 cm-1.

Wavenumbers (∆cm-1) Figure 5. A) Raman and B) SERS of 3-methylhistidine (R= CH3). Conditions: Raman, pure solid, 500 mW and 3 min scan, SER, 6mM, 100 mW and 3 min. Labeled SER bands have been observed for histidine (R = H) by electrolytic SERS. Inset: molecular structure.

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accomplished by varying reactant concentrations delivered to 96 well micro-plates. Reactant variables include eight Si-alkoxide precursors (tetramethylorthosilicate (TMOS), tetraethylorthosilicate (TEOS), methyltrimethoxysilane (MTMOS), ethyltrimethoxysilane (ETMOS), methyltriethoxysilane (MTEOS), ethyltriethoxysilane (ETEOS), aminotrimethoxysilane (ATMOS), and aminotriethoxysilane (ATEOS)), and two types of metal particles (silver or gold). The second task will screen the sol-gel libraries with key physiological chemicals and drugs for SER activity. This will be accomplished by measuring the SER spectra of library subsets using the following four standard chemicals: p-aminobenzoic acid (PABA), aniline (AN), benzoic acid (BA), and phenyl acetylene (PA); and twelve initial target chemicals: 3-methyl histidine, hydroxyproline, deoxypyridinoline, calcium phosphate, uric acid, alendronate, scopolamine, dextroamphetamine, raloxifene, lovastatin, acetaminophen, and acetylsalicylic acid. The third task will demonstrate the ability of the proposed sol-gel SERS plates to discriminatively detect and quantify the key chemicals in a chemical matrix equivalent to a urine specimen. This will be accomplished by analyzing the chemicals in simulated urine samples prepared according to clinically defined formulations representing an average human composition. An initial chemometrics urinalysis model will be developed for identifying, quantifying and correlating key components in urine of physiological interest with the Raman spectra. 2.4. The Probability of Success - Dr. Frank Inscore, as the Principal Investigator, and Dr. Stuart Farquharson, as Program Manager, and Dr. John Murren of Yale University as a Consultant have the required expertise to perform the proposed research. The PI has over eight years experience in designing Raman systems to make difficult and demanding measurements requiring extreme sample preparation protocols and rigorous optical alignment procedures for collecting reproducible spectral data. This includes the implementation of continuous wave (CW), pulsed, and solid-state lasers combined with dispersive instrumentation and multichannel detection employing a charge coupled device (CCD) for acquiring normal Raman and resonance enhanced Raman spectra of various inorganic-organic models of related metalloprotein enzymatic systems.40,41,42,43 The PI also has extensive experience in designing and collecting Raman data for various sampling configurations, sample states and conditions (e.g., in vacuo and at cryogenic temperatures). The PI also has acquired considerable expertise and experience in the analysis and application of FT-Raman, SERS and metal-doped sol-gel chemistry at RTA that is relevant to the successful completion of the proposed project. The PM has the experience and expertise in the analysis and application of FT-Raman.25,44,45,47 The PM also has considerable experience and expertise in designing new Raman analyzers for many applications including sensor design for Raman and surface-enhanced Raman spectroscopy applications.24-,46-

52 This includes numerous sampling systems, and several Raman systems, including a state-of-the-art fiber optic FT-Raman spectrometer.52,53 He has designed, patented, and implemented several fiber optic probes for in-situ remote monitoring in harsh physical and chemical environments.54 Dr. Farquharson also has extensive experience in performing and managing large interdisciplinary experimental research projects. He has been the Principal Investigator or Manager on contracts from DOD, DOE, NASA, NIH and NSF. Dr. John Murren is a Professor at Yale University School of Medicine (Medical Oncology) and Director of the Lung Cancer Treatment Unit. Dr. Murren is very active in the evaluation of new chemotherapy drugs and drug combinations used for cancer treatment. He will provide guidance in our urinalysis experiments (e.g. likely interferents), and understanding of drug metabolic pathways.55 Finally, we presented a conceptual Urine Analyzer design to Hamilton Sundstrand, which was very well received. Based on their design review, and our previous working relationship, Hamilton Sundstrand will support our Phase II research and Phase III commercialization efforts (see support letter). 2.5. Background and Technical Approach - We at Real-Time Analyzers believe that a method based on surface-enhanced Raman spectroscopy can be developed to provide real-time detection and quantification of several key chemicals, biochemicals, and metabolites in urine to monitor astronaut health and indicate appropriate preventive treatment. This is based on our SERS detection of several chemicals, such as creatinine, lactic acid, and uric acid in urine specimens, the DNA bases, amino acids, including 3-methylhistidine, and numerous drugs and their metabolites (see Figures 4 – 6).24 A background to this approach follows. Microgravity and Human Physiology - Extended weightlessness causes numerous deleterious changes in human physiology, including space motion sickness (SMS), cephalad fluid shifts, reduced immune response, and loss of bone and muscle mass. The signs of SMS (nausea, dizziness) and fluid shifts (headaches, increased heart rate) are easily detected, while changes in hormone and bone metabolism are not. Consequently, a more detailed analysis of astronaut physiology is required to assess these effects. Many of these physiological changes are reflected in the chemical composition of urine. For example, 3-methylhistidine is a known product of muscle protein breakdown and is quantitatively excreted in urine,8-10 while the urinary concentration of hydroxyproline and deoxypyridinoline released during collagen breakdown show promise as indicators of bone turnover.11,12 Renal stone formation,



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associated with bone loss, can be evaluated by analyzing for calcium oxalate, calcium phosphate, uric acid, citrate, magnesium ammonium phosphate, and other stone-forming salts. Furthermore, the metabolic products of drugs administered to relieve SMS (e.g. promethazine and scopolamine),56-58 reduce muscle loss (amino acid infusion59) or bone loss (alendronate, lovastatin,60 raloxifene61), or renal stone formation (e.g. D-penicilamine) can be analyzed to regulate dosage and adjust diet. Unfortunately, the approach used in previous missions (shuttle and Mir), astronauts logging their diet, collecting and sending urine samples back to earth for analysis, would not allow timely preventive measures. This wait may further jeopardize the health of astronauts performing physical labor associated with the construction of the International Space Station. In particular, a normal dose of an anti-SMS drug for one astronaut may metabolize as a high dose for another, causing drowsiness and making tasks difficult to perform and potentially dangerous.7,62,63,64 Earth based urinalysis employs multiple steps to separate the chemicals and perform the required detection. This typically includes particulate filtration, pH adjustment, and chromatographic separation (usually high performance liquid chromatographic, HPLC), prior to introduction into a mass spectrometer (MS). Inclusion of standards throughout this process is required to ensure measurement accuracy. These methods are labor intensive and time consuming, and the massive instruments (e.g. MS) are inappropriate for the ISS. It should be noted, however, that an effort to make this traditional approach to urinalysis practical for the ISS has been undertaken by a research team at Johns Hopkins University headed by Dr. Potember.18,65 They have developed a rugged time-of-flight mass spectrometer (TOFMS) to measure biomarkers. Virtues of the TOFMS technologies are that it is small (less than one cubic ft), lightweight (less than 5 kg), and requires low power (less than 50 watts). To introduce quantitative samples into the TOFMS, without time consuming chromatographic columns (>30 minutes analysis times), the Johns Hopkins team has been investigating matrix-assisted laser desorption ionization (MALDI) sampling. With MALDI sampling, a matrix standard must be used (and supplied), and high-powered ultraviolet pulse lasers are required. Unfortunately, these lasers are inefficient and typical power requirements are near 100 W. The ability to monitor and assess the effectiveness of therapeutic agents used by astronauts during space flight is also problematic. Evidence exists that suggest the therapeutic effectiveness of some drugs, such as scopolamine/dextroamphetamine (a drug combination used to prevent motion sickness) and acetaminophen (a drug used frequently for pain relief by astronauts) may change in space. This is reflected by the fact that concentration levels of such drugs (and hence their pharmacokinetic behavior) measured in bio-fluid samples (blood-plasma, urine, and saliva) during the course of pre- and post-flight time by typical chromatographic, mass spectrometric and immuno-assay techniques on earth are not invariant, and that these subsequent changes ultimately depend on mission length and individual physiological responses to space flight. According to the National Research Council Space Studies Board "Analysis of in-flight specimens for markers of bone resorption and formation would offer a unique opportunity to determine relative efficacy of these various exercise programs."15 The Board further states that the current exercise regimes are ineffective and physiological data is inadequate to properly develop methods to offset the maladies of weightlessness. The proposed system will allow pre- and post-flight ground analysis at the end of Phase II and on-station analysis shortly thereafter (through Phase II production by Hamilton Sundstrand). Raman Spectroscopy - Similar to an infrared spectrum, a Raman spectrum consists of a wavelength distribution of bands specific to molecular vibrations corresponding to the sample being analyzed, which allows confident identification of chemicals and biochemicals (selectivity). For example, Figure 5 shows the Raman spectrum of 3-methyl histidine, which is slightly different from that of histidine. In practice, a laser is focused on the sample, the inelastically scattered radiation (Raman) is optically collected, and directed into a spectrometer, which provides wavelength dispersion, and a detector converts photon energy to electrical signal intensity. Historically, the very low conversion of incident radiation to inelastic scattered radiation limited Raman spectroscopy to applications, which were difficult to perform by infrared spectroscopy, in particular, aqueous solutions. In addition to sensitivity, Raman spectroscopy has been limited by long-term instrument stability, fluorescence interference, and wavelength reproducibility. These four limitations have been largely overcome in the past decade by several technological advances, principally: air cooled stable diode lasers, notch filters, full spectrum detectors (i.e. no scanning), high quantum efficiency detectors, and associated fast electronics, data acquisition and analysis, which have made Raman spectroscopy standard equipment in analytical laboratories,66 and allowed the development of portable systems. An attractive advantage to this technique is that in many cases samples do not have to be extracted or prepared, and a fiber optic probe can simply be aimed at a sample to perform chemical analysis. In this regard, Raman spectroscopy


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has been used to identify various chemicals (within glass cylinders). However, these measurements are best performed for pure or at least highly concentrated samples. Further improvements can be realized by using a Fourier transform Raman spectrometer.67 These systems employ diode pumped Nd:YAG lasers that provide excitation in the near infrared, virtually eliminating fluorescence interference associated with visible laser excitation. Another advantage of FT systems is high wavelength accuracy (Connes advantage)68afforded by the HeNe wavelength reference laser. This allows reliable spectral subtraction and library matching,69 as well as continuous or "on-demand" monitoring. Spectral subtractions can be used to isolate contributions of trace chemicals in the presence of much more concentrated interferent chemicals,69,69 and library matching can provide rapid chemical identification. The former may be very important, in that uric acid produces a significant SER spectrum that might need to be subtracted to observe other key chemicals. It also allows employing other urine components as internal concentration standards, such as creatinine to quantify 3-methyl histidine. Here, however, spectral analysis will be augmented by the chemical selectivity of the sol-gels to be developed (see below). Nevertheless, even with these improvements, the very low conversion of incident radiation to inelastic scattered radiation limits the sensitivity of Raman spectroscopy and provides only moderate detection limits for normal Raman scattering. Relatively high laser powers and long acquisition times are required to obtain a spectrum with a reasonable S/N, which in general still allow only modest detection limits to be estimated for normal Raman. For example, Figure 5 shows Raman spectra of pure 3-methyl histidine. The detection limit for 3-methyl histidine in water or lactic acid is ~1% (Figure 5 is a pure solid sample). Thus, normal Raman scattering would be capable of only moderate detection limits, such as 100 mg/mL. Surface Enhanced Raman Spectroscopy - In 1974,70 it was discovered that when a molecule is in close proximity to a roughened silver electrode, the Raman signal was increased by as much as six orders of magnitude.49 The mechanism responsible for this large increase in scattering efficiency has been the subject of considerable research.71 Briefly, the incident laser photons generate a surface plasmon field at the metal surface that provides an efficient pathway to transfer energy to the molecular vibrational modes, and produce Raman photons.71 This is possible only if: 1) the material is in the form of particles much smaller than the laser incident wavelength (Raleigh regime, surface imperfections of similar size also work) to couple the energy, 2) the material has the appropriate optical properties to couple the light (extinction), 3) the available free electrons, when excited, are confined by the particle size forming surface modes or generating surface plasmons, and 4) the molecule has matching optical properties (absorption) to couple to the plasmon field.49,72 These very specific conditions, restrict SERS to the coinage metals, silver, gold, and copper with diameters between 5 and 200 nm.72,73 SERS has been demonstrated for a number of inorganics, organics, and biochemicals, using three primary methods developed to produce SER active media: activated electrodes in electrolytic cells,48 activated silver and gold colloid reagents,74,75,76 and metal coated substrates.77,78,79,80,81 Unfortunately, these methods have not been reduced to a product because it has proven difficult to manufacture a surface by these methods that yields reproducible enhancements or reversible adsorptions or both. Oxidation-reduction cycles are used to create surface features (roughness) on electrodes with the appropriate size to generate surface plasmons, but this roughness is difficult to reproduce from one measurement to the next.49,82 Reducing a metal salt solution can be used to produce a colloid containing metal particles capable of generating surface plasmons. The resultant particle size and aggregate size are strongly influenced by the initial chemical concentrations, temperature, pH, and rate of mixing, and consequently are also difficult to reproduce.75 Depositing one of the SER active metals onto a surface with the appropriate roughness can also be used to prepare a surface capable of supporting surface plasmons. The largest enhancements are obtained when the sample is dried onto the surface, in effect concentrating the analyte on the metal. This also results in measurements that are difficult to reproduce. The relative merits and limitations of these methods have recently been reviewed.83 In an effort to overcome these limitations, we have been developing metal-doped sol-gels as an active SER medium. This medium should be capable of providing SER measurements that are reproducible, reversible, and quantitative, yet are not restricted to specific environments, such as electrolytes, solvents, or evaporated surfaces. 24 The general concept is shown Figure 1, where nanocomposite material has been coated on the inside walls of glass vials to yield a general use SER product: Simple SERS Sample Vials. We have 1) measured the SER spectrum of 1 nanogram/milliliter of PABA in methanol (estimated detection limit of 10 pg/mL), and achieved a signal increase of a factor of 107,25 2) have reproduced measurements from vial-to-vial with a standard deviation less than 10%, 3) have demonstrated reversibility using a flowing system (within 5 minutes at 1 ml/min flow through a coated NMR tube,25 and 4) we have successfully measured the amino acids, DNA bases, several drugs and their metabolites in


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both aqueous and non-aqueous solutions using our Simple SERS Sample Vials. In particular, we measured 1 mg of 3-methyl histidine in 1 mL of water and the signal-to-noise ratio (S/N) of 52 suggests a current detection limit of 60 microg/mL (defined as S/N=3, Figure 5). Measurements at the required detection limits (<1 microg/mL, Table 1) is anticipated to be straightforward using a new hybrid FT-Raman spectrometer (increased sensitivity with 785 nm laser and Si-APD) developed under another SBIR program (see Related R&D). However, we recently employed 785 nm laser excitation and found near-equivalent SERS-enhancement compared to previous 1064 nm laser excitation, even when taking the ν4 wavelength dependency of Raman scattering into account. This suggested that our particle size, distribution, and/or aggregation were far from optimum. In recent years we have used our Simple SERS Sample Vials to measure several hundred different chemicals. In general, we calculate enhancement factors between 104 and 106. (The difference is due to the polarizability of the analyte and/or the extent of interaction with the metal.) These values may prove insufficient for detecting certain drugs and/or metabolites present at very low concentration levels in the body fluids (e.g. 1ng/L to 1ng/mL). Except for highly polarizable molecules, we typically measure LODs of 10 microg/L, suggesting that an improvement of 2 to 4-orders of magnitude is required to achieve the lower detection limits. Recently, we re-evaluated our metal-doped sol-gels in regards to optimum particle size and aggregation. TEM measurements show that the silver particles are largely unnaggregated and small (5-20 nm). We are currently examining methods to increase particle size and aggregation (variations in concentration and heating). According to theory improvements of 2 to 6 orders of magnitude can be expected. Such improvements in both the instrumentation and metal-doped sol-gel chemistry will be important for achieving the sensitivity required in this proposal. Sol-Gel Chemistry - The sol-gel process is a chemical route for the preparation of metal oxides and other inorganic materials such as glasses and ceramics.84,85 The sol-gel process involves the preparation of a sol of metal-alkoxide precursors in a suitable solvent, which undergo a series of reactions including their initial hydrolysis followed by poly-condensation to form a gel. Expulsion of the solvent from the gel by a drying process, results in a highly porous xerogel consisting of the metal oxides and any other additives that may have been introduced during the process. Additional heating (fired) can be used to crystallize and/or densify the material. Typically, the sol-gel process involves a silicon alkoxide (such as tetramethyl orthosilicate), water and a solvent (methanol or ethanol), which are mixed thoroughly to achieve homogeneity on a molecular scale. The sol-gel matrixes offer several additional properties useful to the proposed ISS application: physical rigidity and high abrasion resistance, negligible swelling in aqueous solutions, chemical inertness, high photochemical and thermal stability, and excellent optical transparency, and low intrinsic fluorescence.86 We have successfully developed metal-doped sol-gels that can coat a variety of substrate-surfaces to produce a wide range of sensor designs, including glass vials, multi-well microplates (glass and polystyrene), and glass capillaries. We have used the latter to detect flowing samples as well as to perform chemical separations. The Simple SERS Sample Vials are produced according to the following procedure. First, a silver amine precursor complex is prepared from a solution of ammonium hydroxide and silver nitrate. Second, the sol-gel solution is prepared from TMOS and methanol. Third, the amine complex and sol-gel solution are mixed, then the solution is spin-coated onto the inner walls of a glass vial, and dried. Fourth, the substrate is heated to form the xerogel. This step defines the porosity (size and distribution) and silver particle size. Fifth, the silver ion is reduced to silver metal particles (Ago) using dilute sodium borohydride. And sixth, the substrate is washed and dried prior to the addition of a sample. Previously, we established that a volume ratio of 1:5:4, silver amine complex to TMOS to methanol heated at 120 oC for 2 hours yielded optimum SERS signals for PABA.25 It is worth noting that gold-doped sol-gel coated vials have also been prepared in a similar fashion by using an aqueous solution of HAuCl4 (or NaAuCl4), nitric acid as a gellation catalyst, and a Si-alkoxide precursor (e.g. TMOS). These conditions were optimized using a simplistic experimental design approach. Knowledge of sol-gel chemistry and surface-enhancement theory was used to optimize chemistry and physical properties, while performing a minimum number of experiments. Nevertheless, the use of only PABA to maximize the sensitivity may have reduced the sensitivity to other analytes. For example, we estimate a surface enhancement of <105 for 3-methyle histidine. Unfortunately, tailoring sensitivity to every analyte of interest would be time consuming and tedious. Combinatorial Chemical Synthesis - To alleviate this problem, we are employing combinatorial chemistry to systematically synthesize large numbers of well-defined sol-gel compositions (libraries) by combining the reactants in all combinations.87 We are employing 96-well micro-plates to develop the chemistry. Initially two reservoirs (8 and 12-cell) are filled with the two starting solutions (here TMOS and the amine complex) with incrementally increasing concentrations. Then multi-channel pipettes (8 and 12) are used to deliver microliter samples to each



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well fairly rapidly (by hand it takes ~4 minutes). Once completed, the plate is placed into an oven to cure the sol-gel. We are able to prepare as many as 20 plates per day or 1892 sol-gels with different SERS activity. The success of a library is determined by testing the activity of the sol-gel coated well. Since the number of wells quickly escalates using this procedure, testing of each well becomes impossible and high-throughput screening techniques are used. This is accomplished by selecting and testing an ordered subset of the 96 wells. The most active wells can be used to refine the chemistry and improve SERS activity. Using this approach, we have modified the alkoxide chemistry to obtain SERS active sol-gels that preferentially "solvate" polar or non-polar analytes. For example, the alkoxide precursor MTMOS has a higher -CH3 concentration (lower -OH) than TMOS, and consequently a higher affinity for non-polar chemicals (hydrophobic).86,88 Task I will focus on employing combinatorial chemistry to develop sol-gels that are selective and active (and stable) towards various key analytes to be screened for in Task II and Task III. During the past year we successfully developed our first chemically selective SER-active sol-gels, consisting of the four Libraries outlined in Table 2. Table 2. Summary of chemically selective surface-enhanced Raman active metal-doped sol-gels.

