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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Effects of training on muscle O2 transport at VO2max

To quantify the relative contributions of convective and peripheral diffusive components of O2 transport to the increase in leg O2 uptake (VO2leg) at maximum O2 uptake (VO2max) after 9 wk of endurance training, 12 sedentary subjects (age 21.8 +/- 3.4 yr, VO2max 36.9 +/- 5.9 ml.min-1.kg-1) were studied. VO2max, leg blood flow (Qleg), and arterial and femoral venous PO2, and thus VO2leg, were measured while the subjects breathed room air, 15% O2, and 12% O2. The sequence of the three inspirates was balanced. After training, VO2max and VO2leg increased at each inspired O2 concentration [FIO2; mean over the 3 FIO2 values 25.2 +/- 17.8 and 36.5 +/- 33% (SD), respectively]. Before training, VO2leg and mean capillary PO2 were linearly related through the origin during hypoxia but not during room air breathing, suggesting that, at 21% O2, VO2max was not limited by O2 supply. After training, VO2leg and mean capillary PO2 at each FIO2 fell along a straight line with zero intercept, just as in athletes (Roca et al. J. Appl. Physiol. 67: 291-299, 1989). Calculated muscle O2 diffusing capacity (DO2) rose 34% while Qleg increased 19%. The relatively greater rise in DO2 increased the DO2/Qleg, which led to 9.9% greater O2 extraction. By numerical analysis, the increase in Qleg alone (constant DO2) would have raised VO2leg by 35 ml/min (mean), but that of DO2 (constant Qleg) would have increased VO2leg by 85 ml/min, more than twice as much. The sum of these individual effects (120 ml/min) was less (P = 0.013) than the observed rise of 164 ml/min (mean). This synergism (explained by the increase in DO2/Qleg) seems to be an important contribution to increases in VO2max with training.

NASA Discipline Musculoskeletal↗
NASA NTRS2017

The Evolution of Planetary Protection Implementation on Mars Landed Missions

NASA has developed requirements dedicated to the prevention of forward and backward contamination during space exploration. Historically, international agreements provided guidelines to prevent contamination of the Moon and other celestial bodies, as well as the Earth (e.g., sample return missions). The UN Outer Space Treaty was established in 1967 and the Committee on Space Research (COSPAR) maintains a planetary protection policy complying with Article IX of this treaty. By avoiding forward contamination, the integrity of scientific exploration is preserved. Planetary Protection mission requirements are levied on missions to control contamination. These requirements are dependent on the science of the mission and on the celestial bodies encountered or targeted along the way. Consequently, categories are assigned to missions, and specific implementation plans are developed to meet the planetary protection requirements. NASA missions have evolved over time with increasingly more demanding scientific objectives and more complex flight systems to achieve those objectives and, thus, planetary protection methods and processes used for implementation have become much more intricate, complicated, and challenging. Here, we will portray the evolution of planetary protection implementation at JPL in several important areas throughout the course of NASA sponsored robotic Mars lander or rover missions, starting from Mars Pathfinder through the beginning of Mars 2020. Highlighted in the discussion will be process changes in planetary protection requirements development and flow down. Development and implementation of new and improved methods used in the reduction of spacecraft bioburden will be discussed as well as approaches and challenges that come along with setting up remote laboratories to perform bioassays. The consequences and forward planning of delays on missions will be highlighted as well as lessons learned on the impact of communication and training in achieving planetary protection requirements. The evolution of methods used for the detection of microbial bioburden on spacecraft hardware will be considered. These methods use standard microbiology as well as the adaptation of advances in biotechnology, molecular biology, and bioinformatics. Technical approaches developed for the prevention of contamination and recontamination of hardware during Assembly, Test, and Launch Operations will be discussed.

