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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Synthetic β-sheets mimicking fibrillar and oligomeric structures for evaluation of spectral X-ray scattering technique for biomarker quantification

Archetypical cross-β spines sharpen the boundary between functional and pathological proteins including β-amyloid, tau, α-synuclein and transthyretin are linked to many debilitating human neurodegenerative and non-neurodegenerative amyloidoses. An increased focus on development of pathogenic β-sheet specific fluid and imaging structural biomarkers and conformation-specific monoclonal antibodies in targeted therapies has been recently observed. Identification and quantification of pathogenic oligomers remain challenging for existing neuroimaging modalities. We propose two artificial β-sheets which can mimic the nanoscopic structural characteristics of pathogenic oligomers and fibrils for evaluating the performance of a label free, X-ray based biomarker detection and quantification technique. Highly similar structure with elliptical cross-section and parallel cross-β motif is observed among recombinant α-synuclein fibril, Aβ-42 fibril and artificial β-sheet fibrils. We then use these β-sheet models to assess the performance of spectral small angle X-ray scattering (sSAXS) technique for detecting β-sheet structures. sSAXS showed quantitatively accurate detection of antiparallel, cross-β artificial oligomers from a tissue mimicking environment and significant distinction between different oligomer packing densities such as diffuse and dense packings. The proposed synthetic β-sheet models mimicked the nanoscopic structural characteristics of β-sheets of fibrillar and oligomeric states of Aβ and α-synuclein based on the ATR-FTIR and SAXS data. The tunability of β-sheet proportions and shapes of structural motifs, and the low-cost of these β-sheet models can become useful test materials for evaluating β-sheet or amyloid specific biomarkers in a wide range of neurological diseases. By using the proposed synthetic β-sheet models, our study indicates that the sSAXS has potential to evaluate different stages of β-sheet-enriched structures including oligomers of pathogenic proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Water Cycle-Driven Infectious Diseases as Multiscale, Reliable, Continuously Updating Water Cycle Sensors

We propose a novel synthesis of observational and simulated data (climatological and biological) to enhance understanding of the real-world interplay between climate (here, the water cycle) and the epidemiology of water cycle-driven infectious disease. Aligning with Focal Area 2, predictive modeling using AI techniques, we will develop systems of hierarchical models to discover latent features of the water cycle. Our approach will leverage state-of-the-art in Artificial Intelligence (AI) to measure the degree to which climate change-driven shifts in water cycle can be predicted by supplementing sparse and irregular climate data with water cycle-driven infectious disease resources.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Moving With Parasites: Relationships Between Animal Movement and Infectious Disease Across Systems and Scales

Animal movement patterns are important for ecological processes such as population dynamics and infectious disease transmission. Because animals move in response to environmental cues like temperature and precipitation, changes to the environment – whether they are seasonal, interannual, or long-term – can change these processes, leading to changes in population sizes or infectious disease prevalence across space and time. My work uses a combination of simulation modeling and data analysis at multiple spatial and temporal scales to understand the environment-movement-disease connection in diverse animal taxa and environments. In this seminar, I will highlight the diverse ways that the environment can influence infectious disease dynamics via changes to animal movement patterns, including through a global study of migration in ungulate populations, a study of American White Ibis adapting to urban environments in South Florida, and examples of avian influenza prevalence in wild waterfowl. Together, these examples highlight that understanding environment-movement interactions can help predict how infectious disease dynamics might change in the future, as changes to climate, land use, and habitats alter animal movement patterns.