Library 1 Ag + TMOS Selective for polar-negative species Library 2 Ag + (TMOS+MTMS) Selective for weakly polar-negative species Library 3 Au +TMOS Selective for polar-positive species Library 4 Au + TEOS Selective for weakly polar-positive species

Figure 7 shows surface-enhanced Raman spectra of p-aminobenzoic acid (PABA) using Library 1 and 3, and phenyl acetylene (PA) using Library 2 and 4. For Libraries 1 and 3, the polar PABA passes through the polar sol-gel and is enhanced by either the silver or gold particles. For electropositive silver, the PABA anion (pKa = 4.8) interacts through the carboxylate group and COO- bands appear at 840 and 1405 cm-1. For electronegative gold, PABA interacts through the amine group and -NH2 bands appear at 1355 and 1585 cm-1. For Libraries 2 and 4, the non-polar PA passes through the non-polar sol-gel and is enhanced by either the silver or gold particles. For electropositive silver, PA interacts strongly through the cylindrical π cloud around the carbon-carbon triple bond and a -C≡C- doublet occurs near 2000 cm-1. For electronegative gold, this interaction is unlikely and only very weak bands occur near 2000 cm-1. The polar/non-polar selectivity of the polar-negative and weakly polar-negative sol-gels was tested by adding a 1:1 molar mixture of PABA and PA. The selective enhancement is quite good (Figure 8). The spectrum obtained using the polar sol-gel suggests 78% PABA and 22% PA reached or is active at the metal surface, while the spectrum obtained using the weakly polar sol-gel suggests a 9% PABA and 91% PA activity. The band peak intensities at 2000 cm-1 for PA and 1450 cm-1 for PABA were used for these calculations, and are expanded in Figure 8 for clarity. Silver-doped TMOS favored more rapid transit of the polar PABA than the non-polar PA. Figure 7. SER spectra of A) PABA using Libraries 1 (top) and 3 (polar-negative and polar-positive sol-gels), and B) PA using Libraries 2 (top) and 4 (weakly polar-negative and weakly polar-positive sol-gels). PABA is 1 mg/mL, PA is 1% v/v. Spectral conditions: 75 mw 1064 nm, 100 scans (1.5 min), 8 cm-1 resolution. The y-axis for all spectra represent intensity in arbitrary units.

B A

Wavenumber (∆cm-1) Wavenumber (∆cm-1)

2NH COOH

C CH

rela

tive

inte

nsity

rela

tive

inte

nsity


11

Figure 8. SERS of 1:1 M/M of PABA and PA in A) polar-negative and C) weakly polar-negative sol-gels. The lower traces, compare the pure chemicals; B) 1 mg/ml PABA in polar-negative sol-gel and D) 1% PA in weakly polar-negative sol-gel, while the insets magnify the minority species for clarity (x5 in A and x10 in B). Spectral conditions as in Figure 5.

Part 3: Technical Objectives The overall objective of the proposed program (through Phase III) is the development of an analyzer integrated into the International Space Station (ISS) toilets capable of immediate detection of key chemicals in urine to monitor and assess astronaut health. The following six comprehensive tasks have been designed to develop this proposed analyzer, as well as the required method of analysis with the following objectives and specific questions to be answered. Task 1 - Spectral Library Development. The overall objective of this task is to build a SER spectral library to allow rapid spectral matching (or functional group analysis) for identification of biochemical markers, drugs and their metabolites present in human urine. This will be accomplished by extending the Phase I measurements to include an in-depth analysis of 12 primary bio-indicators specific for assessing muscle/bone loss and renal stone formation, and 12 priority drugs (and their metabolites) that may be used to minimize or counter the adverse physiological affects associated with changes in the concentration levels of these biomarkers present in urine. Questions to be answered? Are all of the 24 chemicals SER-active? What is the preferred sol-gel for each bio-indicator and target drug? Are there potential interferants? How well does the spectral match software identify each? How well does it identify a chemical not in the library? Task 2 – Chemical Selectivity Development. The overall objective of this task is to refine the ability of the 4 basic SER-active sol-gels developed in Phase I to selectively extract biochemicals and drugs present in human urine, and enhance their Raman spectra. This will be accomplished by measuring reversibility of representative bio-indicators and drugs drawn through the 4 sol-gels. Questions to be answered? Which sol-gels provide irreversible adsorption of the bio-indicators and target drugs and SER-activity? What are the estimated LODs? Can the spectral deconvolution software identify each urine component (bio-indicators and drugs) on each sol-gel? Task 3. Component selection and testing. The overall goal of this task is to design a lab-on-a-chip that can be used to analyze chemical components present in human urine by SERS. This will be accomplished by designing a chip based on the Phase I results and the background information provided above. Questions to be answered: Are there components available to perform the desired extractions and separations? Are they effective in the context of our SER-active sol-gels, separately, and together? What is the best sequence of sol-gels? How universal is it for various urine components and drugs? Are the mixtures effectively separated and

C A

Wavenumber (∆cm-1) Wavenumber (∆cm-1)

D B rela

tive

inte

nsity

rela

tive

inte

nsity



12

detected? What happens when other chemicals from Task 1 are analyzed? What are the detection limits? Task 4. Lab-on-a-chip fabrication (with Advanced Fuel Research as subcontractor). The overall goal of this task is to build many microfluidic chips that can be used to test the preliminary lab-on-a-chip design. This will be accomplished by fabricating poly(methyl methacrylate) chips. The process of Muck et al., slightly modified, will be followed.89 The microfluidic chips will be prepared in a class 10 clean room at AFR, and all safety (HF) procedures will be followed. Questions to be answered: Can AFR produce the test chips? Does the process need further modification? Does the interface perform as planned (no leaks)? Can the various channels be loaded, reduced? What size, length is best? Can separation materials be introduced? Task 5. Define Analytical Figures of Merit. The aim of this task is to establish performance criteria for the lab-on-a-chip. This will be accomplished by measuring the analytical figures of merit for the analyzer, as outlined by the FDA: sensitivity, reproducibility, linearity, accuracy, precision, resolution, and selectivity. Questions to be answered: What are the LODs for each of the biomarkers, drugs and their metabolites? What is the reproducibility of the chips? Which channel design provides the best selectivity, reproducibility, and sensitivity? What is the best standardization method for quantitating target analyte concentrations? Task 6 - Prototype Design. The overall goal of this task is to design a prototype system to be used and tested by NASA in Phase III. This will be accomplished by redesigning the lab-on-a-chip for system integration and autonomous operation. No questions to be answered.


13

Part 4: Work Plan (Phase II Results) Task 1 - Spectral Library Development. The overall objective of this task was to build a surface-enhanced Raman spectral library to allow rapid spectral matching (or functional group analysis) for identification of biochemical markers, drugs and their metabolites present in human urine. This was accomplished by measuring the SERS-activity of 25 analytes and 25 potential interferents using some 20 different chemically-selective sol-gels (Libraries). The proposed 24 analytes (12 biomarkers and 12 drugs) that were the focus of this program are listed in Table T1.1. Ten of the 12 biomarkers were commercially available (the two collagen bound bone-loss markers were not) and all were SERS-active. Similarly, 10 of the 12 proposed drugs were commercially available, and all were SERS-active. Three additional drugs (secondary) were also measured, including the metabolites of acetaminophen and allopurinol. Table T1.1. List of biomarkers and associated drugs studied during Phase II.

Biomarkers Drugs Muscle loss indicators: Anti-bone loss: Anti-stone formation: Creatinine (CRE)

Deoxypyridinoline – collagen bound* Etidronate (ETI) Hydrochlorothiazide (HCT)

3-Methylhistidine (3-MeHIS) Clodronate (CLO) Allopurinol (ALLO) Bone loss indicators: Stone formation indicators: Pamidronate (PAM) Penicillamine (PEN) Hydroxyproline (HO-PRO) Calcium oxalate (CaOx) Alendronate (ALE) Anti-motion sickness:

Hydroxylysine (HO-LYS) Calcium phosphate (CaP) Risedronate (RIS) Promethazine (PROM)** Pyridinoline (H-Pyd) Uric acid (UA) Ibandronate (IBA) Scopolamine (SCOP) ** Pyridinoline-collagen bound* Cystine (CYST) Raloxifene (RAL) Anti-inflammatory:

Deoxypyridinoline (H-dPyd) Tiludronate*/Zoldronic acid* Acetaminophen (AM)** *Four analytes not available. **Additional drugs measured. In the Phase I proposal we described 4 chemically-selective sol-gels (Libraries 1-4) to be used for this study. During the Phase I program we modified the Library 1 and 2 chemistries to produce 4 additional sol-gels. During the Phase II program, the number of chemistries was further expanded to some 20 available sol-gels that could be used for screening chemical selectivity (see Quarterly Report 7). By examining many biomarkers and drugs using all 20 libraries it was found that 6 proved most useful. L1, L2, and L4 correspond to the chemistries designated 1, 2, and 4 while L3 corresponds to the chemistry designated 2d in the Phase I Final Report. We also developed and used two new chemistries, which essentially are chemistry 1 (or L1) modified by the inclusion of polymers, either poly(ethyleneglycol) or poly(dimethylsiloxane) (PEG and PDMS, respectively), designated L5 and L6. The relative concentrations of the precursors used to prepare these 6 libraries are summarized in Table T1.2.

Table T1.2. Synthesis summary for SERS-active, chemically-selective, sol-gel chemical libraries (L1-L6).

Sol-Gel Metal Precursor (A) Sol-Gel Precursor (B) A (µL)

B (µL)

Selective for:

L1 5/1/10: 1N AgNO3/28%NH3OH/MeOH 1/5: TMOS/MTMS 100 120 mildly polar - negative

L2 5/5/10: 1N AgNO3/28%NH3OH/MeOH MTMS 100 100 non-polar - negative

L3 5/5/10: 1N AgNO3/28%NH3OH/MeOH 1/5/1:TMOS/MTMS/ODS 100 175 very non-polar-negative

L4 4/1: 0.25N HAuCl4(aq)/70% HNO3 TMOS 100 100 very polar - positive L5

5/1/10: 1N AgNO3/28%NH3OH/MeOH 1/5: TMOS/MTMS (+ 10 µL PEG)

100 120

polar – negative

L6 5/1/10: 1N AgNO3/28%NH3OH/MeOH 1/5: TMOS/MTMS (+ 10 µL PDMS)

100 120

non-polar - negative

APTMS: aminopropyltrimethoxysilane, MTMS: methyltrimethoxysilane, PDMS: polydimethylsiloxane, PEG: polyethylene glycol, ODS: octadecyltrimethoxysilane, TMOS: tetramethylorthosilicate. During the Phase I program, screening SERS-activity for the analytes using different sol-gels was initially performed in 96-well microplates. It was found that better results were obtained using glass capillaries (1.1 mm



14

outer diameter, 800 micron inner diameter) filled with metal-doped sol-gels. These capillaries operate in the active mode, in that the sample is forced to flow through the sol-gel. We therefore used these capillaries to test SER-activity for the analytes throughout the Phase II program. Furthermore, the capillaries became the basis of the Phase II micro-chip sampling system. The basic design and use of the SER-active capillaries is shown in Figure T1.1, and are prepared as follows. The alkoxide and amine precursors are prepared according to Table T1.2, mixed, and then drawn into the capillary by syringe. Typically 0.4 mL of solution coats a 4 cm length of capillary. The sol solution gels in 5 minutes, and a more rigid structure is obtained after 24 hours. A solution of 0.1g/100mL NaBH4 is drawn through the capillary to reduce the metal. This is followed by a 0.035% HNO3 acid wash, and then the capillary is then ready to be used.

Figure T1.1. Photograph of sol-gel coated melting point capillaries attached to syringes, before (top) and after reduction with sodium borohydride. Initial SERS-activity screening on the various sol-gels employed 1 mg samples in 1 mL HPLC water. The samples were drawn into the capillaries, which were mounted on an XY sample stage above a fiber optic probe coupled to RTA’s Industrial Raman Analyzer. Spectra were obtained using 80 or 100 mW of 785 nm excitation at the sample and 1 minute acquisition time. Once the initial screening was performed, the samples were serially diluted over 4 orders of magnitude to 0.01 mg/L to determine sensitivity. The required sensitivity is ~ 1 mg/L for the metabolites and 10s of microg/L for the drugs. Tables T1.3 and T1.4 summarize the SERS-activity in terms of the lowest measured concentration (LMC) for the 10 biomarkers and 13 drugs, respectively. The best measurements were ultimately obtained by concentrating the sample using ion exchange resins (Task 3), and are included in the tables for comparison. Also, normal Raman spectra (NRS) of the analytes were acquired as neat liquids or pure solids in the same glass capillaries using 300 mW at 785 nm for 5 minutes. The NRS and SERS are shown for the 10 urinary biomarkers in Figures T1.2-T1.11. This includes the two muscle loss indicators, CRE and 3-MeHIS, the quantifiable bone loss indicators H-Pyd and H-dPyd, the non-quantifiable bone loss indicators HO-PRO and HO-LYS, and the stone formation indicators, UA, CaP, CaOx and CYST. During the Phase I program we focused on hydroxyproline as an indicator of bone loss, however, research into the chemical and metabolic reaction pathways associated with osteoporosis indicates that free and bound pyridinoline and deoxypyridinoline, associated with collagen cross-linking, are more quantitative indicators of bone loss. And they are present in urine. We were able to obtain the free forms of pyridinoline and deoxypyridinoline from Quidel Corporation, but not their bound form. Analysis of hydroxyproline is still important, and remained part of this study Table T1.3. Summary of Biomarker screening results: SERS-response on select chemistries in mg/L.

CRE 3-MeHis HO-PRO HO-LYS H-Pyd H-Dpd CaP CaOx UA CYST L1 1 1 neg 1000t dnt dnt 500 neg 500 1000 L2 1000 10 neg neg neg dnt 500 500 500 neg

L3 1000 1000 1000 neg 1.8 neg 1.8 500 500 500 neg

L4 neg neg 1f neg neg dnt neg neg neg neg

L5 neg 1000 neg neg dnt neg 1.8 500 500 500 1000

L6 1000 1000 neg neg dnt dnt 500 neg 500 neg

IEX Library L1sL3d L5 L1t L3 L5 L5 L2 L1 L1

LMC 0.1 0.001 dnt 0.01 0.018 1.8 1 1 0.05 0.1 Peaks 1421 1563 1534 1397 1393 1372 925 894 633 613

dnt=did not try, f = flow method, t = TMOS only, S = SPE, d = +PDMS



15

Table T1.4. Summary of Drug screening results: SERS-response on select chemistries in mg/L.

CLO ETI PAM ALE IBA RIS RAL HCT ALLO PEN SCOP PROM AM L1 100 1000 1000 100 10t 1 10 1000 10 1000 neg 1000 1000 L2 1000 1000 1000 100 neg 100 100 neg 0.1 1000 neg 1000 1000

L3 1000 1000 1000 1000 neg 1000 1000 100 1000 1000 neg 1000 1

L4 neg neg neg neg neg neg neg 0.01f neg 100 0.01f 0.01f 0.01f

L5 neg 100 100 1000 neg 100 1000 1000 500 neg neg dnt dnt

L6 100 1000 1000 1000 neg 1 1000 100 500 1000 neg dnt dnt

IEX Library L1 L3s L1 L1 L1t L5 L3d L1 L5 L1

LMC 0.01 0.01 0.01 0.01 0.01 0.001 0.01 1 0.001 0.01 dnt dnt dnt Peaks 674 644 639 647 1010 1034 1593 678 721 1110 999 1025 1578 dnt = did not try, f = flow method, t = TMOS only, S = SPE, d = +PDMS; Note: OxP (ALLO metabolite) LMC 0.01 mg/L on L5; PAM, IBA, ALE LMC 0.01 mg/L on both IEX and SPE with L1 (L1t for IBA)

Fig. T1.2. A) NRS and B) SERS of Creatinine on L1.

Fig.T1.3. A) NRS and B) SERS of 3-Methylhistidine on L1Note: 1-methyl histidine was measured in Phase 1, see Fig T5.2) .

A B

A B

N

N

O

NH2

OH

O

NH2

N

N

Fig. T1.5. A) NRS and B) SERS of Hydroxy-lysine on L1t (with HCl wash, and 2nd reduction step.

A B

OH

NH2

HO

OH2N

Fig. T1.4. A) NRS and B) SERS of Hydroxy-proline, 0.01 mg/L on gold L4.

O

OH

NH

HO

A B



16

Fig. T1.11. A) NRS and B) SERS of L-Cystine on L1.

A B

O

S

HO

HO

O

NH2

S

NH2

Fig. T1.6. SERS of H-Pyridinoline in 0.2M acetic acid A) 1.8 mg/L on L3; and B) L3 (chem2c, reported in Phase I) with acetic acid (SERS) subtracted.

Fig. T1.7. SERS of H-deoxyPyridinoline 1.8 mg/L on L5 (conditions same as in Fig. T1.6).

A B

O

HO

HO

O

NH2

NH2

HO

O

NH2

OH

OH

Fig. T1.9. A) NRS and B) SERS of Calcium oxalate on L2.

Fig. T1.8. A) NRS and B) SERS of Calcium phosphate on L2.

A B

A B

Ca+2

Ca+2

Ca+2

P

O

-O

O-

O-

PO

O-

-O

-O

O-

O

O

O-

Ca+2

Fig. T1.10. A) NRS and B) SERS of Uric acid on L1.

A B N

N NH

HN

O

OH

HO


17

The NRS and SERS are shown for the 13 drugs in Figures T1.12-T1.24. This includes the anti-bone loss drugs CLO, ETI, PAM, ALE, IBA and RIS), a selective estrogen receptor modulator, RAL, the anti-stone formation drugs HCT, PEN and ALLO, the anti-motion sickness drugs SCOP and PROM, and the anti-inflammation drug AM.

Fig. T1.12. A) NRS and B) SERS of Clodronate disodium on L1.

Fig. T1.13. A) NRS and B) SERS of Etidronate disodium on L1.

A B

A B

Cl

Cl

PHO

OH

O

P

HO

HO

O

CH3

OH

PHO

OH

O

P

HO

HO

O

Fig. T1.16. A) NRS and B) SERS of Ibandronate sodium on L1t.

Fig. 16 T1.17. A) NRS and B) SERS of Risedronate sodium on L1.

A B

A B

N

OH

PHO

OH

O

P

HO

HO

O

CH3CH3

OH

PHO

OH

O

P

HO

HO

ON

Fig. T1.15. A) NRS and B) SERS of Alendronate sodium on L1.

Fig. T1.14. A) NRS and B) SERS of Pamidronate disodium on L1.

