Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Biomarker”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Serum biomarkers for diagnosis and prediction of type 1 diabetes

Type 1 diabetes (T1D) culminates in the autoimmune destruction of the pancreatic ß-cells, leading to insufficient production of insulin and development of hyperglycemia. Serum biomarkers including glucose, glycated molecules, c-peptide, and autoantibodies have been well established to diagnose T1D from other subtypes of diabetes. However, these molecules often mark a late stage of the disease when ~90% of the pancreatic insulin-producing ß-cells have already been lost. With the prevalence of T1D increasing worldwide and because of the physical and psychological burden induced by this disease, there is a great need for prognostic biomarkers to predict T1D development or progression. This would allow us to identify individuals at high risk for early prevention and intervention. Therefore, considerable efforts have been dedicated to the understanding of disease etiology and the discovery of novel biomarkers in the last few decades. The advent of high-throughput and sensitive ‘-omics’ technologies for the study of proteins, nucleic acids, and metabolites have allowed large scale profiling of protein expression and gene changes in T1D patients relative to disease-free controls. In this review, we briefly discuss the classical diagnostic biomarkers of T1D and mainly focus on the novel biomarkers that are identified as markers of ß-cell destruction and screened with the use of state-of-the-art ‘-omics’ technologies.

Yi, Lian↗
DOE OSTI2015

The NINDS Parkinson's disease biomarkers program: The Ninds Parkinson's Disease Biomarkers Program

Background: Neuroprotection for Parkinson Disease (PD) remains elusive. Biomarkers hold the promise of removing roadblocks to therapy development. The National Institute of Neurological Disorders and Stroke (NINDS) has therefore established the Parkinson’s Disease Biomarkers Program (PDBP) to promote discovery of biomarkers for use in phase II-III clinical trials in PD. Methods: The PDBP facilitates biomarker development to improve neuroprotective clinical trial design, essential for advancing therapeutics for PD. To date, eleven consortium projects in the PDBP are focused on the development of clinical and laboratory-based PD biomarkers for diagnosis, progression tracking, and/or the prediction of prognosis. Seven of these projects also provide detailed longitudinal data and biospecimens from PD patients and controls, as a resource for all PD researchers. Standardized operating procedures and pooled reference samples have been created in order to allow cross-project comparisons and assessment of batch effects. A web-based Data Management Resource facilitates rapid sharing of data and biosamples across the entire PD research community for additional biomarker projects. Results: Here we describe the PDBP, highlight standard operating procedures for the collection of biospecimens and data, and provide an interim report with quality control analysis on the first 1082 participants and 1033 samples with quality control analysis collected as of October 2014. Conclusions: By making samples and data available to academics and industry, encouraging the adoption of existing standards, and providing a resource which complements existing programs, the PDBP will accelerate the pace of PD biomarker research, with the goal of improving diagnostic methods and treatment.

biofluids↗
DOE OSTI2017

Parkinson’s disease biomarkers: perspective from the NINDS Parkinson’s Disease Biomarkers Program

Biomarkers for Parkinson’s disease (PD) diagnosis, prognostication and clinical trial cohort selection are an urgent need. While many promising markers have been discovered through the National Institute of Neurological Disorders and Stroke Parkinson’s Disease Biomarker Program (PDBP) and other mechanisms, no single PD marker or set of markers are ready for clinical use. Here we discuss the current state of biomarker discovery for platforms relevant to PDBP. We discuss the role of the PDBP in PD biomarker identification and present guidelines to facilitate their development. These guidelines include: harmonizing procedures for biofluid acquisition and clinical assessments, replication of the most promising biomarkers, support and encouragement of publications that report negative findings, longitudinal follow-up of current cohorts including the PDBP, testing of wearable technologies to capture readouts between study visits and development of recently diagnosed (de novo) cohorts to foster identification of the earliest markers of disease onset.

