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Detecting nitrogen groups at nanomolar concentrations in bovine biological samples using a chemiluminescence… Leemhuis, Jonathan 2020

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 DETECTING NITROGEN GROUPS AT NANOMOLAR CONCENTRATIONS IN BOVINE BIOLOGICAL SAMPLES USING A CHEMILUMINESCENCE NITROC OXIDE ANALYZER  by  JONATHAN LEEMHUIS  B.Sc., Brigham Young University – Idaho, 2012   A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  Master of Science  in  THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES  (Experimental Medicine)    THE UNIVERSITY OF BRITISH COLUMBIA   (Vancouver)   April 2020   © Jonathan Leemhuis, 2020  ii  The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, a thesis entitled:  Detecting Nitrogen Groups at Nanomolar Concentrations in Bovine Biological Samples Using a Chemiluminescence Nitric Oxide Analyzer  submitted by Jonathan Leemhuis  in partial fulfillment of the requirements for the degree of Master of Science in Experimental Medicine  Examining Committee: Dr. Christopher Miller, Ph.D., UBC Faculty of Medicine, Clinical Assistant Professor Supervisor  Dr. Gilly Regev, Ph.D., Sanotize CEO, Former UBC Faculty of Medicine Supervisory Committee Member  Dr. Bevin McMullin, Ph.D., Field Medical Advisor - Pfizer Canada Supervisory Committee Member Dr. Scott Tebbutt, Ph.D., HLI Education Director, UBC Department of Medicine Professor External Examiner       iii  Abstract  The ability to accurately and promptly detect low concentrations of nitrites (NO2-), nitrates (NO3-), and other nitrogen groups, in a range of biological tissues and fluids, is of significant benefit in biological research and for nitric oxide’s (NO) development as a drug. There are several methods used to carry out such analyses, but all vary in their accuracy, selectivity and efficiency. The groundwork for a standard analytical method that is accurate, sensitive, selective, and economical was established. Using a Sievers 280i Nitric Oxide Analyzer (NOA) with a novel, adapted protocol, it was demonstrated consistent measurement of nanomolar (nM) concentrations of nitrite and micromolar (µM) concentrations of total nitrogen groups (TNG) in various bovine biological fluids including blood, milk, urine, and a slurry derived from muscle and fat. Initially, the precision and accuracy of the NOA was tested and defined using nitrite and nitrate standard solutions. Once the testing parameters of the NOA had been established, the nitrite and nitrate levels in biological samples were measured. The various biological samples were spiked with specific concentrations of sodium nitrite or sodium nitrate. Biological fluid samples were analysed by injection into a purge vessel containing an acidified iodide solution or a heated acidified vanadium (III) chloride solution to convert nitrite or the total nitrogen groups to NO. This allowed sensitive analysis of NO through chemiluminescence by the reaction of NO with ozone and subsequent photon emission of the nitrogen dioxide radical (NO2●). The limit of blank (LoB) and limit of detection (LoD) were used as a measure of reliability. This novel method was shown to have reliable and robust performance in the measurement of nM concentrations of nitrites and µM concentrations of TNGs in a range of biological tissues and fluids.   iv  Lay Summary  Nitric oxide is important to mammalian physiology and has therapeutic potential. It is very important to measure nitrogen oxides (NOx) to understand this. Few analytical technologies have been designed to measure NOx in samples like milk and muscle. This project was designed to develop two methods that detect NOx groups by chemiluminescence better than current methods in biological mediums. Sample preparation, storage, and analysis should be simple, easily accessible, and quick for practical application. The goal of this thesis was to prepare, process, and analyze biological samples for their NOx content. The results were sensitive and reliable. The methods to analyze NOx, were more efficient and sensitive than common laboratory methods. Processing with ethanol was successful and extracted interfering compounds. Storage in a -20°C freezer was also effective. These methods to measure nitrite and nitrate are useful and effective techniques to quantify NOx in mammalian samples.    v  Preface  The majority of the work for this dissertation—project details, sample processing, data gathering, data analysis, and composition—was performed by the author, J. Leemhuis.   Dr. G. Regev assisted with project design and schedule. Dr. M. Sheridan, a post-doctoral fellow assisted with designing a data gathering schedule and writing the abstract. The UBC Statistics Department gave advice on graphing data and potential methods of data analysis.  Methods involving the Sievers Nitric Oxide Analyzer were adapted from standard operating procedures developed in Dr. Miller’s laboratory and device operator’s manuals. Ideas for sample processing methods were obtained through a literature search of previously published materials. Instrument qualification methods and data were gathered during a joint project with Elanco Pharmaceuticals.   vi  Table of Contents  Abstract .................................................................................................................................................... iii Lay Summary ........................................................................................................................................... iv Preface ....................................................................................................................................................... v Table of Contents ..................................................................................................................................... vi List of Tables ......................................................................................................................................... viii List of Figures .......................................................................................................................................... ix List of Abbreviations ................................................................................................................................ x Acknowledgements ................................................................................................................................. xii Dedication .............................................................................................................................................. xiii 1. INTRODUCTION ............................................................................................................................. 1 1.1. Occurrence, Production, and Metabolites. ................................................................................. 1 1.2. Common Methods of Quantification. ........................................................................................ 2 1.3. Use of Chemiluminescence for Quantification. ......................................................................... 4 2. EXPERIMENTAL DESIGN ............................................................................................................. 7 2.1. Chemicals ................................................................................................................................... 7 2.2. Instrumentation and Equipment ................................................................................................. 7 2.3. Instrumentation Methods ........................................................................................................... 7 2.4. Instrument Qualification ............................................................................................................ 8 2.5. Linearity ..................................................................................................................................... 8 2.6. Precision and accuracy ............................................................................................................... 9 2.7. Selectivity................................................................................................................................... 9 2.8. Robustness ................................................................................................................................. 9 2.9. Biological Sample Processing .................................................................................................. 10 2.10. Sample Analysis ....................................................................................................................... 11 2.11. Data Analysis ........................................................................................................................... 11 vii  3. RESULTS AND DISCUSSION ...................................................................................................... 14 3.1. Instrument Qualification .......................................................................................................... 14 3.1.1. Linearity ........................................................................................................................... 14 3.1.2. Precision and Accuracy .................................................................................................... 14 3.1.3. Selectivity ......................................................................................................................... 16 3.1.4. Robustness ........................................................................................................................ 17 3.1.5. Conclusions of Qualification ............................................................................................ 17 3.2. Biological Sample Spiking....................................................................................................... 18 3.2.1. Milk .................................................................................................................................. 18 3.2.2. Urine ................................................................................................................................. 19 3.2.3. Blood ................................................................................................................................ 20 3.2.4. Meat .................................................................................................................................. 22 3.2.5. Fat ..................................................................................................................................... 23 3.2.6. Conclusions of Biological Sample Spiking. ..................................................................... 24 4. CONCLUSION ............................................................................................................................... 28 Bibliography............................................................................................................................................ 30 Appendix A – Figures and Tables........................................................................................................... 34 Appendix B – Recommended Standard Operating Procedure for Biological Sample Assays ............... 39    viii  List of Tables  Table 1 - Precision and accuracy of the nitrite and TNG methods determined in qualification 34 Table 2 - Selectivity data from instrument qualification  35 Table 3 - Limit of Blank, Limit of Detection, and Standard Error of the Limit of Detection for each method with varying biological media  37 Table 4 - Robustness test of age on change in reducing solution effectiveness  37 Table 5 - Comparison of meta- and mega- analyses of slopes from the nitrite and TNG method  37   ix  List of Figures  Figure 1 - Basic comparison of the nitrite and TNG methods  33 Figure 2 - Diagramed explanation of the processing steps of biological sample analysis  33 Figure 3 - Linear regression of standards analyzed with the nitrite and TNG methods  34 Figure 4 - Graphs to visualize the precision and accuracy of the nitrite and TNG methods  35 Figure 5 - Linear regression of nitrite spiked biological media  35 Figure 6 - Linear Regression of nitrate (NO3-) spiked biological media  36 Figure 7 - Meta-Slope analysis for each sample media type  36   x  List of Abbreviations %diff.  Percent difference  %RSD  Percent relative standard deviation AUC  Area under the curve  CO(NH2)2 Urea  DIH2O  Deionized water  eNOS   Endothelial Nitric Oxide Synthase  etOH   Ethanol  gNO   Gaseous Nitric Oxide  GAA   Glacial Acetic Acid  HPLC   High-pressure liquid chromatography  HCl   Hydrochloric acid  iNOS   Inducible Nitric Oxide Synthase  LoB   Limit of Blank  LoD   Limit of Detection  meas  As-Measured  µM   High concentration  MetHb  Methemoglobin  MS   Mass Spectrometry  NaI   Sodium iodide  NaOH   Sodium hydroxide  NH3  Ammonium solution  nM   Low concentration  nNOS   Neuronal Nitric Oxide Synthase  NOA   Sievers Nitric Oxide Analyzer 280i  NO3-  Nitrates  NO   Nitric Oxide  NOS   Nitric Oxide Synthase  NO2-  Nitrites  prep   As-Prepared  RNNO  N-nitrosamines  RSNO  S-nitrosothiols  xi  TNG   Total nitrogen groups  VCl3  Vanadium (III) Chloride    xii  Acknowledgements Thanks goes to all those who have been in the Miller Nitric Oxide lab from the beginning of this project, specifically Dr. Chris Miller, Dr. Gilly Regev, James Martins, and Dr. Bevin McMullin for their help, examples, and encouragement to start the master’s program. Thanks also goes to Dr. Michael Sheridan for helping me get my data gathering on track and helping me start the writing process. Special thanks go to Dr. Gilly Regev for her insight and ideas that helped guide the project during its course. Thanks also goes to my external examiner, Dr. Scott Tebbutt, and examining committee chair, Dr. Jeffery Joy, who each stepped in at the last minute when emergency adjustments needed to be made the week before my master’s thesis defence.  Special thanks to my mom who provided me a location to live and rest during the majority of my degree which eased much of the financial burden of being a graduate student. Thanks also to my siblings, friends, and co-workers whose encouragement and enthusiasm helped me push through to the end. Thanks also to them for their patience in allowing me to put priority on my project and course work. Thanks to my wife, who encouraged me and inspired hope and diligence to reach the goals I set to finish my degree. She also patiently lifted my spirits when setbacks threatened or required changes in those goals. Additional thanks go to my classmates, desk buddies, and other staff who made working and learning throughout this degree at the University of British Columbia fun and engaging.    xiii  Dedication  To my father. He taught me to look at the world from many perspectives.   1  1. INTRODUCTION 1.1. Occurrence, Production, and Metabolites. Nitric oxide (NO) is a small molecule that performs many physiological roles from cell signaling to immune response.1-3 It is a highly reactive radical with a free electron located on the nitrogen atom. NO does not spontaneously form at standard temperature and pressure due to the endothermic nature of the reaction between oxygen (O2(g)) and Nitrogen (N2(g)) gasses. Though small amounts of gaseous nitric oxide (gNO) is produced during lightning strikes, a much greater amount is artificially created when O2(g) reacts with N2(g) during combustion of hydrocarbon-based fuels. The released gNO further reacts with atmospheric O2(g) forming oxides of nitrogen (NOx) that become a major component of air pollution and acid rain. These oxides are pollutants when released into the environment; however, NOx salts and solutions are utilized in food processing and production as preservative for meats. They are also found naturally and abundantly in many plants and common root and leafy green vegetables. Though nearly innocuous in the concentrations present in these foods, high enough doses could inhibit the ability of hemoglobin to bind O2. Therefore, reliable and sensitive analysis methods are beneficial to many industries in addition to safety authorities and medical therapeutics. Biologically, NO is endogenously synthesized in the human body through the enzymatic action of nitric oxide synthases (NOS), O2, and L-arginine. There are three types of NOS: neuronal (nNOS), endothelial (eNOS), and inducible (iNOS). The first two are calcium dependent and produce a small amount of NO for localized use: smooth muscle relaxation, synaptic plasticity, vasodilation, and regulating vascular function.4, 5 The latter of the three, iNOS, is calcium-insensitive, and can produce large amounts of NO upon stimulation during a proinflammatory response.5, 6 NO has a half-life in the body of less than six seconds, and a radius of biological action of approximately 200 µm from its site of origin.7 Beyond this point it is inactivated through loosely binding to sulfhydryl groups of cellular thiols or by nitrosylation of the heme moieties of hemoglobin to form methemoglobin (MetHb)8, 9. The conversion of methemoglobin back to hemoglobin through the interaction with the enzyme MetHb reductase releases the NO into the blood where it is oxidized into nitrites (NO2-) and nitrates (NO3-). The conversion of NO into NO2- and NO3- is a major pathway for NO in aqueous solutions in general. Metabolites of NO in the body include the two nitroxides listed above, and also S-nitrosothiols (RSNO) and N-nitrosamines (RNNO).10, 11 Though this is present in our knowledge base now, it wasn’t until the early 1990s that NO was first measured using electron paramagnetic resonance. 