Kazarians, Gayane A.↗
NASA NTRSDate not supplied

Yeast Strain Development and Hardware Testing in Preparation of a Lunar BioSensor

With Artemis missions underway, it is clear we are going back to the Moon to stay. Before sending Astronauts for long-duration missions, it is crucial to understand the technological and biomedical countermeasures needed to protect them before they get there. We can use knowledge gained from biological CubeSats to guide the next generation of experiments to support human habitation on the Moon. Lunar Explorer Instrument for space biology Applications (LEIA) is NASA’s latest BioSensor, adapted BioSentinel, the only CubeSat to travel Beyond Low Earth Orbit. BioSentinel launched on Artemis I and is currently >50 million kilometers from Earth (as of July 2024). LEIA aims to identify biological responses to the Lunar environment, which unprotected against would pose a threat to astronauts (cancer, cardiovascular disease, neurological impairment). The suite of instruments within LEIA detects Lunar radiation using two on-board radiation sensors (ARES charged particle detector, Mini-Fast Neutron Detector), then monitors real-time biological responses to the Lunar environment via an autonomous microfluidic system, fit with 3-LED emitter and detector boards and the alamarBlue metabolic indicator dye. LEIA will use a genetic approach in addition to synthetic biology to test counter-measure production in space, with the goal to inform and protect astronauts for future Moon missions. We have conducted preliminary tests in preparation for launch to the anticipated South Pole of the Moon, optimizing the biology (strain down-selection, desiccation tolerance, radiation sensitivity) and improving the hardware (including a blue LED to detect the beta-carotene countermeasure product). Our team will discuss these findings in several parts – an overview of the LEIA mission (Mark Settles), adapting flexible CubeSat platforms for deep-space applications (Sergio Santa Maria, Kira Rienecker), developing new technologies to support LEIA ground studies (Chinmayee Govinda Raj), and yeast strain development and hardware testing in preparation for LEIA (presented here).

synthetic biology↗
DOE OSTI2026

CAHS: Context-Aware Homology Search

Protein homology search is foundational to bioinformatics: it supports annotation transfer, structure/function inference, and evolutionary analysis over rapidly expanding sequence repositories (e.g., UniProtKB). Profile hidden Markov models (pHMMs), as implemented in HMMER, remain the most widely trusted approach because they provide statistically calibrated E-values; however, their gap behavior is fixed once a profile is trained, despite biological evidence that insertion/deletion tolerance varies across flexible loops and intrinsically disordered regions. We present CAHS (Context-Aware Homology Search), a lightweight query-time adapter for pHMM search that incorporates learned and biologically motivated signals without changing HMMER's downstream search pipeline or its calibrated E-value reporting. Given a query sequence, CAHS computes per-residue representations from a protein language model and a disorder predictor, maps these to profile coordinates, and modulates only match-state transition rows (gap-open and gap-extension probabilities) while preserving Plan7 constraints. We comprehensively evaluate CAHS across six structurally diverse protein families and multi-domain architectures against a 570k-sequence target corpus. CAHS expands detection capability, retrieving thousands of additional remote homologs at relaxed thresholds by maintaining alignment quality through flexible regions. For multi-domain proteins, context-aware modulation resolves 94% of fragmented alignments. Crucially, CAHS preserves hit-set invariance at stringent operating points (E<10-10), demonstrating increased statistical confidence without inflating false positives. Furthermore, sharper statistical distinction between homologs and background noise during early filter stages yields up to a 3.87× acceleration in end-to-end wall-clock time on high-performance computing clusters. Overall, CAHS illustrates a practical AI-for-science design pattern: augmenting a trusted probabilistic model with query-specific learned signals to improve interpretable, reproducible inference in data-rich biology.

