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At least 199 records · Page 11

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NASA NTRS2017

Biosensor Integration Development ExMC/Canadian Space Agency Collaboration

In support of the NASA Human Research Program Exploration Medical Capability (ExMC) Element, NASA Ames Research Center (ARC) established a collaborative effort with the Canadian Space Agency (CSA). The collaboration focuses on leveraging CSA capability in the areas of biosensors and decision support that will augment future development of such components for Exploration Missions. The CSA advancement of biosensors enables NASA to focus on the integration and data management associated with these types of components through the system currently under development by the Medical Data Architecture (MDA) project. This approach has enabled the establishment of a successful collaborative working relationship between ExMC and CSA.Applying lessons learned from the fiscal year 2016 (FY16) Human Exploration Research Analog (HERA) campaign, CSA and NASA ARC developed a solution to provide real-time feedback to researchers who monitor the collection of vital signs data from a wearable Astroskin garment. The advances in the interfaces included the development of an iPad application (by CSA) to wirelessly forward the vital signs data to the MDA system, which collected the vital signs data through a receiver developed by NASA ARC. The development of these interfaces aims to provide communications between the Astroskin and the MDA system such that data may be seamlessly collected, stored and retrieved by the MDA. The first steps towards this goal were demonstrated in FY16. In FY17, ExMC will complete the first in a series of test beds that establishes a system to automate collection and management of vital sign data from the Astroskin, and other sources of data, to provide information for a crewmember to make medical decisions. In addition, the MDA Test Bed 1 will enable CSA to evaluate and optimize biosensor advancement and facilitate decision support algorithm development.

Vital signs↗

NASA NTRS2017

Biosensor Integration Development ExMC/Canadian Space Agency Collaboration

Astroskin↗

NASA NTRS1980

Emergency Medical Service

Lewis Research Center helped design the complex EMS Communication System, originating from space operated telemetry, including the telemetry link between ambulances and hospitals for advanced life support services. In emergency medical use telemetry links ambulances and hospitals for advanced life support services and allows transmission of physiological data -- an electrocardiogram from an ambulance to a hospital emergency room where a physician reads the telemetered message and prescribes emergency procedures to ambulance attendants.

Source record↗

DOE OSTI2025

Domain Shift Analysis in Chest Radiographs Classification in a Veterans Healthcare Administration Population

This study aims to assess the impact of domain shift on chest X-ray classification accuracy and to analyze the influence of ground truth label quality and demographic factors such as age group, sex, and study year. We used a DenseNet121 model pre-trained MIMIC-CXR dataset for deep learning-based multi-label classification using ground truth labels from radiology reports extracted using the CheXpert and CheXbert Labeler. We compared the performance of the 14 chest X-ray labels on the MIMIC-CXR and Veterans Healthcare Administration chest X-ray dataset (VA-CXR). The validation of ground truth and the assessment of multi-label classification performance across various NLP extraction tools revealed that the VA-CXR dataset exhibited lower disagreement rates than the MIMIC-CXR datasets. Additionally, there were notable differences in AUC scores between models utilizing CheXpert and CheXbert. When evaluating multi-label classification performance across different datasets, minimal domain shift was observed in the unseen VA dataset, except for the label “Enlarged Cardiomediastinum.” The subgroup with the most significant variations in multi-label classification performance was study year. These findings underscore the importance of considering domain shift in chest X-ray classification tasks, paying particular attention to the temporality of the exam. Our study reveals the significant impact of domain shift and demographic factors on chest X-ray classification, emphasizing the need for improved transfer learning and robust model development. Addressing these challenges is crucial for advancing medical imaging research and improving patient care.