2  This was done after isolating heme like molecule which had bound NO. This method would have been lengthy and labour intensive, leading to the innovation of, and resulting in, specified methods for the purpose of measuring NO and its related analytes. 1.2. Common Methods of Quantification. As stable metabolites, NO2- and NO3- are often quantified in order to indirectly measure NO. As a result, multiple analytical techniques and instruments have emerged.12 One of the most prominent methods of NO2- and NO3- measurement is by using the Griess reagent.13-15 An azo dye in the reagent binds with NO2- producing a colour with peak absorbance at 540 nm. The colour intensity, as measured by a UV-Vis spectrophotometer, is correlated to the concentration of NO2- in the solution. The process is repeated after enzymatically reducing NO3- to NO2- to quantify both metabolites. The overall assay is quick and uses equipment readily available to most labs. The cost of a UV-Vis spectrometers ranges from $5,000 to $20,000 CAD depending on options and abilities like wavelength range, cuvette count and size, and resolution. It’s per sample costs are also quite low—from $1.50 CAD to upwards of $200 CAD—and depend on the number of samples tested and how often solutions and supplies are replaced. Even at the upper price range of the analyzer the Griess reagent combined with UV-Vis is not reliable for detecting concentrations below the micromolar range, and error from poor pipette techniques or contaminated dilutants can easily lead to spurious results. Analysis by Griess reagent methodology also fails when a solution medium is something other than a clear ionic solution; the inherent color and opacity of a medium obscures the absorption of light needed for the method. Electrochemistry, a staple of many labs due to the wide availability of pH meters, is another common method that uses ion-selective probes to measure NO or its metabolites.16, 17. It is not an expensive method as set-ups of ion selective probes and an accompanying meter start around $3,000 CAD and per sample costs can be <$0.01 CAD. This increases as electrodes selective for other ions are added and options and outputs are added to the meter, but costs typically won’t go over $10,000 CAD. However, the main challenge with these methods is that measurable sample sizes depend on the size of the probe itself and assays using electrochemical probes often require sample sizes greater than one milliliter. These versions of ion selective electrodes typically have stable detection to the micromolar range; however, there are ion-selective probes for micro analysis of NO2- and NO3-. Such micro analysis systems require more complicated chemistry by using nonstandard filling solutions, are difficult to calibrate and keep calibrated, and require non-commercially available surface modifications for probes to obtain a 3  greater range of detection.17, 18 Customizing probes and solutions can add thousands more dollars in costs to an ion selective instrument before an assay can be attempted reliably. Analysis also becomes impractical due to the requirements for efficiency when using biofluids such as blood and saliva and to the need for constant calibration, or adjustments due to custom modifications may slow the process down. Another common method for measuring NO metabolites is high-pressure liquid chromatography (HPLC).11, 19, 20 HPLC is utilized in highly vetted methods to measure NO metabolites, and is used to get precise measurements into the low micromolar range. These methods are coupled with colorimetric analysis like Griess reagent or fluorometric methods using UV detection. An HPLC instrument can also be coupled with an auto sampler, increasing ease and throughput. However, these systems require columns, carrier solutions, and are often quite expensive. High costs make them not easily accessible, and estimates can start around $15,000 CAD for a used system. Adding accessories, like auto samplers and additional columns, can quickly add multiple thousands to the cost making it not uncommon for a lab to spend $60,000 to $120,000 on an HPLC system. Furthermore, significant sample preparation is required for methods including HPLC, which increases the risk of altering the target analytes decreasing accuracy and precision. Because of the cost involved with obtaining an HPLC system, many labs that only require a few samples will hire another lab to have them analyze their samples or have them develop a method. This can range anywhere from $100 to upwards of $1000 CAD per sample depending on how involved the analyzing lab is required to be. The most sensitive method used for analysis of NO metabolites is mass spectrometry (MS).21 Since MS directly detects the mass of particles composing a sample, it can be used to easily differentiate between different NO metabolites while requiring little sample preparation. Properly calibrated, MS can separately detect all forms of NxOx, including differing isotopes of each atom, resulting in a much clearer picture of NO metabolites than other methods.22 The method’s disadvantages are its longer assay times and high cost for equipment purchase and maintenance. Prices for MS instruments begin around $150,000 CAD and need to be coupled with a gas column or a liquid column which costs an additional $50,000 to $100,000 CAD. Purely academic labs can manage with a less expensive model, but industry requiring continuous sampling or sampling at a much higher quantity or quality can easily spend more for instruments with greater detection, autosamplers, and replacement columns (gas or liquid) adding much more in per sample costs which can range from $50 to over $1000 CAD. Since most assays requiring 4  the measurement of NO2- and NO3- do not merit this level of precision, the cost of this technique is largely unwarranted.  1.3. Use of Chemiluminescence for Quantification. Another measurement technique for NO metabolite analysis, more frequently used over the last few decades, is chemiluminescence.20, 23 Nitric oxide analysis by chemiluminescence was developed to directly and accurately measure gaseous NO through its reaction with ozone and subsequent decay of the nitrogen dioxide radical: NO + O3 → NO2* + O2 NO2* → NO2 + hv With the use of a photomultiplier tube and a red light filter blocking wavelengths <600nm, the intensity of the light emitted from this reaction is used to determine the amount of NO entering the instrument’s reaction chamber.24 When plotted against known standards, the signals produce a linear range of response that is sensitive enough to detect picomoles of NO.25 Quantitative analysis of NOx- can be attained by combining this technique with a method using a reducing agent in a purge vessel to convert NO’s metabolites back into NO and then use an inert carrier gas to transport the NO to the reaction chamber. The reducing agent can vary depending on the desired targets: Vanadium (III) chloride (VCl3) in 95ºC 1.0 M HCl can be used to reduce nitrogen from an oxidation state of +5 to its +2 state in nitric oxide whereas sodium iodide (NaI) in room temperature glacial acetic acid is limited to reducing nitrogen from an oxidation state no higher than +3. Biological samples have oxygen bound nitrogen containing species such as: NO3-, NO2-, RSNO, and RNNO each with an oxygen bound nitrogen having oxidation states of +3 or higher. Though RNNO can be detectable in individuals with environmental exposure, it is likely that biological samples will have undetectable amounts of RNNO since their formation requires free secondary amine groups and a highly oxidative environment (from either high heat or high acidity) to be created in a stable manner.26-28 However, RSNOs do occur quite readily in blood as erythrocytes’ cellular mechanisms begin to convert NO2- and NO3- to RSNOs for physiological use.29 The VCl3 reducing agent can be used to detect total nitrogen groups (TNG) in a sample, and when a sample contains primarily NO2- and NO3- the selectivity of the NaI reducing agent can separate the two concentrations through subtraction.30  This combination of the selectivity from the reducing agents with the sensitivity from the instrument provides for the analysis of nanomolar concentrations in µL samples. Chemiluminescence assays also provide quick analysis with some instrument models allowing for nine samples measured every 15 min. 5  Since the scope of this project requires the analysis of varying biological media and timely analysis of sample sets at potentially the nM range, the utility and specifications provided by the Sievers Nitric Oxide Analyzer 280i (NOA) (GE Analytical Instruments; Boulder, CO, USA) are potentially well suited for measurement of biological tissues and fluids. In addition, the analyzer, glass ware, and reagents are comparatively economical ($25-$35,000 CAD; $0.34 to $574 CAD per sample). To analyze biological media (blood, urine, milk, muscle, fat, etc.), the NOA, like most other analytical instruments, also requires sample processing. The presence of proteins or lipids in these biological samples can cause problems in the purge vessel such as the foaming of the reducing agent or the accelerated buildup of residue on the purge vessel’s sintered glass frit. These require frequent cleaning of the purge vessel with its associated glassware and tubing. Protein contaminants in the reducing solution can also cause signal interference by providing binding sites for NO reduced from its metabolites. This is particularly important regarding RSNOs because their oxygen bound nitrogen has an oxidation state of +3 like nitrite,31 and thus a process that will reduce their concentration to a negligible level is ideal. The RSNOs of note for this project—S-nitrosoalbumin, S-nitrosoglutathione, and S-nitrosohemoglobin—are all large enough to be removed in a crystalized protein precipitate. An effective, yet simple, method of removing proteins and lipids from these biological samples is by precipitation using a centrifuge and cold ethanol (EtOH). EtOH has been shown as an ideal choice since it can be stored easily, does not cause interference with the NOA, and is documented as an effective way to crystallize proteins.32  Changes made to the manufacturer’s analytical methods require qualification and validation. For example, an instrument and method previously approved will need further assessment when additional steps, such as sample processing and reduction reactions, are included in a method. A large part of this process includes finding what can be called the limit of blank (LoB) and limit of detection (LoD): a statistical way of determining the extent to which the new method is effective. Determining these limits for the entire process helps the researcher to know it can quantify a given analyte, in this case NO metabolites. Combined, the LoB and LoD clarify the detection ability and precision of a method in a robust and reliable way.30, 33  The LoB is the measured values at which a detectable sample becomes indistinguishable from the blank sample. The LoD is the measured value at which positive identification of a signal is significant, or the lowest possible mean whose 95% confidence interval does not include the 6  LoB. Each limit should utilize a recommended minimum of 60 samples to be established for a given method. This is done to provide robustness in the calculation, but it comes as a recommendation to adapt to research budgets and minimize requirements. These limits can be used later to determine the limit of quantification, and further the accuracy of the new method. The latter is one of the final steps before a new method’s validation and falls outside the scope of this project. There is limited data in the literature regarding the selectivity and robustness of NOA methods in measuring NO metabolites, and little data describing the NOA’s precision, accuracy, or detection potential.30 Moreover, there is no comparison of the capability of the NOA to measure accurately and repeatedly NO2- and NO3- in different biological mediums. Based off what can be inferred from literature, manufacturer specifications, and experience with other analytes, the NOA is an excellent choice for the analysis of NO metabolites in biological media at detection ranges suitable for therapeutic analysis. This work is aimed to explore the parameters of the NOA and qualify methods for the analysis of NO metabolites in biological mediums by determining their reliability through slope regression and finding the LoB and LoD.33   7  2. EXPERIMENTAL DESIGN 2.1. Chemicals. Sodium nitrite (NaNO2), sodium nitrate (NaNO3), sodium iodide (NaI), vanadium (III) chloride (VCl3), and ammonium solution (NH3) were purchased from Sigma-Aldrich (St. Louis, MO, USA); urea (CO(NH2)2) was purchased from Fisher Scientific (Fair Lawn, NJ, USA); sodium hydroxide (NaOH), hydrochloric acid (HCl), and glacial acetic acid (GAA) were purchased from Anachemia through VWR (Radnor, PA, USA); bovine samples of milk, blood, and urine were obtained from the University of British Columbia Dairy Farm (Agassiz, BC, Canada); compressed nitrogen and oxygen were obtained from Praxair (Mississauga, ON, Canada); and isotonic saline was purchased from Baxter (Mississauga, ON, Canada). Packaged cuts of raw beef as a source of muscle and fat tissue were obtained from various butchers and grocery stores in Vancouver, BC. Deionized water (DIH2O) was obtained from a Milli-Q water system with Q-POD from Millipore installed in the lab (18.2 MΩ, 3 ppb TOC, Etobicoke, ON, Canada). 2.2. Instrumentation and Equipment. The chemiluminescence instrument used was a Sievers Nitric Oxide Analyzer 280i including the liquid analysis bundle with purge vessel, bubbler, and tubing (GE, Boulder, CO, USA). Temperature control for the water jacket on the purge vessel was done with a circulating water bath (VWR Scientific Products by PolyScience, Niles, IL, USA). Flow rate was measured and monitored using a 4100 series thermal mass flow meter (TSI, Minnesota, USA). Standards and samples were prepared using volumetric flasks (200 mL KIMAX, Rockwood, TN, USA; 10 mL VWR, Mississauga, ON, Canada); Dicing was done with disposable scalpels (Jai Surgicals Ltd, Gurgaon, India), sonication was performed with a Heat Systems Ultrasonics Microson Ultrasonic MS-50 Cell Disruptor (80-100% power output, now Qsonica, LLC, Newtown, CT); and filtration was done with Whatman No. 1 filter paper. Sampling of standards and solutions was done with 100-250 µL syringes (VICI, Brockville, ON, Canada; Hamilton, Reno, NV, USA). A Centrifuge 5418 R (Eppendorf Canada, Mississauga, ON, Canada) was used during sample preparation. 