A B

A B

NH2

OH

PHO

OH

O

P

HO

HO

ONH2

OH

PHO

OH

O

P

HO

HO

O


18

Fig. T1.19. A) NRS and SERS of Hydrochlorothiazide on B) L3, and C) 0.01 mg/L on gold L4.

A B C N

H

SNH

OO

Cl

S

O

O

H2N

Fig. T1.22. A) NRS and SERS of Promethazine HCl on B) L2, and C) 0.01 mg/L on gold L4.

A B C

S

N

CH3

NCH3H3C

Fig. T1.18. A) NRS and B) SERS of Raloxifene in MeOH on L2.

A B

Fig. T1.23. A) NRS and SERS of Scopolamine HCl on B) gold L4 (chem3a, from Phase I) and C) 0.01 mg/L on gold L4.

A B C

N

H

H

O OH

O

O

HO

S

OH

O

ON

Fig. T1.21. A) NRS and SERS of Penicillamine on B) L2, and C) 0.01 mg/L on gold L4.

A B C

O

HO

HS

NH2

H3C

H3C

Fig. T1.20. A) NRS and B) SERS of Allopurinol on L2.

A B

N

N NH

N

OH


19

Although the majority of primary target drugs in this study, such as the bis-phosphonate bone-loss drugs, are generally excreted unchanged in urine, other drugs metabolize, such as acetaminophen and allopurinol. The SERS (and NRS) of the metabolites of these two drugs, acetaminophen-glucuronide (AM-G) and oxipurinol (OxP), were also measured (metabolites from other drugs were not readily available). As shown in Figures T1.25 and T1.25, acetaminophen and its metabolite produce different SER spectra. ALLO is a xanthine oxidase inhibitor that lowers the level of uric acid in urine. Approximately 90% of ALLO is metabolized to OxP. ALLO is rapidly excreted in urine (T1/2 = 40 min), while OxP is excreted over a much longer period (T1/2 =14-30 hrs). The NRS and SERS for OxP are shown in Figure T1.26 (compare to ALLO Fig T1.20).

In addition to these 25 measured analytes, 25 additional chemicals that may be present in astronaut urine and could be potential interferents were measured (Table T1.5). This included five additional drugs, the pain reliever - acetylsalicylic acid (ASA, aspirin), representative sleeping aids – barbitol and phenobarbitol, and stimulants caffeine and Adderall (Figures T1.27-T1.30). The latter drug is a single entity amphetamine product combining the neutral sulfate salts of dextroamphetamine and amphetamine, with the dextro isomer of amphetamine saccharate and d,l-amphetamine aspartate monohydrate. Table T1.5. List of drugs, vitamins, and natural products of metabolism as interferents that may appear in urine.

Drugs Vitamins/Supplements Natural metabolites Acetylsalicylic acid (ASA) Vitamin A Lactic acid Glucose Barbital Vitamin E Hippuric acid Gluconic acid Phenobarbital Thiamine Nicotinic acid Cholesterol Caffeine Pyridoxamine Glutamic acid Estradiol Allderall Citric Acid Histidine Pregnane-diol 1-methylhistidine Theophyllene Cystine/cysteine Xanthene/Hypoxanthene

Fig. T1.24. Acetaminophen, A) NRS and SERS B) 0.1 mg/mL on L2, and C) L4 (gold).

A B C

HN

O

OH

A B

NH

O

OO

O

O

O

O

O

Fig. T1.25. A) NR and B) SERS of AM-G; 0.1 mg/mL on L2.

Allopurinol Oxypurinol Fig. T1.26. A) NRS and B) SERS of Allopurinol; C) NRS and D) SERS of Oxypurinol; 0.5 mg/mL on L5.

A B C D

N

N NH

N

OH OH

N

N

HO NH

N


20

2.600

0.000

0.200

0.400

0.600

0.800

1.000

1.200

1.400

1.600

1.800

2.000

2.200

2.400

1850350 500 750 1000 1250 1500 1750 Fig. T1.27. A) NRS and B) SERS of Acetylsalicylic acid. on L3 (Chem2c).

In addition to drugs astronauts also take vitamins (and supplements) to help prevent the negative effects of low gravity. For this reason we measured vitamins A and E, thiamine, pyridoxamine (B6), and citric acid, all of which are potential interferents in urine (Figures T1.31- T1.38).

Fig. T1.28. A) NRS of Barbituric acid, and SERS of B) Barbital, and C) Phenobarbital; 0.1 mg/mL on L3.

A B

HN

O

NH

O

O

Fig. T1.30. A) NRS and B) SERS of Adderall 18 (25 mg; active ingredient Dextroamphetamine). L2.

Fig. T1.29. A) NRS and B) SERS of Caffeine on gold L4.

NH2

N

NN

N

O

O

A B

A B

Figure T1.32. A) NRS and B) SERS of Vitamin-E on L5. Figure T1.31. A) NRS and SERS of Vitamin-A in MeOH on B) gold L4 and C) silver L2.

A B

A B C

OH O

HO

O O

OHO


21

1.000

0.000

0.100

0.200

0.300

0.400

0.500

0.600

0.700

0.800

0.900

1850350 500 750 1000 1250 1500 1750

2.100

0.600

0.700

0.800

0.900

1.000

1.100

1.200

1.300

1.400

1.500

1.600

1.700

1.800

1.900

2.000

1850350 500 750 1000 1250 1500 1750 Wavenumbers (∆cm-1)

Fig. T1.33. A) NRS and B) SERS of Thiamine on L2 (Chem2b).

Wavenumbers (∆cm-1) Fig. T1.34. A) NRS and B) SERS of Pyridoxamine on L1.

During the Phase I program we also measured several natural occurring biochemicals that appear in urine as the result of various metabolic processes. This included lactic acid, hippuric acid, and nicotinic acid. In addition, all of the amino acids are present in urine to some extent, and we have measured all of their SER spectra. But since these measurements are the focus of another SBIR program, here we only report glutamic acid since it has a high urine concentration, cystine and cysteine (Figures T1.39 and T1.40), and histidine (Figure T1.41). Cystine, composed of two cysteine amino acids, is of interest because the drug, PEN solubilizes cystine by displacing one of the cysteines as part of the anti-stone forming process and thereby releasing a free cysteine that ends up in urine. Both cystine and cysteine have unique SERS features (Figures T1.40.B and T1.40.C).

3.500

0.000

0.250

0.500

0.750

1.000

1.250

1.500

1.750

2.000

2.250

2.500

2.750

3.000

3.250

1850350 500 750 1000 1250 1500 1750

4.500

0.000

0.500

1.000

1.500

2.000

2.500

3.000

3.500

4.000

1850350 500 750 1000 1250 1500 1750 Wavenumbers (∆cm-1)

Fig. T1.37. A) NRS and B) SERS of Hippuric acid on L2.

Wavenumbers (∆cm-1) Fig. T1.38. A) NRS and B) SERS of Nicotinic acid on L3 (Chem2c).

Figure T1.35. A) NRS and B) SERS of Citric acid on L1.

A B

OH

HO

O

OH

O

O

HO

2.400

0.000

0.200

0.400

0.600

0.800

1.000

1.200

1.400

1.600

1.800

2.000

2.200

1850350 500 750 1000 1250 1500 1750

OH

OH

O

A B

Wavenumbers (∆cm-1) Fig. T1.36. A) NRS and B) SERS of Lactic acid on L1.

N

N

NH2

N+

SOH

Cl-

A B

rela

tive

inte

nsity

N

NH2

OH

OH

A B

rela

tive

inte

nsity

NH

O

O

HO A B re

lativ

e in

tens

ity

N

O

OH

A B re

lativ

e in

tens

ity


22

7.500

0.000

0.500

1.000

1.500

2.000

2.500

3.000

3.500

4.000

4.500

5.000

5.500

6.000

6.500

7.000

1850350 500 750 1000 1250 1500 1750

Wavenumbers (∆cm-1) Fig. T1.39. A) NRS and B) SERS of Glutamic acid on L1 (Chem1b).

Wavenumbers (∆cm-1) Figure T1.40. A) NRS and B) SERS of Cystine on L1, and C) NRS and D) SERS of Cysteine on L3 (chem2c).

0.800

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0.250

0.300

0.350

0.400

0.450

0.500

0.550

0.600

0.650

0.700

0.750

1850350 500 750 1000 1250 1500 1750

Wavenumbers (∆cm-1) Fig. T1.41. NRS and B) SERS of Histidine on L3 (Chem2c).

Fig. T1.42. A) NRS and D) SERS of 1-MeHIS (Nτ); on L1t with HCl wash.

Histidine is included in this study since it is the base structure for 3-methyl histidine. For the same reason we also measured 1-methyl histidine because there were some uncertainty reported in literature as to the position of the methyl group. Nevertheless, as can be seen in Figures T1.41 and T1.42, all three histidines produce unique spectra. The biochemical interferents studies are important health indicators in their own right, specifically glucose and cholesterol. Glucose is an important indicator of diabetes (although blood glucose better represents the condition), but its SER spectrum has been difficult to obtain (as indicated Phase I Final Report Figure 4.17). We made additional attempts to measure glucose using many of the sol-gel chemistries. A representative SER spectrum and the NRS of a solution are shown in Figure T1.43. Only three peaks are observed with significant intensity, a weak peak at 845 cm-1, a strong peak at 895 cm-1, and a broad peak at 1410 cm-1. These peaks are tentatively assigned to a C-C stretch, O-C-H bend, and a C-C-H bend, respectively, based on the NRS peak assignments. However, the paucity of peaks suggested that only part of the molecule was being enhanced (due to surface proximity or selective plasmon field interaction) or it may be a molecular fragment produced by photo-degradation. To test the latter, we measured the oxidation product of glucose, gluconic acid, which can also be produced by photo-degradation. As can be seen, the SERS of gluconic acid is extremely similar to glucose (Figure T1.43). The only difference is the absence of the weak 845 cm-1 peak. To further clarify the glucose SER spectrum, we also measured glucose using 1064 nm laser excitation (as well as using reduced powers). As Figure T1.44 shows, this glucose SERS looks virtually identical to gluconic acid. However, the fact that the spectrum is present at all powers (down to 20 mW), suggest that photo-oxidation is not occurring. Further measurements are required to clarify this point.

A B C D

O

OH

NH2

HO

O

A B re

lativ

e in

tens

ity

rela

tive

inte

nsity

OH

O

NH2

N

N

A B re

lativ

e in

tens

ity

HN

NNH2

OH

O

A B


23

Cholesterol is normally measured in blood since it is involved in plaque build-up on artery and vein walls, but in certain pathological conditions cholesterol crystals can be found in acidic to neutral urine. The SERS of cholesterol was obtained on both gold- and silver-doped sol-gels as shown in Figure T1.45. We also measured the hormones estradiol and pregnane-diol (Figures T1.46 and T1.47). It should be noted that pregnane-triol (as proposed for in Phase I), testosterone and spermine were also measured, but were found to be inactive on the initial sol-gel chemistries tried, and measurements in Phase II were not pursued.

2.400

0.200

0.400

0.600

0.800

1.000

1.200

1.400

1.600

1.800

2.000

2.200

1850350 500 750 1000 1250 1500 1750

Figure T1.45. A) NRS and SERS of Cholesterol on B) L4 (chem3b), and C) L2.

Fig. T1.46. A) NRS and B) SERS of Estradiol on L2 (Chem 2b).

5.000

0.000

0.500

1.000

1.500

2.000

2.500

3.000

3.500

4.000

4.500

1850350 500 750 1000 1250 1500 1750

Wavenumbers (∆cm-1) Fig. T1.47. A) NRS and B) SERS of Pregnane-diol on L2.

Figure T1.48. A) NRS and B) SERS of Xanthine; C) NRS, and D) SERS of Hypoxanthine; on L2.

Figure T1.43. A) NRS and B) and C) SERS of glucose. Conditions: A) 1g/mL in HPLC water B) 1 mg/mL in HPLC water on L1, 785 nm, and C) 48 mW of 1064 nm, 1-min.

A B C

Figure T1.44. A) NRS and SERS of gluconic acid. Conditions: A) 50 wt% in water, 1 mg/mL in HPLC water on L1.

A B

845 895 1410

A B C

OH

OH

H

HH

A B

rela

tive

inte

nsity

OH

OH

OH

OH

O

OH

O

O

H H

H

rela

tive

inte

nsity

N

N

N

N

O

O

NH

N

NH

N

O

A B C D

A B

O OH

OH

OH

OH

OH

OH


24

The enzyme, xanthine oxidase, catalyzes the oxidation of hypoxanthine to xanthine, which is further converted to uric acid. Since allopurinol inhibits this process, it also influences the relative amounts of hypoxanthine, xanthine, and uric acid in urine. As Figures T1.48 and T1.49 shows, the xanthenes, and theophyllene (which is produced via a similar metabolic process) produce unique SER spectra. As part of this program, we evaluated the ability of four spectral library search routines to identify the SER spectra of the biomarkers and drugs. The Euclidean Distance Algorithm (EDA), the Absolute Value Algorithm (AVA), the Least Squares Algorithm (LSA), and the Correlation Algorithm (CA) have been successfully applied to Raman spectra, and we incorporated them into a LabVIEW program. These four different search algorithms are summarized in Figure T1.50. Euclidean Distance Algorithm (EDA) Absolute Value Algorithm (AVA) Least Squares Algorithm (LSA)

HQI 2 1Lib Unkn⋅

Lib Lib⋅ Unkn Unkn⋅⋅−⋅

Correlation Algorithm (CA)

HQI 1Libm Unknm⋅( )2

Libm Libm⋅( ) Unknm Unknm⋅( )⋅−

Where: In all cases, Lib is the library entry being searched and Unkn is the unknown sample spectrum. Each method scores the spectral match in terms of a hit quality index (HQI), where the best score or match is 0 (Lib = Unkn) and the worst score or match is at higher values. Initially, we tested the algorithms using a very limited library composed of 7 biomarkers and 9 drugs. Spectra different from that used in the library were used for these tests (the HQI scores were presented in Table 3 of Quarterly Report #4). It was found that the best results were obtained by 1) subtracting the glass background produced by the capillary from both the sample and the spectra in the library, and 2) taking the first derivative. Smoothing the data improved scores, but not significantly. In all cases the EDA and CA methods resulted in a positive match (after this pretreatment). However, the CA method gave the best overall results for identifying each chemical (low HQI score) as well as discriminating against chemicals (high HQI scores). This result proved correct even when we added all of the chemicals studied in this program (biomarkers, drugs, metabolites, and potential interferents) plus all of the basic amino and nucleic acids (a total of 102 SER-active chemicals). As an important test, the spectrum obtained for a 1 microg/L 3-MeHIS sample pre-concentrated using an ion exchange column was examined using the Correlation Algorithm. As shown in Figure T1.51, this biomarker was correctly identified with a very low HQI of 0.069. Furthermore, the next closest match (the LabVIEW program ranks closest 10) is the structurally similar amino acid histidine (HIS), which nevertheless has a

A B

O

N

N

N

HN

O

Fig. T1.49. A) NRS and B) SERS of Theophyllene on L1.

HQI1

n

i

Libi Unkni−∑=

nHQI

1

n

i

Libi Unkni−( )2∑=

n

Libm Libn

n

i

Libi∑=

n− Unknm Unkn

n

n

i

Unkni∑=

n−

Figure T1.50. Equations for the spectral library search algorithms.


25

much higher HQI score of 0.434. This is not unexpected as distinct differences observed in the SERS (Fig. T1.52).

In addition to these measurements, the search routines were challenged by using SERS of analytes at different pH, on different SERS-active sol-gels, and with or without an acid treatment (i.e. HCl wash). As demonstrated in Phase I, the spectra of these chemicals are constant between pH 4 and 8, and only if the pH was outside this range was a sample misidentified (see Report # 5). In general, the alkoxide chemistry of the sol-gels produces insignificant changes in the SER spectra. In fact, only in a few cases does the acid wash or metal (i.e. silver vs gold) result in significant spectral differences. For chemicals that had such spectral differences, proper identification occurred if both spectral versions were in the library. We also evaluated S-Quant, a classical least squares algorithm, to determine chemical composition of mixtures. This program first searches the library for the best spectral match, and then this spectrum is subtracted from the original spectrum to produce a new spectrum, the residual spectrum. The search routine then uses this residual spectrum as the unknown. The process is repeated until the noise throughout the residual spectrum is uniform (no more peaks). The program then creates a spectrum composed of each of the matched spectra. The contribution of each spectrum is varied (weighted) until the composite spectrum matches the measured spectrum, as defined by a residual consisting of a flat baseline. We evaluated this program using a simple 50/50 mixture of Allopurinol and it’s metabolite Oxypurinol (both at 0.25 mg/mL, Figure T1.53), since drugs and their metabolites may not be easily separated using ion exchange (or other chromatography). It must be stated that these two chemicals can be identified by their unique non-overlapping peaks at 717 and 651 cm-1, respectively. The results of the S-Quant program are shown in Figure 59D. The unknown spectrum was fit with equal contributions of Allopurinol and Oxypurinol, at 56.0% and 55.8% respectively. The total is not 100%, because the program is attempting to fit the noise in the spectrum with 1-2% of other chemicals (some negative) to achieve a flat baseline. In other words, the program is correctly indicating a 50/50 mix of the two chemicals. Since all of the library spectra are 1 mg/mL concentrations, this program only gives relative concentrations. Actual concentrations would require a calibration curve for each chemical.

Figure T1.52. SERS of A) 1 microg/L of 3-MeHIS as the unknown sample, and B) 1 mg/mL of HIS from the spectral library.

A B

Figure T1.51. Display of Spectral Library Search and Match software. The program ranks the best matches (lowest scores) and overlays the unknown and matched spectra for visual comparison (SERS reference library = 102 chemicals).

OH

O

NH2

N

N

OH

O

NH2

N

N


26

Questions to be answered? Are all of the 24 chemicals SERS-active? All of the chemicals that we were able to obtain were SERS-active. What is the preferred sol-gel for each bio-indicator and target drug? Six sol-gel libraries allowed measuring all of the target analytes as summarized in Tables 4.3 and 4.4. Are there potential interferants? Yes, such as histidine for 3-methyl histidine. How well does the spectral match software identify each? It has proven exceptional, correctly identifying any of the target analytes in a library of over 100 chemicals that could potentially be in urine. How well does it identify a chemical not in the library? The software ranks all of the chemicals based on how well their spectra match the measured sample. If there is a close match (i.e. and HQI score less than 0.5) then the unknown is probably very similar in structure. If no score is below 0.75, then the chemical is not in the library and likely rather different than any of the library chemicals. Task 2 – Chemical Selectivity Development. The overall objective of this task was to refine the ability of the 4 basic SER-active sol-gels developed in Phase I to selectively extract biochemicals and drugs present in human urine, and enhance their Raman spectra to improve sensitivity. This was accomplished by measuring SERS-activity as a function of flow time for the 25 analytes using the 6 chemically selective sol-gel libraries selected in Task 1. As stated, the Task 1 results indicated that 6 chemically selective sol-gels allowed measuring the 25 target analytes at 1 mg/mL in static measurements. During the Phase I program we determined that flowing the analytes through the sol-gel capillaries improved sensitivity if the sol-gel extracted the analyte, effectively increasing the concentration. In this task, the biomarkers were prepared at 1 mg/L, while the drugs were prepared at 10 microg/L to determine if this approach could achieve the required concentration ranges for analysis. The ability of the sol-gels to extract the target analytes was investigated by measuring the SERS signal as the sample flowed through a capillary as a function of time. The apparatus is shown in Figure T2.1. In one configuration Figure T2.1A), a peristaltic pump (VWR model 54856-070, West Chester, PA) was used to cycle the sample (20 mL) through the capillary at a rate of 1 to 2.5 mL/min until a signal was observed, then a 3-way valve was used to switch the stream to a solvent, either water or methanol to flush the analyte out of the sol-gel. SER spectral collection was initiated when the sample solution entered the capillary and spectra were collected continuously (20 sec/spectrum) for ~5-30 minutes. Early on it was found that the sol-gels that yielded the most sensitive signals were those in which the analyte was bound irreversibly. Consequently, the solvent flush was essentially unnecessary, and instead, a syringe pump (Sage model 341B, Thermo Electron, Waltham, MA, Figure T2.1B) was used to monitor the time required to generate a signal. Typically, a 50 mL syringe filled with a 20-50 mL sample was passed through the sol-gel filled capillary at a rate of 1 to 10 mL/min (typically 2 mL/min). It is worth noting that sol-gel plugs of the MTMS based chemistry (L2) could handle flow rates greater than 10 mL/min, while those using the TMOS and ODS based chemistries (L1 and L3 respectively) became detached at rates greater than 2.5 mL/min. This limitation was overcome to some degree by adding the polymer component (PEG or PDMS) to the L1 sol-gel to produce L5 and L6. It also improved sensitivity.

