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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Advancing stem cell technologies for conservation of wildlife biodiversity

ABSTRACT Wildlife biodiversity is essential for healthy, resilient and sustainable ecosystems. For biologists, this diversity also represents a treasure trove of genetic, molecular and developmental mechanisms that deepen our understanding of the origins and rules of life. However, the rapid decline in biodiversity reported recently foreshadows a potentially catastrophic collapse of many important ecosystems and the associated irreversible loss of many forms of life on our planet. Immediate action by conservationists of all stripes is required to avert this disaster. In this Spotlight, we draw together insights and proposals discussed at a recent workshop hosted by Revive & Restore, which gathered experts to discuss how stem cell technologies can support traditional conservation techniques and help protect animal biodiversity. We discuss reprogramming, in vitro gametogenesis, disease modelling and embryo modelling, and we highlight the prospects for leveraging stem cell technologies beyond mammalian species.

Developmental Biology↗
DOE OSTI2021

Recommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelines

Background: The importance of infectious disease epidemic forecasting and prediction research is underscored by decades of communicable disease outbreaks, including COVID-19. Unlike other fields of medical research, such as clinical trials and systematic reviews, no reporting guidelines exist for reporting epidemic forecasting and prediction research despite their utility. We therefore developed the EPIFORGE checklist, a guideline for standardized reporting of epidemic forecasting research. Methods and findings: We developed this checklist using a best-practice process for development of reporting guidelines, involving a Delphi process and broad consultation with an international panel of infectious disease modelers and model end users. The objectives of these guidelines are to improve the consistency, reproducibility, comparability, and quality of epidemic forecasting reporting. The guidelines are not designed to advise scientists on how to perform epidemic forecasting and prediction research, but rather to serve as a standard for reporting critical methodological details of such studies. Conclusions: These guidelines have been submitted to the EQUATOR network, in addition to hosting by other dedicated webpages to facilitate feedback and journal endorsement.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

NM Science, Technology and Telecommunications committee: State of the Lab [Slides]

Our priority throughout COVID has been protecting our employees and our communities. To this end, we stood up internal testing and vaccination programs; kept disease risk low via maximum teleworking; leveraged world-class expertise to support federal and state through disease modeling and forecasting; and stored vaccines for the school district. COVID-19 taught us there are many ways to leverage technology to work safely and effectively.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Chronic Cardiotoxicity Assays Using Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes (hiPSC-CMs)

Cardiomyocytes (CMs) differentiated from human induced pluripotent stem cells (hiPSCs) are increasingly used in cardiac safety assessment, disease modeling and regenerative medicine. A vast majority of cardiotoxicity studies in the past have tested acute effects of compounds and drugs; however, these studies lack information on the morphological or physiological responses that may occur after prolonged exposure to a cardiotoxic compound. In this review, we focus on recent advances in chronic cardiotoxicity assays using hiPSC-CMs. We summarize recently published literature on hiPSC-CMs assays applied to chronic cardiotoxicity induced by anticancer agents, as well as non-cancer classes of drugs, including antibiotics, anti-hepatitis C virus (HCV) and antidiabetic drugs. We then review publications on the implementation of hiPSC-CMs-based assays to investigate the effects of non-pharmaceutical cardiotoxicants, such as environmental chemicals or chronic alcohol consumption. We also highlight studies demonstrating the chronic effects of smoking and implementation of hiPSC-CMs to perform genomic screens and metabolomics-based biomarker assay development. The acceptance and wide implementation of hiPSC-CMs-based assays for chronic cardiotoxicity assessment will require multi-site standardization of assay protocols, chronic cardiac maturity marker reproducibility, time points optimization, minimal cellular variation (commercial vs. lab reprogrammed), stringent and matched controls and close clinical setting resemblance. A comprehensive investigation of long-term repeated exposure-induced effects on both the structure and function of cardiomyocytes can provide mechanistic insights and recapitulate drug and environmental cardiotoxicity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1999