2.3. Instrumentation Methods. Two reducing methods were used for analysis: one, the nitrite method for analysis of NO2-, and two, the TNG method for analysis of NO3-. The nitrite method reducing solution was prepared by creating a solution of 168 mM NaI in DIH2O. A jacketed purge vessel was attached to a circulating hot water bath and set to 25ºC and 0.5 mL of nitrite method reducing solution plus 2 mL of GAA were added to the purge vessel. The TNG method reducing solution was prepared by creating a solution of 51 mM VCl3 in 1.0 M HCl. The 8  circulating water bath was set at 95°C and about 2.5 mL of the TNG method reducing solution was added to the purge vessel’s reaction chamber. A brief illustration of this, and the method’s intended targets, can be found in Figure 1. For both reducing methods, a trap filled with 10 mL of 1.0 M NaOH was placed in between the purge vessel and the NOA. A liquid filter was placed between the trap and the analyzer to prevent droplets and the occasional aspiration of liquid from reaching the NOA. Using the stop cock on the NaOH trap outlet, the flow of the NOA intake was adjusted until the reaction cell pressure reached 5.7 torr while the system was open. Compressed nitrogen was used as the carrier gas for the duration of the experiment and the line from the compressed nitrogen tank was attached to the purge vessel intake. Flow was increased to reach just over 1 L/min as measured by the flow meter. The purge vessel was sealed, and its outlet was attached to the inlet of the NaOH trap. A needle valve on the purge vessel was used to adjust the flow until the closed system pressure matched the open system pressure. This flow was ~0.45 L/min. A cold-water line was attached to the purge vessel condenser with a constant flow. Cell pressure and flow rates were monitored and adjusted as needed throughout experiment assays. After each assay the purge vessel was filled with dilute HCl (5 mL of 0.5 M HCl followed by filling the balance of the purge vessel with DIH2O) to reduce interference from any deposited material on the interior surface of the purge vessel glass.  2.4. Instrument Qualification. The NOA was qualified for use in this study by testing its linearity, precision, accuracy, selectivity, and robustness at similar concentrations to those being used in the biological sampling experiments. Solutions at varied concentrations of NaNO2 (0.25 - 200 µM) and NaNO3 (0.5 - 200 µM) were prepared. These solutions were used with their respective methods to perform linearity, precision, and accuracy tests. These concentrations were chosen as they represented a range of detection values used with other instruments with bookends above and below such values (about 10 µM). 2.5. Linearity was measured from a series of NaNO2 (0.25, 0.5, 1, 5, and 10 µM) and NaNO3 (0.5, 2, 5, 8, and 10 µM) standards for nitrite method and for the TNG method, respectively. These concentrations represented the range at which the intended spiked biological samples would be measured and were used to determine if linear analysis of the spiked biological samples was the correct approach. A 100uL sample of standard was injected into the purge vessel using an analytical liquid syringe. The “Liquid” software in the NOA was used for data collection and for analysis of slope, y-intercept, NOA cell pressure and R2 and GraphPad Prism 6 was used to plot 9  and evaluate the residuals. The measured concentrations of standards were also plotted against their corresponding as-prepared or assumed concentrations. The procedure was repeated three times and data was collected on two separate occasions by three separate operators and combined. Linearity was determined through the R2 values and the randomness of the residual plots. 2.6. Precision and accuracy tests were done with 0.75 µM and 7.5 µM NO2-/ NO3- standards. Repeated measurements of these samples represented the repeated measurements of unknown biological samples to test the reliability of the method to capture accurate data. Samples were measured in replicates of six and the area under the curve (AUC) was measured using the “Liquid” software, to determine the instrument’s precision. These measurements were also compared against the linearity data to determine accuracy of the instrument. Data for this section was collected on multiple days and between multiple operators to rule out user variability. It was compared using percent differences (%diff.) to determine accuracy and percent relative standard deviation (%RSD) to determine precision. 2.7. Selectivity of the NOA was determined by using alternate nitrogen compounds. Solutions of 10 µM of both NH3 and CO(NH2)2 were prepared and compared to 10 µM NO2-/NO3- samples in the nitrite and TNG methods, respectively. These measurements were done to rule out the possibility of interference from non-oxygen bound nitrogen components of biological material and fluids. Concentrations of 10 µM were chosen to guarantee that interference was well below potential detection levels. 2.8. Robustness was evaluated by comparing the changes in signal detected by the NOA when altering the following parameters: Volume of the injected samples, initial volume of the reducing solution, purge vessel temperature and when the reducing agent becomes the limiting reactant. The effect of changing the sample volume was tested to determine the number of injections it would take to disrupt the consistent effectiveness of the reducing solution and was done in two parts: high volume (100 µL; 0.75 µM injections) and low volume (10 µL; 20 µM injections). The concentrations of the samples were chosen to match the upper and lower bounds of the detection range of each method. Reducing solution volume was increased by 1.5x to evaluate possible changes to NO signal in case the reducing solution volume is altered during an assay or when changed between assays. Increasing the volume of the reducing solution would also increase the amount of reducing agent present in the reaction cell, and therefore potentially increase the rate of the reduction reaction. This step was done to determine whether such a 10  change will perceivably affect the analysis of a given sample, and to determine if controlling the quantity of reducing solution used is required for each method. To evaluate temperature changes on the nitrite method the circulating water bath was set to ±10°C of the method’s determined temperature control setting. This was done to see whether the method could be used reliably at room temperature in the absence of a circulating water bath. Temperature changes were tested with both high and low volume injections using the same standards at all three temperatures for comparison. Since the TNG method’s temperature is strictly controlled, this method was not tested for temperature changes. The point at which the reducing agent becomes the limiting reactant was determined mathematically. The number of samples injected in a 60 min analysis was chosen as 36 allowing for 3 injections for every 5 min of analysis. The number of moles of NO2- for a high (750 µM) and low (10 µM) concentration sample, injected with low and high volume respectively, were determined and compared against the number of moles of reducing agent available in the volumes and concentrations used in both methods. This was done to show that the reducing solutions were saturated sufficiently to not hinder a typical assay. 2.9. Biological Sample Processing. For ease of access to the quantity and variety of samples needed for the study, bovine biological samples were used. Saline, milk, urine, and blood samples were spiked with either NaNO2 for the nitrite method or NaNO3 for the TNG method before processing (see Figure 2). This “spiking” was done by serial dilutions of a 1 mM solution to reach final concentrations of 50, 100, 200, 600, and 1000 µM. Meat and fat tissue were prepared before spiking by hand mincing by disposable scalpel into ~3 mm cubes, mixing with isotonic saline at 1 g/mL, and sonicating three times for 30 sec intervals. The resulting solution was vacuum filtered using segments of clean open celled foam and the filtrate was collected in a capped 15 mL tube propped up inside the vacuum filtration flask. All the samples were spiked with NO2-/ NO3- by placing 990 µL aliquots of biological sample in 1.5 µL capped microcentrifuge tubes and adding 10 µL of spiking solution.  Then, samples were mixed with -20°C EtOH in a 4:6 sample: EtOH ratio, vortex-mixed, and centrifuged (15,200g at 4°C for 4 min). Supernatants were removed and placed in new tubes, and old tubes and pellets were discarded. Post processing, samples were at final NO2-/NO3- concentrations of 200, 400, and 800 nM and 2.4 and 4.0 µM. They were then grouped into low concentration (nM) and high concentration (µM) sets. Samples were placed in a -20°C freezer for storage until analysis. DIH2O was used as a negative control and NO2-/NO3- spiked saline was used as a positive control. Processing and spiking were repeated with 5 biological replicates. Each nM and µM spiked set was prepared 11  with its own DIH2O spiked blank creating 7 distinct samples in the combined sets. Each sample had 3 experimental replicates making a total of 21 stored tubes (12 in the low concentration set and 9 in the high concentration set) for each biological replicate.  2.10. Sample Analysis. Samples were removed from the freezer and immediately centrifuged (16,900g at 4°C for 30 sec) to spin out proteins that would crystalize during storage. Supernatants were transferred to new micro-centrifuge tubes and placed on ice inside a closed thermal storage container to be kept cold for the duration of the analysis. Analysis of the experimental replicates was carried out using either the nitrite or TNG method and the purge vessel was prepared accordingly.  Standard NaNO2 solutions ranging from 125 nM to 100 µM were prepared and measured alongside samples to ensure the accuracy of the NOA. These standards were also used to create a standard curve. Using a 250 µL analytical syringe, 100 µL sample injections were used during the analysis. Each experimental replicate was measured in triplicate. After 2 experimental replicates (6 sample injections), the reducing solution in the purge vessel was drained and replaced. The NaOH trap was continuously monitored and refreshed with new 1.0 M NaOH when needed to ensure foaming did not reach the NOA intake tubing, or at a minimum it was refreshed after a full set was completed (27 or 36 sample injections).  2.11. Data Analysis. Data was recorded through the use of Liquid, part of the NOAnalysis 3.21 software package created to communicate with the NOA, and also compiled into tab delimited files. Excel was used to access and organize the data while GraphPad Prism 6 was used for regression and statistical analysis. Calculated data points were used in regression analysis. For biological samples, the additional step of subtracting blank sample data from the spiked sample data was done to determine the amount of standard solution that remained after processing. For all sample types, slopes were created by comparing the as-measured values of sample sets to their as-prepared concentrations ([meas.]/[prep.]). Linearity was assessed through evaluation of the residual plots for unbiased distribution of the data points in relation to linear regression, and for the goodness of fit for a linear curve by assessing R2 to be above 0.800. They were constrained to a Y-intercept of 0.0 and tested for significance against the hypothetical value of m=1 using an extra sum-of-squares F-test with p-value <0.05 in GraphPad Prism 6. For precision and accuracy, calculated slopes were compared against the instrument manufacturer’s specifications of ±5-10% from expected result. Slopes from different methods were compared for significance against each other to look for anomalous patterns by using t-tests with a p-value < 0.05. Slopes were evaluated by mega-analysis (combining all data sets before doing regression 12  analysis) and by meta-analysis (performing and combining regression analyses of individual sets before comparison), to determine if any one sample set was outside the limits of the others. The lower detection limits of the methods were determined through calculating the limit of blank (LoB) and limit of detection (LoD) according to guidelines listed in the document EP17-A from the Clinical and Laboratory Standards Institute.33 To determine the LoB, each set of biological samples had their own set of 90 blank measurements per method. Because noise from the NOA never allows the measurements to go below zero, the following equation was used to determine the LoB: LoB = µB + 1.645σB where µB is the mean of the blank measurements, σB is their standard deviation, and 1.645 is the z-score for a significance level of 0.05 or the values within the 95% confidence interval.  The LoD was established using 45 available measurements for each biological sample. The data was taken from the lowest spiked sample concentrations for each method, 200nM for the nitrite method and 2400nM for the TNG method, and calculated using the following equation: LoD = LoB + 1.645σS or LoD = µB + 1.645σB + 1.645σS where the LoB is used to act as the lowest possible value outside the LoD 95% confidence interval, and the standard deviation of the low value sample measurements, σS, is used to determine the confidence interval. The standard error of the LoD (SELoD) was also calculated according to Appendix A of document EP17-A and can be described as the estimation of how closely the sample LoD falls near the true LoD.33 It is calculated using the following equation: SELoD = √[(2.1142 ×𝜎𝐵2𝑁𝐵) + (1.6452 ×𝜎𝑆22(𝑁𝑆 − 𝐾))] where additionally NB is the number of blank measurements, NS is the number of low concentration sample measurements, and K is the number of low concentration samples. The LoB represents the upper limit of the 95% confidence interval of the sample mean of the blank measurements and therefore does not require further estimation of its error.  Additionally, calculated sample data—slopes, LoB, LoD—were assessed for similarity to the saline positive control, order of magnitude for its limits, interaction in the purge vessel reaction chamber, additional steps in processing, and sample storage ease. This was done to determine the feasibility of daily assays in a laboratory setting using these methods, and to 13  answer the question if processing and analysis is attainable for a reasonable set of samples in one day. Combining this assessment with the statistical significance of the results should provide a good evaluation of the efficacy of these methods.   14  3. RESULTS AND DISCUSSION 3.1. Instrument Qualification.  3.1.1. Linearity. Both the nitrite and TNG methods resulted in instrument slope data with R2 values of 0.998 and 0.984 respectively for linear curves. The slopes differed between methods, with the nitrite method average instrument slope of 120.4±1.1 mV*min/µM versus the TNG method’s average instrument slope of 71.7±1.3 mV*min/µM (Figure 3). The plotted 95% prediction bands emphasize the reliability of creating standard curves with the methods. This, in conjunction with the instrument slope data, further shows that the two methods give different results and couldn’t be compared directly without a normalizing standard to accompany analysis of an unknown sample. However, they are reliably linear, as the data was collected over the course of multiple days.  3.1.2. Precision and Accuracy. Evaluation of the nitrite and TNG methods produced varying results regarding their accuracy and precision. The nitrite method analysis of samples below 1 µM resulted in a %diff. range of -9.7% to 1.2%, and the greatest difference came from assays performed by less experienced operators (Table 1). A similar pattern was observed among the standards above 1 µM except that the average %diff. was 10 times less with a range between -0.2% and 0.9% across all experiments. This result was well within the manufacturer’s specification that liquid analysis falls within an error of ±5-10%. Also, the precision of individual assays, measured using %RSD, varied greater than data from combined assays. This occurred because adding degrees of freedom to a standard deviation calculation will decrease the overall variance. More experienced operators created data with greater precision than new operators. The precision of the nitrite method followed a similar pattern to the accuracy test, and comparing precision between high and low concentrations assays resulted in a 3.4-fold difference in %RSD. As the concentration of the samples increased the measured error in the method also increased. However, this increase was not proportional to that of samples of lower concentration. The %RSD of the high concentration assays was greater than expected, but it was still lower than that of the low concentration assays. This is summarized in the plot of the accuracy and precision assays of the nitrite method comparing its as-measured concentrations (meas) to its as-prepared (prep) concentrations (Figure 4A). The slope (1.004±0.003 meas/prep) compared to the hypothetical value of m=1 indicates its accuracy as a method (P=0.1835), and the tightness 15  of the 95% prediction bands indicates the precision and likelihood of further assays being similar.  