Figure T1.53. SERS of A) 50/50 mixture of Allopurinol and Oxipurinol (0.25 mg/mL each), and pure B) ALLO and C) OxP. D) S-Quant Results (part of LabView front panel, see Report #8).

A B C

D


27

Fig. T2.1. Photographs of apparatus used for flow measurements. A) Peristaltic pump with 3-way valve to flow sample until detection, then solvent to remove (20 mL vial reservoirs). B) Syringe pump for continuous flow to monitor signal increase due to chemical extraction by the sol-gel (10-50 mL sample in 50 mL syringe). The first representative biomarker tested (during Phase I) was 1-MeHis (mislabeled as 3-MeHis by the manufacture, see Fig T5.2). A 1 mg/L solution was prepared and flowed at 2 mL/min through a capillary containing a 2 cm plug of L1 (polar sol-gel). As can be seen in Figures T2.2 and T2.3, the spectral intensity (based on the 1564 cm-1 peak height) reaches 80% of the maximum in the first 20 seconds. A 10 microg/L sample was also measured, and although a signal was perceptible after just 5 minutes, it was somewhat unstable. Similar experiments were performed using 1 mg/L samples on the non-polar sol-gels L2 and L3, and in both cases, the 1564 cm-1 peak was detected, but at a lower intensity. CRE was also measured as it was flowed through an L1-filled capillary. The signal for a 1 mg/L samples slowly increased and became significant after 12 minutes (Figures T2.4 and T2.5). Next, the bone-loss indicator, HO-PRO was tested (we did not have sufficient quantities to test H-Pyd). Initially, this biomarker, active on L4-filled capillary (gold-doped) was difficult to measure. We found that a second reduction step dramatically improved the overall sensitivity, typically by a factor of 100. This double reduction allowed measuring 1 mg/L HO-PRO. (It also allowed detecting many of the drugs at 0.01 mg/L (10 microg/L) for HCT, PEN, SCOP, PROM and AM that were nominally active on gold.) Here a 1 mg/L HO-PRO sample was flowed through a doubly reduced L4 capillary. The sample signal increased rapidly within 1 minute, as shown in Figure T2.6.

Syringe Pump Laser Spot on Capillary

1564

cm

-1 b

and

inte

nsity

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00

Fig. T2.3. SERS of 1-MeHIS on L1 after flowing A) 100-sec (pt.5), B) 80-sec (pt.4), C) 60-sec (pt.3), D) 40-sec (pt.2), as in Fig.4.61

A B C D

XY Stage

3-way valve

Peristaltic Pump

Sample Solvent A B

Time (min) Fig. T2.2. Concentrating 1-MeHIS on L1 as a function of flow. Conditions: initial concentration was 0.001mg/mL, and flow rate was 2 mL/min, spectra: 100 mW of 785 nm, 20-sec each.


28

As a final example, uric acid was measured during flow through an L1 filled capillary. Here the signal increased slowly, but after 7 minutes, the laser spot on the capillary was moved and a significant signal appeared, indicating that the laser was degrading the sol-gel (Figure T2.7)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0 2 4 6 8 10 12 14

Raman Shift, cm-11850 350 500 750 1000 1250 1500

The first drug tested using flow to concentrate the analyte was raloxifene (Phase I). Initially, a 0.001 mg/mL sample was flowed at 2 ml/min through an L1 capillary, and the SERS appeared after 1 minute, reaching a maximum in just 2 minutes, as shown for the1166 cm-1 peak Figure T2.8 (baseline at 1200 cm-1 subtracted). Since the desired sensitivity for raloxifene is considerably lower (~ 10 microg/L) the flow experiments were repeated using 100 microg/L. Again, the SER spectrum is detected, but after longer flow times (Figure T2.9).

1165

cm

-1 b

and

inte

nsity

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0 1 2 3 4 5 6

1165

cm

-1 b

and

inte

nsity

Fig.T2.9. SERS of RAL on L1 A) 1 mg/L after 2-min (see Fig. T2.8), and B) 0.1 mg/L after 5-min.

Time (min) Fig. T2.8. Concentrating RAL on L1 as a function of flow. Initial concentration was 1 mg/L, 100 mW of 785 nm, 20-sec each.

Fig. T2.7. SERS of UA on L1 after 7 minutes of flow. Conditions: 1 mg/L in HPLC water, flow rate 1 mL/min, 100 mW of 785 nm, 20-sec.

643

cm-1

Pea

k A

rea

Time (min) Fig. T2.4. Concentrating CRE as a function of flow on L1 with HCl wash. Conditions: initial concentration was 0.001 mg/mL in HPLC water and flow rate was 1 mL/min, spectra: 100 mW of 785 nm, 20-sec each.

Fig. T2.5. SERS of CRE (pt. 29) after 10 minutes of flow. Conditions as in Fig. 4.63.

Fig. T2.6 SERS of HO-PRO on L4 A) after 4-min flow B) 20-sec flow. Conditions: 1 mg/L in HPLC water, flow rate 1.5 mL/min; spectra: 80 mW of 785 nm, 60-sec.

A B


29

The ability to detect the other drugs at microg/L concentrations using the flow technique was also examined. The following drugs represent the variety of results. The SERS were measured for a 5 microg/L ALLO sample as it flowed through an L2 filled capillary. At this low concentration, more time (over 12-min) was required to obtain a detectable signal (721 cm-1 peak, Figures T2.10 and T2.11). In the case of RIS, 20-min were required for a 10 microg/L sample flowed through an L1 capillary (Figures T2.12 and T2.13). It was also noted, that moving the laser position along the capillary dramatically increased the signal intensity, suggesting that either a relatively inactive spot was originally chosen, or the laser caused sol-gel degradation. In the case of ETI, again ~12 minutes were required to detect the SERS, but shortly thereafter the signal began to decrease (Figures T2.14 and T2.15). This also suggests that the sol-gel or the analyte may be degrading. In all cases efforts continued to improve the uniformity and stability of the sol-gels, principally by the incorporation of the polymers into the alkoxides.

0.000.010.020.030.040.050.060.070.080.090.10

0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 16.00

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

0.00 5.00 10.00 15.00 20.00 25.00

721

cm-1

ban

d in

tens

ity

Time (min) Fig. T2.10 Concentrating ALLO as a function of flow on L2 Conditions: initial concentration was 0.000005 mg/mL in HPLC water and flow rate was 2.5 mL/min, spectra: 100 mW of 785 nm, 20-sec each.

Fig. T2.11. SERS of ALLO (pt. 34) after 12 minutes of flow Conditions: 0.000005 mg/mL on L2 in HPLC water, flow rate of 2.5 mL/min, 100 mW at 785 nm, 20-sec.

Time (min) Fig. T2.12. Concentrating RIS as a function of flow on L1. Conditions: initial concentration was 0.00001 mg/mL in HPLC water and flow rate was 2.5 mL/min, spectra: 100 mW of 785 nm, 20-sec each.

1033

cm

-1 b

and

inte

nsity

Fig. T2.13. SERS of RIS A) (pt. 53) after 20 minutes of flow, and B) (pt. 63) on new spot. Conditions: 0.00001 mg/mL on L1 in HPLC water, flow rate of 2.5 mL/min, 100 mW at 785 nm, 20-sec.

A B


30

0.000.020.040.060.080.100.120.140.160.18

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00

As described in the proposal, flow could be mimicked by “pistoning” the sample back and forth through the sol-gel to concentrate the analyte. This would allow the use of a syringe to manually manipulate the sample, so that significant urine samples were not required. To perform these experiments, a syringe containing 100-500 microL of sample was pushed back and forth through the sol-gel 5 times (10 passes) and a spectrum recorded. A typical example is shown for RIS in Figure T2.16. As can be seen, the LMC was improved by a factor of 10 compared to static measurements. In general, the pistoning approach allowed measuring samples to 1 mg/L, suggesting that it is a viable approach for biomarkers, but NOT for the drugs. The results for this task are summarized in Tables T2.1 and T2.2. Note that most of the biomarkers could be detected at physiological concentrations by pistoning at 1 mg/L, while most of the drugs could be detected by flowing at 10 microg/L (indicated in red). Table T2.1. Summary of Biomarker flow and piston results (vs static): LMC in mg/L on sol-gel libraries.

CRE 3-MeHis HO-PRO HO-LYS H-Pyd H-Dpd CaP CaOx UA CYST Static 1.0

L1 1.0 L1

100 L4

1000* 18 L3

dnt 500 L3

500 L2

500 L2

1000 L1

Piston 1.0 L1

1.0 L1

10.0 L4

neg 1 L1

1.8 L3

dnt 1.0 L3

5.0 L6**

5.0 L2

neg 1 L1

Flow 1.0 L1

0.01 L1

1.0 L4

neg 1 L1

0.9 L3

dnt 1.0 L3

1.0 L6**

1.0 L2

1.0 L1

* = sol-gel chemistry with TMOS only, ** = sol-gel chemistry 2a with PDMS

Table T2.2. Summary of Drug flow and piston results (vs static): LMC in mg/L on sol-gel libraries.

CLO ETI PAM ALE IBA RIS RAL HCT ALLO PEN SCOP PROM AM Static 100

L6 100 L5

100 L5

100 L1

10* 1 L1

10 L1

100 L6

0.1 L2

100 L4

1.0 L4

1.0 L4

1.0 L3

Piston neg1 L1

neg1 L1

neg1 L1

1.0 L6

neg1 L1

0.1 L1

neg1 L1

neg1 L3

0.01 L2

neg1 L2

1.0 L4

1.0 L4

1.0 L3

Flow 1.0 L2

0.01 L1

neg1 L1

0.01 L6

neg1 L1

0.01 L1

0.01 L1

0.01 L4

0.005 L2

0.01 L4

0.01 L4

0.01 L4

0.01 L4

* = sol-gel chemistry with TMOS only

Time (min) Fig. T2.14. Concentrating ETI as a function of flow on L1. Conditions: initial concentration was 0.00001 mg/mL in HPLC water and flow rate was 2.5 mL/min, spectra: 100 mW of 785 nm, 20-sec each.

Fig. T2.15. SERS of ETI (pt. 32) after 10 minutes of flow Conditions: 0.00001 mg/mL on L1 in HPLC water, flow rate of 2.5 mL/min, 100 mW at 785 nm, 20-sec.

647

cm-1

ban

d in

tens

ity

Fig. T2.16. SERS of RIS in an L1 capillary before and after pistoning (10 passes) at 0.1 mg/L. Conditions: 100 mW at 785 nm, 20-sec.



31

Questions to be answered? Which sol-gels provide irreversible adsorption of the bio-indicators and target drugs and SER-activity? This data is summarized in Tables T2.1 and T2.2. What are the estimated LODs? Instead of calculating LODs, we improved sensitivity sufficiently to measure the analytes at the required physiological concentrations (again see the same tables). Can the spectral deconvolution software identify each urine component (bio-markers and drugs) on each sol-gel? Yes, see Task 1. Task 3. Component selection and testing. The overall goal of this task was to design a lab-on-a-chip that can be used to analyze chemical components present in human urine by SERS. This was accomplished by performing a series of tests to determine the components and functionality required for the lab-on-a-chip. A preliminary design illustrating the required functionality that such a chip should have was presented and discussed in the Phase II proposal. That design and discussion are repeated here verbatim, followed by the experiments performed to select the components. 1. A sample compartment will be used to accept a liquid sample

(see components in Fig. T3.1). 2. The urine sample will be drawn through a micron filter to

remove any entrained particles. 3. The sample will continue through an inorganic extraction

material (ion retardation resin) that will remove inorganic salts. 4. The aqueous sample will be extracted with a polar solvent

(dichloromethane). Neutral organic species (drugs) will be extracted into the organic phase. Note that this step will require modifications for application in a microgravity environment.

5. The organic phase will be directed into a series of SER-active sol-gels designed to selectively extract the target bio-indicators and drugs by type (Set 1). This is NOT a chromatographic style separation. A) A very-weakly-polar (essentially non-polar) silver-doped sol-gel will extract non-polar-negative drugs/ biomarkers (NP-neg), but pass the other chemicals. B) A weakly-polar gold-doped sol-gel will extract weakly-polar-positive species (WP-pos), but pass other chemicals. C) A weakly-polar silver-doped sol-gel will extract weakly-polar-negative species (WP-neg), but pass other chemicals. D) A negative-polar silver-doped sol-gel will extract polar-negative species (P-neg). As an example of selectivity, we have seen that scopolamine and hydroxyproline are most active on electronegative gold, and that alendronate and 3-methyl-histidine are most active on electropositive silver (see Fig. T3.2).

Fig. T3.1. Flow diagram used to define separation components.

100ml Tank

Filter

Ion Retardant

Extract Aq/Org

pH

SetOne

Cation Exchange

SetThree

SetTwo

Waste

Org Aq

aa

bb

NaOH

Figure T3.2. SERS 1mg/ml 100 mW, 1min, 785 nm A) ALE, Ag-TMOS/MTMS , B) 3-MeHIS, Ag-MTMS, C) HO-PRO, Au-TMOS, D) SCOP, Au-TMOS/MTMS.

A B C D

D C B A

Figure T3.3. SERS TMOS/MTMS 100 mW, 1-min, 785 nm A) Reconstituted urine, B) reconstituted urine doped with 0.001 mg/mL of 3-MeHIS and RAL in a 50:50 mixture, C) RAL extracted from organic phase (dichloromethane) component 5, D) 3-MeHIS extracted off cationic exchange column (component 9).



32

6. The aqueous phase will be directed into a chamber, where the pH will be adjusted with 1M HCl to a final pH of 1.0 to ensure complete protonation.

7. This pH adjusted aqueous sample will enter into a cation exchange column. The protonated species will strongly adsorb onto the material, while the basic/neutral species will quickly pass through.

8. These basic/neutral species will enter into a series of SER-active sol-gels designed to selectively extract the target chemicals by type (Set 2). Set 2 follows a similar sequential sol-gel configuration as described for Set 1 above.

9. A NaOH gradient mobile phase from 0.1 M to 1.0 M will then be used to elute off the remaining species that are adsorbed on the column. Species elute off the column in order of increasing PKa/pI values (i.e. as pH increases due to increasing NaOH concentration, the protonated species will elute when the pH equals/exceeds their respective pKa/pI values. Each fraction is subsequently directed into the appropriate sol-gel (Set 3).

10. The feasibility of this extraction, separation, and detection method to be incorporated into our proposed lab-on-a-chip is demonstrated in Figure T3.3, where a lyophilized male urine sample (Sigma-Aldrich) was reconstituted with distilled water and doped with 3-MeHIS and RAL.

11. To optimize the sensitivity, the solution will be “pistoned” in and out of the sol-gel region numerous times. The Phase I data suggest that sensitivity can be improved by up to 1000 times. This coupled with 532 nm laser excitation suggest that sensitivity at the part-per-trillion level can be achieved (see below).

The following basic experiments were performed to evaluate the use of a filter and the value of an organic solvent in the above flow diagram. Since urine contains many large MW molecules and numerous salts, sometimes as particulate mater, it is necessary to include a filter to remove these substances. A saturated solution of uric acid was prepared and measured in a SERS-active capillary before and after filtration. A 0.2 µm pre-cut 13 mm Nylon 66 membrane filter (in a filter holder) was used to remove the particulate matter (Figure T3.4). As can be seen the filtrated sample yields a better quality spectrum (more pronounced peaks and less noise). It was also found that all of the samples could be passed through this filter without diminishing signal, including urine samples at various pH, as well as temperature (samples became turbid at room temperature).

Fig. T3.4. A) Photograph of syringe and in-line Nylon 66 membrane particle filter and saturated uric acid solutions before and after filtration. SERS of UA B) before and C) after filtration in L2-filled capillaries. The role of the organic phase was to extract non-polar drugs and possibly biomarkers into this phase for SERS measurements, with the goal of reducing the complexity of the spectra analysis. After reviewing the solubility properties of the 25 target analytes and performing a few experiments, it was realized that only Raloxifene fell into this category (as shown in Figure T3.3). Since this drug also dissolves in water, the organic solvent extraction step is not necessary and it was eliminated. The next series of experiments examined the chemical composition of urine (simulated, reconstituted, and real) in terms of the Raman and SER spectra, how it and its major components change with pH, and how the proposed ion retardation and ion exchange filters can be used to remove unwanted urine components and separate the target analytes. The major components of urine: urea, creatinine, uric acid and lactic acid, and lyophilized urine were purchased from Sigma-Aldrich. Each of these four urine components as pure solids produce distinctive Raman spectra (Figure T3.5), but only the urea produces a perceptible Raman signal in either simulated (urea 20 mg/mL, creatinine 1.4 mg/mL, uric acid 0.15 mg/mL and lactic acid 0.2 mg/mL) or lyophilized urine (reconstituted as 1g/30

A B C

Before After

Nylon Filter



33

mL water, pH = 5.67, Figure T3.6). In contrast, only uric acid and creatinine produce SER spectra at neutral pH (Figure T3.7). Urea does not appear to produce a SER spectrum under any condition, while lactic acid requires a very acid pH (see below). Furthermore, it is found that the SER spectra of simulated, reconstituted, and real urine samples are dominated by uric acid with some contribution from creatinine (Figure T3.8).

As part of the Phase I study, the pH dependence of creatinine, uric acid and lactic acid were studied in detail. In each case, stock solutions of the analyte were prepared at 1 mg/mL and then pH adjusted using HNO3 or NaOH (no buffers, verified by pH electrode), and then for each pH a sample was drawn into a separate SER-active capillary for measurement. For creatinine, samples were prepared from pH 11 to 3, and their spectra measured (10.8, 7.5, 6.9, 5.9, and 4.5 shown in Fig. T3.9A). The SER signal intensity was good at neutral pHs, but degraded at 4.5 and 10.8. It was noted that the peak at 614 cm-1 decreased with increasing pH value, while peaks at 675 and 1740 cm-1 increased, and bands at 850, 930, and 1420 cm-1 stayed relatively constant. A plot of the 614, 675 and 1740 cm-1 peak intensities divided by the 1420 cm-1 peak intensity as a function of pH is shown in Fig T3.9B. A plot of the pH dependence for each of the ion concentrations based on the pKa’s shows that the 614 cm-1 peak corresponds to the cation species, and the 675 and 1740 cm-1 peaks correspond to the neutral species. It is important to note that in the pH range of 5-9, which encompasses the urine pH range (5.5 to 7.5), the creatinine SERS spectrum does not change.