chest X-ray image classification↗

DOE OSTI2026

Bemnifosbuvir: An HCV NS5B Inhibitor With Multiple Modes of Action

Bemnifosbuvir (BEM) is a potent, pan-genotypic inhibitor targeting the hepatitis C virus (HCV) NS5B polymerase. Its antiviral activity was evaluated in an ascending dose phase I clinical trial involving 30 patients treated once a day for 7 days. After treatment initiation, plasma HCV RNA declined in a biphasic manner with a mean reduction of 2.3 log 10 IU/mL after 24 hours and 4.4 log10 IU/mL by day 7 for the highest dose. Alanine aminotransferase (ALT) also normalized in most patients. We employed a multiscale mathematical model fitted to the HCV RNA and ALT dynamics to quantify the antiviral activity and evaluate the modes of action of BEM. We found that models in which BEM only acted as a typical HCV RNA polymerase inhibitor and reduced the intracellular production of HCV RNA did not fit the data as well as models in which BEM had multiple modes of action, including suppressing viral assembly and secretion and enhancing intracellular HCV RNA degradation. BEM's effectiveness in inhibiting intracellular HCV RNA production increased with dose (150 mg/day: 88.2%, 300 mg/day: 98.8%, 600 mg/day: 99.5%), while inhibition of viral assembly and release was ~95% effective regardless of dose. We observed a dose-dependent enhancement in the degradation of intracellular HCV RNA, with degradation rates 1.5-fold higher in patients receiving 300 mg/day and 2.7-fold higher in those receiving 600 mg/day than in patients receiving 150 mg/day. No significant differences in antiviral activity were detected between HCV genotypes 1b and 3 or between patients with and without compensated cirrhosis.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Kinetic and structural evidence for specific DMSO interference with reversible binding of uncharged bis-oximes to hAChE and their reactivation kinetics of OP-hAChE

The structural basis of inhibitory effect of organic solvent dimethyl sulfoxide (DMSO) on human acetylcholinesterase (EC 3.1.1.7; hAChE) was inferred from the effect of DMSO on kinetics of reversible inhibition of uncharged, heterocyclic bis-oximes to hAChE, from DMSO effect on rates of reactivation of inactive organophosphate (OP)-hAChE conjugates by bis-oximes and by X-ray structures of bis-oxime and DMSO binding to hAChE. Here, the reversible inhibition constant of DMSO for hAChE in 0.1 M phosphate buffer pH 7.4 at 22 °C, was K i = (0.32 ± 0.04) % (or 45 ± 5 mM). The K i of the bis-oxime LG-703 for hAChE was 3.2-fold larger in 1 % DMSO, consistent with direct competition between LG-703 and DMSO. The X-ray structure of the LG-703∗hAChE complex (PDB ID: 6U3P) shows DMSO and LG-703 bound to individual hAChE monomers, LG-703 in the chain A and DMSO in the chain B. In the co-crystallization both small molecules were present at a similar excess over their corresponding K i values for hAChE (7.8-fold for DMSO and 6.5-fold for LG-703) and formation of two different complexes (DMSO∗hAChE and LG-703∗hAChE), in the same crystal, appears consistent with inhibition kinetics. Furthermore, rates of reactivation of paraoxon-inhibited hAChE (POX-hAChE) and of VX-hAChE by LG-703 and by a novel heterocyclic bis-oxime LG-1922 were reduced 2 – 3-fold in DMSO, consistent with observation of the active-center-bound DMSO molecules in the newly solved structure of the LG-1922∗POX-hAChE complex presented here and in our POX-hAChE structure (PDB ID: 8DT2) showing obstruction of the reactivator access to the conjugated P atom.

Acetylcholinesterase inhibition↗

DOE OSTI2021

New approach to precisely measure γ-ray intensities for long-lived fission products, with results for the decay of 95 Zr

For many fission products, the rays emitted following decay provide an easily-detectable signature that can be used to identify their quantities and distributions in a sample. As a result, γ-ray spectroscopy is often exploited to study fission-product yields, provided sufficiently accurate information on the γ-ray intensity is available. However, in many cases, the uncertainties in the existing nuclear data are large enough that they compromise the precision achievable for modern experiments and applications. To address this need, we have developed a new experimental method that is well suited to precisely measure absolute γ-ray intensities in the β decay of long-lived fission products. The approach involves the production of a radiopure sample by implantation of a mass-separated ion beam from the CAlifornium Rare Isotope Breeder Upgrade (CARIBU) facility on a thin carbon foil. The emitted β-decay radiation is detected with a 4π gas proportional counter and a meticulously efficiency-calibrated high-purity germanium (HPGe) detector. As a first measurement to demonstrate the approach, we studied the absolute γ-ray intensities of the strongest transitions following the β decay of 95 Zr and its decay-daughter 95 Nb, and determined them to fractional precisions of better than 1–2%. In addition, with a larger sample of activity produced through neutron irradiation of an isotopically-enriched Zr foil, we performed a high-precision measurement of the relative γ-ray intensities following the decay of 95 Zr with just the HPGe detector. Here, the sample-production method at CARIBU and the coincidence detection approach demonstrated here can be applied to study fission products with half-lives longer than a day, which includes isotopes important not only for nuclear-energy and national-security applications, but also for medical-isotope research and environmental monitoring.