The TNG method was less consistent than the nitrite method. New operators were more consistent, producing more precise results, than more experienced operators who were more accurate (Table 1). This phenomenon may appear as a contradiction but can be explained by behaviour based on experience level. Less experienced operators tended to continue injecting standards even when conditions were unfavorable. As a result, their injections were more evenly timed and consistent relative to each other. This meant that their measured values also consistently showed whatever unfavorable conditions may have been present. The more experienced operator tended to watch pressures, signal noise, base line signal, etc. and could assess when optimal injection conditions likely were present. As a result, their injections were not as evenly spaced and less consistent relative to each other. Thus, being more consistent relative to instrument conditions, their measured concentrations were more like the prepared values despite a larger spread in the data. The high concentration assays’ %diff. ranged from -5.6% to 38.9%, and the low concentration assays ranged from 9.9% to 54.8% when comparing data taken on multiple single days. As expected, when multiple operators participated the %diff. dropped. For high concentration assays that meant that the %diff. was 16.2% for multiple analysts performing assays on a single day and 8.9% over multiple days. Samples less than 1 µM, when measured using the TNG method, fell far outside the manufacturer’s specifications and had no discernable pattern in their results: %diff. varied widely and was positive, indicating the instrument consistently measured higher than the intended concentration (Table 1). Thus, the analysis of low concentration samples with the TNG method will likely result in an overestimation of the measured concentration. When results from other operators were included the %diff. improved to 24.3% on a single day of experiments and 34.4% over multiple days. The combination of multiple assays from high concentration samples and low concentration samples shows the likely potential that with further measurements a micromolar concentration sample could be reliably analyzed. Conversely a sample smaller than micromolar concentration may not be reliable due to the consistently high %diff. The TNG method’s precision varied between operators as made evident by its decease when assays were combined. The new operator produced %RSD of only 9.1% from a low concentration assay, and the discrepancy in accuracy between multiple assays nearly tripled the %RSD to 26.2%. Further, combining 16  only the more experienced operator’s low concentration assays increased the %RSD to 32.7%. For high concentration assays, the experienced operator’s assays were relatively consistent and combining them had little result. Combining them with the new operator’s assays resulted in an increase of %RSD to 20.8%. These results emphasize the assay-to-assay difference that could occur with the TNG method and showed how experience with the instrument can be the difference between falling into manufacturer’s specifications or not. Graphing the precision and accuracy data of the TNG method (Figure 1B) resulted in a slope (1.092±0.037 meas/prep) with a p-value of 0.020 when compared to a slope of m=1. This p-value falls within a 99% confidence interval and indicates that nanomolar quantitative analysis by this method should be done skeptically. The spread of the 95% prediction bands also indicates this need for skepticism; however, the method could potentially be utilized for higher concentrations with additional assays and analysis of data.  3.1.3. Selectivity. The nitrite method showed to be very selective, with negligible signal from solutions containing NH3 and CO(NH2)2 (Table 2). The NO3- standard analyzed with the nitrite method showed a 98.2% decrease in potential signal. Knowing there is such a large decrease of signal from nitrate samples in the nitrite method, any nitrate in samples to be analyzed will likely be minimized to the point of non-interference. The TNG method showed a drop of 8.3% in signal strength from the NO2- standard when compared to NO3- standards. However, it will be important to note that this comparison came from data generated from two different assays. As referenced above, while using the TNG method there was considerable variability from assay to assay even on the same day and a difference of 8.3% could very likely be within the error limits of the method. Signals obtained from injections of NH3 and CO(NH2)2 samples were 95.3% and 95.5% weaker respectively than the signal of NO3- standards of the same concentration. This result was comparable to that of DIH2O injections of the same size in the TNG method (data not shown). These results coincide with the fact that the nitrogen in the NO2- and NO3- ions both have positive oxidation states, +3 and +5 respectively, and the nitrogen in ammonia and urea both have oxidation states of -3 thus requiring oxidation rather than reduction to bind to oxygen. The nitrite and TNG methods are both designed to reduce nitrogen and therefore have unfavorable conditions to facilitate the oxidation of nitrogen from the other compounds toward NO. It should also be safe to assume that only nitrogen with a positive oxidation state will cause a signal after it’s reduction to NO and subsequent reaction with ozone in the NOA reaction cell.  17  3.1.4. Robustness. Altering the initial volume of reducing solution in the purge vessel had no effect on the signal produced. Assays where initial reducing solution volume was increased by 1.5x were compared to standard assays using a paired t-test, and the resulting p-values indicated there were no significant differences (P>0.05). This was understandable since the reducing solutions ability to reduce is concentration dependent rather than volume dependent. They are also purposefully saturated; therefore, even a moderate change to the initial volume would not affect the outcome of the analysis. However, as samples were injected into the reducing solution during an assay there was a trend for the effectiveness of the reducing solution to decrease as it became more dilute with each injection. This trend increased as the size of the injection increased, and up to 1.5 mL of analyte could be added before a noticeable change in signal was observed. Also, the TNG method was more susceptible to change than the nitrite method (data not shown).   Temperature changes showed minimal impact on the effectiveness of the nitrite method to give accurate results. With a decrease in temperature, high volume samples showed a 7.0% drop in signal strength and the low volume injections dropped by 1.2%. With the increase in temperature, high volume NO2- standards decreased in signal strength by 0.5%, whereas low volume NO2- standards increased in signal strength by 2.0% (data not shown). To minimize this effect, it was decided to temperature control the nitrite method as well as the TNG method, thus eliminating the possibility of signal being affected by a change in ambient temperature during an assay. 3.1.5. Conclusions of Qualification. Instrument qualification showed that the analysis of standards with the nitrite method detected into the nM range, and the TNG method detected to the µM range. The nitrite method also fell within the instrument manufacturer’s specified range of nM to mM and %diff. of ±5-10% with even less variation in the µM range.25 Regardless, temperature control, limiting it to 25°C, was added to the nitrite method to ensure changing ambient temperatures did not change the signal from the analysis. Even though the TNG method fell outside the expected specifications for most of its tests during the method qualification assays, some small modifications could be utilized to ensure a higher quality analysis for the rest of the study. The TNG method was modified to include a more consistent cleaning step to reduce contamination. An ice bath was also added to chill water flowing to the condenser to slow vacuum distillation of etOH and GAA thus allowing an increase in the duration of analysis before refreshing the bubbler. Though during winter 18  months tap water flow was sufficient, summer water temperatures were not low enough to prevent vacuum distillation. To increase robustness, both methods were modified to include draining and replacing the reducing solution so the age of the reducing solution (how many injections it received) would not affect an analysis.  Though the addition of an analyst seemed to cause minimal change to the results of the nitrite method, the changes to the TNG method’s results were quite dramatic. This was likely due to the nature of the TNG method which requires more monitoring and minor adjustments of equipment throughout an assay which a new analyst may have difficulty keeping track of without additional experience. As a result, a single analyst was used to carry out the experiment. For the nitrite method this would have a minimal effect, losing some robustness of the method to gain a small amount of precision and accuracy. However, for the TNG method using only one analyst allows for a large benefit in accuracy at the cost of reducing robustness. This will allow the opportunity to test the method in the µM range. These changes were carried forward to confidently analyze biological samples spiked with nitrites and nitrates.  3.2. Biological Sample Spiking.  3.2.1. Milk.  The measurement of nitrites and TNG in milk was selective and detected to the ranges predicted by the qualification assays. After processing out the protein and fat content from the milk samples, they acted like the standard solutions used earlier in the project. The analysis resulted in very low limits and fit well to the linear model. Analysis of milk with the nitrite method reached nM concentrations, and the TNG method reached µM concentrations. Both method’s selectivity was assisted by the processing steps taken prior to analysis. NO2--spiked milk samples measured with the nitrite method resulted in a slope of 1.026±0.004 [meas]/[prep] (Figure 5C; Table 3). Comparatively, the NO3--spiked milk samples measured with the TNG method resulted in a slope of 1.035±0.007 [meas]/[prep] (Figure 6C; Table 3). Since milk samples were spiked prior to processing, this indicated that the molecular matrix of the whole milk did not interfere with the concentration of the added analytes. Using a t-test there was no significant difference between the slopes from each method with a p-value of 0.2160. There was also no significant difference from the nitrite method between milk samples and the positive control with a p-value of 0.8575. The comparison of the TNG method to the positive control resulted in a p-value of 0.0481 which 19  indicated that though the TNG method slope was similar, it was not enough to make a direct quantification of TNGs. This also shows that the processing steps following spiking did not have a noticeable effect on the concentration of the added analytes due to the assays similarity to the positive control’s results. The slopes for milk samples had R2 of 0.9945 for the nitrite method and 0.9813 for the TNG method showing that the linearity of the analysis is not affected by the sample. This shows also that the sample processing and storage was adequate for the coupling of these methods and milk samples in terms of linearity.  The LoB and LoD of the milk sample analysis showed quite a large discrepancy between each method. The LoB and LoD was 220 nM and 268 nM respectively for the nitrite method, and 3.262 µM and 3.410 µM respectively for the TNG method (Table 3). Further, the SELoD of the nitrite and TNG methods were small in comparison to their LoD counterpart, indicating that the estimated LoDs calculated were close to the “true” LoD for the instrument and sample type: SELoDs were 13 nM and 0.245 µM respectively (Table 3). This reflected what was determined in the qualification portion of the experiment, further confirming the nM detection range of the nitrite method. Though TNGs can only be quantified in the µM range, the ability of the nitrite method to conveniently measure nitrites below 300 nM is advantageous.  The development of processing milk required some trial and error, as differing ratios of etOH were combined with whole milk. This was done to find a ratio that did not overly dilute the solution, but also decreased the density of the solution enough to precipitate the milk fats into the pellet rather than forming a crust on the surface of the supernatant. This was important for the purpose of pipetting the supernatant with as few contaminants as possible. Eventually the method obtained (listed in the experimental section) was efficient and easy for the operator to follow as many samples needed processing. The combined nM and µM sets contained 21 experimental replicates would take approximately 4 hours to complete including processing time and instrument set-up and clean-up. Since there were 3 experimental replicates per distinct sample it is possible to analyze 7 distinct samples, or 1 biological replicate, in that amount of time.  3.2.2. Urine. The processing of urine was very straight forward, and analysis with the nitrite method was selective and had a nM detection limit. The nitrite methods performed excellently in the presence of much higher concentrations of nitrate relative to the nitrite concentration detected. Nitrite-spiked urine sample results were analyzed to have a slope 20  that was not significantly different from the positive control using the nitrite method: 1.028±0.005 [meas]/[prep] (Figure 5D; Table 3) with a p-value of 0.6340. This indicates the nitrite method to again have nM detection and be robust due to this strong correlation. The NO3--spiked urine sample’s slope was 0.804±0.020 [meas]/[prep] (Figure 6D; Table 3) and was significantly different from the positive control with a p-value <<0.05. The TNG method assays of urine samples do not match that of the nitrite method and comparing urine analysis from the two methods shows significant difference (p <<0.05). Also, urine sample analysis for linearity resulted in R2 values of 0.9921 and 0.8671 for nitrite and TNG methods respectively. This difference in slope may be due to the range in which the detection occurred, as the following discussion of the LoB and LoD will indicate. Urine’s nitrite method LoB was 421 nM and LoD was 496 nM with an SELoD of 23 nM. Its TNG method LoB and LoD were 16.159 µM and 16.556 µM respectively with an SELoD of 1.267 µM (Table 3). These data clearly show that the inherent TNG concentration of the urine samples has an impact on the effectiveness and detection limits of the TNG method. Its efficacy only holds true in the micromolar range, and the variability of the TNG concentration in the unspiked samples reduced the value of the calculated slope of the method. Such high concentrations prevent direct measurement of unknown samples in the nanomolar range but may be overcome by analytical techniques such as standard addition. The high inherent TNG concentration in urine also pushed the analyzed concentrations to a range higher than expected and may also have skewed the data. Despite this high inherent concentration detected through the TNG method, the nitrite method maintains its detection limit, allowing for determination of a nitrite unknown at approximately 500 nM. This further shows the robustness of the nitrite method.  The processing step often did not produce a pellet, which indicated that the protein content of the urine samples was very low. It further indicated that the high LoB of the urine samples was due nearly entirely to nitrate. Measuring urine without processing still caused problems with the analysis by way of foaming and clogging the frit of the purge vessel once injected into the reducing solution. Processing urine remained practical and did not hinder the method. 3.2.3. Blood. The biological complexity of blood resulted in reduced slope values, but the methods still maintained their ranges and detection limits. Blood sample assays’ slopes were 0.772±0.008 and 0.872±0.010 [meas]/[prep] (Figure 5B; Figure 6B; Table 3) for the nitrite 21  and TNG methods, respectively, with significant difference between the two (p=3.665×10-13). Comparison between the slope values for blood samples and the positive control also showed significant difference (p<<0.05). The analysis of blood samples with the nitrite method resulted in a tighter regression fit (R2= 0.9543) than the TNG method (R2=0.9043). The LoBs for the nitrite and TNG methods were 278 nM and 5.723 µM respectively with LoDs of 357 nM and 6.147 µM respectively (Table 3). The SELoD values for each method were 18 nM and 0.314 µM for the nitrite and TNG method respectively. Blood was expected to have high TNG levels since bovine diets contain foods that are often high in nitrogen groups, specifically nitrates. With a TNG LoB of around 6 µM, blood [TNG] was not as elevated as originally thought; however, the efficiency of the processing steps to remove cellular material and proteins from the blood may be responsible for this result.  