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Results for “Sensitivity and Specificity”

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.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

An enzyme immunoassay for rat growth hormone - Applications to the study of growth hormone variants

A sensitive and specific competitive enzyme immunoassay for rat growth hormone (GH) is described and its use in the detection of GH variants is demonstrated. In the present assay, soluble GH and GH adsorbed to a solid-phase support compete for monkey anti-GH antibody binding sites. The immobilized antibody-GH complex is detected and quantified using goat antimonkey immunoglobin G covalently conjugated to horseradish peroxidase. It is noted that the assay can be performed in 27 hours and that sensitivities in the range of 0.19 to 25 ng can be obtained in the region of 10 to 90 percent binding.

Farrington, Marianne A.↗
NASA NTRS2007

Determination of Scopolamine in Human Saliva Using Solid Phase Extraction and LC/MS/MS

Purpose: Scopolamine is the preferred treatment for motion sickness during space flight because of its quick onset of action, short half-life and favorable side-effect profile. The dose administered depends on the mode of administration and usually ranges between 0.1 and 0.8 mg. Such small doses make it difficult to detect concentrations of scopolamine in biological fluids by using conventional HPLC methods. To measure scopolamine in saliva and thereby to evaluate the pharmacokinetics of scopolamine, we developed an LC/MS/MS method using off-line solid phase extraction. Method: Samples (0.5mL) were loaded onto Waters Oasis HLB co-polymer cartridges (10 mg, 1 mL) and eluted with 0.5 mL methanol without evaporation and reconstitution. HPLC separation of the eluted sample was performed using an Agilent Zorbax SB-CN column (50 x 2.1 mm) at a flow rate of 0.2 mL/min for 4 minutes. The mobile phase for separation was 90:10 (v/v) methanol: ammonium acetate (2 mM) in water, pH 5.0 +/- 0.1. Concentrations of scopolamine were determined using a Micromass Quattro Micro(TM) mass spectrometer with electrospray ionization (ESI). ESI mass spectra were acquired in positive ion mode with multiple reaction monitoring for the determination of scopolamine m/z = 304.2 yields 138.1 and internal standard (IS) hyoscyamine m/z = 290.2 yields 124.1. Results: The method is rapid, reproducible, specific and has the following parameters: scopolamine and the IS are eluted at 1.7 and 3.2 min respectively. The linear range is 50-5000 pg/mL for scopolamine in saliva with correlation coefficients > 0.99 with a CV < 0.5 %. The intra-day and inter-day CVs are < 15 % for quality control samples with concentrations of 75, 300, 750 and 3000 pg/mL of scopolamine in human saliva. Conclusion: Solid phase extraction allows more rapid sample preparation and greater precision than liquid extraction. Furthermore, we increased the sensitivity and specificity by adjusting the LC mobile phase and using an MS/MS detector.

Wang, Zuwei↗
NASA NTRSDate not supplied

Developmental Hardware Testing Results and Forward Plans for the Spacecraft Water Impurity Monitor (SWIM) Organic Water Module (OWM)

We present testing results for developmental hardware of the Spacecraft Water Impurity Monitor (SWIM) Organic Water Module (OWM). SWIM-OWM will monitor spacecraft potable water and system water for trace organic contaminants. The system will detect and identify the specific organic chemical that makes up a given total organic carbon reading. We have built a first development unit (1DU) for SWIM-OWM, which directly injects aqueous water samples and detects chemicals with both a thermal conductivity detector and mass spectrometer sensor. The gas chromatography mass spectrometer (GCMS) system that comprises SWIM-OWM draws on the success of ISS-proven mass spectrometer hardware, and the demonstration of GCMS detection of trace organic contaminants in ISS cabin air. SWIM-OWM benefits from the excellent sensitivity and specificity afforded by GCMS. We have demonstrated detection of a set of chemicals relevant to both crew health and performance as well as system monitoring; these target chemicals range from light, volatile organics such as acetone and ethanol, to heavier, very non-volatile compounds such as dimethyl sulfone and o-phthalaldehyde. Direct aqueous injection was chosen for the general applicability of the technique to clean water sampling and to preclude sample pre-processing, which facilitates an on-line implementation of the SWIM-OWM when deployed in a spacecraft or habitation module. A specific advantage of direct aqueous injection when coupled with appropriate methods is that both the light, volatile organics and heavier non-volatiles can be detected from a single injection, in a single chromatogram. Results from 1DU testing will be discussed, and forward plans will be outlined for continued maturation of SWIM-OWM with the goal of implementing a technology demonstration for the purposes of maturing the engineering design and operations in an environment relevant to NASA’s future goals of exploring and setting up habitation on the Moon and Mars.