Animal movement↗
NASA NTRS1987

A solid phase enzyme-linked immunosorbent assay for the antigenic detection of Legionella pneumophila (serogroup 1): A compliment for the space station diagnostic capability

It is necessary that an adequate microbiology capability be provided as part of the Health Maintenance Facility (HMF) to support expected microbial disease events and environmental monitoring during long periods of space flight. The application of morphological and biochemical studies to confirm the presence of certain bacterial and fungal disease agents are currently available and under consideration. This confirmation would be facilitated through employment of serological methods to aid in the identification of bacterial, fungal, and viral agents. A number of serological approaches are currently being considered, including the use of Enzyme Linked Immunosorbent Assay (ELISA) technology, which could be utilized during microgravity conditions. A solid phase, membrane supported ELISA for the detection of Legionella pneumophila, an expected disease agent, was developed to show a potential model system that would meet the HMF requirements and specifications for the future space station. These studies demonstrate the capability of membrane supported ELISA systems for identification of expected microbial disease agents as part of the HMF.

Hejtmancik, Kelly E.↗
DOE OSTI2021

A participant-derived xenograft model of HIV enables long-term evaluation of autologous immunotherapies

HIV-specific CD8+ T cells partially control viral replication and delay disease progression, but they rarely provide lasting protection, largely due to immune escape. Here, we show that engrafting mice with memory CD4+ T cells from HIV+ donors uniquely allows for the in vivo evaluation of autologous T cell responses while avoiding graft-versus-host disease and the need for human fetal tissues that limit other models. Treating HIV-infected mice with clinically relevant HIV-specific T cell products resulted in substantial reductions in viremia. In vivo activity was significantly enhanced when T cells were engineered with surface-conjugated nanogels carrying an IL-15 superagonist, but it was ultimately limited by the pervasive selection of a diverse array of escape mutations, recapitulating patterns seen in humans. By applying mathematical modeling, we show that the kinetics of the CD8+ T cell response have a profound impact on the emergence and persistence of escape mutations. This “participant-derived xenograft” model of HIV provides a powerful tool for studying HIV-specific immunological responses and facilitating the development of effective cell-based therapies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Machine Learning in Infectious Disease for Risk Factor Identification and Hypothesis Generation: Proof of Concept Using Invasive Candidiasis

Machine learning (ML) models can handle large data sets without assuming underlying relationships and can be useful for evaluating disease characteristics, yet they are more commonly used for predicting individual disease risk than for identifying factors at the population level. We offer a proof of concept applying random forest (RF) algorithms to Candida-positive hospital encounters in an electronic health record database of patients in the United States. Candida-positive encounters were extracted from the Cerner HealthFacts database; invasive infections were laboratory-positive sterile site Candida infections. Features included demographics, admission source, care setting, physician specialty, diagnostic and procedure codes, and medications received before the first positive Candida culture. We used RF to assess risk factors for 3 outcomes: any invasive candidiasis (IC) vs non-IC, within-species IC vs non-IC (eg, invasive C. glabrata vs noninvasive C. glabrata), and between-species IC (eg, invasive C. glabrata vs all other IC). Fourteen of 169 (8%) variables were consistently identified as important features in the ML models. When evaluating within-species IC, for example, invasive C. glabrata vs non-invasive C. glabrata, we identified known features like central venous catheters, intensive care unit stay, and gastrointestinal operations. In contrast, important variables for invasive C. glabrata vs all other IC included renal disease and medications like diabetes therapeutics, cholesterol medications, and antiarrhythmics. Known and novel risk factors for IC were identified using ML, demonstrating the hypothesis-generating utility of this approach for infectious disease conditions about which less is known, specifically at the species level or for rarer diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Bistable dynamics and Hopf bifurcation in a refined model of early stage HIV infection

Recent clinical studies have shown that HIV disease pathogenesis can depend strongly on many factors at the time of transmission, including the strength of the initial viral load and the local availability of CD4+ T-cells. In this article, a new within-host model of HIV infection that incorporates the homeostatic proliferation of T-cells is formulated and analyzed. Due to the effects of this biological process, the influence of initial conditions on the proliferation of HIV infection is further elucidated. The identifiability of parameters within the model is investigated and a local stability analysis, which displays additional complexity in comparison to previous models, is conducted. The current study extends previous theoretical and computational work on the early stages of the disease and leads to interesting nonlinear dynamics, including a parameter region featuring bistability of infectious and viral clearance equilibria and the appearance of a Hopf bifurcation within biologically relevant parameter regimes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Lipids status and copper in a single astrocyte of the rat model for amyotrophic lateral sclerosis: Correlative synchrotron-based X-ray and infrared imaging