4π↗

DOE OSTI2021

Nucleic acid binding by SAMHD1 contributes to the antiretroviral activity and is enhanced by the GpsN modification

SAMHD1 impedes infection of myeloid cells and resting T lymphocytes by retroviruses, and the enzymatic activity of the protein—dephosphorylation of deoxynucleotide triphosphates (dNTPs)—implicates enzymatic dNTP depletion in innate antiviral immunity. Here we show that the allosteric binding sites of the enzyme are plastic and can accommodate oligonucleotides in place of the allosteric activators, GTP and dNTP. SAMHD1 displays a preference for oligonucleotides containing phosphorothioate bonds in the Rp configuration located 3’ to G nucleotides (GpsN), the modification pattern that occurs in a mechanism of antiviral defense in prokaryotes. In the presence of GTP and dNTPs, binding of GpsN-containing oligonucleotides promotes formation of a distinct tetramer with mixed occupancy of the allosteric sites. Mutations that impair formation of the mixed-occupancy complex abolish the antiretroviral activity of SAMHD1, but not its ability to deplete dNTPs. The findings link nucleic acid binding to the antiretroviral activity of SAMHD1, shed light on the immunomodulatory effects of synthetic phosphorothioated oligonucleotides and raise questions about the role of nucleic acid phosphorothioation in human innate immunity.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Towards data-driven next-generation transmission electron microscopy

Electron microscopy touches on nearly every aspect of modern life, underpinning materials development for quantum computing, energy and medicine. We discuss the open, highly integrated and data-driven microscopy architecture needed to realize transformative discoveries in the coming decade.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Spatio-temporal dynamics of Hendra virus in Australia reveal stable maintenance of diverse viral clades among Pteropus bats

Hendra virus (HeV) was discovered in 1994 in Australia. Limited genomic data have hindered comprehensive understanding of HeV’s evolutionary dynamics. Here, in this work, we recovered 48 HeV genomes from bats and 9 from horses from Australia between 2016 and 2020, revealing four distinct clades. Each clade was distributed over a large spatial area with multiple clades co-circulating within a single bat roost on the same day and over consecutive years. The diversity and temporal stability of co-circulating clades suggest that viral dynamics are driven by episodic shedding of existing lineages maintained at the population level, rather than immune-driven strain-replacement dynamics. HeV isolates of different clades displayed variation in phenotypic properties but minimal antigenic differences. We provide an overview of evolutionary dynamics, phenotypic properties and assessment of countermeasures for HeV, and provide insights into the processes that maintain virus diversity in bats and influence the potential for viral emergence.

genetic variation↗

DOE OSTI2020

Correlation between hemolytic activity, cytotoxicity and systemic in vivo toxicity of synthetic antimicrobial peptides

The use of non-standard toxicity models is a hurdle in the early development of antimicrobial peptides towards clinical applications. Herein we report an extensive in vitro and in vivo toxicity study of a library of 24 peptide-based antimicrobials with narrow spectrum activity towards veterinary pathogens. The haemolytic activity of the compounds was evaluated against four different species and the relative sensitivity against the compounds was highest for canine erythrocytes, intermediate for rat and human cells and lowest for bovine cells. Selected peptides were additionally evaluated against HeLa, HaCaT and HepG2 cells which showed increased stability towards the peptides. Therapeutic indexes of 50–500 suggest significant cellular selectivity in comparison to bacterial cells. Three peptides were administered to rats in intravenous acute dose toxicity studies up to 2– 8 × MIC. None of the injected compounds induced any systemic toxic effects in vivo at the concentrations employed illustrating that the correlation between the different assays is not obvious. This work sheds light on the in vitro and in vivo toxicity of this class of promising compounds and provides insights into the relationship between the different toxicity models often employed in different manners to evaluate the toxicity of novel bioactive compounds in general.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Complex of human Melanotransferrin and SC57.32 Fab fragment reveals novel interdomain arrangement with ferric N-lobe and open C-lobe