Water Monitoring↗
NASA NTRSDate not supplied

Developmental Hardware Testing Results and Forward Plans for Spacecraft Water Impurity Monitor (SWIM) Organic Water Module (OWM)

We present testing results for developmental hardware of the Spacecraft Water Impurity Monitor (SWIM) Organic Water Module (OWM). SWIM-OWM will monitor spacecraft potable water and system water for trace organic contaminants. The system will detect and identify the specific organic chemical that makes up a given total organic carbon reading. We have built a first development unit (1DU) for SWIM-OWM, which directly injects aqueous water samples and detects chemicals with both a thermal conductivity detector and mass spectrometer sensor. The gas chromatography mass spectrometer (GCMS) system that comprises SWIM-OWM draws on the success of ISS-proven mass spectrometer hardware, and the demonstration of GCMS detection of trace organic contaminants in ISS cabin air. SWIM-OWM benefits from the excellent sensitivity and specificity afforded by GCMS. We have demonstrated detection of a set of chemicals relevant to both crew health and performance as well as system monitoring; these target chemicals range from light, volatile organics such as acetone and ethanol, to heavier, very non-volatile compounds such as dimethyl sulfone and o-phthalaldehyde. Direct aqueous injection was chosen for the general applicability of the technique to clean water sampling and to preclude sample pre-processing, which facilitates an on-line implementation of the SWIM-OWM when deployed in a spacecraft or habitation module. A specific advantage of direct aqueous injection when coupled with appropriate methods is that both the light, volatile organics and heavier non-volatiles can be detected from a single injection, in a single chromatogram. Results from 1DU testing will be discussed, and forward plans will be outlined for continued maturation of SWIM-OWM with the goal of implementing a technology demonstration for the purposes of maturing the engineering design and operations in an environment relevant to NASA’s future goals of exploring and setting up habitation on the Moon and Mars.

Water Monitoring↗
NASA NTRS1972

The simultaneous quantitation of ten amino acids in soil extracts by mass fragmentography

A specific and sensitive method for the identification and simultaneous quantitation by mass fragmentography of ten of the amino acids present in soil was developed. The technique uses a computer driven quadrupole mass spectrometer and a commercial preparation of deuterated amino acids is used as internal standards for purposes of quantitation. The results obtained are comparable with those from an amino acid analyzer. In the quadrupole mass spectrometer-computer system up to 25 pre-selected ions may be monitored sequentially. This allows a maximum of 12 different amino acids (one specific ion in each of the undeuterated and deuterated amino acid spectra) to be quantitated. The method is relatively rapid (analysis time of approximately one hour) and is capable of the quantitation of nanogram quantities of amino acids.

Pereira, W. E.↗
NASA NTRS1981

Enhanced skeletal muscle insulin sensitivity in year-old rats adapted to hypergravity

Rats induced into a hypermetabolic state by exposure to chronic (7 mo) centrifugation at 4.15 g exhibited increased glucose uptake at lower plasma insulin levels than weight-matched control animals following oral glucose administration. In order to determine the insulin sensitivity of specific tissues, the effect of exogenous insulin on glucose uptake by isolated perfused livers and hindlim skeletal muscle from rats adapted to chronic centrifugation for one year was compared with perfused tissue from 2.5 mo-old noncentrifuged control animals of equal body weight. Metabolic glucose clearance by skeletal muscle from hypergravic rats did not prove significantly greater than control muscle when perfused in the absence of insulin (10.6 vs 8.1 microliters/min-g-muscle), but was twice as fast (23.0 vs 9.5) at perfusate insulin levels of 35 micro-U/ml. Conversely, glucose uptake by hypergravic livers was significantly decreased (P is less than 0.001) compared with control livers (10.3 vs 27.8) at perfusate insulin levels of 40 micro-U/ml. Results suggest that skeletal muscle rather than liver is primarily responsible for the enhanced sensitivity to insulin and the increased energy expenditure observed in rats subjected to hypergravity.