Cell Culture in Microgravity: Opening the Door to Space Cell Biology

Adaptational response of human cell populations to microgravity is investigated using simulation, short-term Shuttle experiments, and long-term microgravity. Simulation consists of a clinostatically-rotated cell culture system. The system is a horizontally-rotated cylinder completely filled with culture medium. Low speed rotation results in continuous-fall of the cells through the fluid medium. In this setting, cells: 1) aggregate, 2) propagate in three dimensions, 3) synthesize matrix, 4) differentiate, and 5) form sinusoids that facilitate mass transfer. Space cell culture is conducted in flight bioreactors and in static incubators. Cells grown in microgravity are: bovine cartilage, promyelocytic leukemia, kidney proximal tubule cells, adrenal medulla, breast and colon cancer, and endothelium. Cells were cultured in space to test specific hypotheses. Cartilage cells were used to determine structural differences in cartilage grown in space compared to ground-based bioreactors. Results from a 130-day experiment on Mir revealed that cartilage grown in space was substantially more compressible due to insufficient glycosaminoglycan in the matrix. Interestingly, earth-grown cartilage conformed better to the dimensions of the scaffolding material, while the Mir specimens were spherical. The other cell populations are currently being analyzed for cell surface properties, gene expression, and differentiation. Results suggest that some cells spontaneously differentiate in microgravity. Additionally, vast changes in gene expression may occur in response to microgravity. In conclusion, the transition to microgravity may constitute a physical perturbation in cells resulting in unique gene expressions, the consequences of which may be useful in tissue engineering, disease modeling, and space cell biology.

Pellis, Neal R.↗
NASA NTRS2004

NASA Classroom Bioreactor

Exploration of space provides a compelling need for cell-based research into the basic mechanisms that underlie the profound changes that occur in terrestrial life that is transitioned to low gravity environments. Toward that end, NASA developed a rotating bioreactor in which cells are cultured while continuously suspended in a cylinder in which the culture medium rotates with the cylinder. The randomization of the gravity vector accomplished by the continuous rotation, in a low shear environment, provides an analog of microgravity. Because cultures grown in bioreactors develop structures and functions that are much closer to those exhibited by native tissue than can be achieved with traditional culture methods, bioreactors have contributed substantially to advancing research in the fields of cancer, diabetes, infectious disease modeling for vaccine production, drug efficacy, and tissue engineering. NASA has developed a Classroom Bioreactor (CB) that is built from parts that are easily obtained and assembled, user-friendly and versatile. It can be easily used in simple school settings to examine the effect cultures of seeds or cells. An educational brief provides assembly instructions and lesson plans that describes activities in science, math and technology that explore free fall, microgravity, orbits, bioreactors, structure-function relationships and the scientific method.

Scully, Robert↗
NASA NTRS2016

Biomolecular Analysis Capability for Cellular and Omics Research on the International Space Station

International Space Station (ISS) assembly complete ushered a new era focused on utilization of this state-of-the-art orbiting laboratory to advance science and technology research in a wide array of disciplines, with benefits to Earth and space exploration. ISS enabling capability for research in cellular and molecular biology includes equipment for in situ, on-orbit analysis of biomolecules. Applications of this growing capability range from biomedicine and biotechnology to the emerging field of Omics. For example, Biomolecule Sequencer is a space-based miniature DNA sequencer that provides nucleotide sequence data for entire samples, which may be used for purposes such as microorganism identification and astrobiology. It complements the use of WetLab-2 SmartCycler"TradeMark", which extracts RNA and provides real-time quantitative gene expression data analysis from biospecimens sampled or cultured onboard the ISS, for downlink to ground investigators, with applications ranging from clinical tissue evaluation to multigenerational assessment of organismal alterations. And the Genes in Space-1 investigation, aimed at examining epigenetic changes, employs polymerase chain reaction to detect immune system alterations. In addition, an increasing assortment of tools to visualize the subcellular distribution of tagged macromolecules is becoming available onboard the ISS. For instance, the NASA LMM (Light Microscopy Module) is a flexible light microscopy imaging facility that enables imaging of physical and biological microscopic phenomena in microgravity. Another light microscopy system modified for use in space to image life sciences payloads is initially used by the Heart Cells investigation ("Effects of Microgravity on Stem Cell-Derived Cardiomyocytes for Human Cardiovascular Disease Modeling and Drug Discovery"). Also, the JAXA Microscope system can perform remotely controllable light, phase-contrast, and fluorescent observations. And upcoming confocal microscopy capability will allow for optical sectioning of biological tissues to determine microanatomical localization of biomarkers. Furthermore, NASA's geneLAB effort addresses integration of genomic, epigenomic, transcriptomic, proteomic and metabolomic datasets, by applying an innovative open source science platform for multi-investigator high throughput utilization of the ISS. In sum, the expanding ISS capability for analysis of biomolecules is enabling innovative research in a broad spectrum of areas such as cellular and molecular biology, biotechnology, tissue engineering, biomedicine, and Omics, providing manifold benefits for humanity.