Bhattaram, Swethasree [Georgia Institute of Techno↗
DOE OSTI2020

Combinatorial Biosynthesis of Sulfated Benzenediol Lactones with a Phenolic Sulfotransferase from Fusarium graminearum PH-1

Total biosynthesis or whole-cell biocatalytic production of sulfated small molecules relies on the discovery and implementation of appropriate sulfotransferase enzymes. Although fungi are prominent biocatalysts and have been used to sulfate drug-like phenolics, no gene encoding a sulfotransferase enzyme has been functionally characterized from these organisms. Here, we identify a phenolic sulfotransferase, FgSULT1, by genome mining from the plant-pathogenic fungus Fusarium graminearum PH-1. We expressed FgSULT1 in a Saccharomyces cerevisiae chassis to modify a broad range of benzenediol lactones and their nonmacrocyclic congeners, together with an anthraquinone, with the resulting unnatural natural product (uNP) sulfates displaying increased solubility. FgSULT1 shares low similarity with known animal and plant sulfotransferases. Instead, it forms a sulfotransferase family with putative bacterial and fungal enzymes for phase II detoxification of xenobiotics and allelochemicals. Among fungi, putative FgSULT1 homologues are encoded in the genomes of Fusarium spp. and a few other genera in nonsyntenic regions, some of which may be related to catabolic sulfur recycling. Computational structure modeling combined with site-directed mutagenesis revealed that FgSULT1 retains the key catalytic residues and the typical fold of characterized animal and plant sulfotransferases. Our work opens the way for the discovery of hitherto unknown fungal sulfotransferases and provides a synthetic biological and enzymatic platform that can be adapted to produce bioactive sulfates, together with sulfate ester standards and probes for masked mycotoxins, precarcinogenic toxins, and xenobiotics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Hierarchical Conditioning of Diffusion Models Using Tree-of-Life for Studying Species Evolution

A central problem in biology is to understand how organisms evolve and adapt to their environment by acquiring variations in the observable characteristics or traits of species across the tree of life. With the growing availability of large-scale image repositories in biology and recent advances in generative modeling, there is an opportunity to accelerate the discovery of evolutionary traits automatically from images. Toward this goal, we introduce Phylo-Diffusion, a novel framework for conditioning diffusion models with phylogenetic knowledge represented in the form of HIERarchical Embeddings (HIER-Embeds). We also propose two new experiments for perturbing the embedding space of Phylo-Diffusion: trait masking and trait swapping, inspired by counterpart experiments of gene knockout and gene editing/swapping. Our work represents a novel methodological advance in generative modeling to structure the embedding space of diffusion models using tree-based knowledge. Our work also opens a new chapter of research in evolutionary biology by using generative models to visualize evolutionary changes directly from images. We empirically demonstrate the usefulness of Phylo-Diffusion in capturing meaningful trait variations for fishes and birds, revealing novel insights about the biological mechanisms of their evolution. (Model and code can be found at imageomics.github.io/phylo-diffusion)

Khurana, Mridul↗
DOE OSTI2023

PathTracer Comprehensively Identifies Hypoxia-Induced Dormancy Adaptations in Mycobacterium tuberculosis

Mining large-scale data to discover biologically relevant information remains a challenge despite the rapid development of bioinformatics tools. Here, we have developed a new tool, PathTracer, to identify biologically relevant information flows by mining genome-wide protein–protein interaction networks following integration of gene expression data. PathTracer successfully mines interactions between genes and traces the most perturbed paths of perceived activities under the conditions of the study. Here, we further demonstrated the utility of this tool by identifying adaptation mechanisms of hypoxia-induced dormancy in Mycobacterium tuberculosis (Mtb).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The diatom Fragilariopsis cylindrus : A model alga to understand cold-adapted life

Diatoms are significant primary producers especially in cold, turbulent, and nutrient-rich surface oceans. Hence, they are abundant in polar oceans, but also underpin most of the polar food webs and related biogeochemical cycles. The cold-adapted pennate diatom Fragilariopsis cylindrus is considered a keystone species in polar oceans and sea ice because it can thrive under different environmental conditions if temperatures are low. In this perspective paper, we provide insights into the latest molecular work that has been done on F. cylindrus and discuss its role as a model alga to understand cold-adapted life.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Plant Single-Cell Solutions for Energy and the Environment (Second Workshop Report)