Since the processing steps appeared to have no effect on the quantity of nitrite remaining in solution, as seen in the saline control and the milk and urine samples, we can assume that any change in the slope is due to the existing matrix of compounds in each biological sample. Red blood cells, or erythrocytes, have the ability to bind and sequester nitrite and nitrate ions by either storing them within themselves or converting to RSNO; furthermore, hypoxic conditions can also induce deoxyhemoglobin to produce NO from nitrite to induce vasodilation and increase blood flow.29 These processes could in turn cause a drop in analyte concentration as erythrocytes could convert nitrite and nitrate to NO before being removed, along with any sequestered NO metabolites, before analysis. As further evidence, when processing methods were being evaluated, whole blood samples were processed but frozen without removing the supernatant from the pellet. There was a marked reduction in analyte concentration in these samples when compared to samples processed according to the methods in this study (data not shown). This indicates that the surface of the pellet still contains the necessary molecular machinery to reduce, bind, or convert nitrite and nitrate in a hypoxic environment. Transferring the supernatant to new tubes before freezing became a necessary step for preserving the remaining analytes in solution.  These results show that the blood samples, once processed, act predictably and reliably with the nitrite method and can still be effectively stored. The quicker the blood can be processed and the nitrites or TNGs can be isolated from the other blood components, the closer to accurate the analysis will be. Since it is known that blood has the mechanisms to form RSNOs, these results also point to the processing steps having the ability to remove 22  them from the samples along with the rest of the blood contents. If the method is to be used in a lab, and samples aren’t processed immediately, then there should be a consistent time window established to reduce variation in the samples. Regardless, the processing and analysis of blood with the nitrite and TNG method were convenient and effective. Preparation of the samples for storage was easy, and analysis was not hindered by the sample after processing. 3.2.4. Meat. The processing and sampling of tissue was more time-consuming due to the added steps of cutting, sonicating, and filtering for processing. Both methods had detection ranges as qualifications predicted, but the qualifications did not predict the resulting slopes from the data. Processed meat analysis resulted in slopes of 0.945±0.006 [meas]/[prep] and 1.156±0.017 [meas]/[prep] for the nitrite method and the TNG method respectively (Figure 5E; Figure 6E; Table 3). These slopes were significantly different from each other (p=1.49x10-36) and from the positive control (Nitrite p=5.42x10-24; TNG p=2.80x10-13), and there was a slight reduction in concentration from biological samples that were nitrite-spiked. Skeletal muscle has been reported to be the largest reservoir of stored nitrate in the body and has mechanisms which include nNOS and sialin, enzymes that can reduce nitrite to nitric oxide or transport nitrate directly into muscle cells respectively.34-37 Nitric oxide can bind to proteins in the sample that are then removed during processing or converted into a form undetectable by the nitrite method. However, this was contrasted by a slight increase of concentration for nitrate-spiked samples analyzed by the TNG method. This increase was proportional to the concentration of nitrate used to spike the samples, indicating that there may be another process at play which is upregulated by nitrate to stimulate the release or oxidation of nitrogen species that are detectable by the TNG method.37 Though it has been shown that myotubes can uptake dietary nitrate,35 this doesn’t account for what appears to be an increase in concentration in a closed system. Since the samples were spiked with nitrate before most of the cellular material was processed out, but after disruption of the cell membranes through sonication, it can be determined that the increase in concentration occurred during the processing step before the supernatant was isolated. Furthermore, a possible explanation could be related to the process of converting L-arginine to NO. As sonication would have caused much disruption of the cellular material, it is possible that the NOSs present would have begun converting free L-arginine and releasing NO. This now-free NO could attach to free proteins or simply be oxidized to nitrite or nitrate which would 23  be detectable through the TNG method.38 It is not known whether nitrate can stimulate this process, and it does not explain why this increase in TNG concentration appeared to be proportional to the increase of added nitrate. The proportional increase could have also been a discrepancy in the data, hinting to a systematic error that was not eliminated. The processing step for meat samples required some development before a method was finalized. Tissues were both chopped into ~3 mm cubes and pureed with a Tissue Homogenizer TH115 (Omni International, Kennesaw, GA, United States) and disposable hard tissue tips to determine which technique was most useful. It was also filtered by various means until an effective way was determined. Chopping followed by sonication seemed the most effective, as the pieces of meat were still large enough not to clog filters. In both cases standard filters would clog with small fatty particulates. Since the object of the filtering was to remove any pieces large enough to clog the pipettes, switching to an open-cell foam that was tight enough to catch large pieces but not get clogged by small particles proved the most effective and sped up filtering times immensely. The smaller particles could be spun out after the solutions were mixed with etOH. Though tedious at times, the sequestering of meat sample sizes, dicing, sonicating, and filtering sequence was not unduly long, and processing and analyzing could be handled in one day if needed. Linearity was indicated by the R2 values of the slopes: 0.9847 for the nitrite and 0.8896 for the TNG method. The LoBs and LoDs for processed meat samples analyzed with the nitrite and TNG methods were 282 nM and 9.481 µM respectively and 344 nM and 9.799 µM respectively (Table 3). The SELoDs for these methods were also 16 nM and 0.513 µM indicating again that the nitrite method’s estimated LoD was close to its true LoD; however, both SELoDs are close to a 5% difference in relation to their respective LoDs, which suggests that the methods are sufficient to mitigate error present earlier in the experiment. With skeletal muscle being a store for nitrate, it is not surprising that it, along with other nitrogen groups, would be elevated and reducible with the TNG method.39 This data made it apparent that the nitrite method’s lower detection limit was due to its selectivity. 3.2.5. Fat. This tissue analysis took extra time due to added required processing steps and had an unexpectedly high TNG LoB and LoD. The methods remained selective in the qualified ranges. Processed fat samples resulted in slopes of 0.992±0.004 [meas]/[prep] and 1.114±0.016 [meas]/[prep] for nitrite and TNG methods respectively (Figure 5F; Figure 6F; Table 3). The slope’s R2 values were 0.9919 and 0.8416 respectively for the nitrite and TNG 24  methods, showing a closer regression fit for the former over the latter. Both slopes were significantly different from the positive control (Nitrite: P=1.46x10-7; TNG: P=4.68x10-8) and from each other (P=5.32x10-17). The LoB, LoD, and SELoD for the nitrite method were 354 nM, 401 nM, and 24 nM respectively, and for the TNG method they were 18.884 µM, 19.355 µM, and 1.449 µM (Table 3). Fat samples had the highest LoB and LoD for the TNG method of all the biological samples.  This can likely be accounted for by fat tissue having the necessary molecular mechanisms for converting nitrite to nitrate for storage. Also, by comparing Figure 2F and 3F with Figure 2E and 3E, we see the fat extract samples acted very similarly to meat extract samples. This points to the fact that fat extracts had similar composition to the meat extract samples, but we can also reason from the data that it was to a smaller degree since the slopes of the concentration curves in Figures 2 and 3 are closer to the control. As expected, the samples with potentially the highest nitrate and nitrite content had the highest TNG LoBs.  Processing of the fat samples required chopping, sonication, and filtration of the fat tissue. It was necessary to do this and mix with etOH before spinning as a layer of fat would form on the top of the tube otherwise. This was the best method to use to avoid pipette clogs, but perhaps could have been avoided with a more powerful processor. Homogenization was attempted with the handheld model mentioned above, but fat residue reduced the performance of the blending tips and very quickly clogged filters. However, if the homogenizer increased in size and power the sample size may also have needed to increase. The ~20 g sample size was not big enough to put into a blender and increasing the sample size would have caused excessive waste. Homogenizing all the samples before separation would have reduced the 5 biological replicates to one. If these samples were to be processed on a regular basis, the acquisition of even a hand-cranked grinder for small quantities would speed up the process. Samples could be finely ground individually, mixed with saline, sonicated, and pipetted without filtration. Such a change could speed the tissue processing by a large margin to where the processing and sample analysis could take place on one day. 3.2.6. Conclusions of Biological Sample Spiking. The success of the processing steps provided for increased selectivity and nM detection with the nitrite method and µM detection with the TNG method. The meta-analysis of the individual assays from each biological sample was not significantly different to those of the mega-analyses (Table 5). This indicates a strong correlation between the regression of each biological replicate and the regression of 25  the whole body of data for each biological sample type.  Figure 7 shows the meta-analysis slopes and table 5 shows the corresponding t-tests that were done with the slopes received from the mega-analysis. From this we can conclude that the processed fat samples analyzed by the nitrite method, along with the positive control of saline samples from the TNG method, were not significantly different from m=1. Also, no significant difference was found when comparing these meta-analysis slopes to their mega-analysis counterparts, indicating that individual biological replicates were representative of the analysis as a whole. Analysis of the biological samples resulted in a pattern like the qualification steps in which the nitrite method was found to have a lower detection limit than the TNG method. The inherent higher TNG levels in blood, meat, urine, and fat resulted in a larger standard deviation in the data for those biological sample sets.38 As a result, the LoDs for each set were higher than other biological samples that do not have the same inherent high concentration of nitrogen groups. When considering the decision to leave out multiple analysts the nitrite method can still adequately measure in the nM range even if a small amount of additional error was added. Even though the changes to the TNG method did help improve repeatability and accuracy, the addition of other analysts may have also led to the results being even more varied from the nitrite method. It is advisable to repeat a series of these same experiments with additional analysts and similar, but not identical, equipment set ups.  The linear slope models fit well for all sample types, and fit individual assays, which indicated linearity in all cases (data not shown). Considering these data and that the TNG method’s LoDs fall within the micromolar range, it is as sensitive and reliable as other quick analysis methods making it useful for many common applications. However, having a higher detection limit than the nitrite method, which consistently detected nM concentration, these methods would not be able to be used together below µM concentrations. Furthermore, the TNG method’s results for the same samples showed a signal close to 50 times greater pointing to the reliability of the nitrite method to be selective and accurate when analyzing samples of all types.  In addressing the differences of linear model fit that some biological samples had in comparison to the control, it is important to note that all samples were processed with etOH. It can be postulated that the difference in slopes came during processing before the addition of etOH. This would allow some components of the active biological samples to interact 26  with the added nitrates or nitrites before their precipitation with etOH. This was confirmed through comparing the spiked saline controls to the other biological samples. Milk and urine samples were consistent with the control, but in contrast the blood, meat, and fat samples showed change from their expected spiked concentrations. This suggested that the interactions of those biological samples with the spiking compounds caused the change rather than the whole processing step. Processing to remove biologically active substances from the samples allowed for storage in a -20°C freezer with no noticeable degradation. Processed samples were not always stored for the same length of time, but it did not make a noticeable change when samples were analyzed. Storing just supernatants from biological samples processed with etOH provided much more consistent results than biological samples, which were processed but not separated from their pellet or unprocessed yet stored under the same conditions (data not shown). Processing with EtOH had the added benefit of mitigating foaming of the reducing agent by removing compounds such as proteins and other cell structures. This increased the life of the reducing agent and allowed for full sets of samples and standards to be completed at one time, thus adding consistency. Processing biological samples with etOH proved to effectively isolate TNGs for analysis and remove biological compounds prone to react with said TNGs. The most cumbersome part of the process was spiking the solutions in a timely manner with nM concentration standards. If the spiking step was removed, as it would be with a clinical unknown sample, the processing step would be quick and effective. Due to its greater precision, the LoB and LoD values of the nitrite method were considerably lower than the those of the TNG method. Samples analyzed with the more selective nitrite method had greater consistency along with an overall lower concentration of measured metabolites, so their LoBs were in the nanomolar range. The LoD is dependent on the value of the LoB; therefore, the TNG method LoDs were higher due to the LoBs obtained from the blank spiked biological samples. The TNG method LoDs also reflect the increased variability of the TNG method over the nitrite method (Table 3).  Being both precise and repeatable, the nitrite method was as reliable with the biological samples as it was with standard solutions. TNG method reliability depended on the biological sample, as each one interacted differently with the spiking solution and couldn’t be compared to the positive control directly. The etOH in the processed samples also caused some hindrance with the TNG method.  Since the TNG method is kept at 95°C during the NOA analysis, 27  etOH from the sample readily evaporated and was absorbed in the bubbler. This caused premature flushing of the bubbler. The temperature of the condenser on the purge vessel was required to be maintained consistently between 4°C and 0ºC to prevent this from happening. This became difficult at times, causing interruptions to the analysis, and the addition of an ice water and peristaltic pump combination or a second chilled circulating water bath would streamline that portion of the method.    