Mondon, C. E.↗
NASA NTRS1999

Kennedy Space Center Coronary Heart Disease Risk Screening Program

The number one cause of death in the U.S. is coronary heart disease (CHD). It is probably a major cause of death and disability in the lives of employees at Kennedy Space Center (KSC) as well. The KSC Biomedical Office used a multifactorial mathematical formula from the Framingham Heart Study to calculate CHD risk probabilities for individuals in a segment of the KSC population that required medical evaluation for job certification. Those assessed to be high-risk probabilities will be targeted for intervention. Every year, several thousand KSC employees require medical evaluations for job related certifications. Most medical information for these evaluations is gathered on-site at one of the KSC or Cape Canaveral Air Station (CCAS) medical clinics. The formula used in the Framingham Heart Study allows calculation of a person's probability of acquiring CHD within 10 years. The formula contains the following variables: Age, Diabetes, Smoking, Left Ventricular Hypertrophy, Blood Pressure (Systolic or Diastolic), Cholesterol, and HDL cholesterol. The formula is also gender specific. It was used to calculate the 10-year probabilities of CHD in KSC employees who required medical evaluations for job certifications during a one-year time frame. This KSC population was profiled and CHD risk reduction interventions could be targeted to those at high risk. Population risk could also be periodically reevaluated to determine the effectiveness of intervention. A 10-year CHD risk probability can be calculated for an individual quite easily while gathering routine medical information. An employee population's CHD risk probability can be profiled graphically revealing high risk segments of the population which can be targeted for risk reduction intervention. The small audience of NASA/contractor physicians, nurses and exercise/fitness professionals at the breakout session received the lecture very well. Approximately one third indicated by a show of hands that they would be interested in implementing a similar program at their NASA Center. Questions were asked pertaining to standardization for age, the validity of using the idealized male values also for the female population, and indications of the screening test's sensitivity and specificity.

Tipton, David A.↗
DOE OSTI2026

Toward Intelligent Multimodal Holography for Real-Time Chemical Imaging of Dynamic Ion Separation

Molecular-level visualization of ion transport and separation dynamics in complex environments is crucial for advancing energy systems, water purification, and critical materials recovery. Achieving this requires imaging platforms that combine structural sensitivity, chemical specificity, and real-time operation. Digital off-axis holography (DOAH) provides high-throughput, label-free quantitative phase imaging but inherently lacks chemical selectivity. Integrating DOAH with complementary spectroscopic channels such as fluorescence or hyperspectral imaging introduces the needed molecular specificity, while also creating challenges in multimodal data fusion, synchronization, and computational throughput. Artificial intelligence offers a powerful route to address these limitations by uniting physics-based reconstruction with data-driven interpretation. In this Perspective, we outline a framework for intelligent multimodal holography and demonstrate its potential using a preliminary AI-driven test case. Raw DOAH holograms of lanthanide solutions subjected to magnetic field gradients were analyzed using multi-agent AI workflows that autonomously selected reconstruction tools, extracted NMF components, and generated scientific claims consistent with true paramagnetic and diamagnetic behavior. This demonstration shows how AI-enabled reasoning can deliver real-time chemical–structural interpretation directly from raw holograms. Together, these advances define a path toward adaptive, intelligent holography platforms capable of supporting in situ chemical separations, dynamic ion transport analysis, and next-generation interfacial science.