Fig. T3.6. NRS A) Urea (20 mg/mL), B) Simulated urine (see text), and C) Reconstituted urine (10,000 mwt cutoff), Conditions: 290 mW at 785 nm, 10-min.

A B C

A B C D

Fig.T3.5. NRS of Urine components A) Urea, B) Creatinine, C) Uric acid, and D) Lactic acid. Conditions: pure solids, 290 mW at 785 nm, 10-min.

Fig. T3.8. SERS of A) Simulated urine on L1, B) Reconstituted urine on L3, C) Real male urine sample (from volunteer at RTA) on L1, and D) Reconstituted urine on gold L4. Conditions: as prepared in Fig. T3.6.

Fig. T3.7. SERS of Urine components. A) Urea on L3, B) Creatinine on L1, C) Uric acid on L1, and D) Lactic acid on L1, Conditions: 1 mg/mL (UA 0.5 mg/mL). Note: all appear to be inactive on gold L4 (not shown).

A B C D

A B C D

O

H2N NH2

N

N

O

NH2

OH

OH

O

N

N NH

HN

O

OH

HO


34

Uric acid showed little pH dependence as shown for spectra collected at pHs of 9.10, 7.41, 6.05, 5.25, and 4.08 (Fig. T3.10). The only indication of a change in molecular species as the pH transitions the pKa of 5.4 is a slight change in the peak at 595 cm-1, which appears to be absent at pH of 4.08. It was noted that at basic pHs (near and above the other pKa of 10.3) the solubility of uric acid in water was higher. Lactic Acid samples were prepared from pH 11 to 3, and their spectra measured (9.7, 5.6, 4.4, and 2.9 shown in Fig. T3.11). Lactic acid is only SER-active in the neutral form below the pKa of 3.08 and consequently will not be observed in urine at relevant physiological pH’s.

This data suggests that lactic acid will not interfere with measurements of biomarkers or drugs at physiological pHs, but creatinine and uric acid will. Although it may be possible to remove their spectra contributions, this will be insufficient, since their nominally high concentrations in urine are likely to block the target analytes from reaching the SER-active metal. It is clear that these urine components must be removed from the sample in order to perform analysis of the target analytes. As proposed, an ion retardation resin was examined to determine if it would remove creatinine and uric acid. A sample of reconstituted urine at pH 5.7 was pH adjusted to 4.6, and 8.7 to produce 3 samples covering the normal pH range of urine. The SER spectra for the 3 samples were measured before and after passing through a 5 mL disposable glass pipette packed with ~1 mL volume of a ion retardation resin (AG 11A8 by BioRad, MA). At pH 4.6 the SER signal is diminished, while at pH 5.7, uric acid dominates the spectrum. At pH 8.7 the uric acid signal is slightly diminished with a trace of creatinine present. However, in all 3 cases, the ion retardation resin does not appear to change the spectra, and certainly does NOT remove the uric acid.

Wavenumbers (∆cm-1) Fig. T3.10. UA SERS pH dependence on L3 (chem2c), 0.5 mg/mL. 100 mW, 785 nm, 1-min.

9.10 7.41 6.05 5.25 4.08

rela

tive

inte

nsity

Wavenumbers (∆cm-1) Figure T3.11. SERS of 1 mg/mL LA on L3 (chem2c) at pH’s indicated; 100 mW, 785 nm, 1-min.

9.7 5.6 4.4 2.9

rela

tive

inte

nsity

0

0.001

0.0020.003

0.004

0.005

0.006

0.0070.008

0.009

0.01

0 2 4 6 8 10 12 14

pH

Con

cent

ratio

n [M

]

Creatinine++ CreatinineCreatinine+

pK2 =9.20pK1 =4.83B A

10.8 7.5 6.9 5.9 4.5

1740

614

Wavenumbers (∆cm-1) Figure T3.9. A) SER spectra of 1 mg/mL CRE at pHs indicated (100 mW 785 nm, 1-min, L3 (chem2c)). B) Plot of 614 ( ), 675 ( ), and 1740 cm-1 (■), normalized band intensities as a function of pH representing CRE++, CRE+ and CRE, respectively. Concentrations of CRE++, CRE+ and CRE based on pKa’s as a function of pH are


35

Fig.T3.14. SERS of a 1:1 mixture of SCOP and SCN on L4. A) After and B) before passing through ion-retardation column. On separate L4 capillaries.

Although the focus of the last experiment was to determine if the ion exchange resin could remove creatinine and uric acid, it also was included as a necessary component to remove dissolved salts that the filter might pass, particularly NaCl and KCl. Such salts at high concentration can potentially alter the SERS response through surface-deactivation or particle aggregation. To test the effectiveness of the ion retardation resin to eliminate such salts, a 1 ml solution containing 0.5 mg/mL of SCOP and KSCN in water was measured on gold L4 (Figure T3.14B). KSCN was chosen since it produces a very intense SER peak at 2100 cm-1, while the other salts only produce a Ag-Cl peak at ~ 230 cm-1, which is not observed due to a low-wavenumber cut-off filter in the Raman analyzer. SCOP was included as a control, since it should appear in the sample spectrum even when passed through the resin. As shown (Figure T3.14A), the spectrum of the sample passed through the resin is dominated by SCOP and there is no evidence of SCN-, indicating that this ion had been effectively trapped. It is worth noting that measurements using a silver-doped sol-gel yielded similar results. As an initial example of the value of the ion retardation resin, a 0.5 mg/mL sample of allopurinol in reconstituted urine was measure before and after it was passed through the resin (Figure T3.15). As shown, the removal of salts improves the spectrum substantially. Although the ion retardation resin did not remove the creatinine or uric acid it is still an essential component for the proposed lab-on-a-chip, especially since high salt levels diminish the separation capabilities of the ion-exchange resins (see below).

The next component tested was the ion exchange resin. Again, the first experiment examined the SER spectra obtained from urine at various pH to determine if uric acid could be removed as a function of pH. As above, a glass pipette was filled with a strong cation-exchange resin (model AG50W, Bio-Rad). A 1g lyophilized urine in 30 mL water sample was prepared and pH adjusted to 1.0 using 1M HCl. 1 mL of this sample was passed through the resin to “load” the column. Next, NaOH was passed through the column, 1 mL at a time, each increasing in strength from

Fig.T3.12. SERS of Reconstituted urine on L2 before filtration at pH A) 5.7, B) 4.6 and C) 8.7. Note: A) on L1

A B C

A B C

Fig. T3.13. SERS of Reconstituted urine on L2 after ion-retardation step, for pH A) 5.7, B) 4.6, and C) 8.7. But here A) on L2.

A B

Fig. T3.15 SERS of 0.25 mg/mL ALLO A) in reconstituted urine and B) after filtration and ion-retardation (pH 6.8), and C) in pure water for comparison. All on L1.

A B C



36

0.1M to 1M. Samples were collected in vials then transferred to SER-active capillaries and measured (Figure T3.15, not a 96 well plate as stated in Quarterly Report #6). As the pH increased the SERS of uric acid became apparent from 4-6, while creatinine dominated at pH 8. Next, the 25 target analytes were each separately loaded on this ion exchange resin and measured as a function of pH, by eluting samples using increasing 1 mL NaOH concentrations and measuring the SERS-activity. In time it was found that the biomarkers could easily be measured at the require 1 mg/L, and most of the drugs could be measured at the required 10 microg/L. For example, 3-MeHis, RIS, CaP, Allo, and OXP were measured at 1 microg/mL (Figures T3.16 and T3.17), HO-LYS and IBA at 10 microg/mL (Figures T3.18), and even H-Pyd at 18 microg/mL (Figures T3.19). Note that oxypurinol was captured on an anion exchange resin and eluted off using an acid (Figure T3.17C).

Towards the development of the lab-on-a-chip, methods were developed to load the ion retardation and exchange

Fig. T3.15. SERS of reconstituted urine collected from an ion exchange column collected as pH fractions of ~1, 2, 4, 5, 6, 8, and 12 measured on L1 capillaries, eluted off with NaOH. Note UA and CRE contribution at pH 2-6, and 8 respectively.

1

2

4

5

6

8

12

pH

Fig.T3.16. SERS of 0.001 mg/L A) 3-MeHIS and B) RIS on L5; pre-concentrated with cation exchange resin (pH ~2), and eluted off with 1M NaOH.

Fig.T3.17. SERS of A) 1 mg/L CaP and B) 0.001 mg/L ALLO on L5; pre-concentrated with cation exchange resin (pH ~2) and eluted off with 1M NaOH; C) OXP 0.001 mg/L on L3 pre-concentrated with anionic exchange resin (pH~10), and eluted off with 1M HCl.

A B

A B C

Fig.T3.19. SERS of A) 0.01 mg/L HO-LYS and B) 0.01 mg/LIBA, both on L1t (HCl washed), pre-concentrated with cation exchange resin (pH ~2), and eluted off with 1M NaOH.

Fig.T3.18. SERS of 0.018 mg/L H-Pyd on L3 pre-concentrated with cation exchange resin (pH ~2), and eluted off with NaOH base gradient.

A B



37

resins into the 1-mm glass capillaries (Figure T3.20A). This was accomplished by first loading a ~0. 5 mm plug of MTMS sol-gel (no metal doping) into the capillary and letting it gel to form a porous frit to hold the resins. Then the resins were dissolved in water and ~ 2 cm segments were loaded. Several experiments were performed to demonstrate that the resins within these capillaries function as designed. These capillaries, the SERS-active capillaries, the filter and a syringe as the method of delivering and flowing sample formed the basis of the lab-on-a-chip components (Figure T3.20) and the first experiment to evaluate the design.

Fig.T3.20. Photographs of A) MTMS frit, B) ion retardation resin, C) ion-exchange resin, D) filter in filter holder, E: syringe, F: urine sample, G: SERS-active capillary (L1). The ideal test sample would contain a biomarker and a drug associated with bone loss or muscle loss (stone formation is less important). Unfortunately, such a pair could not be measured (the bone loss biomarkers H-Pyd and H-dPyd available only in acetic acid, cost too much to perform but a few measurements, and there are no accepted preventive muscle loss drugs). Consequently, the combination of 3-methylhistidine and Risedronate became the best test case for a biomarker and drug that would realistically be found in an astronaut urine sample. An artificially doped urine sample was prepared by adding 1 mL of a 1/1 volume mixture of 3-methylhistidine and Risedronate, both at 1 mg/mL in HPLC water, to a 1 mL reconstituted urine sample (0.5 g in 15 mL HPLC water). This produced a urine sample containing 0.25 mg/mL of each analyte. This sample solution was vortexed and allowed to equilibrate at room temperature for 5 minutes. Two 10 microL samples were drawn into SERS-active capillaries (L1) by syringe and measured, one before and one after passing the 2 mL urine sample through the nylon filter. In this case and all others, Tygon tubing connected the syringe to the capillary. There was no noticeable difference between the spectra (Fig.T3.21A and B). The entire urine sample was then drawn through a capillary filled with ion retardation resin, and again ~10 microL was drawn into a SERS-active capillary and measured. Peaks associated with both 3-methylhistidine and Risedronate are readily apparent, but so are peaks associated with uric acid (Fig.T3.21C). Nevertheless, these spectra again show that the ion-retardation resin substantially improves the SERS-response, presumably by removing dissolved salt ions.

Fig.T3.21. SERS of reconstituted urine sample doped with 3-methylhistidine and Risedronate, A) before and B) after filtration, and C) after passing through an ion retardation (IR) capillary, and after passing D) 0.1 M KOH (3-MeHIS) and E) 0.5 M KOH (RIS) through the ion exchange (IEX) capillary. Note that the analytes can be identified in C), but are unmistakable in D) and E).

E D

C B A

UA RIS

3-MeHIS

B C

D: filter E: syringe

G: SERS-active capillary

F:

urine sample

A: MTMS Frit

B: ion-retardation resin

C: ion-exchange resin



38

Next, 1 mL of the artificially doped urine sample was pH adjusted to 2 by adding 1M HCl. Approximately 25 microL of this sample was loaded onto an ion exchange resin (cation). Next, three 1 mL solutions of 0.1, 0.5, and 1.0 M KOH were passed through the resin, while collecting the eluted sample, 2 drops each, into the wells of a 96-well micro-plate. Approximately 1 drop was drawn from each of the 30 filled wells into SERS-active capillaries and measured (somewhat time consuming). It was found that 3-methylhistidine was carried off the column by the 0.1 M KOH (wells 1-10, and Risedronate by the 0.5 M KOH (wells 12-20). This is consistent with the pKA’s for these chemicals, 5.9 and ~8, respectively, since these base concentrations result in pHs of ~6 and 8, respectively. Although reasonable SER spectra were obtained, it is clear that uric acid is still present in the sample containing 3-methylhistidine. For this reason, a urine sample doped only with 3-methylhistidine was prepared and measured using various sol-gel libraries after following the above procedure. It was found that sol-gel chemistry L3 yielded a quality SER spectrum of this analyte with little contribution from uric acid (Figure T3.22).

Next a series of experiments were performed using urine samples artificially doped with 3-methylhistidine and Risedronate at physiologically relevant concentrations to determine the volume of sample required, the amount of ion retardation and exchange resins required, the volume of acid to prepare the ion exchange column, and the volume of base to elute the analytes. It was found that the following conditions yielded very good results: a sample volume of 1 mL, 250 mg of each resin loaded into capillaries, 25 microL of 1M HCl to acidify the ion exchange resin, 0.5 mL of 0.1M NaOH for 3-methylhistidine or 0.5M NaOH for Risedronate, and collecting the first 100 microL for SERS analysis. These conditions were used to successfully measure 1 mg/L 3-methylhistidine and 0.01 mg/L Risedronate artificially added to reconstituted urine (separately, Figure T3.23) Finally, based on all of these experiments, a lab-on-a-chip would consist of the components as shown in Figure T3.24. Note that the use of a continuous base gradient and capillaries (or channels) would be used to measure additional biomarkers and drugs.

Fig.T3.22. SERS of 1 mg/L 3-MeHIS separated from reconstituted urine (see text) on A) L3 (chem2c), B) L2, C) L1 and D) L5. Note that uric acid is absent in A-C), but not D).

A B C D

Fig.T3.23. SERS of A) 1 mg/L 3-MeHIS and B) 0.01 mg/L RIS separated from reconstituted urine (see text). Both on L3 (chem2c). Note: separate urine sample for each analyte.

A B

Figure T3.24. Illustration of the lab-on-a-chip components that will effectively separate 1 mg/L 3-methylhistidine and 0.01 mg/L Risedronate from urine. The analysis should take less than 10 minutes. Compare to Fig. T3.1.



39

Questions to be answered: Are there components available to perform the desired extractions and separations? Yes, the evaluation results are summarized in Figure T3.24. Are they effective in the context of our SER-active sol-gels, separately, and together? Yes. What is the best sequence of sol-gels? L3 for both biomarkers and drugs. How universal is it for various urine components and drugs? L5 is best for UA, while L3 (chem2c) excludes UA. Are the mixtures effectively separated and detected? Yes, see Fig. T3.21. What happens when other chemicals from Task 1 are analyzed? Method is amenable to all analytes; spectral deconvolution software provides confirmation. What are the detection limits? See lowest measured concentrations in Tables T1.3 and T1.4, and T2.1 and T2.2., in general 1 mg/L for biomarkers and 10 microg/L for drugs achieved. Task 4. Lab-on-a-chip fabrication (with Advanced Fuel Research as subcontractor). The overall goal of this task was to build many microfluidic chips that can be used to test the preliminary lab-on-a-chip design. This was accomplished by fabricating two successful polymethylmethacrylate (PMMA) chip designs after making considerable modifications to the process described by Muck et al. This task consisted of several parts, 1) preparing a silicon master chip (AFR subcontract), 2) producing PMMA chips, 3) incorporating SERS-active sol-gels and separation materials into the chip channels, and 4) performing SERS measurements using the chips. This task was substantially delayed as the initial design mask was incorrect, and the photo-resist identified by Muck could not be used as described (it is our opinion that much of the chemistry described by Muck was intentionally miss-stated). Together, these circumstances caused more a 5 month delay in delivery of the first chips (May, 2006), and consequently we requested a 6 month extension. While we awaited the chips we focused on part 3) learning to load smaller and smaller channels with our SERS-active sol-gels. The initial test chip included a variety of channel widths for testing, including ranging from 100 to 500 microns (see below). Consequently, we ordered glass and plastic capillary tubing ranging from 200 to 600 microns. Initial measurements were performed on 600 ID glass capillaries, as these were not much smaller than the 800 micron ID of our standard 1-mm capillaries, and the volume would be close to a 500 micron wide channel that is 250 microns deep. Initial measurements were performed by loading the standard silver-doped sol-gel chemistries (L1 - L3) into the capillaries. It was found that long plugs of 2 cm or more were very difficult to reduce, while short plugs of 0.5 cm detached during reduction or sample loading. This was even true for L3, which incorporates octadecyltrimethoxy silane, which produces relatively open structures due to the long organic chain. For these reason, several modifications to the sol-gel chemistry were investigated. This included the incorporation examining internally coated, instead of filled capillaries, incorporation of different alkoxides, such as PDMS, and modification of the sol-gel curing process. One way to overcome the restricted flow caused by the sol-gel plugs in the capillaries is to open the center of the capillary so that flow would be unrestricted. This was accomplished by filling a capillary in the usual way (mixed precursors drawn into the capillary by syringe), but then forcing the sol solution back out after 20 seconds, before it gels. This process was repeated 6 times to form a thin film of sol-gel on the inner wall of the capillary (Figure T4.1). This multi-layered approach also gives us flexibility in terms of coating thickness. These open tubular capillaries were prepared using a modified chemistry L1 (TMOS only). First two 1 mg/mL samples, pyridine and acetylsalicylic acid, were measured in internally coated capillaries of standard diameter, and then a 1 mg/mL 3-methyl histidine was measured in a internally coated 600 micron ID capillary (Figure T4.2). Not surprising, it was found that these coated capillaries were somewhat less sensitive, as the analyte has to diffuse through the sol-gel to the SERS-active metal, as opposed to the standard capillaries, in which the analyte is forced to the metal surface as it is introduced into the capillary.


40

To aid the development of methods to loading smaller and smaller diameter capillaries (and ultimately chip channels), an apparatus used to coat gas chromatography columns was purchased (Rinse Kit FOR GC columns, Part No. 23626, Sigma Aldrich, Figure T4.3). It consists of a reservoir for the sol-gel solution, a side arm for applying gas pressure, a small slit to fit a capillary into the reservoir opening and a side support arm. To load capillaries, first the reservoir is filled with a sol solution, and one end of the capillary is inserted into the reservoir opening and sealed with a graphite ferrule. Gas pressure (40 psi) applied through a side arm forces the sol solution from the reservoir through the column and into the capillaries. The next method investigated to improve the flow through the sol-gels was the incorporation of polydimethyl siloxane (PDMS) in the alkoxide precursor. As with ODS this siloxane should yield more porous sol-gels. As mentioned previously, it also appears to adhere to glass and plastic capillary walls very well. 600 micron capillaries were filled with modified L1 and L3 in which PDMS was added (see L6 chemistry in Table T1.2, Figure T4.4). The PDMS-L1 modified chemistry (designated L6) in a 600 micron ID capillary was used to measure 1 mg/mL Risedronate (Figure T4.5).

A B

A B C

Figure T4.1. Microscope photograph of a 600 micron ID capillary internally coated with a reduced silver-doped sol-gel.