28  4. CONCLUSION The detection of NO and its metabolites, or a sample’s total nitrogen, is a process that effects many industries and fields. It is utilized to detect nitrate contamination in water, to conduct food safety testing, and for analysis in clinical settings where NO is used as a drug for therapeutic purposes. Current standard methods of analysis either lack the detection ranges to be used in all cases or are to inefficient in terms of time or money to make them practical for measuring clinically sourced samples from a therapeutic setting. Being able to quantify the stable metabolites of NO allows for indirect methods like a nitrite or TNG method, which with the proper processing and isolation steps could be assumed to measure only nitrate, to become quite useful for NO detection. The NOA directly measures NO by reacting it with ozone and quantitatively detecting the subsequent photon emission. The extra step of reducing NO’s metabolites adds more potential for error, but because of the accuracy of the nitrite method this error is overshadowed by the method’s benefits. Another aspect limiting this project was that sample processing and analysis injections were performed manually by one operator. The manual aspect of the analysis portion introduces more error to measurements. An autoinjector with precise and consistent injections would help, leaving the operator to monitor aspects of the instrumentation that require closer attention. Having a single operator does not represent well the use of a method or procedure by a group of individuals. The error of the methods was improved by using this strategy; however, it does not fully represent whether or not this method can be used by others using a similar instrument. Repeating aspects of the project with multiple analysts would be a good additional step to furthering what was accomplished here. This work has shown that the accurate and precise measurement of NO at a nM detection range can be done quickly and inexpensively using chemiluminescent methods. Biological samples provide new issues over simple aqueous solutions due to their protein content and other biological material. These additional materials have the potential of causing interference and decreasing the efficiency of the assay, but they can be removed through forced crystallization and precipitation by processing with cold etOH. Since some biological samples (blood, meat, and fat) bind NO metabolites, we have shown here that the processing step will preserve the remaining metabolites. A-yet-to-be-determined conversion ratio could be applied to account for the missing yield. No disadvantage was gained by using the TNG method over other common methods, but the increased TNG concentrations in the meat and fat samples are still unexplained. A combination of low yield processes involving nitrate sequestering and L-arginine conversion 29  to NO and subsequentially nitrate or a yet unexplained cellular process may point to an answer.35, 37, 38 However, the possibility still remains that user error in the spiking step of processing may also be to blame. This project used bovine-sourced samples as they were an ideal choice due to availability and accessibility of all sample types. Another advantage for using bovine samples was that bovine animals are usually fed a high-nitrate diet. As a result, the inherent nitrogen group levels in their blood and tissues are higher than that of humans. Having the analysis work in samples with naturally elevated levels of nitrogen groups reflected positively on its robustness.  The analysis of nitrogen groups is a part of many fields, from biochemistry to food production. The analysis of NO is also becoming increasingly used in therapeutics as a biomarker for the body’s immune response. Various breathing tools exist for the accurate measurement of NO, but there is yet to be a method available to accurately measure a blood or urine sample for that same biomarker. The methods in this project had significantly lower detection range than current accepted methods at a lower cost point. A simple and efficient process using chemiluminescent analysis is a step forward to affordable and quick nitrogen group measurement for use in the field of therapeutics.    30  Bibliography  1. Fang, F. 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The TNG method is more powerful in that it reduces oxygen-bound nitrogen up to an oxidation state of +5, including all that the nitrite method can reduce, but it is less safe as it requires an operating temperature of 95°C and the vanadium solution is both toxic and highly acidic.    Figure 2 - Diagramed explanation of the processing steps of biological sample analysis. Biological replicates represent a sample of milk, blood, urine, meat, or fat. Spiking solution is a standard solution of either NaNO2 or NaNO3 in DIH2O at concentrations ranging from 50 to 1000 µM. The term “freeze” indicates a period of time ranging from an hour to over a month. Foam box photo from   35  Table 1 - Precision and accuracy of the nitrite method and TNG method determined prior to measurements with biological samples. Assays were done with nitrite and nitrate respectively dissolved in DI water. The %diff. was calculated using the measured concentration compared to the theoretical concentration of the solutions. Analyses were performed on different days and by different analysts. PRI=primary analyst; ALT=alternate analyst.    Nitrite Method TNG Method Sample Conc. Day Analyst %diff %RSD %diff %RSD Low Single Single (PRI1) 1.2 4.1 54.8 28.4 Low Single Single (PRI2) -4.9 3.3 9.9 28.4 Low Single Single (ALT1) -9.7 8 38.6 9.1 Low Single Multi -7.3 6.3 24.3 21.9 Low Multi Single -1.9 4.8 32.4 32.7 Low Multi Multi -4.5 7 34.4 26.5 High Single Single (PRI1) 0.8 1.6 -5.6 8.6 High Single Single (PRI2) -0.2 1.1 -6.5 6.9 High Single Single (ALT1) 0.9 2.3 38.9 3.8 High Single Multi 0.3 1.8 16.2 20.9 High Multi Single 0.3 1.4 -6 7.5 High Multi Multi 0.5 1.7 8.9 20.8  0 3 6 9 12050010001500Concentration of Standard (M)Area Under the Curve (mV*min)m=120.41.1 mV*min/Mm= 71.71.3 mV*min/M Figure 3 – Linear regression of standards analyzed with the nitrite method (×) and the TNG method (+). Data is combined from analysis sessions at the start and end of the day on two separate occasions for each method. Due to the differences in slope between the two methods, they are not directly comparable without the use of a normalizing standard. However, reliable standard curves standard curves can be repeatedly made by both methods.  36  0 2000 4000 6000 8000 10000020004000600080001000012000Theoretical Nitrite Conc. (nM)Measured Nitrite Conc. (nM)m=1.004+/-0.003A)0 2000 4000 6000 8000 10000020004000600080001000012000Theoretical Nitrate Conc. (nM)Measured Nitrate Conc. (nM)m=1.092+/-0.037B) Figure 4 - Graphs to visualize the precision and accuracy of the nitrite method (A) and the TNG method (B). Note the difference in the 95% prediction bands for each method. Since the relationship between two points is always linear, this is not a measure of linearity, but it is useful in displaying the accuracy and precision of the nitrite method.   Table 2 - Selectivity data from instrument qualification. NOx- represents the opposite nitroxide ion for which the method is selective.   Ammonia Urea NOx- Nitrite Method As-Prepared (nM) 10000 10000 7393 Avg. Measured (nM) N/A N/A 132 %diff. N/A N/A -98.21 TNG method As-Prepared (nM) 10000 10000 10158 Avg. Measured (nM) 467 450 9318 %diff. -95.33 -95.50 -8.27  0 1 0 0 0 2 0 0 0 3 0 0 0 4 0 0 0 5 0 0 001 0 0 02 0 0 03 0 0 04 0 0 05 0 0 0T h e o re t ic a l N itr ite  C o n c . (n M )Measured Nitrite Conc. (nM)A )m = 1 .0 2 5* + /-0 .0 040 1 0 0 0 2 0 0 0 3 0 0 0 4 0 0 0 5 0 0 001 0 0 02 0 0 03 0 0 04 0 0 05 0 0 0T h e o re t ic a l N itr ite  C o n c . (n M )Measured Nitrite Conc. (nM)B )m = 0 .7 7 2* + /-0 .0 080 1 0 0 0 2 0 0 0 3 0 0 0 4 0 0 0 5 0 0 001 0 0 02 0 0 03 0 0 04 0 0 05 0 0 0T h e o re t ic a l N itr ite  C o n c . (n M )Measured Nitrite Conc. (nM)C )m = 1 .0 2 6* + /-0 .0 040 1 0 0 0 2 0 0 0 3 0 0 0 4 0 0 0 5 0 0 001 0 0 02 0 0 03 0 0 04 0 0 05 0 0 0T h e o re t ic a l N itr ite  C o n c . (n M )Measured Nitrite Conc. (nM)D )m = 1 .0 2 8* + /-0 .0 050 1 0 0 0 2 0 0 0 3 0 0 0 4 0 0 0 5 0 0 001 0 0 02 0 0 03 0 0 04 0 0 05 0 0 0T h e o re t ic a l N itr ite  C o n c . (n M )Measured Nitrite Conc. (nM)E )m = 0 .9 4 5* + /-0 .0 060 1 0 0 0 2 0 0 0 3 0 0 0 4 0 0 0 5 0 0 001 0 0 02 0 0 03 0 0 04 0 0 05 0 0 0T h e o re t ic a l N itr ite  C o n c . (n M )Measured Nitrite Conc. (nM)F )m = 0 .9 9 2 + /-0 .0 0 4 Figure 5 - Linear regression of nitrite-spiked biological media. Data points represent means of multiple replicates excluding outlying data; bounds of the slopes indicate the range in which correctly measured data will fall with a 90% probability. 37  Slopes were constrained to Y=0 and compared against a slope of m=1. Significant difference to the slope of m=1 indicated by a "*" on each chart.  A) Saline, B) Blood, C) Milk, D) Urine, E) Meat, F) Fat.  0 1 0 0 0 2 0 0 0 3 0 0 0 4 0 0 0 5 0 0 001 0 0 02 0 0 03 0 0 04 0 0 05 0 0 0T h e o re tic a l N itra te  C o n c . (n M )Measured Nitrate Conc. (nM)A )m = 1 .0 1 5 + /-0 .0 0 70 1 0 0 0 2 0 0 0 3 0 0 0 4 0 0 0 5 0 0 001 0 0 02 0 0 03 0 0 04 0 0 05 0 0 0T h e o re tic a l N itra te  C o n c . (n M )Measured Nitrate Conc. (nM)B )m = 0 .8 7 2* + /-0 .0 100 1 0 0 0 2 0 0 0 3 0 0 0 4 0 0 0 5 0 0 001 0 0 02 0 0 03 0 0 04 0 0 05 0 0 0T h e o re tic a l N itra te  C o n c . (n M )Measured Nitrate Conc. (nM)C )m = 1 .0 3 5* + /-0 .0 070 1 0 0 0 2 0 0 0 3 0 0 0 4 0 0 0 5 0 0 001 0 0 02 0 0 03 0 0 04 0 0 05 0 0 0T h e o re tic a l N itra te  C o n c . (n M )Measured Nitrate Conc. (nM)D )m = 0 .8 0 4* + /-0 .0 200 1 0 0 0 2 0 0 0 3 0 0 0 4 0 0 0 5 0 0 001 0 0 02 0 0 03 0 0 04 0 0 05 0 0 0T h e o re tic a l N itra te  C o n c . (n M )Measured Nitrate Conc. (nM)E )m = 1 .1 5 6* + /-0 .0 170 1 0 0 0 2 0 0 0 3 0 0 0 4 0 0 0 5 0 0 001 0 0 02 0 0 03 0 0 04 0 0 05 0 0 0T h e o re tic a l N itra te  C o n c . (n M )Measured Nitrate Conc. (nM)F )m = 1 .1 1 4* + /-0 .0 16 Figure 6 – Linear Regression of nitrate-spiked biological media. Data points represent means of data sets excluding outliers. Bounds of the slopes indicate the 90% prediction interval for measurement data obtained in the same manner. Slopes were constrained to Y=0 and compared to a slope of m=1. Significance from a slope of m=1 indicated by a "*" on each chart. A) Saline, B) Blood, C) Milk, D) Urine, E) Meat, F) Fat. a lin eB lo o dM ilkU r in eM e a tF a tS lo p eA ) a lin eB lo o dM ilkU r in eM e a tF a tS lo p eB ) Figure 7 – Meta-Slope analysis for each sample media type. Each point represents the combination of slope calculations from each experimental assay. Points whose error bars cross the dotted line indicate significance to the slope of m=1. Outliers were calculated on an assay-to-assay basis and omitted using the automatic outlier exclusion option available in GraphPad. A) Nitrite spiked media by nitrite method, B) Nitrate spiked media by TNG method.   38  Table 3 – Limit of Blank (LoB), Limit of Detection (LoD), and Standard Error of the Limit of Detection (SELoD) for each method with varying biological media. Also includes slope and error along with R2 values for each linear curve. The “*” indicates which curves were significantly different than a slope of m=1.  Table 4 - Robustness test of change in reducing solution effectiveness as sample volumes are added throughout an experiment. Age is measured in number of sample injection into the solution. %diff Age (#injections) ~200µM ~7.5µM Nitrite Method 1 1.4% 9.0% 6 4.6% -0.4% TNG Method 1 6.5% -56.0% 6 18.8% 166.2%  Table 5 – Comparison by T-test of meta- analysis and mega-analysis slopes from the nitrite and TNG method. All P-values are greater than 0.05.  Method P value Meta-slope Mega-slope Difference SE of difference t ratio df Nitrite        Saline 0.5490 1.041 1.025 0.01596 0.02658 0.6004 192 Blood 0.9261 0.7674 0.7722 -0.00484 0.05214 0.0928 228 Milk 0.8409 1.021 1.026 -0.00482 0.02398 0.2010 218 Urine 0.8377 1.034 1.028 0.00600 0.02926 0.2051 203 Meat 0.8644 0.9387 0.9451 -0.00642 0.03754 0.1710 223 Fat 0.6799 1.004 0.9921 0.01182 0.02861 0.4132 213 TNG         Saline 0.9773 1.014 1.015 -0.00102 0.03581 0.0285 131 Blood 0.5963 0.8428 0.8722 -0.02940 0.05535 0.5312 114 Milk 0.9298 1.038 1.035 0.00348 0.03936 0.0883 118 Urine 0.8484 0.8240 0.8041 0.01986 0.1037 0.1915 138 Meat 0.8852 1.169 1.156 0.01260 0.08710 0.1447 134 Fat 0.8399 1.133 1.114 0.01850 0.09138 0.2025 125    Nitrite Method VCl3 Method Sample Type LoB (nM) LoD (nM) SELoD (nM) Slope ([meas]/[prep]) R^2 LoB (nM) LoD (nM) SELoD (nM) Slope ([meas]/[prep]) R^2 Saline 245 291 15 1.025*+/-0.004 0.9939 798 967 58 1.015+/-0.007 0.9592 Blood 278 357 18 0.772*+/-0.008 0.9543 5723 6147 314 0.872*+/-0.010 0.9043 Milk 220 268 13 1.026*+/-0.004 0.9945 3262 3410 245 1.035*+/-0.007 0.9813 Urine 421 496 23 1.028*+/-0.005 0.9921 16159 16556 1267 0.804*+/-0.020 0.8671 Meat 282 344 16 0.945*+/-0.006 0.9847 9481 9799 513 1.156*+/-0.017 0.8896 Fat 354 401 24 0.992+/-0.004 0.9919 18884 19355 1449 1.114*+/-0.016 0.8415 39  Appendix B – Recommended Standard Operating Procedure for Biological Sample Assays  1. Purpose To lay out an established method for the analysis of biological liquid and tissue samples by means of the Sievers 280i chemiluminescence nitric oxide analyzer (NOA). Liquid sample analysis with the NOA can be hindered by proteins or other large biological molecules. These processing and analysis methods are designed to reduce such interference and provide reliable analyses of biological media.  2. Materials and Equipment The following is a list of materials and equipment key for successful utilization of the Nitrite and TNG methods: − Sodium nitrite (NaNO2) − Sodium nitrate (NaNO3) − Sodium iodide (NaI) − Vanadium (III) chloride (VCl3) − Sodium hydroxide (NaOH) − Hydrochloric acid (HCl) − Glacial acetic acid (GAA) − Ethanol (preferably prechilled to -20°C) − Compressed nitrogen tank and two-stage regulator − Compressed oxygen tank − Deionized water − Biological samples: liquid or tissue − Analytical balance − Certified fume hood − Vacuum pump − Sievers 280i Nitric Oxide Analyzer − Purge vessel − Bubbler − Assorted tubing − Circulating water bath − Ice bath and long coiled tubing or chilled circulating water bath 40  − TSI 4100 thermal mass flow meter  − Volumetric flasks (200 mL and 10 mL) − Microcentrifuge tubes (1.5 mL) − Assortment of pipette tips and pipetters (20, 200, and 1000 µL) − Disposable scalpels − Mortal and pestle − Ultrasonic cell disruptor or sonicator − Medium weight open cell foam  − Vacuum filtration flask − Funnel − 250 µL analytical syringe − Eppendorf 5418 R or similar microcentrifuge  3. Processing Biological Samples To easily and effectively store samples it is important to process them as soon as possible. If space in a -80°C freezer is available, samples may be stored prior to processing, but same day or on-site processing should take priority. Biological sample sizes required will vary depending on experimental design (e.g. direct sampling or standard addition). 3.1. Liquid Sample Processing  i). If directly measuring an unknown biological sample proceed to step iv. ii). Separate one biological replicate into three 990 µL aliquots in separate 1.5 mL capped microcentrifuge tubes. iii). Add 10 µL of spiking solution to each tube. a). Concentration and composition of the spiking solution is dependent on the method and experimental range desired. iv). Add 600 µL of spiked biological solution to a new capped microcentrifuge tube and mix it with 400 µL of -20°C EtOH. v). Vortex each microcentrifuge tube before placing it in the centrifuge at 15,200g for 4 min at 4°C. a). A centrifuge with a temperature setting below 0°C is advantageous. vi). Transfer the supernatants to new capped microcentrifuge tubes and store them in a -20°C freezer until analysis. 41  a). Don’t forget to label every tube as you go to ensure no samples are confused during the processing stage. 3.2. Tissue Sample Processing i). Obtain a tissue sample and dice it with a scalpel or pulverize it by other means. ii). Weigh the sample and mix with isotonic saline in a 1 g/mL ratio. a). If working in 50 mL tubes, a 20 g sample is close to the maximum size. iii). Using an immersion sonicator, sonicate three times for 30 sec. iv). Set up the filter flask with the funnel and a piece of the open-cell foam. a). To avoid having to wash the filter flask between each replicate, prop a 15 mL tube in the filter flask and exchange it to collect each replicate. v). Once the filtrate is collected, process it as you would a liquid sample in section 3.1.  