Melanotransferrin (MTf) is an iron-binding member of the transferrin superfamily that can be membrane-anchored or secreted in serum. On cells, it can mediate transferrin-independent iron uptake and promote proliferation. In serum, it is a transcytotic iron transporter across the blood–brain barrier. MTf has been exploited as a drug delivery carrier to the brain and as an antibody-drug conjugate (ADC) target due to its oncogenic role in melanoma and its elevated expression in triple-negative breast cancer (TNBC). For treatment of TNBC, an MTf-targeting ADC completed a phase I clinical trial (NCT03316794). The structure of its murine, unconjugated Fab fragment (SC57.32) is revealed here in complex with MTf. The MTf N-lobe is in an active and iron-bound, closed conformation while the C-lobe is in an open conformation incompatible with iron binding. This combination of active and inactive domains displays a novel inter-domain arrangement in which the C2 subdomain angles away from the N-lobe. The C2 subdomain also contains the SC57.32 glyco-epitope, which comprises ten protein residues and two N-acetylglucosamines. Our report reveals novel features of MTf and provides a point of reference for MTf-targeting, structure-guided drug design.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Transcript and blood-microbiome analysis towards a blood diagnostic tool for goats affected by Haemonchus contortus

The Alpine goat (Capra aegagrus hircus) is parasitized by the barber pole worm (Haemonchus contortus). Hematological parameters from transcript and metagenome analysis in the host are reflective of infestation. We explored comparisons between blood samples of control, infected, infected zoledronic acid-treated, and infected antibody (anti-γδ T cells) treated wethers under controlled conditions. Seven days post-inoculation (dpi), we identified 7,627 transcripts associated with the different treatment types. Microbiome measurements at 7 dpi revealed fewer raw read counts across all treatments and a less diverse microbial flora than at 21 dpi. This study identifies treatment specific transcripts and an increase in microflora abundance and diversity as wethers age. Further, F/B ratio reflect health, based on depression or elevation above thresholds defined by the baseline of non-infected controls. Forty Alpine wethers were studied where blood samples were collected from five goats in four treatment groups on 7 dpi and 21 dpi. Transcript and microbiome profiles were obtained using the Partek Flow (St. Louis, Missouri, USA) software suites pipelines. Inflammation comparisons were based on the Firmicutes/Bacteriodetes ratios that are calculated as well as the reduction of microbial diversity.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

An image classification deep-learning algorithm for shrapnel detection from ultrasound images

Ultrasound imaging is essential for non-invasively diagnosing injuries where advanced diagnostics may not be possible. However, image interpretation remains a challenge as proper expertise may not be available. In response, artificial intelligence algorithms are being investigated to automate image analysis and diagnosis. Here, we highlight an image classification convolutional neural network for detecting shrapnel in ultrasound images. As an initial application, different shrapnel types and sizes were embedded first in a tissue mimicking phantom and then in swine thigh tissue. The algorithm architecture was optimized stepwise by minimizing validation loss and maximizing F1 score. The final algorithm design trained on tissue phantom image sets had an F1 score of 0.95 and an area under the ROC curve of 0.95. It maintained higher than a 90% accuracy for each of 8 shrapnel types. When trained only on swine image sets, the optimized algorithm format had even higher metrics: F1 and area under the ROC curve of 0.99. Overall, the algorithm developed resulted in strong classification accuracy for both the tissue phantom and animal tissue. This framework can be applied to other trauma relevant imaging applications such as internal bleeding to further simplify trauma medicine when resources and image interpretation are scarce.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Survival analysis of localized prostate cancer with deep learning