Plants are important sources of energy and materials, and they collectively represent a critical component of Earth’s ecosystem. With increasing environmental stresses due to climate change and intensive agricultural practices, the need for resilient plants is greater than ever before. To secure plant resources for bioenergy, biomaterials, food, and ecosystem adaptation, a deeper understanding of the fundamental biology of plants at a cellular level is urgently needed. Plants contain a multitude of specialized cell types that compose tissues and organs. Pathogens often target specific cell types within plants, and the response of one cell to a particular stimulus is likely to be distinct from its neighbor because of underlying molecular and contextual differences. Understanding how these responses are distributed among cells, the main goal of single-cell approaches, will substantially enhance our ability to use targeted engineering for improving plant productivity and resilience. Furthermore, single-cell approaches are necessary to understand the interactions between plants and other ecosystem members such as fungi, bacteria, and archaea. Unlocking these gene-response mechanisms at a cellular level can improve our ability to adapt plants to environmental stresses, increasing their utility as feedstocks for biomaterials and bioenergy. Recent advances in high-throughput sequencing, mass spectrometry, microfluidics and miniaturization, artificial intelligence and machine learning, and bioinformatics have greatly improved our ability to detect and understand processes at a cellular level. In mammalian systems, single-cell transcriptomics has already led to many advances, such as newly identified cell types and cell-targeted treatment of diseases, and mass spectrometry-based single-cell proteomics has recently been demonstrated as a promising emerging technology. However, plant single-cell omics has lagged behind mammalian approaches due to the high cost of the technologies relative to available resources and to the innate biological features of plants, including the complexity of the cell wall and polyploidy. To better understand how single-cell methods could enable plant science, Lawrence Berkeley National Laboratory (Berkeley Lab) hosted a workshop on April 29, 2021, that brought together a diverse group of leaders in plant and/or single-cell biology. Attendees represented federal research programs and domestic and international academic institutions. During the workshop, three presenters described the current state of research in both experimental and computational approaches. While the focus of the workshop was on factors preventing plant biology researchers from fully adopting single-cell methodologies, workshop participants agreed that most barriers could be overcome with focused, strategic investment and coordinated efforts among institutions leading to significant scientific discoveries that would be difficult to obtain using more conventional technologies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Prolonging genetic circuit stability through adaptive evolution of overlapping genes

Abstract The development of synthetic biological circuits that maintain functionality over application-relevant time scales remains a significant challenge. Here, we employed synthetic overlapping sequences in which one gene is encoded or ‘entangled’ entirely within an alternative reading frame of another gene. In this design, the toxin-encoding relE was entangled within ilvA, which encodes threonine deaminase, an enzyme essential for isoleucine biosynthesis. A functional entanglement construct was obtained upon modification of the ribosome-binding site of the internal relE gene. Using this optimized design, we found that the selection pressure to maintain functional IlvA stabilized the production of burdensome RelE for >130 generations, which compares favorably with the most stable kill-switch circuits developed to date. This stabilizing effect was achieved through a complete alteration of the allowable landscape of mutations such that mutations inactivating the entangled genes were disfavored. Instead, the majority of lineages accumulated mutations within the regulatory region of ilvA. By reducing baseline relE expression, these more ‘benign’ mutations lowered circuit burden, which suppressed the accumulation of relE-inactivating mutations, thereby prolonging kill-switch function. Overall, this work demonstrates the utility of sequence entanglement paired with an adaptive laboratory evolution campaign to increase the evolutionary stability of burdensome synthetic circuits.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2004

Radiation-induced bystander effect and adaptive response in mammalian cells

Two conflicting phenomena, bystander effect and adaptive response, are important in determining the biological responses at low doses of radiation and have the potential to impact the shape of the dose-response relationship. Using the Columbia University charged-particle microbeam and the highly sensitive AL cell mutagenic assay, we show here that non-irradiated cells acquire mutagenesis through direct contact with cells whose nuclei have been traversed with a single alpha particle each. Pretreatment of cells with a low dose of X-rays four hours before alpha particle irradiation significantly decreased this bystander mutagenic response. Results from the present study address some of the fundamental issues regarding both the actual target and radiation dose effect and can contribute to our current understanding in radiation risk assessment. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