4. Preparing Nitrite/TNG Method Reducing Solutions Consistent and careful preparation of the reducing agents for both methods reduces variation between assays. Though a standard curve is created each day it is advantageous to have results from day to day that are at least similar. However, if a new reducing solution is created and introduced into the measurements for a given day, a new standard curve should be created. This section will focus on the preparation of the reducing solutions. The iodide reducing solution is not active until mixed with glacial acetic acid in the purge vessel. Alternatively, the Vanadium reducing solution is mixed fully beforehand but is not activated until it reached its reaction temperature of 95°C. 4.1. Nitrite Method Reducing Solution i). Bring the NaI and a 15 mL tube to the analytical balance.  ii). Tare the tube and weight out approximately 400 mg of NaI. a). Because the goal is for an iodide saturated solution, an exact mass measure is not required. b). However, the conversion efficiency of nitrite to nitric oxide is affected by iodide concentration, so an approximate measure of NaI very close to 400 mg is desired. Hence, a few milligrams over or under is not a concern. iii). Dissolve the iodide in about 5 mL of DI water, and then fill the tube to the analytical 15 mL mark. a). Depending on the brand of tube, this is either stamped or engraved directly on the tube, or it is a clear line near the threading, separate from the painted volume markers. 42  iv). Label and store the tube, wrapped in aluminum foil, in the fridge to help it remain viable. 4.2. TNG Method Reducing Solution i). Bring the VCl3, HCl, weight boat, and 50 mL tube to the certified fume hood. a). VCl3 vapours and particles are toxic and breathing them should be avoided. b). If possible, also bring the balance to the fume hood; however, due to the inherent motion and vibration of the fume hood, calibrating and measuring in that location will be difficult. ii). Weigh approximately 400 mg of VCl3 into the weigh boat. a). If the balance is not in the fume hood, use a cover to transfer the weigh boat from fume hood to balance.  b). Be sure to tare the weigh boat and cover before transferring measuring VCl3. c). Because the goal is for a vanadium saturated solution, an exact mass measure is not required. iii). Add ~25 mL of HCl to the 50 mL tube and carefully pour the VCl3 into the tube to dissolve in the acid. When dissolved, fill the tube to the analytical 50 mL mark with HCl. a). When mixing smaller amounts of reducing solution, use the same ratios as mentioned above. b). Dissolving VCl3 in an aqueous solution results in an exothermic reaction. Be aware that the solution can be hot when mixing larger volumes; however, continuous mixing should prevent it from becoming too hot to handle. c). When dissolving the VCl3 and HCl solution initially turns black and opaque. As the reaction continues it will turn clear and cyan coloured. If any black particles have not dissolved completely, filter the solution before storage.  iv). Cap the tube, wrap it in aluminum foil, and place it in the fridge to prevent light exposure and slow the reaction.   5. Preparing the NOA and Methods The nitric oxide analyzer requires some time to set up before analysis begins. This is for two main reasons: to allow the electronic signal from the photo multiplier tube to normalize, and also to allow the physical parameters of the analysis to normalize (e.g. cell pressure, cell temp., circulating water bath temp., etc.). The physical parameters can take up to 20 mins to all reach optimal for the method 43  to run smoothly. The electronic signal can take longer, up to an hour, and is critical for it to reach normality for the analysis.  5.1. Starting up the instrument i). Flip the power switch on the back of the NOA to the “ON” position. ii). In the first menu select: Start > Start. iii). Wait for the NOA self-diagnostic to start checking the cell temperature before manually turning on the vacuum pump. a). Due to issues with blown fuses, the vacuum pump power should not be routed through the NOA.  iv). Turn on the oxygen supply to 0.5 LPM. 5.2. Setting up the analysis mode i). When the NOA is finished its self-diagnostic it will display either mV, PPB, or PPM on the display. a). The signal will initially display higher than baseline. This is normal as the instrument’s electronics require a “warm-up” time. It can take 30-60 min to calm to baseline: anywhere between 4 to 40 mV depending on the ambient air composition.  b). If monitoring the baseline with the “Liquid” program, it is not uncommon for the baseline to fluctuate while the NOA is sampling ambient air. As long as the baseline noise does not appear to be on a downward trajectory, the NOA is ready to measure. ii). Ensure the NOA is measuring in voltage. a). From the main menu: Control > Setup > Change > Operator > Analysis > Operation > Units > Voltage > ENTER. iii). Ensure the NOA is in Nitric Oxide mode. a). From the main menu: Control > Setup > Change > Operator > Analysis Modes > Select Nitric Oxide > ENTER. iv). Ensure the NOA is set to high sensitivity. a). From the main menu: Control > Setup > Change > Operator > Analysis > Operation > Sensitivity > High > ENTER.  6. Preparing Standards and Methods A reliable standard curve is crucial to a reliable analysis regardless of the method. Make sure the reagents are not expired or other standard solutions have been prepared recently. Also, be careful to 44  keep the workspace free from nitrite contamination. Working with nM concentrations requires extra care as a very small amount of contamination can easily throw off the results. Creating a standard curve before measurements is also a good way to ensure that the NOA is ready for analysis. Care should also be taken to prepare the methods well with clean glassware and secure junctions and being as consistent as possible. A well functioning method prepared consistently can go a long way in improving results. 6.1. Standard Solution Preparation i). In a 15 mL tube, weigh out 1.035 g of NaNO2 and fill to the analytical 15 mL mark. ii). Using that 1 M standard NaNO2 solution, prepare serial dilutions ranging from 10 µM to 0.10 µM. a). It may be useful to test the signal from your biological samples to check if it falls within that range. iii). Bring the clearly labelled tubes to the fume hood where the NOA is warming up. a). Do not allow them to sit for too long as exposure to air or extended exposure to light can affect their concentration as nitrite shifts to nitrate. 6.2. Nitrite Method Preparation  i). Obtain the sodium iodide solution, Glacial acetic acid, and standard solutions and bring them to the NOA. a). For the following steps refer to Figure B1 for locations of the parts of the purge vessel and bubbler. ii). Ensure the circulating water bath is filled and firmly attached to the thermal jacket of the purge vessel and turn it on, adjusting the temperature to 25°C. iii). Ensure the condenser tubing is firmly attached and submerged in the ice bath before turning on the flow on the faucet flow. iv). Fill the bubbler with 10 mL of 1.0 M NaOH and refit the bubbler top, with Teflon sleeve, to the bubbler bottom with the green bracket. v). Attach the sampling line, fitted with an IFD liquid filter, to the gas outlet of the bubbler and ensure the cell pressure of the NOA reaction cell is at 4.5 to 5.5 torr. a). Check the cell pressure by returning to the NOA main menu and selecting Control > Status OR by waiting for the bottom of the analysis screen of the NOA to scroll through the status to the cell pressure. b). If the cell pressure is out of range some maintenance is required: Cleaning lines, clearing the frit restrictor, vacuum pump oil change, etc. 45  vi). Remove the septum screw cap of the purge vessel and drain the soaking solution (dilute HCl) into an appropriate receptacle. vii). Ensure the drain stopcock valve is closed and add 2.5 mL of glacial acetic acid and 0.5 mL of sodium iodide solution into the reaction cell. a). A 2 mL graduated pipette fitted to a standard 10 mL disposable syringe works excellently. viii). Ensure the regulator and gas lines are correctly and securely fit to the N2 tank. a). This should be already set up if the NOA is being used and properly maintained.  b). If attaching a new N2 tank, make sure you are using a two-stage regulator with threaded attachment type (580 SS). Gas line attachments post regulator, though not required to be threaded, need to be firmly attached as there will be back pressure during the analysis.  ix). With the inert gas line safely in the fume hood, open the N2 tank valve to allow N2 to flow freely through the line. a). The first stage of the regulator should read above 500 PSI, and the second stage should be adjusted to about 8 PSI. b). Using a variable valve, sometimes by attaching a second flow meter between the regulator and the thermal mass flow meter, adjust the flow rate to about 1 L/min. x). Ensure the inert gas line, fitted with the thermal mass flow meter, is firmly connected to the gas inlet of the purge vessel and the gas inlet stopcock valve is open. a). Be careful not to torque the glass fitting on the purge vessel because it can break. b). If for any reason you need to remove the inert gas line, close the inlet stopcock first to prevent back pressure from pushing reducing solution through the purge vessel’s glass frit. xi). Using the needle valve of the purge vessel, adjust the flow until it reaches 0.200 L/min. a). There will be fluctuation of about 0.010 L/min and this is normal. xii). Leaving the purge vessel open, and using flexible tubing, attach the bubbler inlet to the gas outlet of the purge vessel. a). Make sure that the stopcock valve for the gas outlet of the purge vessel is open. xiii). While monitoring the cell pressure of the NOA, re-attach the septum screw cap and take note if the pressure rises of falls. 46  a). If the pressure falls, increase the inert gas flow using the needle valve until the cell pressure rebounds. b). If the pressure rises, decrease the inert gas flow using the needle valve until the cell pressure reduces. c). This process can go back and forth for a little while. To reduce the amount of time spent on this task, also judge the pressure in the purge vessel by removing and attaching the septum screw cap. The goal is to have the septum hold on only slightly so there is a mild vacuum. If the negative pressure is too strong, you will have vacuum distillation of the reducing solution. If the positive pressure is too strong you will cause less NO to come out of solution and the set-up may spring leaks. xiv). When the desired equal pressure between the inert gas flow and sampling flow is reached, take note of the flow rate and try to keep it constant throughout the analysis. xv). With the flow rates matched, the cell pressure stable, and the reducing solution purged, the instrument is ready for measurements. 6.3.  TNG method Preparation  i). Obtain the TNG reducing solution and NaNO2 standards and bring them to the NOA. a). Since the TNG method can reduce both nitrite and nitrate, it is allowable to use the same standard, in this case a nitrite standard, across both methods if they are being used to measure the same samples. If only the TNG method is being used, it is possible to use a nitrate standard. If so, prepare the nitrate standard the way you would prepare the nitrite standards by creating a 1 M standard solution and then following the rest of the steps in section 6.1. ii). Ensure the circulating water bath is filled and firmly attached to the thermal jacket of the purge vessel and turn it on, adjusting the temperature to 95°C. iii). Follow steps iii – vi from section 6.2. iv). Ensure the drain stopcock valve is closed, and then add 3.0 mL of TNG reducing solution into the reaction cell. a). WARNING: The purge vessel will start to get HOT. Use caution when touching it and adjusting tubing, as contact with the thermal jacket will cause burns when the water bath is up to temperature. b). A 2 mL graduated pipette fitted to a standard 10 mL disposable syringe works excellently. 47  v). Follow steps viii – xv from section 6.2. vi). The TNG method is now ready to measure.  7. Starting up the Analysis Software Even with all the before preparation, without the software it would not be possible to proceed with an analysis. This particular program, “Liquid,” is designed to receive a serial signal from the NOA and format it in order to calculate the area under the curve of the plotted data. By doing this, “Liquid” enables the operator to very quickly create standard curves and get concentration data from the electronic signal. “Liquid” is part of a software package distributed with the NOA, NOAnalysis, and as such is not without its quirks. It is legacy software, but luckily Windows 10 continues to support it and its requirements. 7.1. Starting up The Software i). Turn on the computer connected to the NOA and ensure that the Serial-to-USB adapter is connected.  a). Try not to move the adapter from USB port to USB port. Each USB port will have to be set up in Windows to be identified as a unique virtual serial port. This is something that can be accomplished through the properties of the Serial-to-USB adapter in Window’s Device Manager. ii). Navigate to “Liquid” and open the program (Figure B2). a). If “Liquid” is not on the desktop, or if the shortcut has stopped working, find it by searching within Windows for “Liquid.exe,” and it should quickly come up. iii). A setup menu will pop up upon opening (Figure B3). a). Port number should be COM1. b). Firmware version should be 3.x. c). Set the Baud Rate to 38400. d). A good interval setting is 1/8 sec (data will be sampled at 8 points per second). It provides a balance between resolution and noise to improve peak resolution. e). Concentration units should be set to nM. f). Changing these settings requires matching the change to those in Windows for the virtual serial port and the output from the NOA. All three—instrument output, computer input, and software—must match for the signal from the NOA to be logged with the software. 48  iv). On the main menu screen, press the “Acquire” button and select a file name (Figure B4). a). If just starting the instrument, use the name test or another name to indicate this data is from a setup period. b). If creating a file for an analysis, a naming scheme like “YYYYMMDD” followed by the experiment name works well for organizing. It is common for there to be many files created, so a scheme that automatically organizes them by date is useful. Feel free to develop a usable naming scheme to personalize your results. v). You are now on the Acquire screen. Ensure that a signal is being logged in the graph (Figure B5). a). If the software is not visibly logging and the red light in the bottom left of the screen is flashing, then the program is not receiving a signal from the NOA. Review step iii. b). If the software is not visibly logging and the red light is NOT flashing, adjust the graph scale to match the output indicated on the screen of the NOA. This is done by selecting the top number of the Y-axis and typing in the desired number. vi). In optimal conditions, the baseline reading of the NOA for this closed system and active reducing agent should be approximately 6 mV. a). The number is seen on the display of the NOA and a line will begin to be plotted on the graph on the computer screen.  8. Sample Analysis Try not to do this step hastily, but it is also time sensitive. Warming the solutions before precipitating as much of the crystalized protein as possible will allow those proteins to go back into solution. This can cause contamination of introduced molecules that could interfere with the reduction of nitrite to nitric oxide. This is especially important for the TNG method, as increased protein concentration can also create false signal. This can be partially overcome by using a technique like standard addition, but it will be problematic for direct sampling.  8.1. Nitrite and TNG Method i). Obtain samples to measure from the freezer and spin them in the centrifuge at 16,900g for 30 sec at 4°C. ii). Transfer the supernatant to new tubes and put them on ice in a small lidded cooler. 