In recent years, data-driven, deep-learning-based models have shown great promise in medical risk prediction. By utilizing the large-scale Electronic Health Record data found in the U.S. Department of Veterans Affairs, the largest integrated healthcare system in the United States, we have developed an automated, personalized risk prediction model to support the clinical decision-making process for localized prostate cancer patients. This method combines the representative power of deep learning and the analytical interpretability of parametric regression models and can implement both time-dependent and static input data. To collect a comprehensive evaluation of model performances, we calculate time-dependent C-statistics C td over 2-, 5-, and 10-year time horizons using either a composite outcome or prostate cancer mortality as the target event. The composite outcome combines the Prostate-Specific Antigen (PSA) test, metastasis, and prostate cancer mortality. Our longitudinal model Recurrent Deep Survival Machine (RDSM) achieved C td 0.85 (0.83), 0.80 (0.83), and 0.76 (0.81), while the cross-sectional model Deep Survival Machine (DSM) attained C td 0.85 (0.82), 0.80 (0.82), and 0.76 (0.79) for the 2-, 5-, and 10-year composite (mortality) outcomes, respectively. In addition to estimating the survival probability, our method can quantify the uncertainty associated with the prediction. The uncertainty scores show a consistent correlation with the prediction accuracy. We find PSA and prostate cancer stage information are the most important indicators in risk prediction. Our work demonstrates the utility of the data-driven machine learning model in prostate cancer risk prediction, which can play a critical role in the clinical decision system.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Proof of principle study: synchrotron X-ray fluorescence microscopy for identification of previously radioactive microparticles and elemental mapping of FFPE tissues

Biobanks containing formalin-fixed, paraffin-embedded (FFPE) tissues from animals and human atomic-bomb survivors exposed to radioactive particulates remain a vital resource for understanding the molecular effects of radiation exposure. These samples are often decades old and prepared using harsh fixation processes which limit sample imaging options. Optical imaging of hematoxylin and eosin (H&E) stained tissues may be the only feasible processing option, however, H&E images provide no information about radioactive microparticles or radioactive history. Synchrotron X-ray fluorescence microscopy (XFM) is a robust, non-destructive, semi-quantitative technique for elemental mapping and identifying candidate chemical element biomarkers in FFPE tissues. Still, XFM has never been used to uncover distribution of formerly radioactive micro-particulates in FFPE canine specimens collected more than 30 years ago. In this work, we demonstrate the first use of low-, medium-, and high-resolution XFM to generate 2D elemental maps of ~ 35-year-old, canine FFPE lung and lymph node specimens stored in the Northwestern University Radiobiology Archive documenting distribution of formerly radioactive micro-particulates. Additionally, we use XFM to identify individual microparticles and detect daughter products of radioactive decay. The results of this proof-of-principle study support the use of XFM to map chemical element composition in historic FFPE specimens and conduct radioactive micro-particulate forensics.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2024

Entropy removal of medical diagnostics

Shannon entropy is a core concept in machine learning and information theory, particularly in decision tree modeling. To date, no studies have extensively and quantitatively applied Shannon entropy in a systematic way to quantify the entropy of clinical situations using diagnostic variables (true and false positives and negatives, respectively). Decision tree representations of medical decision-making tools can be generated using diagnostic variables found in literature and entropy removal can be calculated for these tools. This concept of clinical entropy removal has significant potential for further use to bring forth healthcare innovation, such as quantifying the impact of clinical guidelines and value of care and applications to Emergency Medicine scenarios where diagnostic accuracy in a limited time window is paramount. This analysis was done for 623 diagnostic tools and provided unique insights into their utility. For studies that provided detailed data on medical decision-making algorithms, bootstrapped datasets were generated from source data to perform comprehensive machine learning analysis on these algorithms and their constituent steps, which revealed a novel and thorough evaluation of medical diagnostic algorithms.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Enhanced sensitivity to trace 238 U impurity of sapphire via coincidence neutron activation analysis

Sapphire has mechanical and electrical properties that are advantageous for the construction of internal components of radiation detectors such as time projection chambers and bolometers. However, it has proved difficult to assess its 232 Th and 238 U content down to the picogram per gram level. Here, this work reports an experimental verification of a computational study that demonstrates 𝛾⁢𝛾 coincidence counting, coupled with neutron activation analysis (NAA), can reach ppt sensitivities. Combining results from 𝛾⁢𝛾 coincidence counting with those of earlier single-𝛾 counting based NAA shows that a sample of Saint Gobain sapphire has 232 Th and 238 U concentrations of <0.26 ppt and <2.3 ppt, respectively; the best constraints on the radiopurity of sapphire.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