Figure T4.2. SERS of A) PYR, B) ASA, C) 3-MeHIS Conditions: A) and B) 800 micron ID, and C) 600 micron ID capillaries internally coated with L1. Conditions: 1 mg/mL in HPLC water, 100 mw of 785 nm, 1-min.

Fig. T4.5. SERS of RIS A) 1mg/mL, L1, B) 1mg/L L6, and C) 1mg/mL L6 600 micron ID capillary; 90 mW, 785 nm, 1-min.

Fig. T4.4. 600 micron ID capillaries; A) L6, B) L1, C) L3 (+PDMS). Sealed with rubber caps, cured 24 hours and reduced by standard method.

A B C

A B C

Fig. T4.3. Apparatus for loading small capillaries and chip channels.

Reservoir

Gas Line

Connection to capillary or chip channel


41

Another important requirement is that the sol-gels must bond to the PMMA channels of the chips. To test this idea, a length of 500 micron ID PTFE (poly(tetrafluoro ethylene)) tubing was filled with L2. Upon curing (~2 hrs), the sol-gel filled tubing was cut into segments (~5 cm each), which were reduced following the standard method. The sol-gel did not detach during curing or upon flowing the reducing agent. In fact, one of these segments was reduced 5 days later and as shown in Figure T4.6, it not only remained attached but exhibited good SERS activity for ALLO. It is anticipated that adherence will be even better in the PMMA channels due to the ability to form chemical bonds directly with the silanol groups of the sol-gel.

Another requirement for developing the SERS-active microchips is the ability to load the separation materials into the chip channels. Although we know that we can use MTMS sol-gel frits to hold these materials, we also investigated the ability of designing ion exchange capability using our sol-gel chemistry. A sol-gel anion-exchange material was created by using N-octadecyldimethyl[3-(trimethoxysily)propyl]ammonium chloride (C-18 TMOS, 100 microL) with TMOS (100 microL), and 95% triflouroacetic acid (200 microL) as a catalyst. Due to the presence of a positively charged quaternary ammonium group in the C-18 TMOS, the resulting sol-gel coating carries a positive charge. This sol-gel anion-exchange resin was successfully incorporated into a 250 micron capillary. Two samples were prepared to test the IEX capillary, 1-MeHIS (50 microg/L in urine) and OxP (5 microg/L in water.) First, a 100 microL sample of 1-MeHIS at 50 microg/L doped in reconstituted urine was pH adjusted (15 microL of 1M KOH to impart a negative charge) and passed through this capillary. The sample was successfully extracted and pre-concentrated. The sol-gel was washed with 500 microL of HPLC water to remove the sample matrix, following which the extracted sample was eluted off the sol-gel coating by a 1M HCl solution (100 microL). The eluent was then drawn into a standard SERS-active capillary (L1) and measured. The same procedure was followed for the OxP. The SER spectrum for both analytes were weak, with 1-MeHIS dominated by uric acid peaks. Clearly the extraction efficiency of this ion exchange material requires further development. Since the MTMS frits work, attempt to develop a sol-gel based ion exchange resin was discontinued. As the chemical-selectivity and SER-activity for the standard sol-gel libraries in terms of the target analytes was being developed, it became clear that these libraries yielded the desired results, and that the sol-gel process, not the chemistry, should be investigated. To this end, the relative precursor volumes and gelling conditions were investigated (temperature, gel time, amount of oxygen, etc.). It was found that by maintaining a constant temperature, the sol-gel cure process was more consistent and more uniform activity was obtained. This also allowed reducing the sol-gel earlier during the gelation with significantly less flow restriction. Consequently, measurements using smaller diameter glass capillaries filled with sol-gel chemistries L1 and L2 were repeated. Ultimately, it was found that L2 could readily be incorporated into capillaries with IDs of 250 microns, as well as a 200 micron ID channel etched into a Si-wafer micro-chip (kindly supplied by Dr. Eric Wong, Jet Propulsion Laboratory). Figures T4.8 and T4.9 show the SER spectra obtained for 10 microg/L samples of etidronate (pre- concentrated on separation materials) obtained in these devices, respectively.

A B

Figure T4.6. A) SERS of 0.5 mg/mL Allopurinol in L2 sol-gel loaded poly(tetrafluoro ethylene) tubing, and B) NRS of the PTFE tubing, 300 mW at 785 nm, 5-min. Insets, PTFE tubing with and without sol-gel.

Figure T4.7. SERS of A) 1-MeHIS (Nt-MeHIS), 50 microg/L urine and B) OxP, 5 microg/L water. Note: samples passed through sol-gel based ion exchange resin.

A B


42

In a kick-off meeting between RTA and AFR, the development of the micro-fluids master was discussed, including the design. Although a 14-channel chip was proposed containing 2- and 4-SERS-active sol-gel segments in sequence, it was clear from the measurements described above that flow would be very difficult, and so two simpler designs were developed. They contain most of the important features to develop the methods required to load the SERS-active sol-gels into the channels. The designs are for 2 inch diameter silicon wafers. The first design is simply 4-channels (each 250 micron width) suitable for practicing loading sol-gels and obtaining SERS. It also will serve to produce the 20 deliverable chips for Phase III measurements (each with a different sol-gel chemistry). The second design contains 6 straight channels and 2 T-channels with widths of width 100, 200, 300, 400, and 500 microns. The mechanical drawings provided to Microtronics to fabricate the masks are shown in Figure T4.10.

Fig.T4.10. Drawing of initial microchip designs. The masks were developed on 4-inch x 4-inch x 0.09-inch soda lime glass plate (grey regions represent anti-reflective chrome coat). The following specifications were provided: A) all circular end holes 2.0 mm diameter on 0.25 mm horizontal strips; B) 1) all circular end holes on vertical and horizontal strips 2.0 mm diameter, 2) vertical strips spaced 3.62 mm apart on centers, 3) width of vertical strips as follows: a) 0.5, b) 0.4, c) 0.3, d) 0.4 mm including above horizontal connecting strip, e) 0.1 mm including above horizontal connecting strip, f) 0.2, g) 0.1, h) 0.05 mm. As previously stated, the lab-on-a chip masters were prepared following the method of Muck by Advanced Fuel

Figure T4.8. SERS of 10 microg/L etidronate obtained in a sol-gel filled (L2) 250 micron ID glass capillary. Conditions: 40 mW of 785 nm, 20-sec. Inset: glass capillary, the dark color is the protective polymer coating.

Figure T4.9. SERS of 10 microg/L etidronate obtained in a sol-gel filled (L2) 200 micron ID U-channel in a Si-chip. Conditions: 60 mW of 785 nm, 20-sec. Inset: Photo of chip, actual size.

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Research (under subcontract). AFR employed a class 10 clean room to prepare the master and followed all necessary safety (HF) procedures. The overall process is shown in Figure T4.11 and involves two basic phases: 1) standard photolithography for patterning the wafer with a protective photoresist coating and 2) wet chemical etching to thin the silicon wafer and produce the raised ridges. Figure T4.11. Illustration of chip fabrication process.89 Two-inch diameter silicon (100) wafers (p-type, 1-10 ohm-cm, 500 µm thick) with a 1000 nm thick thermal oxide coating were used. First the wafer was cleaned by soaking in an 80oC bath of NH4OH:H2O2:H2O (1:1:5) for 10 minutes, and then rinsed with de-ionized water. Second, the wafer was spin-coated with a negative tone photoresist (SU-8 2, Microchem Corp.) at ~ 2000 rpm for 30 seconds to produce a ~ 2 µm coating (the photoresist indicated by Muck could not be used, and consequently all of the following parameters were refined by AFR). Third, the wafer was soft-baked on a programmable hotplate by ramping the temperature from 25 to 95oC and holding for two minutes. The wafer was then allowed to cool to room temperature. Fourth, the mask was manually aligned on the wafer using the major flat for guidance (A in Figure T4.11). Fifth, the wafer was exposed to 365 nm UV light (B in Figure T4.11). Sixth, a post-exposure bake was performed to complete the cross-linking of the exposed resist regions, using conditions identical to the preliminary soft-bake. Seventh, the unexposed resist was then removed by submersion in a stirred bath of SU-8 developer for two minutes followed by a 90 second rinse in isopropanol, and a spin-drying stage (C in Figure T4.11). Eighth, the wafer was hard-baked at ~ 165oC for 15 minutes and allowed to cool on the hotplate, completing the patterning phase of the processing. Ninth, the wafer was submersed in a room temperature bath of a buffered oxide etchant consisting of a blend of 40% ammonium fluoride and 49% hydrofluoric acid in a 7:1 volume ratio until the wafer is hydrophobic (~12 minutes, D in Figure T4.11). After a one minute rinse with de-ionized water, the wafer is immediately submersed in a 30% (wt/wt) solution of aqueous KOH at 80oC with vigorous stirring (E in Figure T4.11). A photograph of the second chip design master is shown in Figure T4.12, along with a microscope image of the channel f T-section. The latter shows well-defined corners, and reveals the tapered shape of the ridges owing to the anisotropic nature of the Si (100 and111 planes). The top of the ridge was measured at 99.6 µm, which compares favorably to the target value of 100 µm. Based on the width of the ridge base and assuming that the sidewall angle with respect to the Si surface is 54.7 degrees [1], the height of the ridge is calculated to be ~ 83 µm. This corresponds to a KOH etch rate of ~ 0.92 µm/min for the Si(100), which is in fair agreement with the predicted etch rate of ~1.3 µm/min for 30% KOH at a temperature of 80oC [2]. Thus far, the “tallest” micro-machined ridges we have achieved on Si were measured to be ~ 138 µm (determined in an optical microscope) for a KOH etch period of 150 minutes.

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Figure T4.12. Photograph of Master Chip (design #2) and microscope image (x110) of e channel.



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Part 3 of making the micro-fluidic chips was performed at RTA. Following the procedure of Muck, a mold was prepared by gluing the chip Masters to 4x4” glass supports using epoxy. A Teflon circle was cut and placed around each Master, and then filled with the PMMA monomers (F in Figure T4.11). Unfortunately, the prescribed PMMA solution and curing conditions did not work. After investigating these conditions, it was found that a 10% benzoin methyl ether concentration was required, the 20/80 w/v ratio of PMMA/MMA had to be procured under nitrogen (2-min at 60 °C), and UV cure required 5 hours (a UV lamp was purchased for this part; Dymax Blue Wave 200 model 38905). Unfortunately, this cured acrylic bonds to the master chip, and it could not be separated without destroying the master. Eventually, the following procedure was developed. A 4 gm/2 drop solution of PMMA and benzoyl peroxide (Electron Microscopy Sciences, Hatfield, PA)was mixed and allowed to pre-cure for 10 minutes. At the same time a thin coat of Teflon spray (DuPont, Delaware) was applied to the master chip. The acrylic monomer solution was then poured onto the master contained in the Teflon ring. Cure was complete in 24 hours at 25 oC or 2 hours at 75 oC. The acrylic chip separated from the master with a little amount of prying (Figure T4.13B). Once these chips were formed the ports at the end of the channels were drilled through using a 1 mm bit. Next, several methods were explored to bond the chips to glass substrates (2”x3” microscope slides were used), as opposed to another sheet of acrylic described by Muck (since this would produce a strong Raman background). Ultimately, it was found that coating the microscope slide with a thin layer of the same PMMA/ solution, clamping it to the chip, and allowing it to cure at room temperature for 4-5 hours resulted in a strong bond with good seals. Nevertheless, as can be seen in Figure T4.13C, we still have difficulty producing flat chips, and consequently only preliminary measurements were performed.

Fig. T4.13. Photograph of A) Chip Design 1 Master, B) PMMA chip produced from master, and C) Chip Design 2 attached to 2”x3” glass slide. While the above micro fluidic chip development was underway, alternative methods to fabricate credit card sized lab-on-chips were explored. The focus was to develop a working chip that could be used to separate 3-methyl histidine and Risedronate from a urine sample and measure them at physiological concentrations. The following basic design was developed (Figure T4.14). It consists of a central channel in which the ion exchange resin could be loaded and two side channels containing SERS-active sol-gels to measure the two analytes. The chip was manufactured as follows. A 1.75” by 2.75” rectangle was cut out of a ¼” sheet of acrylic. Three 1 mm wide channels, 1 mm deep were milled into the sheet in a trident pattern. Four 1 mm holes were drilled through the sheet to allow introducing the resin, sol-gels, reducing agent, sample, acid and bases. As described above, the ¼” acrylic chip was bonded to a 2”x3” glass microscope slide using the PMMA/peroxide monomer solution, clamped and allowed to cure at room temperature. After 5 hours, a syringe and #22 needle were used to load the outside channels with L2 sol-gel and a plug of MTMS in the central channel. The sol-gels were allowed to cure for 12 hours. Next the outside channels were reduced with sodium borohydride, again using a syringe with a #22 needle. The surface of the chip was then cleaned with isopropyl alcohol and the luer port connectors were attached (NanoPort Assemblies, Part No N-333, Upchurch Scientific, Oak Harbor, WA). The adhesive gasket is cured at 120 oC in 1 hour (or 60 oC in 12 hours). The luer ports were not attached until after the channels are loaded and reduced, since they are prone to getting clogged by the sol-gel and could retain some of the reducing agent. These ports provided

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the lab-on-a-chip to real world fluidic interface (as opposed to the Teflon block interface proposed). To obtain SERS from these chips, a 4”x 6.5” Plexiglas plate was machined to fit the standard 96-well plate reader and hold the chips (see Figure E.1).

Figure T4.14. Photograph of of A) machined Trident chip, B) chip attached to 2”x3” glass slide, and C) Trident Chip with luer ports. Questions to be answered: Can AFR produce the test chips? AFR was subcontracted to make the chip masters, and had a number of set-backs, but eventually developed the process. Does the process need further modification? Thicker substrates are required. Does the interface perform as planned (no leaks)? Yes, commercial luer locks were used that simplified the real-world interface. Can the various channels be loaded, reduced? Yes, see above. What size, length is best? We were able to load 200 micron channels AND flow analyte. Can separation materials be introduced? Yes. Task 5. Define Analytical Figures of Merit. The aim of this task was to establish performance criteria for the lab-on-a-chip. This was accomplished by measuring the analytical figures of merit for the analyzer, as outlined by the FDA: sensitivity, reproducibility, linearity, accuracy, precision, and selectivity. Although the focus of this task was to determine the analytical figures of merit for the micro-fluidic chips, the difficulties encountered in manufacturing these chips, forced us to perform these tests on the SERS-active capillaries. We believe that the chip performance would have the same linearity, accuracy, precision, and selectivity, and similar sensitivity, and reproducibility. Sensitivity may be reduced due to a smaller channel size as compared to the laser focal spot (~365 micron diameter, i.e. fewer analyte molecules in the beam), while the reproducibility will depend on manufacturing. In the case of the former, changing optical components in the fiber optic sample probe can address this difference. In the case of the latter, improved replication of the chips using a photolithographic master, such as shown in Figs.T4.13-14, will result in reproducibility equivalent to the capillaries. We proposed to improve sensitivity by developing chemically-selective sol-gels, evaluating sample flow and pistioning, and exploring the use of shorter laser excitation wavelengths. The goal was limits-of-detection (LODs based on a signal-to-noise ratio of 3) of 1 mg/L for the biomarkers, and 0.01 mg/L for the drugs. Based on Phase I results, LODs of 10 to 100 microg/L were predicted. In fact, as described in Task 2, not only were these LODs achieved by using an ion exchange resin, but the analytes were actually measured at these target concentrations (see lowest measured concentration, LMC). Nevertheless, measurements at even lower concentrations are always desirable. The use of shorter laser excitation wavelengths can further improve sensitivity by more closely matching the plasmon absorption maximum. As described in the proposal, the plasmon maximum for 15 nm silver particles is ~ 450 nm, while the maximum SERS response occurs at ~500 nm (Figure T5.1).90 Our silver particles are 30-80 nm in diameter, which shifts both of these maxima by ~100 nm, but also reduces the magnitude of the plasmon absorption by ~ 10 (blue line in Figure T5.1). Nevertheless, shifting to laser excitation at 532 or 633 nm should increase the

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46

SER signal by at least 20 times, and as much as 100 times. Attempts to obtain SER spectra using 20 mW at 532 nm laser (1064 nm frequency doubled using a KDP crystal) and a recently purchased 17 mW at 633 nm HeNe laser (Model MRP170, THOR Labs) failed. This was even true for attempts to obtain normal Raman spectra of pure chemicals at the shorter wavelength. Closer examination of our Raman analyzer revealed that the spectral response of the system is essentially non-existent below 650 nm (red line in Figure T5.1). This is not due to the Si detector, but the inefficiency of the beam splitter, which was not taken into account when proposed. However, there was sufficient response at wavelengths longer than 725 nm when using 633 nm laser excitation (above 2000 cm-1 in the Raman spectrum). Unfortunately, our analytes do not produce any significant peaks above ~1700 cm-1. One of the few chemicals that produce a SERS peak above this wavenumber is cyanide (CN-) with a peak at 2140 cm-1. Figure T5.1. A) Theoretical SERS enhancement for RTA 50 nm silver particles (blue line) and Raman analyzer response (red line). SERS of B) 1 and C) 0.1 mg/L using 785 and 633 nm laser excitation, respectively. We measured 100 microg/L cyanide in a SERS-active vial using the 633 nm laser and a 1 mg/L cyanide sample using the 785 nm laser. The calculated enhancement was 34 times when including the sample concentration, signal intensity, laser power, laser wavelength (4th power dependence), and spectral response efficiency ((1mg/L/0.1 mg/L)x (0.07/0.4)x(84 mW/12 mW)x(785 nm/633 nm)4(100%/15%)). Although our Raman system is clearly not optimized for operation at this wavelength, significant improvements in sensitivity can be expected using a more efficient beam splitter. Measuring the SER signal intensity as a function of concentration allows determining linearity, multiple measurements allows determining precision, measuring a mixture allows determining accuracy, and measuring several of the samples on multiple capillaries allows determining repeatability. During the Phase I program, 1-methyl histidine (mislabeled 3-methyl histidine by the supplier, Figure T5.2) was measured over a concentration range of 0.001 to 1 g/L (pH adjusted to 7.5). For each concentration, 50 microL of the 1-MeHis solution was drawn into a SERS capillary (chem2c), and five spectra were collected at random spots along the capillary. The concentration was related to the height of the 1565 cm-1 band in the 1-MeHis SER spectrum. In each case, the largest 2 outliers were discarded (modified T-test). The results of the concentration curve are shown in Fig. T5.3. This procedure provided better than normal reproducibility for the SERS capillaries with relative standard deviation (RSD) of 10-15%. As can be seen, the concentration curve initially increases linearly from zero, but then “rolls-over” as the available silver surface area decreases and monolayer coverage is reached (at ~0.005 mg/mL). This SER response has been previously described in the literature and ascribed to a standard Langmuir-Blodgett isotherm equation.

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Although the Phase I measurement was a good start, it did not cover the relevant concentration range and it did not account for the use of an ion exchange resin to concentrate the sample. A stock solution (3-MeHIS) was prepared in HPLC water, and serially diluted to generate samples having concentrations of 5000, 1000, 500, 100, 50, and 10 microg/L. Each sample was pH adjusted to 1 using 1M HCl, passed through an ion retardation column, pre-concentrated on an ion exchange column, eluted off with 0.1M NaOH, and the first 100 microL was loaded into a SERS-active capillary (L3, chem2c) and measured. Similar to the Phase I measurements, spectra were recorded at 10 positions along the capillary (1.5 mm apart), but none were removed. The ten spots were averaged to produce a single spectrum at each concentration and the 1364 cm-1 peak height (baseline at 1433 cm-1 subtracted) was used to prepare a calibration curve (Figure T5.4). The ten points were used to determine the RSD for each concentration, and it was found the RSD = ~20% for 5, 1, 0.5 microg/L, and 40% for the lower concentrations.