Ricchiuti, Giovanna↗
DOE OSTI2024

Multihead Attention U‐Net for Magnetic Particle Imaging–Computed Tomography Image Segmentation

Magnetic particle imaging (MPI) is an emerging noninvasive molecular imaging modality with high sensitivity and specificity, exceptional linear quantitative ability, and potential for successful applications in clinical settings. Computed tomography (CT) is typically combined with the MPI image to obtain more anatomical information. Herein, a deep learning‐based approach for MPI‐CT image segmentation is presented. The dataset utilized in training the proposed deep learning model is obtained from a transgenic mouse model of breast cancer following administration of indocyanine green (ICG)‐conjugated superparamagnetic iron oxide nanoworms (NWs‐ICG) as the tracer. The NWs‐ICG particles progressively accumulate in tumors due to the enhanced permeability and retention (EPR) effect. The proposed deep learning model exploits the advantages of the multihead attention mechanism and the U‐Net model to perform segmentation on the MPI‐CT images, showing superb results. In addition, the model is characterized with a different number of attention heads to explore the optimal number for our custom MPI‐CT dataset.

Juhong, Aniwat↗
DOE OSTI2026

Neural Posterior Estimation for Scalable and Accurate Inverse Parameter Inference in Li-Ion Batteries

Diagnosing the internal state of Li-ion batteries is critical for battery research, operation of real-world systems, and prognostic evaluation of remaining lifetime. By using physics-based models to perform probabilistic parameter estimation via Bayesian calibration, diagnostics can account for the uncertainty due to model fitness, data noise, and the observability of any given parameter. However, Bayesian calibration in Li-ion batteries using electrochemical data is computationally intensive even when using a fast surrogate in place of physics-based models, requiring many thousands of model evaluations. A fully amortized alternative is neural posterior estimation (NPE). NPE shifts the computational burden from the parameter estimation step to data generation and model training, reducing the parameter estimation time from minutes to milliseconds, enabling real-time applications. The present work shows that NPE can infer parameters equally or more accurately than Bayesian calibration, even if it leads to higher voltage reconstruction errors. We also demonstrate that the higher computational costs for data generation are tractable even in high-dimensional cases (ranging from 6 to 27 estimated parameters). The NPE method also offers several interpretability advantages over Bayesian calibration, such as local parameter sensitivity to specific regions of the voltage curve. The NPE method is demonstrated using an experimental fast charge dataset, with parameter estimates validated against measurements of loss of lithium inventory and loss of active material. The implementation is made available in a companion repository (https://github.com/NatLabRockies/BatFIT).

25 ENERGY STORAGE↗
DOE OSTI2026

Aggregation Methods for Quantifying PTM and Structural Changes in Bottom-Up Proteomics

Bottom-up proteomic workflows rely on sequential preprocessing steps, commonly including peptide-to-protein aggregation (“roll-up”), to enhance data reliability and interpretability. While roll-up is effective for protein-centered analyses, it may be suboptimal for applications focused on post-translational modifications (PTMs) or protein structural changes, such as limited proteolysis–mass spectrometry (LiP-MS). Here, we investigate how different roll-up strategies influence site-level quantification in PTM differential analysis. Moreover, we introduce a novel site-centric roll-up approach tailored for LiP-MS, which quantifies proteolytic fragments rather than solely tryptic peptides. We benchmark these methods through simulation studies, comparing their sensitivity and specificity in detecting structural and PTM-driven changes. We found that the median and mean roll-up methods outperform the sum method in both PTM and LiP proteomics, and site-level quantification in LiP outperforms peptide-level quantification. Our findings offer the first systematic, data-driven guidance for selecting roll-up techniques in site-level proteomic analyses, with implications for both PTM-focused and structural proteomics studies.

aggregation↗
DOE OSTI2026

Mechanistic Insights for Plasma-Catalytic CO 2 Reduction over TiO 2 in a Dielectric Barrier Discharge Reactor