Guinart-Ramirez, Y.↗
NASA NTRS2017

Network Analysis of Rodent Transcriptomes in Spaceflight

Network analysis methods leverage prior knowledge of cellular systems and the statistical and conceptual relationships between analyte measurements to determine gene connectivity. Correlation and conditional metrics are used to infer a network topology and provide a systems-level context for cellular responses. Integration across multiple experimental conditions and omics domains can reveal the regulatory mechanisms that underlie gene expression. GeneLab has assembled rich multi-omic (transcriptomics, proteomics, epigenomics, and epitranscriptomics) datasets for multiple murine tissues from the Rodent Research 1 (RR-1) experiment. RR-1 assesses the impact of 37 days of spaceflight on gene expression across a variety of tissue types, such as adrenal glands, quadriceps, gastrocnemius, tibalius anterior, extensor digitorum longus, soleus, eye, and kidney. Network analysis is particularly useful for RR-1 -omics datasets because it reinforces subtle relationships that may be overlooked in isolated analyses and subdues confounding factors. Our objective is to use network analysis to determine potential target nodes for therapeutic intervention and identify similarities with existing disease models. Multiple network algorithms are used for a higher confidence consensus.

genomics↗
NASA NTRS2018

Biomedical Science and Technology on the International Space Station - Benefits for Humanity (Ciencia Y Tecnologia Biomedica En La Estacion Espacial Internacional - Beneficios Para La Humanidad)

The International Space Station is a unique laboratory for performing investigations that affect human health both in space and on Earth. During its time in orbit, the space station has enabled research that is providing a better understanding of many aspects of human health including aging, trauma, disease and environmental impacts. Driven by the need to support astronaut health, several biological and human physiological investigations have yielded important results that we on Earth can also benefit from. These results include new ways to mitigate bone loss, insights into bacterial behavior, and innovative wound-healing techniques. Advances in telemedicine, disease models, psychological stress response systems, nutrition and cell behavior are just a few more examples of the benefits that have been gained from applying studies in orbit to human health back on Earth.

Love, John E.↗
NASA NTRS2024

Biofabrication in Space - A Perspective

Human exploration of Mars is one of the primary goals of NASA. A three-year human exploration mission to Mars is a viable design reference mission (Design Reference Mission). If we are sending a four member crew, comprehensive understanding of the health conditions of the crew is important. Based on the biomedical results of long-duration crew members at ISS, and during gravitational transitions, a few maladaptation have been observed. Discovering the root-cause of these aberrations and finding suitable mitigations at the molecular and cellular levels are of importance for a successful mission. Developing and executing the technologies to carry out tissue generation in space as well as the development of an analog hardware for tissue generation under terrestrial conditions will be discussed. These tissues were typically used to develop disease models and drug toxicology studies for several weeks and many other applications. The significant progress made during the last two decades have unfolded developments in organ generation, stem cell generation in space. When you remove the gravitational force during these cellular building processes while in space, other forces like surface tension, intermolecular forces, Coriolis force, loss of convection, reduced shear force, dominate the environment leading to behavior that we may not observe under terrestrial conditions. Based on these discoveries, the fundamental mechanisms could be better understood and new insights into bioprocesses could be developed for an exciting future.

Antony Jeevarajan↗
DOE OSTI2022

Alternative SIAR models for infectious diseases and applications in the study of non-compliance

In this paper, we use modified versions of the SIAR model for epidemics to propose two ways of understanding and quantifying the effect of non-compliance to non-pharmaceutical intervention measures on the spread of an infectious disease. The SIAR model distinguishes between symptomatic infected (I) and asymptomatic infected (A) populations. One modification, which is simpler, assumes a known proportion of the population does not comply with government mandates such as quarantining and social-distancing. In a more sophisticated approach, the modified model treats non-compliant behavior as a social contagion. We theoretically explore different scenarios such as the occurrence of multiple waves of infections. Local and asymptotic analyses for both models are also provided.

Mathematics↗
DOE OSTI2025

Consistent performance of large language models in rare disease diagnosis across ten languages and 4917 cases