Raman Shift, cm-11850 350 500 750 1000 1250 1500

Figure T5.4. A) SERS of 3-methyl histidine at 1000, 500, 100, 50, and 10 microg/L. Conditions: pH=1, ion retardation and ion exchange, measured on L3 capillary, 100 mW of 785 nm, ten 1-min scans averaged. B) Plot of 1364 cm-1 peak height (baseline at 1430 cm-1 subtracted). Inset of higher concentration. Red dot = 25 microg/L. Since it is clear that the capillaries do not produce the same signal intensity from spot to spot, a program was written to scan a 15 mm length and continuously collect spectra. In 1 minute it makes 10 passes (5 each way), and effectively averaged the spot-to-spot intensities. The success of this “Raster” approach is shown in Figure T5.5, where the identical set of capillaries was measured. Although the S/N was reduced (1 min vs 10 min per spectrum), the concentration curve becomes linear. Since repeat measurements were not performed, the precision (RSD) was not calculated for each concentration. However, the improved shape of the concentration curve suggests that the RSD has improved, and would likely be similar to our SERS-active vials at 15%. Nevertheless, the RSD for all of the concentrations combined allows calculating the reproducibility of the capillaries, which is 27%. If 10-min Raster scans were used, this value would also likely improve.

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Raman Shift, cm-11850 350 500 750 1000 1250 1500

Figure T5.4. A) SERS of 3-methyl histidine at 1000, 500, 100, 50, and 10 microg/L. Conditions: pH=1, ion retardation and ion exchange, measured on L3 (chem2c) capillary, 100 mW of 785 nm, 1-min Raster scan. B) Plot of 1364 cm-1 peak height (baseline at 1430 cm-1 subtracted). Inset of higher concentration. Red dot = 25 microg/L. To test the accuracy of this method, a 25 microg/L 3-methylhistidine sample was independently prepared and measured, and the peak height plotted in the concentration curve (circle). Based on the concentration curve, the measured peak height (0.036±0.01) corresponded to 150 microg/L, but is within the RSD. Risedronate concentration samples were also prepared, but over a lower concentration range (1000 to 1 microg/L). Again each sample was pH adjusted to 1, passed through an ion retardation column, pre-concentrated on an ion exchange column, eluted off with 0.8M NaOH, and the first 100 microL was loaded into a SERS-active capillary (L3, chem2c) and measured. Spectra collected using the Raster approach are plotted in Figure T5.5 along with the measure peak height at 1032 cm-1 (baseline at 989 cm-1 subtracted). This time the data conformed more closely to the Langmuir-Blodgett isotherm. Again, the entire data set was used to calculate a capillary-to-capillary RSD of ~32%. Also, a 250 microg/L Risedronate sample was independently prepared, extracted following the procedure described above, and measured to test the accuracy of the concentration curve. This time the peak height (0.022, green square) placed the concentration at ~300 microg/L, well within experimental error. As a further test of the ability to use this calibration curve, a 10 microg/L Risedronate sample was prepared in reconstituted urine, extracted as above, and measured. The peak height (0.016, red dot) was very close to that measured for the pristine 10 microg/L sample (0.017 peak height).

Raman Shift, cm-11250 350 600 800 1000

Figure T5.5. A) SERS of Risedronate at 1000, 500, 100, 50, 10 and 1 microg/L. Conditions: pH=1, ion retardation and ion exchange, measured on L3 (chem2c) capillary, 100 mW of 785 nm, 1-min Raster scan. B) Plot of 1032 cm-

1 peak height (baseline at 989 cm-1 subtracted). Inset of higher concentration. Green square = 250 microg/L, red dot = 10 microg/L in urine. As proposed, concentration curves for several other biomarkers and drugs were prepared and measured. It was found that analytes that could be detected at very low concentrations (1 microg/L), followed the Langmuir-Blodgett

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at these lower concentrations and leveled off within 2 orders of magnitude, such as Risedronate. Conversely, analytes that could be detected only as low as 50 microg/L followed this curve at higher concentrations, leveling off at correspondingly higher concentrations. We attribute this response to the chemical-selectivity of the sol-gels and the analyte-to-metal interactions, i.e. the greater the interaction, the greater the sensitivity, and the greater the selectivity the lower the surface saturation point. Questions to be answered: What are the LODs for each of the biomarkers, drugs and their metabolites? See Tables T1.3 and T1.4, T2.1 and T2.2. What is the reproducibility of the chips? This was not determined, but is likely to be the same as the glass capillaries, at about 30%. Which channel design provides the best selectivity, reproducibility, and sensitivity? Since the chip manufacturing was substantially delayed, it was only determined that we could load and perform measurements in both glass and plastic channels at 800, 600, 500, 250, and 200 microns. What is the best standardization method for quantifying target analyte concentrations? It appears that the best method would be to sue creatinine and uric acid as internal intensity references. Creatinine is a known constant for urine chemistry. Once the relative uric acid concentration is determined, all other chemicals could be referenced to it, since it appears in virtually all samples due to its 7 ionizable protons (7 pKas.) Task 6 - Prototype Design. The overall goal of this task was to design a prototype system to be used and tested by NASA in Phase III. This has been accomplished by redesigning the proposed compact disc (CD) style lab-on-a-chip based on the Task 3 and 4 data. The proposed analysis of urine from astronauts on long term space missions in a microgravity environment will employ a multi-component analyzer that will be integrated into either Node 3 on the International Space Station (ISS) or on future manned flights. This ultra compact system will be placed into an integrated rack, and will be connected to a water reclamation system currently being developed by Hamilton-Sundstrand. A 10 mL sample container designated for each astronaut will collect urine samples over the course of 24 hrs. After 24 hrs a 1 mL sample is withdrawn for analysis, and the container subsequently flushed with water for the next days use. This analyzer will consist of three major components, the sampling system, the lab-on-a-chip, and a Raman instrument. The final lab-on-a-chip design will depend upon the other two components. Employing a sequence similar to that of the operation outlined in Figure T3.24, the following very simple design is proposed (Figure T6.1). The system consists of four components, A) an injection cartridge, B) the lab-on-a-chip, C) pneumatic valve control manifold, and D) a fiber optic linked Raman probe. In many respects it will operate like a compact disc player. The injection cartridge will contain up to five needles to deliver 1) a vacuum for micro-fluidics control, 2) the sample from the individual astronaut sample container (which will be pH adjusted to 1 using acid from a reservoir), 3) a base gradient prepared by increasing the amount of NaOH mixed in with water (note reservoirs), 4) air from a bladder to allow fluid flow control when combined with the vacuum line, and 5) waste removal line. Again, like a CD player, six chips will be used, one per astronaut (based on expected ISS capacity). Each lab-on-a-chip will consist of a 12 cm diameter disc (CD-size) divided into 30 pie-shaped “slices”, 12-degrees wide (12 mm across outer edge), one slice per sample. Thus, each lab-on-a-chip will provide 30 measurements; 1 per day. (A practical first version using 36-degee slices can be made with the technology developed in this program, see below). Each sample segment will contain five ports (6-10), each 1.5 mm diameter, 2 mm deep to match the cartridge delivery needles. A circular layer of butadiene (septa material, 11) will be bonded to the disc to seal the ports prior to use. The sample acceptance port (7) will also contain a layer of Nylon 66 (or equivalent particle filter material, 12) melted into place. Valves (13) integrated into a second, lower layer of the lab-on-a-chip will be computer controlled through a pneumatic or magnetic manifold below the chip. Recently, a plug-and-play micro-fluidic device has been built that employs computer controlled diaphragm pumps to control flow through desired channels.91 The choice of valve control will be based on available technology at the time of implementing this design. The valves are placed to control flow through the various separating materials and direct the analytes to the appropriate SER-active sol-gel set. An ion retardation channel (14) will contain the required separation materials to extract salts, while an ion exchange (cationic) column (15) will adsorb the protonated analytes. The remainder of the sample will be removed from the chip through port 10 to waste (back to water reclamation). Then the NaOH gradient will be delivered through port 8 through the ion exchange resin and sequentially to 1 of 12 SER-active sol-gels (16). The first 3 sol-gels are for biomarkers (e.g. 3-methyl histidine), the next 8 for drugs, and the last for creatinine. The sequence is based on their relative pKa’s (e.g. 3-MeHis = 5.9, Risendronate ~8.5). These channels will lead back toward the center of the disc where a central vacuum or piston will be used to move the 3 µL sample through the sol-gels for analysis. A fiber optic linked Raman probe will be


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Figure T6.1. Illustration of urine analyzer, composed of a A) sample delivery cartridge, B) lab-on-a-chip, C) pneumatic/magnetic valve control manifold, and D) Raman optic probe. This figure is proprietary. In operation, the cartridge head (A) will lower, the needles will pierce the seal, and 1 mL of urine, acidified with 25 microL 1M HCl, will be loaded through Port 7, through the particle filter (12), and through both ion resins (14 and 15), then out through the waste port (10). This volume will provide a significant amount of analytes adsorbed onto the ion exchange resin, and does not influence the size of the channels. One the ion exchange resin is loaded, 120 microL of NaOH gradient will enter through port 8 and flow through the exchange resin into the SERS-active channels in sequence. Valves would be used to select and deliver 10 microL sample of increasing pH to each channel (e.g. top to bottom). The air line allows offsetting pressure drops. Based on Task 3, a 200 micron square channel - 20 cm long will work and we have successfully loaded a chip obtained from NASA (JPL) that has a



51

serpentine channel of these dimensions and obtained a SERS spectrum of Risedronate separated from urine (off-chip, Figure T6.2). However, this channel dimension would require 36-degree “pie slices” per analysis, limiting each CD chip to 10 analyses. This should be acceptable for a first version of this analyzer. At a flow rate of ~ 0.1 mL/min all of the channels would be loaded (we were able to flow 0.5 mL/min through the 800 micron channels). Then the cartridge head separates from the lab-on-a-chip, and the chip rotates in a step-wise fashion, such that Raman spectra can be collected from each of the SER-active sol-gel segments. Once accomplished, the chip again rotates to align the cartridge of the ports of the next sample segment and awaits the next sample. The total analysis for each sample is expected to take no more than 15 minutes. Analysis of the spectra to identify each biomarker or drug based on spectra matching will be accomplished in less than 1 second. All spectra could be sent to earth for further analysis, as well as for identifying unknowns. It should be realized that the pneumatic manifold and Raman probe are fixed, and the only motion is the rotation of the lab-on-a-chip and the up and down movement of the sample delivery cartridge. This device will require very little power. Furthermore, only 25 microL acid and 120 microL of base are required per analysis, or ~1.5 mL for a 10 sample CD disc, or 4.5 mL for a 30 sample CD disc! The 1 mL urine sample is not included, since it is provided by the astronaut.

Figure T6.2. A) Photograph of lab-on-chip provided by JPL for testing. Note the serpentine channels are 200 x 200 microns, and the serpentine channels are ~ 20 cm long. B) SERS of 1 mg/L Risedronate measured in this chip. Drug extracted from real urine (off-chip) and loaded into this chip and measured. Conditions: 75 mW of 785 nm, 1-min. C) Photograph of 4-channel SERS-active test chip (representative of the deliverables). Mission Tests (Phase III). The overall objective of this task is to test the space-worthiness of the proposed lab-on-a chip. This will be accomplished by supplying NASA with 20 of SER-active lab-on-a-chips for Phase III testing (a deliverable). Twenty 4-channel chips have been manufactured and filled with 4 SERS-active sol-gels (L2, L3, L4 and L5, Figure T6.2C). These tests will include shelf life (2 years/accelerated tests), temperature cycling between -80 and 40 oC, vibrational tests, shock, 20-g forces, micro-gravity, radiation resistance (3 krads), cross-contamination-elimination, etc. This may include shuttle or space station testing as appropriate.

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Performance Schedule - The Phase II research program was accomplished according to the following schedule, tasks, and milestones with the work load distributed as SE-150, ENG-200, RA-200 hours: The program was extended by 6-months. QUARTERS 1 2 3 4 5 6 7 8 Task 1 - Develop Spectral Library. 1 2 3 Task 2 - Develop Chemical Selectivity. 4 5 6 Task 3 - Select and Test Components. 7 8 9 10 11 Task 4 - Fabricate Lab-on-a-chip 12 13 14 15 Task 5 - Define Analytical Figures of Merit. 16 17 18 Task 6 - Design Prototype. 19 20 Milestones 1. Prepare 96-well SER-active sol-gel plates 2. Measure SERS of 24 chemicals 3. Test and refine library search algorithms 4. Identify unique bands and determine detection limits 5. Prepare sol-gel coated capillaries 6. Measure reversibility and prelim LODs 7. Purchase components/chromatography supplies 8. Prepare 4-zoned capillaries 9. Test separation methods 10. Test interferents

11. Re-examine search routine capabilities 12. Finalize test chip design 13. Fabricate test chips 14. Fabricate real-world interface 15. Test fluid deliver, Raman collect, etc. 16. Measure sensitivity 17. Determine reproducibility 18. Demonstrate selectivity 19. Perform field test 20. Design test chips for NASA

This Final Report was delivered to NASA (June 1, 2007) summarizing the experimental and analytical results of the project according to contract specifications. In addition, RTA mailed 20 lab-on-chips (see Figure T6.2c above) for continued testing in Phase III (see Mission Tests above).


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Part 5: Potential Applications The overall goal of this program is to develop an analyzer to measure bio-indicators and prescribed drugs and their metabolites in urine to assess and monitor health of astronauts affected by microgravity conditions during extended missions in space. The analyzer will employ a lab-on-a-chip to extract and separate out chemical components from urine samples and surface-enhanced Raman spectroscopy to detect and identify these indicators. The proposed analyzer is immediately applicable to astronauts working in the International Space Station. For example, monitoring the concentration of pyridinoline may suggest increasing (or decreasing) the dosage of the anti-bone loss drug zoledronate. The proposed analyzer will undoubtedly increase our understanding of the adverse effects of near-zero gravity, allow determining the efficacy of drugs used for treatment, and improve regulating dosage. The analyzer will have continued value through the life of the ISS and into developing a base on the moon. Finally, the knowledge gained will undoubtedly be critical to the strategy of traveling to Mars safely. The proposed analyzer will also have a substantial impact on the health of a significant portion of our population, the elderly, in its ability to measure bone-loss bio-indicators, as well as the drugs being used to treat osteoporosis. Osteoporosis, a condition correlated to enhanced bone fragility and increased risk of fracture. As of 2006, osteoporosis effects 55% of the US population over age 50. More than 50% of healthy American women aged 30-40 are likely to develop vertebral fractures as they age due to osteoporosis.92 Each year, more than 250,000 hip and 500,000 vertebral fractures occur in postmenopausal women in the USA.93 In 2006, it was estimated that fractures represent a $17 billion annual cost to the US healthcare system. The World Health Organization has declared osteoporosis the 2nd largest medical problem, next to cardiovascular diseases.94 Unfortunately, treatment is at best partially successful once progressive bone weakening has started. The primary method of detecting osteoporosis is the measurement of mineral density and bone mass using dual-energy X-ray absorptiometry, which lacks sufficient image quality to adequately detect early stages. It provides a standard (adult) density (SD) score, SD = 0 = healthy, SD = -2.5 onset of osteoporosis. Recently, studies have identified pyridinoline and deoxy-pyridinoline as degradation products of type 1 collagen. Not only can these bone-loss indicators be detected in urine, their concentrations have been found to decrease in response to certain drug therapies, suggesting their use in monitoring treatment efficacy.93 Two methods are currently being developed to detect these bio-indicators, high-performance liquid chromatography (HPLC) and immunoassay. HPLC methods are slow (30-min per analysis), labor intensive, and require daily calibration, while immunoassays are notoriously inaccurate. The proposed lab-on-a-chip, coupled to a Raman analyzer, could be used by clinical labs that perform blood and urine analysis (e.g. Quest Diagostics). The family physician would simply check “test for osteoporosis” during annual physicals for patients. One milliliter of the urine sample is injected into a disposable lab-on-a-chip ($25), it is placed on the Raman Analyzer ($75,000), and a “score” is reported (0 to -5 SD). The process takes 5 minutes. This compares favorably to performing x-rays (machine costs $300,000) and the x-ray cost (>$100 and 30 min analysis time), which is not covered by most insurance. Furthermore, the patient does not have to make separate appointment. RTA plans to pursue a marketing agreement with Quest Diagnostics.