Reaction kinetics experiments coupled with phenomenological kinetic modeling and parameter estimation are used to elicit insights into the mechanism and active sites for the plasma-catalytic dissociation of CO 2 on TiO 2 . Experimental and model insights showed that gas-phase reactions contribute at least two-thirds of the overall product formation at explored conditions; weak temperature dependence, strong sensitivity to specific energy input (SEI), apparent first order in CO 2 , and positive influence of cofed argon (Ar) and oxygen (O 2 ) for the gas-phase contributions all suggest that expected plasma reaction steps such as electron-impact and high-energy collisions are the dominant modes for CO 2 dissociation. The Arrhenius-like expression for gas contributions resulted in a preexponential of 4.40 × 10 –3 s –1 , an E SEI,g of 7.90 × 10 –4 mol/kJ, and an E a,g of 1.00 × 10 –3 J/mol. For surface contributions, the small apparent barrier of 16.3 kJ/mol, relatively weaker dependence on SEI, first-order dependence on CO 2 , and insensitivity to cofed Ar and O 2 all point to CO 2 dissociation on TiO 2 surface facets without vacancies and aided by plasma (leading to vibrationally excited CO 2 and/or a reactive surface with significant surface charge accumulation). The Arrhenius-like expression resulted in a preexponential of 7.81 × 10 –2 s –1 , an E SEI,s of 1.90 × 10 –3 mol/kJ, and an E a,s of 1.63 × 10 4 J/mol. The derived kinetic model further enabled a systematic evaluation of the effect of inputs (plasma power, flow rate, CO 2 inlet concentration, and temperature) to identify process trends and optimal operating conditions.

catalyst↗
DOE OSTI2026

Detection and imaging of chemicals and hidden explosives using terahertz time-domain spectroscopy and deep learning

Detecting concealed chemicals and explosives remains a critical challenge in global security. Terahertz time-domain spectroscopy (THz-TDS) offers a promising non-invasive and stand-off detection technique owing to its ability to penetrate optically opaque materials without causing ionization damage. While many chemicals exhibit distinct spectral features in the terahertz range, conventional terahertz-based detection methods often struggle in real-world environments, where variations in sample geometry, thickness, and packaging can lead to inconsistent spectral responses. In this study, we present a chemical imaging system that integrates THz-TDS with deep learning to enable accurate pixel-level identification and classification of different explosives. Operating in reflection mode and enhanced with plasmonic nanoantenna arrays, our THz-TDS system achieves a peak dynamic range of 96 dB and a detection bandwidth of 4.5 THz, supporting practical, stand-off operation. By analyzing individual time-domain pulses with deep neural networks, the system exhibits strong resilience to environmental variations and sample inconsistencies. Blind testing across eight chemicals—including pharmaceutical excipients and explosive compounds—resulted in an average classification accuracy of 99.42% at the pixel level. Notably, the system maintained an average accuracy of 88.83% when detecting explosives concealed under opaque paper coverings, demonstrating its robust generalization capability. These results highlight the potential of combining advanced terahertz spectroscopy with neural networks for highly sensitive and specific chemical and explosive detection in diverse and operationally relevant scenarios.

Imaging and sensing↗
DOE OSTI2024

Light-induced H 2 generation in a photosystem I-O 2 -tolerant [FeFe] hydrogenase nanoconstruct

The fusion of hydrogenases and photosynthetic reaction centers (RCs) has proven to be a promising strategy for the production of sustainable biofuels. Type I (iron-sulfur-containing) RCs, acting as photosensitizers, are capable of promoting electrons to a redox state that can be exploited by hydrogenases for the reduction of protons to dihydrogen (H 2 ). While both [FeFe] and [NiFe] hydrogenases have been used successfully, they tend to be limited due to either O 2 sensitivity, binding specificity, or H 2 production rates. In this study, we fuse a peripheral (stromal) subunit of Photosystem I (PS I), PsaE, to an O 2 -tolerant [FeFe] hydrogenase from Clostridium beijerinckii using a flexible [GGS] 4 linker group (CbHydA1-PsaE). We demonstrate that the CbHydA1 chimera can be synthetically activated in vitro to show bidirectional activity and that it can be quantitatively bound to a PS I variant lacking the PsaE subunit. When illuminated in an anaerobic environment, the nanoconstruct generates H 2 at a rate of 84.9 ± 3.1 µmol H 2 mg chl –1 h –1 . Further, when prepared and illuminated in the presence of O 2 , the nanoconstruct retains the ability to generate H 2 , though at a diminished rate of 2.2 ± 0.5 µmol H 2 mg chl –1 h –1 . This demonstrates not only that PsaE is a promising scaffold for PS I-based nanoconstructs, but the use of an O 2 -tolerant [FeFe] hydrogenase opens the possibility for an in vivo H 2 generating system that can function in the presence of O 2 .