Gwinn, Katrina↗
NASA NTRS2004

Hopane Biomarkers Traced from Bedrock to Recent Sediments and Ice at the Haughton Impact Structure, Devon Island: Implications for the Search for Biomarkers on Mars

Hopanoid biomarkers have been successsfully traced from Palaeozoic target bedrock to Miocene impact-processed rocks, post-impact sediments, and Qu aternary ice at the Haughton impact Structure, Devon Island, High Arctic, suggesting that similar biomarkers and techniques to detect them might provide a promising strategy in the search for biomarkers in rocks, sediments and ice on Mars.

Parnell, J.↗
DOE OSTI2018

A Ricin Forensic Profiling Approach Based on a Complex Set of Biomarkers

A forensic method for the retrospective determination of preparation methods used for illicit ricin toxin production was developed. The method was based on a complex set of biomarkers, including carbohydrates, fatty acids, seed storage proteins, in combination with data on ricin and Ricinus communis agglutinin. The analyses were performed on samples prepared from four castor bean plant ( Ricinus communis ) cultivars by four different sample preparation methods (PM1 – PM4) ranging from simple disintegration of the castor beans to multi-step preparation methods including different protein precipitation methods. Comprehensive analytical data was collected by use of a range of analytical methods and robust orthogonal partial least squares-discriminant analysis- models (OPLS-DA) were constructed based on the calibration set. By the use of a decision tree and two OPLS-DA models, the sample preparation methods of a test set of ricin preparations were determined. The model statistics of the two models were good and a 100% rate of correct predictions of the test set was achieved.

Fredriksson, Sten-Åke (ORCID:0000000237131990)↗
DOE OSTI2015

Interpreting biomarker data from the COPHES/DEMOCOPHES twin projects: Using external exposure data to understand biomarker differences among countries

In 2011 and 2012, the COPHES/DEMOCOPHES twin projects performed the first ever harmonized human biomonitoring survey in 17 European countries. In more than 1800 mother–child pairs, individual lifestyle data were collected and cadmium, cotinine and certain phthalate metabolites were measured in urine. Total mercury was determined in hair samples. While the main goal of the COPHES/DEMOCOPHES twin projects was to develop and test harmonized protocols and procedures, the goal of the current paper is to investigate whether the observed differences in biomarker values among the countries implementing DEMOCOPHES can be interpreted using information from external databases on environmental quality and lifestyle. In general, 13 countries having implemented DEMOCOPHES provided high-quality data from external sources that were relevant for interpretation purposes. However, some data were not available for reporting or were not in line with predefined specifications. Therefore, only part of the external information could be included in the statistical analyses. Nonetheless, there was a highly significant correlation between national levels of fish consumption and mercury in hair, the strength of antismoking legislation was significantly related to urinary cotinine levels, and we were able to show indications that also urinary cadmium levels were associated with environmental quality and food quality. These results again show the potential of biomonitoring data to provide added value for (the evaluation of) evidence-informed policy making. - Highlights: • External data was collected to interpret HBM data from DEMOCOPHES. • Hg in hair could be related to fish consumption across different countries. • Urinary cotinine was related to strictness of anti-smoking legislation. • Urinary Cd was borderline significantly related to air and food quality. • Lack of comparable data among countries hampered the analysis.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Constraints on the Metabolic Activity of Microorganisms in Atacama Surface Soils Inferred from Refractory Biomarkers: Implications for Martian Habitability and Biomarker Detection