Part 6: Contacts Principle Investigator: Dr. Frank E. Inscore (860-528-9806, x128, [email protected]), a Research Scientist and Manager of Raman Applications at RTA, will be the Principal Investigator of this program. Dr. Inscore received his Ph.D in May of 2000 under Prof. Martin L. Kirk at the University of New Mexico. His research was directed towards elucidating the electronic structure of Mo and W complexes employing a combined spectroscopic and theoretical approach that focused primarily on the use of Raman spectroscopy. The PI has considerable expertise in CCD dispersive systems, and in designing sampling configurations under a variety of conditions (cryogenic/ anaerobic) employing Raman. The PI was previously the manager and key designer for the Raman Lab of Dr. Martin Kirk at the University of New Mexico as a graduate student (Research Assistant). As a Research Associate at the University of Arizona with Prof. John H. Enemark he examined simple and complicated inorganic systems as structural and electronic models of metalloprotein active sites where he further employed his expertise in Resonance Raman spectroscopy. The PI has over 12 years experience with vibrational/Raman spectroscopy, and has published peer-reviewed articles regarding instrumental set-up and analysis of Raman and other spectroscopic data collected.40,41,42,43 The PI has also presented relevant research at three national ACS meetings, a Gordon Research


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Conference, two SPIE presentations, and a Pittsburg conference. The PI has also gained extensive experience in sol-gel chemistry and surface-enhanced Raman spectroscopic applications at RTA. Since joining RTA, Dr. Inscore has performed critical development work of RTA’s SER-active capillaries. He has successfully used this technology to measure chemical warfare agents and their hydrolysis products, and trace pesticides residues. He was also a major contributor for detecting dipicolinic acid extracted from Bacillus anthracis spores on surfaces. This program represents Dr. Inscore’ first SBIR win. He is on 1 patent and 4 pending. Principal Investigator: Dr. Frank E. Inscore, Research Scientist, Real-Time Analyzers, Inc. Education University of New Mexico - Ph. D. Chemistry - 2000 University of New Mexico - B. S. Chemistry Major/Applied Mathematics Minor - 1993 Austin College - B. A. Biology - 1986 Experience Real-Time Analyzers, 2003 – present Manager of Raman applications at RTA: responsible for Raman research and development. University of Arizona, 2000-2003 Post doctoral Research Associate for J.H. Enemark, University of Arizona. Managed group research program: responsible for synthesis/purification of 1st generation geometric and electronic structural models of metalloenzyme active sites, and subsequent characterization via NMR, FAB/ESI-MS, IR/Raman, XRD, XAS/EXAFS, UV-vis/NIR absorption, gas-phase/solution anionic PES, CW/pulsed-EPR spectroscopies, and DFT computations. Additional responsibilities included isolation/purification of various metalloproteins via chromatography, HPLC and FPLC. University of New Mexico, 1994-2000 Research Assistant for M.L. Kirk University of New Mexico. Built and managed Raman facilities: responsible for probing contributions to structure/function relationships in enzyme active sites using resonance Raman, VT-MCD/CD, and UV-vis/NIR absorption spectroscopy. Honors and Awards Research Award of Excellence 1998 &1999 DOE GAANN Fellowship 1994 -1996 Dean Uhl Award for Excellence in Chemistry 1994 Inducted Kappa Mu Epsilon National Mathematics Honorary 1993 Program Manager: Dr. Stuart Farquharson (860-528-9806, x127, [email protected]), President at Real-Time Analyzers will be the Program Manager. He has extensive experience in designing and developing both infrared and Raman spectrometers for multiple industrial applications.95 While employed by the Dow Chemical Company, he designed and integrated a Fourier transform infrared spectrometer into a polymer production plant, for continuous process control. The PM designed and patented the required sample system, designed the optical interface, installed the instrument, and assisted in designing user-friendly data analysis software to ensure customer satisfaction. The PM has extensive experience in Raman and surface-enhanced Raman spectroscopic applications, as well as instrument design, and has published 50 papers in scientific journals and holds 6 patents in the field. He has been a Chair or Co-chair at 10 SPIE Conferences. He has been an invited speaker at more than 20 conferences. In 2002 this includes the Pittsburgh Conference (New Orleans, LA, March), CPAC Summer Institute (Seattle, WA, June), Gordon Research Conference (Newport, RI, July), FACSS (Providence, RI, October), and Eastern Analytical Conference (Somerset, NJ, November). Dr. Farquharson’s resume is available upon request, and is provided in the Phase I and II proposals. Senior Investigator: Mr. Chetan Shende (860-528-9806, x134, [email protected]), a senior chemist at Real-Time Analyzers, will be a senior investigator. He recently completed his MS in Analytical Chemistry from the University of South Florida, under the direction of Dr. Abdul Malik. His main research area was developing column technology for analytical micro-separations using sol-gel chemistry based systems. His MS thesis work involved developing Open-Tubular columns for high resolution capillary gas chromatography (CGC), using polyethylene glycols (PEG) as the stationary phase. Mr. Shende has expertise in sol-gel synthesis and coating capillary columns. His resume is available on request. NASA Technical Representative: Robert Hawersaat (216-433-8157, [email protected]). Hamilton Sundstrand Contact: Patricia O’Donnell, Program Manager (860-654-5649, [email protected])


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Part 7: Future Technical Activities The overall objective of the proposed program (through Phase III) is the development of an analyzer integrated into the International Space Station (ISS) toilets capable of immediate detection of key chemicals in urine to monitor and assess astronaut health. During Phase I we initiated conversations with Hamilton Sundstrand (HS), and discussed the design for their toilet and water reclamation systems to be integrated into Node 3. We also proposed to test our chip performance using HS’s Raman system being developed for a Mars mission. Dr. Farquharson visited HS in Pomona, CA and found that HS only built a single prototype that was unavailable for tests. However, RTA has developed a very rugged Raman analyzer, which may be suitable for space operation (~ 1/5th the weight of the HS prototype), and integration into their toilet system. This is still the desired goal of this program as HS’s Node 3 Water Processor system is finally being integrated into the ISS (Shuttle Mission: 20A/STS-122). As described in Task 6 above, the analyzer will be comprised of three major components: a urine capture device, a lab-on-a-chip, and a Raman analyzer. The entire analyzer will be sufficiently small to fit into a standard ISS integrated rack (IR). In use, 1 ml urine sample will be extracted from water reclamation line exiting HS’ toilet and collected into one of six sample containers (bladder), one per astronaut (ISS capacity). This will be performed 10 times during a 24 hour period per astronaut for a total of 10 mL each. From these individual bladders, we expect to draw 1 mL per analysis per day. We will work with HS to develop a rinse cycle to flush the sample containers once a day after each analysis. The lab-on-a-chip will be designed on a 12-cm disk (1 disk per astronaut, 10 or 30 days of analysis, versions 1 and 2) that will contain 10 or 30 identical pie “slices”, each section self-contained with full extraction/separation capabilities and SERS-activity for detection. The disk will rotate once a day for a new urine analysis. This approach will virtually eliminate the potential for cross-contamination. Multiple disks per astronaut or higher lab-on-a-chip channel densities can be used for longer missions. Mission Tests (Phase III). The overall objective of this task is to test the space-worthiness of the proposed lab-on-a chip. We have supplied NASA with 20 SERS-chips so that some can be 1) tested in space and 2) used to measure actual astronaut urine brought back to earth. Phase III commercialization tests will begin with comprehensive analysis of osteoporosis, including analysis of new bis-phosphonate drugs as they become available (e.g. with Pfizer), and ultimately lead to preliminary clinical tests (possibly at the Nevada Cancer Institute.)

Part 8: Potential Customer and Commercialization Activities 8.1. The Company: Real-Time Analyzers, Inc. (RTA, www.rta.biz) - The mission of Real-Time Analyzers is to develop, produce and market analyzers that detect, identify and quantify trace chemicals in real-time, in industrial or field settings, either continuously or on-demand. Real-Time Analyzers is a spin-off company of Advanced Fuel Research launched September 1, 2001. RTA was formed to consolidate and commercialize the considerable expertise in Raman and surface-enhanced Raman spectroscopy developed at AFR into a focused product line. This approach of bringing high-technology products to market was recently validated when AFR sold its first spin-off company, On-Line Technologies to MKS Instruments, Inc. for over $20 million. Dr. Stuart Farquharson has developed a formal Business Plan for RTA focusing on the Chemical Manufacturing Industry (agricultural chemicals, fine chemicals, petroleum products, polymers, and pharmaceuticals). Dawnbreaker provided the basic tools for developing this Business Plan (www.dawnbreaker.com through DOE sponsorship). Foresight is currently performing an osteoporosis market analysis. The Business Plan is a two phase growth strategy, 1) design, develop, market and sell a portable fiber optic based FT-Raman instrument (Industrial Raman Analyzer, IRA), and 2) develop a trace chemical analyzer (Surface-enhanced Raman Analyzer, SERA) for environmental, pharmaceutical, medical applications and homeland security. The IRA is being marketed to 1) Homeland Security, 2) the DOD, and 3) the Chemical Manufacturing Industry. RTA completed the first growth Phase as of June 2006 when it sold its first two analyzers! Since that time RTA has sold 4 more analyzers, penetrating each of these 3 markets! Initially, Dr. Farquharson was the only full-time employee with 4 part-time employees occupying 600 sq. ft. Early growth has been focusing on product and application development. In January 2002, two AFR employees, an



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instrument design engineer and a PhD chemist, transferred to RTA. In June 2002 RTA hired a mechanical engineer, an optics engineer, and a chemical engineer. In January 2003 RTA added two PhD Raman spectroscopists, an MS sol-gel chemist, and a full-time accountant. The engineers focus on developing the IRA, while the chemists focus on developing the SERA and applications. In January 2004 RTA added a product engineer with 12 years experience producing FT-infrared spectrometers. RTA currently has 7 full-time employees (all with shared and/or overlapping management, technical and manufacturing responsibilities). RTA moved into new facilities in 2005 (5000 sq. ft. of office, lab, and manufacturing space). RTA currently employs several consultants and subcontractors to meet their R&D and manufacturing needs.

RTA’s Revenues 2004-7.

8.2. Markets. This program has provided the foundation for an osteoporosis product, the Urine-analySER. This product and market are part of RTA’s second growth phase, selling SERA products. Osteoporosis – When we submitted this proposal in 2005, there were 10 million men and women suffering from osteoporosis in the USA. As of 2006, there are 44 million US patients! Each year, more than 250,000 hip and 500,000 vertebral fractures occur in postmenopausal women in the USA.93 And more than 50% of healthy American women aged 30-40 are likely to develop vertebral fractures as they age due to osteoporosis. Metabolic bone and joint diseases (osteo-arthritis, cancer, etc) account for an additional 12 million cases of accelerated bone loss per year.92 The World Health Organization has declared osteoporosis the 2nd largest medical problem, next to cardiovascular diseases.94 The estimated yearly cost associated with acute hospital care and rehabilitation was estimated at $17 billion for 2006.93 Unfortunately, treatment is only partially successful once progressive bone weakening has started. Therefore, it is important to identify this condition at an early stage, so that treatment focuses on prevention instead of fixing fractures and attempting to reverse bone loss. Nevertheless, it should be noted that drugs developed to prevent, mitigate or even reverse bone loss are showing signs of success. The primary method of detecting osteoporosis is the measurement of mineral density and bone mass using dual-energy X-ray absorptiometry, which lacks sufficient image quality to adequately detect early stages. More accurate analyses, such as bone biopsies, have been developed, but are undesirably invasive. Recently, studies have identified pyridinoline and deoxypyridinoline as degradation products of type 1 collagen. Not only can these bone-loss indicators be detected in urine, their concentrations have been found to decrease in response to certain drug therapies, suggesting their use in monitoring treatment efficacy.92 Two methods are currently being developed to detect these bio-indicators, high-performance liquid chromatography (HPLC) and immunoassay. HPLC methods are slow (30-min per analysis), labor intensive, require daily calibration, and high up front and maintenance costs have limited their market acceptance. Immunoassay kits (colorimetric microassay plate enzyme immunoassay) have been developed to measure total deoxypyridinoline in urine. However, the analysis requires complicated hydrolysis, incubation and assay steps totally 48 hrs prior, which must be followed precisely to obtain quantitative results. The Urine-analySER could be used to rapidly detect and quantify pyridinoline, deoxypyridinoline, and other biomarkers in urine and assess patient risk, stage, or response to treatment. 8.3. Commercialization Strategy -The overall commercialization strategy is to bring Real-Time Analyzers products to market through strategic partners with the aid of leveraged investment. This strategic path to commercialization involves the following specific steps: 1) Form a spin-off company to consolidate expertise and develop a focused product line (RTA has 4 scientists with over 40 years of Raman experience, and engineers with over 35 years experience designing spectrometers). 2) Develop a superior produce with substantial patent coverage

Revenues 2004 2005 2006 2007 Employees 9 8 8 9-12 Analyzer Sales $122,000 $300,000 Service Contracts $28,500 $2,500 $125,000 $400,000 Vial Sales $12,000 $12,000 $12,000 $12,000 SBIR Funding $582,000 $910,000 $717,000 $300,000 % Revenue SBIR 93.4% 98.1% 74.2% 29.6% Total Revenue $622,500 $927,500 $966,000 $1,012,000


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(the superior performance of the IRA is covered by 4 patents, the SERS technology is covered by 3 patent, and 11 more have been filed). 3) Leverage the protected technology to gain market access through strategic partners (see below). 4) Grow value of company so that acquisition is desirable. Strategic Partners - RTA has profiled more than 50 companies in its target markets and has identified several potential Strategic Partners. Initial meetings have been held to describe RTA's mission, technology, market plans, and strategic partnering. Relevant to this program, RTA has met with Hamilton Sundstrand and the Nevada Cancer Institute. RTA plans to initiate discussions with Quest Diagnostics, as well. In each case, RTA plans to sell the beta-unit (based on successful on-site demonstration) and leverage investment against exclusive-use licenses. Developments in Strategic Partnerships with Hamilton Sundstrand and Nevada Cancer Institute, are worth elaborating. In addition, RTA has been actively pursuing matching state funds through Connecticut Innovations. Hamilton Sundstrand Sensor Systems (HSSS, Pomona, CA) is the Sensor Systems business unit of Orbital Sciences bought in 2001 by Hamilton Sundstrand, one of United Technologies Corporation six business units. HS, with annual sales of $3 billion, bought Sensor Systems to complete their portfolio of space-based atmospheric and space station sensor systems.96 Included in this acquisition was Analect, a company with considerable knowledge of chemical analyzers, and an understanding of Raman analyzers. Patricia O’Donnell, business development manager, has been intimately involved in the development of both the HS toilet and water reclamation system. WE hope to collaborate on the development of the proposed analyzer for ISS Node 3 during Phase III. Nevada Cancer Institute (Las Vegas, NV) - NCI began operations in 2005 with the goal of becoming a recognized world-leader performing state-of-the-art research and implementing groundbreaking methods of prevention, detection and treatment of cancer. According to Director Dr. Vogelzang: "It will expand the tools available for the treatment of cancer. That will be our first and primary thrust." NCI has agreed to assist RTA in the development of a chemotherapy drug analyzer based on measurements of saliva using our SERA technology. The importance of measuring bone-loss in urine due to chemotherapy is a natural extension of this technology, and arrangements will be made to perform these critical clinical tests with NCI with the goal of obtaining FDA approval. Quest Diagnostics Incorporated (www.questdiagnostics.com), a $500 million per year revenue company, is the nation's leading provider of diagnostic testing, information and services that patients and physicians need to make better healthcare decisions. QD performs diagnostic laboratory tests for approximately 145 million patients each year, and over 70% of all healthcare treatment decisions. QD has over 2,000 patient service centers. These service centers each represent one Urine-analySER sale. Connecticut Innovations (CI) is charged with growing the economy of Connecticut’s entrepreneurial technology through venture and other investments. RTA has had several meetings with CI over the past 3 years, and they are currently considering a $500,000 investment.

Part 9: Resources Status No government equipment was required for the Phase II program. The following resources at RTA are available. RTA Industrial Raman Analyzer Production (second generation, 3 systems) - RTA latest FT-Raman system is extremely compact and portable. The entire system fits into a single 19” rack mountable box (19x20x7”). The main features are: 1) a diode laser (1 W at 785 nm, Process Instruments), 2) an interferometer with a quartz beam splitter (MKS), 3) a Si avalanche photodiode detector (RTA), 4) numerous fiber optic probes (designed in-house), and 5) a data station consisting of acquisition and analysis hardware and software (OLT, National Instruments, and a Gateway Pentium II personal computer). The system measures Raman spectra from 785 to 1080 nm (0 to 3200 ∆cm-1). RTA Industrial Raman Analyzer Prototype (second generation, 1 system) - RTA’s initial compact FT-Raman system employs a Nd:YAG laser (800 mw at 1064 nm, Keopsis), a compact interferometer (MKS), and an InGaAs detector (RTA). The system measures Raman spectra from 1064 to 1800 nm (0 to 3500 ∆cm-1). The entire system also fits into a single 19” box. RTA Raman Analyzer Research Grade - This system frequency doubles the high powered Spectra Physics laser to


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generate 20 mW of 532 nm laser excitation. This coupled with the second generation IRA that employs silica detection will be used to increase the SER scattering efficiency from 50 to 100 times. This will provide important data regarding potential modifications to the Hamilton Sundstrand Raman system. General Facilities at RTA - RTA has 15 high-end, interconnected personnel and laptop computers, with Internet access. The systems are all also tied into a Snap Server for day-to-day back-up. RTA has an extensive wet lab equipped with two fume hoods for safe preparation of the required samples. A dry box is also available for preparation of oxygen sensitive chemicals. Also available to RTA are full service machine and electronic shops.

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16 Inoue, H., Y.Date, K.Kohashi, , H.Yoshitomi, , and Y.Tsuruta, “Determination of Total Hydroxyproline and Proline in Human Serum and Urine by HPLC with Fluorescence Detection,” Biol Pharm Bull, 19, 163-6 (1996).

17 Strickland, P.T., Kang, D, Bowman, E.D., Fitzwilliam, A., Downing, T.E., Rothman, N., Groopman, J.D., and Weston, A., “Identification of 1-hydroxypyrene Glucuronide as a Major Pyrene Metabolite in Human Urine by Synchronous Fluorescence Spectroscopy and Gas Chromatrography-Mass Spectrometry,” Carcinogenesis, 15:3, 483-7 (Mar 1994).

18 Potember, R.S., W.A. Bryden, M. Antoine, "Quantitative determination of 3-methylhistidine in urine by matrix-assisted laser desorption mass spectroscopy," STAIF- 2000, paper 106 (2000).

19 Leelavathi DE, Dressler DE, Soffer EF, Yachetti SD, Knowles JA, “Determination of Promethazine in Human Plasma by Automated High-Performance Liquid Chromatography with Electrochemical Detection and by Gas Chromatography-Mass Spectrometry,” J Chromatogr, 339:11, 05-15 (1985).

20 Finnigan product literature (www.finnigan.com), $99,950 for tandem mass spectrometer LCQDUO. 21 Kneipp, K., Wang, Y., Dasari, R. R., and Feld, M. S., “Approach to Single-Molecule Detection Using Surface-

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22 Nie, S. and Emory, S.R., “Probing Single Molecules and Single Nanoparticles by Surface-Enhanced Raman Scattering,” Science, 275, 1102 (1997).

23 Farquharson, S. and P. Maksymiuk, “Simultaneous chemical separation and surface-enhancement Raman spectral detection using silver-doped sol-gels”, Applied Spectroscopy, 57, 479-482 (2003). 24 Lee, Y. H.; W. Smith, S. Farquharson, H.C. Kwon, M.R Shahriari, and P.M. Rainey,"Sol-Gel Chemical Sensors

for Surface-Enhanced Raman Scattering Detection," SPIE, 3537, 252-260 (1998). 25 Lee, Y.-H., S. Farquharson, And P. M. Rainey "Surface-enhanced Raman sensor for trace chemical detection in

water," SPIE, 3857, 76-84 (1999). 26 Farquharson, S., "Miniaturized Fiber Optic Chemical Sensor," STTR Final Phase II Report for NASA Grant

Number NAS9-98024 (submitted February 2000). 27 Farquharson, S., and W. W. Smith, W. H. Nelson and J. F. Sperry, ”Biological agent identification by nucleic

acid base-pair analysis using surface-enhanced Raman spectroscopy,” SPIE, 3533, 207-214 (1998) 28 Farquharson, S., and W. W. Smith, S. Elliott and J. F. Sperry, "Rapid biological agent identification by surface-

enhanced Raman spectroscopy", SPIE, 3855, 110-116 (1999). 29 Lee, Y.H. and S. Farquharson, "Rapid chemical agent identification by surface-enhanced Raman spectroscopy",

SPIE, 4378, 21-26 (2001) 30 Lee, Y.H., and S. Farquharson, "SERS sample vials based on sol-gel process for trace pesticide analysis", SPIE,

4206, 140-146 (2001) 31 Farquharson, S., W.W. Smith, Y.H. Lee, S. Elliott and J. F. Sperry, "Detection of biological signatures: A

comparison of electrolytic and metal-doped sol-gel surface-enhanced Raman media", SPIE, 4575, 62-72 (2002) 32 Farquharson, S. and Lee, Y. H., "High Throughput Identification: Drug Analysis by Surface-Enhanced Raman

Spectroscopy", D&MD Focus Reports, 4-7 (March 2001) 33 Farquharson, S, ”Rapid Drug Assay by Surface-Enhanced Raman Spectroscopy,” SBIR Phase I Final Report for

NIH, Grant No. 1 R43 GM54916-01 (4/14/1998). 34 Farquharson, S., Y.H. Lee, H.C. Kwon, M.R. Shahriari, and P.M. Rainey, "Urinalysis by surface-enhanced

Raman spectroscopy," STAIF- 2000, paper 105 (2000). 35 Farquharson, S., and Y. H. Lee, "Trace drug analysis by surface-enhanced Raman spectroscopy," SPIE, 4200,

89-95 (2000). 36 Wentrup-Byrne, E., Sarinas, S., and Fredericks, P.M., “Analytical Potential of Surface-Enhanced Fourier

Transform Raman Spectroscopy on Silver Colloids,” Applied Spectroscopy, 47, 8, 1192-1197 (1993). 37 Farquharson, S., P. Maksymiuk, K. Ong and S.D. Christesen, "Chemical agent identification by surface-

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