Hydrogenase↗
DOE OSTI2024

Drug-induced kidney injury: challenges and opportunities

Abstract Drug-induced kidney injury (DIKI) is a frequently reported adverse event, associated with acute kidney injury, chronic kidney disease, and end-stage renal failure. Prospective cohort studies on acute injuries suggest a frequency of around 14%–26% in adult populations and a significant concern in pediatrics with a frequency of 16% being attributed to a drug. In drug discovery and development, renal injury accounts for 8 and 9% of preclinical and clinical failures, respectively, impacting multiple therapeutic areas. Currently, the standard biomarkers for identifying DIKI are serum creatinine and blood urea nitrogen. However, both markers lack the sensitivity and specificity to detect nephrotoxicity prior to a significant loss of renal function. Consequently, there is a pressing need for the development of alternative methods to reliably predict drug-induced kidney injury (DIKI) in early drug discovery. In this article, we discuss various aspects of DIKI and how it is assessed in preclinical models and in the clinical setting, including the challenges posed by translating animal data to humans. We then examine the urinary biomarkers accepted by both the US Food and Drug Administration (FDA) and the European Medicines Agency for monitoring DIKI in preclinical studies and on a case-by-case basis in clinical trials. We also review new approach methodologies (NAMs) and how they may assist in developing novel biomarkers for DIKI that can be used earlier in drug discovery and development.

Connor, Skylar (ORCID:0000000233479180)↗
DOE OSTI2025

Reagent-free Hyperspectral Diagnosis of SARS-CoV-2 Infection in Saliva Samples

Rapid, reagent-free pathogen-agnostic diagnostics that can be performed at the point of need are vital for preparedness against future outbreaks. Yet, many current strategies are pathogen-specific and require several reagents. We present hyperspectral sensing, using light to non-invasively measure the composition of several molecules to form a spectral signature, to overcome these barriers. To generate these spectral signatures, we present the ProSpectral TM V1, a novel, miniaturized hyperspectral platform with high spectral resolution with two mini-spectrometers. Furthermore, we developed state-of-the-art ML pipelines for near real-time analysis of spectral signatures in saliva samples. We found that we could accurately identify SARS-CoV-2 infection status in double-blinded saliva samples and demonstrate 100% accuracy on a hold out test dataset. To our knowledge, this establishes the fastest hyperspectral diagnostic platform and in a small form factor, and executable with liquid samples, without ligands or reagents, all while maintaining PCR level specificity and sensitivity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Characterize and control the multi-range structure of solution-phase systems with resonant x-ray scattering

This work aims at demonstrating the feasibility and impact of Anomalous X-ray Scattering (AXS) in characterizing the multi-range structures of solution-state systems. We will show preliminary investigation of long-range correlations in concentrated aqueous electrolytes with a combination of AXS and molecular dynamics (MD) simulations. We will also start exploring the capability of AXS to capture intra- and inter-molecular structure of dilute molecular systems, and specifically its sensitivity to the chemical environment surrounding active metal sites. We anticipate that the development of this method will help us to understand ion solvation and transport, which affect the performances of, for instance, electrocatalytic cells, as well as to identify/control the intrinsic structural factors that lead to selectivity, efficiency, and stability control during catalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Energy Transfer in Lanthanide Luminescent Complexes

The primary objective of this project was to investigate the mechanisms of energy transfer in lanthanide luminescent complexes, focusing on elucidating the role of ligand-to-metal charge transfer processes and the efficiency of sensitization mechanisms. Specifically, this work aimed to determine the mechanistic details of energy transfer pathways in systems incorporating lanthanide ions such as terbium and europium, with a focus on advancing the application of these complexes in molecular imaging and photonic technologies.

Raymond, Kenneth [University of California, Berkel↗