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease, causing death of motor neurons controlling voluntary muscles. The pathological mechanisms of the disease are only partially understood. The hSOD1-G93A ALS rat model is characterized by an overexpression of human mutated SOD1, causing increased vulnerability by forming intracellular protein aggregates, inducing excitotoxicity, affecting oxidative balance and disturbing axonal transport. In this study we followed the bio-macromolecular organic composition and compartmentalization together with trace metal distribution in situ in single astrocytes from the ALS rat model and compared them to the control astrocytes from nontransgenic littermates by simultaneous use of two synchrotron radiation-based methods: Fourier transform infrared microspectroscopy (SRFTIR) and hard X-ray fluorescence microscopy (XRF). Here we show that ALS cells contained more Cu, which colocalized with total lipids, increased carbonyl groups and oxidized lipids, thus implying direct involvement of Cu in oxidative stress of lipidic components without direct connection to protein aggregation in situ.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Development of polarization-sensitive optical coherence tomography imaging platform and metrics to quantify electrostimulation-induced peripheral nerve injury in vivo in a small animal model

Neuromodulation devices are rapidly evolving for the treatment of neurological diseases and conditions. Injury from implantation or long-term use without obvious functional losses is often only detectable through terminal histology. New technologies are needed that assess the peripheral nervous system (PNS) under normal and diseased or injured conditions. We aim to demonstrate an imaging and stimulation platform that can elucidate the biological mechanisms and impacts of neurostimulation in the PNS and apply it to the sciatic nerve to extract imaging metrics indicating electrical overstimulation. A sciatic nerve injury model in a 15-rat cohort was observed using a newly developed imaging and stimulation platform that can detect electrical overstimulation effects with polarization-sensitive optical coherence tomography. The sciatic nerve was electrically stimulated using a custom-developed nerve holder with embedded electrodes for 1 h, followed by a 1-h recovery period, delivered at above-threshold Shannon model k-values in experimental groups: sham control (SC, n = 5, 0.0 mA / 0 Hz), stimulation level 1 (SL1, n = 5, 3.4 mA / 50 Hz, and k = 2.57), and stimulation level 2 (SL2, n = 5, 6.8 mA / 100 Hz, and k = 3.17). The stimulation and imaging system successfully captured study data across the cohort. When compared to a SC after a 1-week recovery, the fascicle closest to the stimulation lead showed an average change of +4 % / – 309 % (SL1/SL2) in phase retardation and –79 % / – 148 % in optical attenuation relative to SC. Analysis of immunohistochemistry (IHC) shows a +1 % / – 36 % difference in myelin pixel counts and –13 % / + 29 % difference in axon pixel counts, and an overall increase in cell nuclei pixel count of +20 % / + 35 % . These metrics were consistent with IHC and hematoxylin/eosin tissue section analysis. The poststimulation changes observed in our study are manifestations of nerve injury and repair, specifically degeneration and angiogenesis. Optical imaging metrics quantify these processes and may help evaluate the safety and efficacy of neuromodulation devices.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

An mRNA vaccine encoding the Ebola virus glycoprotein induces high neutralizing antibody titers and provides strong protection against lethal infections in mouse models