49  a). Either ice from a -20°C freezer or a shaped freezer pack works well for keeping the samples cold. Ice from the ice dispenser may not be quite cold enough to keep samples below freezing for the duration of the analysis. b). It is helpful also to chill the new tubes before transferring the sample supernatants. iii). Bring the samples on ice to the NOA along with the standard solutions. a). BEFORE you start injecting samples, make sure you have followed the above steps to start an analysis and the software is logging data. iv). Wipe off the needle with a Kimwipe and prime the 250 µL analytical syringe with DI water by rinsing it three times before making the first injection. a). ALWAYS wipe the needle from base to tip to avoid puncture wounds. b). Starting with DI water helps prevent contaminating the most sensitive samples with the previous assay. c). Rinse a minimum of three times to follow the extraction principle that states that multiple smaller rinses have a greater ability to extract a compound than one rinse of larger volume. v). Start analysis using a 100 µL injection of the lowest concentration standard solution. a). With the sample about to be injected, rinse the syringe three times and plunge the rinse into the waste container. b). Draw the sample into the syringe about 20 µL past the 100 mark; there will be bubbles. c). Orient the syringe vertically and tap it lightly to encourage bubbles to rise near the needle. d). Draw a small amount of air into the syringe until the small bubbles all merge into one. e). Plunge out the air carefully not to expel too much standard. f). When the air is gone, orient the syringe horizontally and push the plunger in until the volume reaches 100 µL. g). Wipe the tip of the syringe and insert it into the purge vessel through the septum at the top of the reaction cell, being careful not to bump the plunger before the needle is inserted. h). Once inserted, plunge the syringe until it is empty and remove the needle. i). Wipe the needle to remove residual reducing solution and repeat the above steps, but wait until the previous peak has finished plotting on the graph before injecting. j). Repeat until there are three clear peaks on the graph. 50  vi). Using the above steps, alternate between injecting standard and biological samples in a manner ascending in concentration. vii). While waiting between injections, you will likely have time to label each injection. a). Label injections using the “Mark injections” button seen in Figure B5. b). Labelling during analysis avoids possible confusion that may occur when labelling at the end. c). Follow a consistent labeling scheme that reflects the name or properties of the sample, e.g. “100uM,” “10x diluted sample A,” etc.  d). If using the “Amounts” function be conscious of including injection volumes on the front of the label (Figure B9; e.g. “100uL 200nM,” “4uL 50uM,” or “20uL Sample C”). e). When labelling, “Liquid” will understand “uM” as if it was a “µM”  viii). After you have measured 2 biological samples and 3 standard solutions, open the septum cap of the purge vessel and then drain the contents. Close the drain and add fresh reducing solution.  a). Measuring more than this number of samples risks diluting the reducing solution too much and diminishing its ability to reduce. ix). While the septum cap is off, detach the tubing to the bubbler inlet and outlet, and drain its contents. Refill the bubbler with fresh NaOH solution and reassemble the bubbler and tubing. a). Following this procedure, the bubbler shouldn’t risk foaming into the sampling line of the NOA. On the rare occasion that it does, pause the analysis and detach the sample line, drain the IFD filter if liquid reached it, and clear the sampling line of any fluid obstructions. Reassemble once everything is cleaned. x). Check the condition of the ice bath for the condenser and add more ice if needed or drain excess fluid. xi). Re-attach the septum cap and double check the flow rates and cell pressure. Monitor throughout the analysis. a). If the cell pressure had dropped, try increasing the inert gas flow using the needle valve. b). If the cell pressure rises, decrease flow slightly with the needle valve. c). If adjusting the flow with the needle valve does not change the cell pressure, there may be an obstruction in the purge vessel frit. To try clearing this leave all the attachments 51  as you would for an analysis, except close the purge vessel gas inlet stopcock valve until the cell pressure begins dropping dramatically. Open the valve abruptly and see if the cell pressure returns to normal. Repeat the process again if needed. xii). Continue analysis until all the samples and standards have been injected by repeating steps v – xi. xiii). Press the “STOP” button on the acquire screen. a). If you run out of analysis time (“Liquid” has a 60 min analysis time maximum), restart your analysis by returning to the main menu and press the “Acquire” button. Save under a new name.  b). Any data logged during the analysis is automatically saved because the data file is created in real time. If you save with the same file name, it will overwrite your previous data.  9. Data analysis Data analysis consists of three parts using three different programs: “Liquid” (mentioned above) for recording and compiling data, Microsoft Excel for organizing and formatting the data, and GraphPad Prism for statistical analysis and regression. Because “Liquid” compiles data using a tab delimited format, Excel is necessary to read this format so it can be converted into a form usable by Prism. The convenience of “Liquid” is that it has a built-in peak selection and integration function to accompany its abilities to receive serial output directly from the NOA. though it is an older program, its use is still advantageous in that the operator can go from serial data, to integrated peaks, to calculated concentrations in quick succession. Once formatted with Excel, GraphPad Prism provides a platform to set up analyses and graph formats so that data can be input into templates as it is collected. If the above steps have been followed, and peaks are labelled the process of getting from recorded data to analysis in GraphPad is quick and straightforward. 9.1. Recording Data and Creating a Calibration Curve i). The screen following the “Acquire” screen is the “Threshold” screen.  ii). Move the horizontal yellow line up or down until vertical yellow lines intersect your peaks, but ignore unwanted peaks, if possible (Figure B6). iii). Press “Threshold OK”, press “Change Threshold & Peak Width”, confirm your threshold is in the right place, and press “Threshold OK” again. 52  a). During the first attempt to select peaks, “Liquid” makes a broad selection. If the process is repeated the program refines its selection of peaks. However, more importantly, repeat the process you use to select peaks exactly for the sample peaks that will be processed. Follow the general rule that if you did it for the standard curve, do it for all the other peaks. iv). On the “Integrate Peaks” screen select “Integrate” (Figure B7). v). The following screen is the “Process Liquid Data” screen. On this screen double-check that the names of the peaks (displayed in the table on the right, Figure B8) match up with the peaks on the graph.  a). Based off the threshold and peak selection the integrated areas also appear in the name chart under the column “Area.” b). If there is an anomalous peak, or too many labels, use the buttons along the bottom of the screen to select peaks and associated names, delete names, delete areas, insert names, or delete peaks entirely. Avoid deleting peaks, but if you make a mistake use the button labelled “Reintegrate” to start over. c). If making a calibration, or standard, curve be sure to add names using the “Insert Name” button. If the “Name Peak” button is used, the program will not recognize the named peak when compiling the curve. vi). When the peaks are matched with appropriate labels, press “Next Peak” until buttons appear on the right side of the screen (Figure B9). vii). Press “Create Calibration” and the “Calibrate” screen will appear (Figure B10). Review the points; if there are red “x” points on the graph, select the area associated with that point to activate buttons to edit the point (Figure B11).  a). If the point is okay press “Point OK”, If the point should be removed press “Delete Point.” b). If you already have a calibration curve made and you wish to add points to the existing curve, press “Add to Calibration”. viii). Press “Save Calibration” and go through the steps of saving the calibration curve, or press “Continue” and confirm that you don’t want to save the calibration curve at this time. ix). After saving or continuing, you will be returned to the “Process Liquid Data” screen where the option “Calculate Concentrations” will appear (Figure B12).  53  a). If you are finished creating your calibration curve, press this button and proceed to the next screen. b). I recommend unchecking the “Use Intercept” box (Figure B12) unless performing a standard addition experiment. c). If you have not finished creating your calibration curve (all the peaks from standards may not have fit into one set of data), close this screen and press “Process Data” on the main screen, or continue with your standard measurements. x). The final screen is the data display screen (Figure B13), and before saving the data the options to recalculate and reintegrate are available. If everything looks good, press the “Save New Results File” button and assign a relevant file name.  a). I find setting the save as type in the save window to “all files” and selecting the same name as the data file is a convenient way to organize results generated and data recorded. The file will still be saved as the appropriate file type. b). Following this scheme gives three file types per analysis:,, and file_name.rsl. 9.2. Organizing and Formatting with Excel; Analysis in GraphPad i). Start by locating the .rsl files from your analysis.  a). Set the directory path in “Liquid” using the drop-down menus: Edit > Preferences. b). Alternatively, do a file search in windows if you know the file name and the directory is unknown. ii). Right click the .rsl file of choice and select “Open with…”; select Excel. iii). The file should open with some mild formatting issues. a). Excel is capable of accessing tab delimited files; however, double-check the column headers and make sure the names line up. b). Save the file as another file type (like .xlsx) and do not save the original file. If the file is saved with Excel, some characters will change and “Liquid” will no longer be able to access it. A new .rsl file would have to be generated. It is also good practice to leave your originals unedited and only edit copies. iv). After correcting column headers and checking labels for peaks and measurements, perform whatever formatting you may also need for your experimental design. a). Each experiment is different and an identical analysis from experiment to experiment is not always advisable.  54  b). Experimental design and desired analyses of data should be decided on and potentially set up before the experiment starts. Sometimes, it is difficult to foresee the analyses that will be most telling and interpretive. Trial runs and test analyses are a good way to decide on what will be the most effective. v). Transfer data to GraphPad. vi). Arrange your data according to the experimental design you previously chose. a). GraphPad has many options available for creating graphs. An option that works well with the kind of data created during analysis is the XY graph. b). Options within the XY graph setup allow for grouping replicates at the same x-values; plotting points with means, standard deviations, and point counts; or you can plot simple X-Y comparisons.  10. Cleaning and Disposal One of the most important steps for these methods for continued reliable analyses is the cleaning procedure. During experiments, nitrites and nitrates have a tendency to attach themselves to the surface of the glass of the purge vessel. For example, if the nitrite method is used a number of times without the TNG method, and the purge vessel was not cleaned properly, the build up of nitrates on the glass surface will become detached when the TNG method is used causing rogue peaks and altering the signal during sample analysis. Following this cleaning routine eliminates nearly all of these peaks and false signals. 10.1. Cleaning Procedure i). Open the purge vessel’s threaded septum cap, disconnect the bubbler from the purge vessel, and disconnect the NOA sampling line. Leave the line in a safe location sampling ambient air. ii). Close the purge vessel’s gas inlet stopcock valve, and carefully remove the inert gas line. a). Removing the inert gas line without closing the stopcock causes back pressure to push the reducing solution through the glass frit and into the glass tubing. This can cause potential future contamination. b). Removing the inert gas line at an angle or roughly may damage the purge vessel. Use a gentle rotating motion. Closing the stopcock should also help with removing the line.  iii). Connect an air supply up to the gas inlet to keep reducing solution out of the gas inlet tubing.  a). If no air supply is available, a reduced flow from the inert gas supply will also work. 55  iv). Using the DI water wash bottle, rinse from the open top of the purge vessel while leaving the drain open. a). Follow a sequence of rinsing, filling, and draining until the foaming in the purge vessel subsides. v). When the foaming subsides, fill the purge vessel’s reaction chamber about a quarter with DI water, and let the gas continue to flow through it. vi). Using the wash bottle, begin a sequence of putting small portions of DI water in the purge vessel gas inlet and using the flowing gas to gently push it part way into the tubing.  a). Make sure the wash bottle has a fine tip. vii). Continue this pattern until the gas inlet tugging has filled nearly to the needle valve with no bubble partitions. viii). With the gas/air supply gently push the DI water through the glass tubing until it has reached the bottom of the tubing. ix). Repeat steps vi – viii two more times ensuring that no air has accumulated at the bottom of the purge vessel’s glass frit. a). This is a sometimes tedious but necessary step. Without it the next steps will only be partially effective in that the acid will not travel up the inlet tubing easily and any impurities that may have gotten in the tubing will remain until the next analysis. b). Drain the purge vessel’s reaction cell if the liquid volume gets too high and there are still more rinses to complete. x). Open the drain stopcock and drain the contents of the purge vessel reaction cell. xi). Ensure the drain stopcock is closed and add 5 mL of 0.5 M HCl to the purge vessel. xii). Rotate the purge vessel about 45 degrees counter-clockwise so the condenser is about even with the reaction cell opening in the relation to the fume hood’s surface. xiii). With the inlet and outlet stopcocks on the purge vessel open, and the drain closed, begin filling the purge vessel with DI water until water has filled the reaction chamber and mostly filled the condenser. DI water should be to the lip of the top opening of the reaction cell.  a). The dilute HCl needs to reach into the condenser because, as liquids condense, some nitric oxide will be reabsorbed into solution and form nitrates and nitrites again. As the analysis goes on, there is potential for these nitrites and nitrates to attach to the glass walls of the condenser. When TNG reducing solution condenses during analysis, it will carry those nitrates and nitrites back into the reaction cell and cause interference. 56  b). It is important to try to fill the purge vessel as much as possible. xiv). Replace the threaded septum cap and leave the purge vessel partially rotated.  a). Over the period of a few hours, the dilute acid will seep up into the inlet tubing. This process does not need to be monitored. xv). At this stage the purge vessel is ready to sit overnight or until the next set of analyses are ready to be performed.  11. Figures and Diagrams Figures and diagrams below are for the demonstration of some of the core principles needed for successful and efficient utilization of the methods above.   Figure B1 - Purge Vessel and Bubbler Diagram with key parts labelled.  Needle Valve Bubbler Outlet/ To NOA Outlet Stopcock Bubbler Bubbler Inlet Threaded Septum Cap Condenser Outlet Stopcock Gas Outlet Thermal Jacket Drain Stopcock Purge Vessel Reaction Cell Inlet Tubing Gas Inlet Stopcock Inert Gas Inlet 57   Figure B2 - “Liquid” icon. Icon for program used to record and compile data output from the Nitric Oxide Analyzer.  Figure B3 - Setup Menu from "Liquid."   Figure B4 - Main menu screen from "Liquid." 58   Figure B5 - Acquire screen from "Liquid."   Figure B6 - Threshold screen from "Liquid." 59   Figure B7 - Integrate peaks screen from "Liquid."   Figure B8 - Process liquid data screen from "Liquid."   60   Figure B9 - Buttons that appear after processing.   Figure B10 - Calibrate screen from "Liquid."   Figure B11 - Calibration point edit buttons from "Liquid." 61   Figure B12 - Calculate concentrations button from "Liquid."   Figure B13 - Data display screen from "Liquid."   


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