Dryness is one of the main environmental challenges to microbial survival. Understanding the threshold of microbial tolerance to extreme dryness is relevant to better constrain the environmental limits of life on Earth and critically evaluate long-term habitability models of Mars. Biomolecular proxies for microbial adaptation and growth were measured in Mars-like hyper-arid surface soils in the Atacama Desert that experience only a few millimeters of precipitation per decade, and in biologically active soils a few hundred kilometers away that experience two- to fivefold more precipitation. Diversity and abundance of lipids and other biomolecules decreased with increasing dryness. Cyclopropane fatty acids (CFAs), which are indicative of adaptive response to environmental stress and growth in bacteria, were only detected in the wetter surface soils. The ratio of trans to cis isomers of an unsaturated fatty acid, another bacterial stress indicator, decreased with increasingly dry conditions. Aspartic acid racemization ratios increased from 0.01 in the wetter soils to 0.1 in the driest soils, which is indicative of racemization rates comparable to de novo biosynthesis over long timescales (10,000 years). The content and integrity of stress proteins profiled by immunoassays were additional indicators that biomass in the driest soils is sin situ microbial growth in the driest surface soils of the Atacama, and any metabolic activity is likely to be basal for cellular repair and maintenance only. Our data add to a growing body of evidence that the driest Atacama surface soils represent a threshold for long-term habitability (i.e., growth and reproduction). These results place constraints on the potential for extant life on the surface of Mars, which is 100–1000 times drier than the driest regions in the Atacama.

Wilhelm, Mary Beth↗
DOE OSTI2025

The impact of kidney function on Alzheimer’s disease blood biomarkers: implications for predicting amyloid-β positivity

Impaired kidney function has a potential confounding effect on blood biomarker levels, including biomarkers for Alzheimer’s disease (AD). Given the imminent use of certain blood biomarkers in the routine diagnostic work-up of patients with suspected AD, knowledge on the potential impact of comorbidities on the utility of blood biomarkers is important. We aimed to evaluate the association between kidney function, assessed through estimated glomerular filtration rate (eGFR) calculated from plasma creatinine and AD blood biomarkers, as well as their influence over predicting Aβ-positivity. We included 242 participants from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort, comprising cognitively unimpaired individuals (CU; n = 124), mild cognitive impairment (MCI; n = 58), AD dementia (n = 34), and non-AD dementia (n = 26) patients all characterized by [ 18 F] AZD-4694. Plasma samples were analyzed for Aβ42, Aβ40, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), tau phosphorylated at threonine 181 (p-tau181), 217 (p-tau217), 231 (p-tau231) and N-terminal containing tau fragments (NTA-tau) using Simoa technology. Kidney function was assessed by eGFR in mL/min/1.73 m 2 , based on plasma creatinine levels, age, and sex. Participants were also stratified according to their eGFR-indexed stages of chronic kidney disease (CKD). We evaluated the association between eGFR and blood biomarker levels with linear models and assessed whether eGFR provided added predictive value to determine Aβ-positivity with logistic regression models. Biomarker concentrations were highest in individuals with CKD stage 3, followed by stages 2 and 1, but differences were only significant for NfL, Aβ42, and Aβ40 (not Aβ42/Aβ40). All investigated biomarkers showed significant associations with eGFR except plasma NTA-tau, with stronger relationships observed for Aβ40 and NfL. However, after adjusting for either age, sex or Aβ-PET SUVr, the association with eGFR was no longer significant for all biomarkers except Aβ40, Aβ42, NfL, and GFAP. When evaluating whether accounting for kidney function could lead to improved prediction of Aβ-positivity, we observed no improvements in model fit (Akaike Information Criterion, AIC) or in discriminative performance (AUC) by adding eGFR to a base model including each plasma biomarker, age, and sex. While covariates like age and sex improved model fit, eGFR contributed minimally, and there were no significant differences in clinical discrimination based on AUC values. We found that kidney function seems to be associated with AD blood biomarker concentrations. However, these associations did not remain significant after adjusting for age and sex, except for Aβ40, Aβ42, NfL, and GFAP. While covariates such as age and sex improved prediction of Aβ-positivity, including eGFR in the models did not lead to improved prediction for any biomarker. Our findings indicate that renal function, within the normal to mild impairment range, does not seem to have a clinically relevant impact when using highly accurate blood biomarkers, such as p-tau217, in a biomarker-supported diagnosis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Combining biomarker and virus phylogenetic models improves HIV-1 epidemiological source identification