Ebola virus (EBOV) is the causative agent of Ebola disease (EBOD), a viral hemorrhagic fever with a notably high case fatality rate. Current treatments for EBOD are limited to monoclonal antibodies or two licensed viral vector vaccines, a recombinant vesicular stomatitis virus (rVSV)-vectored vaccine or an adenovirus and modified vaccinia Ankara regimen. However, comparisons of protection, efficacy, and durability with alternative nucleotide platforms remain understudied. Here, we evaluated the immunogenicity of an mRNA vaccine expressing the EBOV glycoprotein (GP) in parallel with rVSV- and DNA-based vaccine platforms. The mRNA EBOV-GP vaccine, formulated in lipid nanoparticles, elicited significantly higher levels of total IgG and neutralizing antibody titers compared to the rVSV-EBOV-GP vaccine. Linear antibody epitope analysis indicated a preference for targeting the mucin-like domain in EBOV-GP1 following rVSV-based vaccination, while the mRNA platform distinctly targeted the internal fusion loop of EBOV-GP2. After characterizing the immunogenicity of the mRNA vaccine, two models of EBOD were used to demonstrate its protective efficacy: a surrogate rVSV-based challenge model of EBOD using type-I interferon deficient C57BL/6 mice and infection of BALB/c mice with authentic mouse-adapted EBOV. In both studies, the EBOV mRNA vaccine fully protected the mouse cohorts against morbidity and mortality. Additionally, the EBOV mRNA vaccine produced greater neutralizing antibody titers compared to the DNA EBOV-GP vaccine. These results suggest that an mRNA vaccine expressing EBOV-GP can induce robust, functional humoral responses that are protective against EBOD, warranting further development as an alternative to, or as part of a vaccine strategy including, viral vectored vaccines.

DNA vaccines↗
DOE OSTI2023

Developing a SARS-CoV-2 main protease binding prediction random forest model for drug repurposing for COVID-19 treatment

The coronavirus disease 2019 (COVID-19) global pandemic resulted in millions of people becoming infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and close to seven million deaths worldwide. It is essential to further explore and design effective COVID-19 treatment drugs that target the main protease of SARS-CoV-2, a major target for COVID-19 drugs. In this study, machine learning was applied for predicting the SARS-CoV-2 main protease binding of Food and Drug Administration (FDA)-approved drugs to assist in the identification of potential repurposing candidates for COVID-19 treatment. Ligands bound to the SARS-CoV-2 main protease in the Protein Data Bank and compounds experimentally tested in SARS-CoV-2 main protease binding assays in the literature were curated. These chemicals were divided into training (516 chemicals) and testing (360 chemicals) data sets. To identify SARS-CoV-2 main protease binders as potential candidates for repurposing to treat COVID-19, 1188 FDA-approved drugs from the Liver Toxicity Knowledge Base were obtained. A random forest algorithm was used for constructing predictive models based on molecular descriptors calculated using Mold2 software. Model performance was evaluated using 100 iterations of fivefold cross-validations which resulted in 78.8% balanced accuracy. The random forest model that was constructed from the whole training dataset was used to predict SARS-CoV-2 main protease binding on the testing set and the FDA-approved drugs. Model applicability domain and prediction confidence on drugs predicted as the main protease binders discovered 10 FDA-approved drugs as potential candidates for repurposing to treat COVID-19. Our results demonstrate that machine learning is an efficient method for drug repurposing and, thus, may accelerate drug development targeting SARS-CoV-2.

Research & Experimental Medicine↗
DOE OSTI2023

Single-cell, whole-embryo phenotyping of mammalian developmental disorders

Mouse models are a critical tool for studying human diseases, particularly developmental disorders. However, conventional approaches for phenotyping may fail to detect subtle defects throughout the developing mouse. Here we set out to establish single-cell RNA sequencing of the whole embryo as a scalable platform for the systematic phenotyping of mouse genetic models. We applied combinatorial indexing-based single-cell RNA sequencing to profile 101 embryos of 22 mutant and 4 wild-type genotypes at embryonic day 13.5, altogether profiling more than 1.6 million nuclei. The 22 mutants represent a range of anticipated phenotypic severities, from established multisystem disorders to deletions of individual regulatory regions. We developed and applied several analytical frameworks for detecting differences in composition and/or gene expression across 52 cell types or trajectories. Some mutants exhibit changes in dozens of trajectories whereas others exhibit changes in only a few cell types. We also identify differences between widely used wild-type strains, compare phenotyping of gain- versus loss-of-function mutants and characterize deletions of topological associating domain boundaries. Notably, some changes are shared among mutants, suggesting that developmental pleiotropy might be ‘decomposable’ through further scaling of this approach. Overall, our findings show how single-cell profiling of whole embryos can enable the systematic molecular and cellular phenotypic characterization of mouse mutants with unprecedented breadth and resolution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Multi-modal characterization and simulation of human epileptic circuitry