Background Large language models (LLMs) are increasingly used medicine for diverse applications including differential diagnostic support. The training data used to create LLMs such as the Generative Pretrained Transformer (GPT) predominantly consist of English-language texts, but LLMs could be used across the globe to support diagnostics if language barriers could be overcome. Initial pilot studies on the utility of LLMs for differential diagnosis in languages other than English have shown promise, but a large-scale assessment on the relative performance of these models in a variety of European and non-European languages on a comprehensive corpus of challenging rare-disease cases is lacking. Methods We created 4917 clinical vignettes using structured data captured with Human Phenotype Ontology (HPO) terms with the Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema. These clinical vignettes span a total of 360 distinct genetic diseases with 2525 associated phenotypic features. We used translations of the Human Phenotype Ontology together with language-specific templates to generate prompts in English, Chinese, Czech, Dutch, French, German, Italian, Japanese, Spanish, and Turkish. We applied GPT-4o, version gpt-4o-2024-08-06, and the medically fine-tuned Meditron3-70B to the task of delivering a ranked differential diagnosis using a zero-shot prompt. An ontology-based approach with the Mondo disease ontology was used to map synonyms and to map disease subtypes to clinical diagnoses in order to automate evaluation of LLM responses. Findings For English, GPT-4o placed the correct diagnosis at the first rank 19.9% and within the top-3 ranks 27.0% of the time. In comparison, for the nine non-English languages tested here the correct diagnosis was placed at rank 1 between 16.9% and 20.6%, within top-3 between 25.4% and 28.6% of cases. The Meditron3 model placed the correct diagnosis within the first 3 ranks for 20.9% of cases in English and between 19.9% and 24.0% for the other nine languages. Interpretation The differential diagnostic performance of LLMs across a comprehensive corpus of rare-disease cases was largely consistent across the ten languages tested. This suggests that the utility of LLMs in clinical settings may extend to non-English clinical settings.

Artificial intelligence↗
NASA NTRS2005

Three-Dimensional Cell Culture Models for Infectious Disease and Drug Development

Three-dimensional (3-D) cell cultures hold enormous potential to advance our understanding of infectious disease and to effectively translate basic cellular research into clinical applications. Using novel NASA bioreactor technology, the rotating wall vessel (RWV), we have engineered physiologically relevant 3-D human tissue culture models for infectious disease studies. The design of the RWV is based on the understanding that organs and tissues function in a 3-D environment, and that this 3-D architecture is critical for the differentiated form and function of tissues in vivo. The RWV provides large numbers of cells which are amenable to a wide variety of experimental manipulations and provides an easy, reproducible, and cost-effective approach to enhance differentiated features of cell culture models.

Nickerson, Cheryl A.↗
DOE OSTI2024

Model-form Error Correction using Universal Differential Equations for an Agent-Based Model of Infectious Disease

This report demonstrates universal differential equations (UDEs) as an approach to bridge the gap between ordinary differential equations (ODE) models and agent-based models (ABMs). Using UDE models as surrogates for ABMs allows us to preserve the foundational ODE that represents global disease dynamics while coupling it with a neural network model to approximate functions for the local behaviors of the ABM.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Altered microRNA expression in animal models of Huntington’s disease and potential therapeutic strategies

A review of recent animal models of Huntington’s disease showed many microRNAs had altered expression levels in the striatum and cerebral cortex, and which were mostly downregulated. Among the altered microRNAs were miR-9/9*, miR-29b, miR-124a, miR-132, miR-128, miR-139, miR-122, miR-138, miR-23b, miR-135b, miR-181 (all downregulated) and miR-448 (upregulated), and similar changes had been previously found in Huntington’s disease patients. In the animal cell studies, the altered microRNAs included miR-9, miR-9*, miR-135b, miR-222 (all downregulated) and miR-214 (upregulated). In the animal models, overexpression of miR-155 and miR-196a caused a decrease in mutant huntingtin mRNA and protein level, lowered the mutant huntingtin aggregates in striatum and cortex, and improved performance in behavioral tests. Improved performance in behavioral tests also occurred with overexpression of miR-132 and miR-124. In the animal cell models, overexpression of miR-22 increased the viability of rat primary cortical and striatal neurons infected with mutant huntingtin and decreased huntingtin -enriched foci of ≥ 2 µm. Also, overexpression of miR-22 enhanced the survival of rat primary striatal neurons treated with 3-nitropropionic acid. Exogenous expression of miR-214, miR-146a, miR-150, and miR-125b decreased endogenous expression of huntingtin mRNA and protein in Hdh Q111 /Hdh Q111 cells. Further studies with animal models of Huntington’s disease are warranted to validate these findings and identify specific microRNAs whose overexpression inhibits the production of mutant huntingtin protein and other harmful processes and may provide a more effective means of treating Huntington’s disease in patients and slowing its progression.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A Comparison of Infectious Disease Forecasting Methods across Locations, Diseases, and Time