To identify and stop active HIV transmission chains new epidemiological techniques are needed. Here, we describe the development of a multi-biomarker augmentation to phylogenetic inference of the underlying transmission history in a local population. HIV biomarkers are measurable biological quantities that have some relationship to the amount of time someone has been infected with HIV. To train our model, we used five biomarkers based on real data from serological assays, HIV sequence data, and target cell counts in longitudinally followed, untreated patients with known infection times. The biomarkers were modeled with a mixed effects framework to allow for patient specific variation and general trends, and fit to patient data using Markov Chain Monte Carlo (MCMC) methods. Subsequently, the density of the unobserved infection time conditional on observed biomarkers were obtained by integrating out the random effects from the model fit. This probabilistic information about infection times was incorporated into the likelihood function for the transmission history and phylogenetic tree reconstruction, informed by the HIV sequence data. To critically test our methodology, we developed a coalescent-based simulation framework that generates phylogenies and biomarkers given a specific or general transmission history. Testing on many epidemiological scenarios showed that biomarker augmented phylogenetics can reach 90% accuracy under idealized situations. Under realistic within-host HIV-1 evolution, involving substantial within-host diversification and frequent transmission of multiple lineages, the average accuracy was at about 50% in transmission clusters involving 5–50 hosts. Realistic biomarker data added on average 16 percentage points over using the phylogeny alone. Using more biomarkers improved the performance. Shorter temporal spacing between transmission events and increased transmission heterogeneity reduced reconstruction accuracy, but larger clusters were not harder to get right. More sequence data per infected host also improved accuracy. We show that the method is robust to incomplete sampling and that adding biomarkers improves reconstructions of real HIV-1 transmission histories. The technology presented here could allow for better prevention programs by providing data for locally informed and tailored strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Approach to Cerebrospinal Fluid (CSF) Biomarker Discovery and Evaluation in HIV Infection

Central nervous system (CNS) infection is a nearly universal facet of systemic HIV infection that varies in character and neurological consequences. While clinical staging and neuropsychological test performance have been helpful in evaluating patients, cerebrospinal fluid (CSF) biomarkers present a valuable and objective approach to more accurate diagnosis, assessment of treatment effects and understanding of evolving pathobiology. We review some lessons from our recent experience with CSF biomarker studies. We have used two approaches to biomarker analysis: targeted, hypothesis-driven and non-targeted exploratory discovery methods. We illustrate the first with data from a cross-sectional study of defined subject groups across the spectrum of systemic and CNS disease progression and the second with a longitudinal study of the CSF proteome in subjects initiating antiretroviral treatment. Both approaches can be useful and, indeed, complementary. The first is helpful in assessing known or hypothesized biomarkers while the second can identify novel biomarkers and point to broad interactions in pathogenesis. Common to both is the need for well-defined samples and subjects that span a spectrum of biological activity and biomarker concentrations. Previouslydefined guide biomarkers of CNS infection, inflammation and neural injury are useful in categorizing samples for analysis and providing critical biological context for biomarker discovery studies. CSF biomarkers represent an underutilized but valuable approach to understanding the interactions of HIV and the CNS and to more objective diagnosis and assessment of disease activity. Both hypothesis-based and discovery methods can be useful in advancing the definition and use of these biomarkers.

Biomarkers↗
DOE OSTI2017

Mass Spectrometry-based Assay for High Throughput and High Sensitivity Biomarker Verification