Temporal lobe epilepsy is the fourth most common neurological disorder, with about 40% of patients not responding to pharmacological treatment. Increased cellular loss is linked to disease severity and pathological phenotypes such as heightened seizure propensity. While the hippocampus is the target of therapeutic interventions, the impact of the disease at the cellular level remains unclear. Here, we show that hippocampal granule cells change with disease progression as measured in living, resected hippocampal tissue excised from patients with epilepsy. We show that granule cells increase excitability and shorten response latency while also enlarging in cellular volume and spine density. Single-nucleus RNA sequencing combined with simulations ascribes the changes to three conductances: BK, Cav2.2, and Kir2.1. In a network model, we show that these changes related to disease progression bring the circuit into a more excitable state, while reversing them produces a less excitable, “early-disease-like” state.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Evaluation of the spaceflight cardiovascular risk using the clinical prediction model Astro-CHARM and the NASA Radiation Risk Model

- Exposure to space radiation may pose a risk for cardiovascular diseases (CVD) during and after spaceflight. - The CVD risk should be quantified to plan future long-duration space missions such as the manned flight to Mars. - Assessing CVD risk is complicated by its multifactorial nature, where an individual’s risk is strongly influenced by risk factors such as family history, blood pressure, and lipid profiles. - In the NASA Space Radiation Risk Model, the metrics of radiation exposure-induced cases (REIC) and radiation exposure-induced death (REID) are used to quantify the risk attributable to radiation over a lifetime after exposure.

Ianik Plante↗
DOE OSTI2020

Metabolomics and the pig model reveal aberrant cardiac energy metabolism in metabolic syndrome

Abstract Although metabolic syndrome (MS) is a significant risk of cardiovascular disease (CVD), the cardiac response (MR) to MS remains unclear due to traditional MS models’ narrow scope around a limited number of cell-cycle regulation biomarkers and drawbacks of limited human tissue samples. To date, we developed the most comprehensive platform studying MR to MS in a pig model tightly related to human MS criteria. By incorporating comparative metabolomic, transcriptomic, functional analyses, and unsupervised machine learning (UML), we can discover unknown metabolic pathways connections and links on numerous biomarkers across the MS-associated issues in the heart. For the first time, we show severely diminished availability of glycolytic and citric acid cycle (CAC) pathways metabolites, altered expression, GlcNAcylation, and activity of involved enzymes. A notable exception, however, is the excessive succinate accumulation despite reduced succinate dehydrogenase complex iron-sulfur subunit b (SDHB) expression and decreased content of precursor metabolites. Finally, the expression of metabolites and enzymes from the GABA-glutamate, GABA-putrescine, and the glyoxylate pathways significantly increase, suggesting an alternative cardiac means to replenish succinate and malate in MS. Our platform discovers potential therapeutic targets for MS-associated CVD within pathways that were previously unknown to corelate with the disease.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1994

Three-Dimensional Coculture Of Human Small-Intestine Cells

Complex three-dimensional masses of normal human epithelial and mesenchymal small-intestine cells cocultured in process involving specially designed bioreactors. Useful as tissued models for studies of growth, regulatory, and differentiation processes in normal intestinal tissues; diseases of small intestine; and interactions between cells of small intestine and viruses causing disease both in small intestine and elsewhere in body. Process used to produce other tissue models, leading to advances in understanding of growth and differentiation in developing organisms, of renewal of tissue, and of treatment of myriad of clinical conditions. Prior articles describing design and use of rotating-wall culture vessels include "Growing And Assembling Cells Into Tissues" (MSC-21559), "High-Aspect-Ratio Rotating Cell-Culture Vessel" (MSC-21662), and "In Vitro, Matrix-Free Formation Of Solid Tumor Spheroids" (MSC-21843).