Accurate infectious disease forecasting can inform efforts to prevent outbreaks and mitigate adverse impacts. This study compares the performance of statistical, machine learning (ML), and deep learning (DL) approaches in forecasting infectious disease incidences across different countries and time intervals. We forecasted three diverse diseases: campylobacteriosis, typhoid, and Q-fever, using a wide variety of features (n = 46) from public datasets, e.g., landscape, climate, and socioeconomic factors. We compared autoregressive statistical models to two tree-based ML models (extreme gradient boosted trees [XGB] and random forest [RF]) and two DL models (multi-layer perceptron and encoder–decoder model). The disease models were trained on data from seven different countries at the region-level between 2009–2017. Forecasting performance of all models was assessed using mean absolute error, root mean square error, and Poisson deviance across Australia, Israel, and the United States for the months of January through August of 2018. The overall model results were compared across diseases as well as various data splits, including country, regions with highest and lowest cases, and the forecasted months out (i.e., nowcasting, short-term, and long-term forecasting). Overall, the XGB models performed the best for all diseases and, in general, tree-based ML models performed the best when looking at data splits. There were a few instances where the statistical or DL models had minutely smaller error metrics for specific subsets of typhoid, which is a disease with very low case counts. Feature importance per disease was measured by using four tree-based ML models (i.e., XGB and RF with and without region name as a feature). The most important feature groups included previous case counts, region name, population counts and density, mortality causes of neonatal to under 5 years of age, sanitation factors, and elevation. This study demonstrates the power of ML approaches to incorporate a wide range of factors to forecast various diseases, regardless of location, more accurately than traditional statistical approaches.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Adenosine A2A Receptor Up-Regulation Pre-Dates Deficits of Synaptic Plasticity and of Memory in Mice Exposed to Aβ1–42 to Model Early Alzheimer’s Disease

The intracerebroventricular (icv) injection of amyloid peptides (Aβ) models Alzheimer’s disease (AD) in mice, as typified by the onset within 15 days of deficits of memory and of hippocampal long-term potentiation (LTP) that are prevented by the blockade of adenosine A2A receptors (A2AR). Since A2AR overfunction is sufficient to trigger memory deficits, we tested if A2AR were upregulated in hippocampal synapses before the onset of memory deficits to support the hypothesis that A2AR overfunction could be a trigger of AD. Six to eight days after Aβ-icv injection, mice displayed no alterations of hippocampal dependent memory; however, they presented an increased excitability of hippocampal synapses, a slight increase in LTP magnitude in Schaffer fiber-CA1 pyramid synapses and an increased density of A2AR in hippocampal synapses. A2AR blockade with SCH58261 (50 nM) normalized excitability and LTP in hippocampal slices from mice sacrificed 7–8 days after Aβ-icv injection. Fifteen days after Aβ-icv injection, mice displayed evident deficits of hippocampal-dependent memory deterioration, with reduced hippocampal CA1 LTP but no hyperexcitability and a sustained increase in synaptic A2AR, which blockade restored LTP magnitude. This shows that the upregulation of synaptic A2AR precedes the onset of deterioration of memory and of hippocampal synaptic plasticity, supporting the hypothesis that the overfunction of synaptic A2AR could be a trigger of memory deterioration in AD.

Lopes, Cátia R.↗
NASA NTRS2003

Triazolopyrimidine (trapidil), a platelet-derived growth factor antagonist, inhibits parathyroid bone disease in an animal model for chronic hyperparathyroidism

Parathyroid bone disease in humans is caused by chronic hyperparathyroidism (HPT). Continuous infusion of PTH into rats results in histological changes similar to parathyroid bone disease, including increased bone formation, focal bone resorption, and severe peritrabecular fibrosis, whereas pulsatile PTH increases bone formation without skeletal abnormalities. Using a cDNA microarray with over 5000 genes, we identified an association between increased platelet-derived growth factor-A (PDGF-A) signaling and PTH-induced bone disease in rats. Verification of PDGF-A overexpression was accomplished with a ribonuclease protection assay. Using immunohistochemistry, PDGF-A peptide was localized to mast cells in PTH-treated rats. We also report a novel strategy for prevention of parathyroid bone disease using triazolopyrimidine (trapidil). Trapidil, an inhibitor of PDGF signaling, did not have any effect on indexes of bone turnover in normal rats. However, dramatic reductions in marrow fibrosis and bone resorption, but not bone formation, were observed in PTH-treated rats given trapidil. Also, trapidil antagonized the PTH-induced increases in mRNA levels for PDGF-A. These results suggest that PDGF signaling is important for the detrimental skeletal effects of HPT, and drugs that target the cytokine or its receptor might be useful in reducing or preventing parathyroid bone disease.

NASA Discipline Cell Biology↗