Searching for disease specific biomarkers has become a major undertaking in the biomedical research field as the effective diagnosis, prognosis and treatment of many complex human diseases are largely determined by the availability and the quality of the biomarkers. A successful biomarker as an indicator to a specific biological or pathological process is usually selected from a large group of candidates by a strict verification and validation process. To be clinically useful, the validated biomarkers must be detectable and quantifiable by the selected testing techniques in their related tissues or body fluids. Due to its easy accessibility, protein biomarkers would ideally be identified in blood plasma or serum. However, most disease related protein biomarkers in blood exist at very low concentrations (<1ng/mL) and are “masked” by many none significant species at orders of magnitude higher concentrations. The extreme requirements of measurement sensitivity, dynamic range and specificity make the method development extremely challenging. The current clinical protein biomarker measurement primarily relies on antibody based immunoassays, such as ELISA. Although the technique is sensitive and highly specific, the development of high quality protein antibody is both expensive and time consuming. The limited capability of assay multiplexing also makes the measurement an extremely low throughput one rendering it impractical when hundreds to thousands potential biomarkers need to be quantitatively measured across multiple samples. Mass spectrometry (MS)-based assays have recently shown to be a viable alternative for high throughput and quantitative candidate protein biomarker verification. Among them, the triple quadrupole MS based assay is the most promising one. When it is coupled with liquid chromatography (LC) separation and electrospray ionization (ESI) source, a triple quadrupole mass spectrometer operating in a special selected reaction monitoring (SRM) mode, also known as multiple reaction monitoring (MRM), is capable of quantitatively measuring hundreds of candidate protein biomarkers from a relevant clinical sample in a single analysis. The specificity, reproducibility and sensitivity could be as good as ELISA. Furthermore, SRM MS can also quantify protein isoforms and post-translational modifications, for which traditional antibody-based immunoassays often don’t exist.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2016

TH-A-207B-00: Shear-Wave Imaging and a QIBA US Biomarker Update

Imaging of tissue elastic properties is a relatively new and powerful approach to one of the oldest and most important diagnostic tools. Imaging of shear wave speed with ultrasound is has been added to most high-end ultrasound systems. Understanding this exciting imaging mode aiding its most effective use in medicine can be a rewarding effort for medical physicists and other medical imaging and treatment professionals. Assuring consistent, quantitative measurements across the many ultrasound systems in a typical imaging department will constitute a major step toward realizing the great potential of this technique and other quantitative imaging. This session will target these two goals with two presentations. A. Basics and Current Implementations of Ultrasound Imaging of Shear Wave Speed and Elasticity - Shigao Chen, Ph.D. Learning objectives-To understand: Introduction: Importance of tissue elasticity measurement Strain vs. shear wave elastography (SWE), beneficial features of SWE The link between shear wave speed and material properties, influence of viscosity Generation of shear waves External vibration (Fibroscan) ultrasound radiation force Point push Supersonic push (Aixplorer) Comb push (GE Logiq E9) Detection of shear waves Motion detection from pulse-echo ultrasound Importance of frame rate for shear wave imaging Plane wave imaging detection How to achieve high effective frame rate using line-by-line scanners Shear wave speed calculation Time to peak Random sample consensus (RANSAC) Cross correlation Sources of bias and variation in SWE Tissue viscosity Transducer compression or internal pressure of organ Reflection of shear waves at boundaries B. Elasticity Imaging System Biomarker Qualification and User Testing of Systems – Brian Garra, M.D. Learning objectives-To understand: Goals Review the need for quantitative medical imaging Provide examples of quantitative imaging biomarkers Acquaint the participant with the purpose of the RSNA Quantitative Imaging Biomarker Alliance and the need for such an organization Review the QIBA process for creating a quantitative biomarker Summarize steps needed to verify adherence of site, operators, and imaging systems to a QIBA profile Underlying Premise and Assumptions Objective, quantifiable results are needed to enhance the value of diagnostic imaging in clinical practice Reasons for quantification Evidence based medicine requires objective, not subjective observer data Computerized decision support tools (eg CAD) generally require quantitative input. Quantitative, reproducible measures are more easily used to develop personalized molecular medical diagnostic and treatment systems What is quantitative imaging? Definition from Imaging Metrology Workshop The Quantitative Imaging Biomarker Alliance Formation 2008 Mission Structure Example Imaging Biomarkers Being Explored Biomarker Selection Groundwork Draft Protocol for imaging and data evaluation QIBA Profile Drafting Equipment and Site Validation Technical Clinical Site and Equipment QA and Compliance Checking Ultrasound Elasticity Estimation Biomarker US Elasticity Estimation Background Current Status and Problems Biomarker Selection-process and outcome US SWS for Liver Fibrosis Biomarker Work Groundwork Literature search and analysis results Phase I phantom testing-Elastic phantoms Phase II phantom testing-Viscoelastic phantoms Digital Simulated Data Protocol and Profile Drafting Protocol: based on UPICT and existing literature and standards bodies protocols Profile-Current claims, Manufacturer specific appendices What comes after the profile Profile Validation Technical validation Clinical validation QA and Compliance Possible approaches Site Operator testing Site protocol re-evaluation Imaging system Manufacturer testing and attestation User acceptance testing and periodic QA Phantom Tests Digital Phantom Based Testing Standard QA Testing Remediation Schemes Profile Evolution Towards additional applications Towards higher accuracy and precision Supported in part by NIH contract HHSN268201300071C from NIBIB. Collaboration with GE Global Research, no personal support.; S. Chen, Some technologies described in this presentation have been licensed. Mayo Clinic and Dr. Chen have financial interests these technologies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-A-207B-02: QIBA Ultrasound Elasticity Imaging System Biomarker Qualification and User Testing of Systems