Wolf, David↗
DOE OSTI2022

Epidemiologic and economic considerations regarding persistently infected cattle during vaccinate-to-live strategies for control of foot-and-mouth disease in FMD-free regions

Development of a foot-and-mouth disease (FMD) carrier state following FMD virus (FMDV) infection is a well-established phenomenon in cattle. However, the proportion of cattle likely to become carriers and the duration of the carrier state at a herd or population-level are incompletely understood. The objective of this study was to examine the epidemiologic and economic impacts of vaccination-to-live strategy in a disease-free region or country. We developed and simulated scenarios of FMD spread and control in the US livestock population, which included depopulation for a limited period, followed by a vaccinate-to-live strategy with strong biosecurity and movement restrictions. Six scenarios of FMD spread and control were simulated in the InterSpread Plus (ISP) modeling tool. Data on the number of infected and depopulated cattle (by operation types) from ISP model runs were used to estimate the monthly number of infected but not depopulated (potential carrier) cattle after the infection. Using available literature data on the FMD carrier state, we estimated the monthly proportion of carrier cattle (from infected but not depopulated cattle) over time following infection. Among the simulated scenarios, the median (25th, 75th percentile) number of infected cattle ranged from 43,217 (42,819, 55,274) head to 148,907 (75,819, 205,350) head, and the epidemic duration ranged from 20 (11, 30) to 76 (38, 136) days. In general, larger outbreaks occurred when depopulation was carried out through longer periods, and the onset of the vaccination was late (p > 0.05). The estimated proportion of surviving cattle, which were infected and not depopulated and had the potential to become persistently infected ranged from 14 to 35% of total infected cattle. Production losses in beef and dairy sectors were higher when outbreaks started in multiple states simultaneously, but production losses were small compared to trade losses and consumer avoidance losses. These results can be used to inform the consideration of a vaccinate-to-live strategy for FMD outbreaks and the development of appropriate post-outbreak management strategies. Furthermore, this output will enable a more detailed examination of the epidemiologic and economic implications of allowing convalescent cattle to survive and remain in production chains after FMD outbreaks in FMD-free regions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

How much have adverse occupational health outcomes among construction workers improved over time? Evidence from 25 years of medical screening

Background Construction workers have always had a high risk of occupational illnesses. We used 25 years of data from a medical screening program serving older construction workers to determine how much health outcomes have improved over the past 60 years. Methods We investigated changes in relative risk for chest radiographs consistent with pneumoconiosis, COPD by spirometry, lung cancer mortality, and audiometry-assessed hearing impairment among workers participating in a medical screening program. Results were stratified by decade of first construction employment: before 1960, 1960–1969, 1970–1979, 1980–1989, and after 1990. Poisson and Cox regression analyses assessed relative risk by decade adjusted for age, sex, smoking, and years of construction trade work. Results Subjects were 94% male and, on average, 60 years old with 25 years of construction work. When compared to workers employed before 1960, those first employed after 1990 experienced the following reductions in model-adjusted relative risks: chronic obstructive pulmonary disease, 32%; all pneumoconiosis, 68%; parenchymal abnormalities, 35%; pleural abnormalities, 71%; hearing impairment, 20%; and lung cancer mortality, 48%. Risks started to decline in the 1960s with greatest reductions among workers first employed after 1970. Conclusions This study demonstrates the positive impact that adoption of occupational health protections have had over the past 60 years. The greatest risk reductions were observed for outcomes with strong regulatory and legal incentives to reduce exposures and associated risks, such as those associated with inhalation hazards (asbestos and silica), while lowest improvement was for hearing impairment, for which little regulatory enforcement and few prevention incentives have been adopted.

60 APPLIED LIFE SCIENCES↗