Imaging of tissue elastic properties is a relatively new and powerful approach to one of the oldest and most important diagnostic tools. Imaging of shear wave speed with ultrasound is has been added to most high-end ultrasound systems. Understanding this exciting imaging mode aiding its most effective use in medicine can be a rewarding effort for medical physicists and other medical imaging and treatment professionals. Assuring consistent, quantitative measurements across the many ultrasound systems in a typical imaging department will constitute a major step toward realizing the great potential of this technique and other quantitative imaging. This session will target these two goals with two presentations. A. Basics and Current Implementations of Ultrasound Imaging of Shear Wave Speed and Elasticity - Shigao Chen, Ph.D. Learning objectives-To understand: Introduction: Importance of tissue elasticity measurement Strain vs. shear wave elastography (SWE), beneficial features of SWE The link between shear wave speed and material properties, influence of viscosity Generation of shear waves External vibration (Fibroscan) ultrasound radiation force Point push Supersonic push (Aixplorer) Comb push (GE Logiq E9) Detection of shear waves Motion detection from pulse-echo ultrasound Importance of frame rate for shear wave imaging Plane wave imaging detection How to achieve high effective frame rate using line-by-line scanners Shear wave speed calculation Time to peak Random sample consensus (RANSAC) Cross correlation Sources of bias and variation in SWE Tissue viscosity Transducer compression or internal pressure of organ Reflection of shear waves at boundaries B. Elasticity Imaging System Biomarker Qualification and User Testing of Systems – Brian Garra, M.D. Learning objectives-To understand: Goals Review the need for quantitative medical imaging Provide examples of quantitative imaging biomarkers Acquaint the participant with the purpose of the RSNA Quantitative Imaging Biomarker Alliance and the need for such an organization Review the QIBA process for creating a quantitative biomarker Summarize steps needed to verify adherence of site, operators, and imaging systems to a QIBA profile Underlying Premise and Assumptions Objective, quantifiable results are needed to enhance the value of diagnostic imaging in clinical practice Reasons for quantification Evidence based medicine requires objective, not subjective observer data Computerized decision support tools (eg CAD) generally require quantitative input. Quantitative, reproducible measures are more easily used to develop personalized molecular medical diagnostic and treatment systems What is quantitative imaging? Definition from Imaging Metrology Workshop The Quantitative Imaging Biomarker Alliance Formation 2008 Mission Structure Example Imaging Biomarkers Being Explored Biomarker Selection Groundwork Draft Protocol for imaging and data evaluation QIBA Profile Drafting Equipment and Site Validation Technical Clinical Site and Equipment QA and Compliance Checking Ultrasound Elasticity Estimation Biomarker US Elasticity Estimation Background Current Status and Problems Biomarker Selection-process and outcome US SWS for Liver Fibrosis Biomarker Work Groundwork Literature search and analysis results Phase I phantom testing-Elastic phantoms Phase II phantom testing-Viscoelastic phantoms Digital Simulated Data Protocol and Profile Drafting Protocol: based on UPICT and existing literature and standards bodies protocols Profile-Current claims, Manufacturer specific appendices What comes after the profile Profile Validation Technical validation Clinical validation QA and Compliance Possible approaches Site Operator testing Site protocol re-evaluation Imaging system Manufacturer testing and attestation User acceptance testing and periodic QA Phantom Tests Digital Phantom Based Testing Standard QA Testing Remediation Schemes Profile Evolution Towards additional applications Towards higher accuracy and precision Supported in part by NIH contract HHSN268201300071C from NIBIB. Collaboration with GE Global Research, no personal support.; S. Chen, Some technologies described in this presentation have been licensed. Mayo Clinic and Dr. Chen have financial interests these technologies.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2017

Investigation of Tear Biomarkers as an Indicator of Human Health

Scientific literature suggests that tear biomarkers can be used as a guide towards clinical diagnosis of human health (Hagan et al., 2016). This study will investigate whether tear biomarkers represents a research and clinical opportunity to assess human health prior to, during, and after exposure to the spaceflight environment. The focus of this study is to compare biomarkers previously identified as potentially relevant to both ocular and brain health against unique physiological outcomes of exposure to the space flight environment. Study subjects suffering from terrestrial conditions thought to be similar to Spaceflight Associated Neuro-ocular Syndrome (SANS: formerly VIIP), e.g. patients with idiopathic intracranial hypertension (IIH) and optic neuritis may be relevant to conditions associated with spaceflight. This study will review methodologies, tear biomarkers related to state of ocular and brain health, the strengths and weakness of using tear fluid biomarkers versus other body fluid samples, and will survey current tear fluid biomarker knowledge in research and clinical practice. A strength of using tear biomarkers is that sampling is non-invasive and used as a guide in understanding pathologies, including ocular and systemic inflammatory conditions (Cocho et al., 2016)., Salvisberg et al., 2014). Moreover, tear biomarkers may reflect diseases affecting the central nervous system (CNS) (Salvisberg et al., 2014). For example, in multiple sclerosis (MS), the concordance rate between tear biomarkers versus cerebrospinal fluid (CSF) is approximately 83%, indicating that, in the majority of cases, tears are at least as effective as CSF in potentially identifying novel MS biomarkers (Devos et al., 2001).

Morton, Stephen↗
DOE OSTI2023

Predicting chronic postsurgical pain: current evidence and a novel program to develop predictive biomarker signatures

Chronic pain affects more than 50 million Americans. Treatments remain inadequate, in large part, because the pathophysiological mechanisms underlying the development of chronic pain remain poorly understood. Pain biomarkers could potentially identify and measure biological pathways and phenotypical expressions that are altered by pain, provide insight into biological treatment targets, and help identify at-risk patients who might benefit from early intervention. Biomarkers are used to diagnose, track, and treat other diseases, but no validated clinical biomarkers exist yet for chronic pain. To address this problem, the National Institutes of Health Common Fund launched the Acute to Chronic Pain Signatures (A2CPS) program to evaluate candidate biomarkers, develop them into biosignatures, and discover novel biomarkers for chronification of pain after surgery. This article discusses candidate biomarkers identified by A2CPS for evaluation, including genomic, proteomic, metabolomic, lipidomic, neuroimaging, psychophysical, psychological, and behavioral measures. Acute to Chronic Pain Signatures will provide the most comprehensive investigation of biomarkers for the transition to chronic postsurgical pain undertaken to date. Data and analytic resources generatedby A2CPS will be shared with the scientific community in hopes that other investigators will extract valuable insights beyond A2CPS’s initial findings. This article will review the identified biomarkers and rationale for including them, the current state of the science on biomarkers of the transition from acute to chronic pain, gaps in the literature, and how A2CPS will address these gaps.

60 APPLIED LIFE SCIENCES↗