NASA Discipline Radiation Health↗
NASA NTRS1993

Alterations in skeletal muscle related to impaired physical mobility: an empirical model

The objective of this investigation was to study impaired physical mobility and the resulting skeletal muscle atrophy. An animal model was used to study morphological adaptations of the soleus and plantaris muscles to decreased loading induced by hindlimb suspension of an adult rat for 7, 14, and 28 consecutive days. Alterations in weight, skeletal muscle growth, and changes in fiber type composition were studied in synergistic plantar flexors of the rat hindlimb. Body weight and the soleus muscle mass to body mass ratio demonstrated significant progressive atrophy over th 28-day experimental period with the most significant changes occurring in the first 7 days of hindlimb suspension. Hindlimb suspension produced atrophy of Type I and Type IIa muscle fibers as demonstrated by significant decreases in fiber cross-sectional area (micron 2). These latter changes account for the loss of contractile force production reported in the rat following hindlimb unloading. When compared to traditional models of hindlimb suspension and immobilization, the ISC model produces a less severe atrophy while maintaining animal mobility and health. We conclude that it is the preferred animal model to address nursing questions of impaired physical mobility.

Non-NASA Center↗
DOE OSTI2023

Structure-informed clustering for population stratification in association studies

Background: Identifying variants associated with complex traits is a challenging task in genetic association studies due to linkage disequilibrium (LD) between genetic variants and population stratification, unrelated to the disease risk. Existing methods of population structure correction use principal component analysis or linear mixed models with a random effect when modeling associations between a trait of interest and genetic markers. However, due to stringent significance thresholds and latent interactions between the markers, these methods often fail to detect genuinely associated variants. Results: To overcome this, we propose CluStrat, which corrects for complex arbitrarily structured populations while leveraging the linkage disequilibrium induced distances between genetic markers. It performs an agglomerative hierarchical clustering using the Mahalanobis distance covariance matrix of the markers. In simulation studies, we show that our method outperforms existing methods in detecting true causal variants. Applying CluStrat on WTCCC2 and UK Biobank cohorts, we found biologically relevant associations in Schizophrenia and Myocardial Infarction. CluStrat was also able to correct for population structure in polygenic adaptation of height in Europeans. Conclusions: CluStrat highlights the advantages of biologically relevant distance metrics, such as the Mahalanobis distance, which captures the cryptic interactions within populations in the presence of LD better than the Euclidean distance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Paired Simulations and Experimental Investigations into the Calcium-Dependent Conformation of Albumin

Serum albumin is the most abundant protein in blood plasma, and it is involved in multiple biological processes. Serum albumin has recently been adapted for improving biomaterial integration with bone tissue, and studies have shown the importance of this protein in bone repair and regeneration. However, the mechanism of action is not yet clear. In stark contrast, other studies have demonstrated that albumin blocks cell adhesion to surfaces, which is seen as a limitation to its bone healing role. These apparent contradictions suggest that the conformation of albumin facilitates its bioactivity, leading to enhanced bone repair. Serum albumin is known to play a major role in maintaining the calcium ion concentration in blood plasma. Due to the prevalence of calcium at bone repair and regeneration sites, it has been hypothesized that calcium binding to serum albumin triggers a conformational change, leading to bioactivity. In the current study, molecular modeling approaches including molecular docking, atomic molecular dynamics (MD) simulation, and coarse-grained MD simulation were used to test this hypothesis by investigating the conformational changes induced in bovine serum albumin by interaction with calcium ions. The computational results were qualitatively validated with experimental Fourier-transform infrared spectroscopy analysis. We find that free calcium ions in solution transiently bind with the three major loops in albumin, triggering a conformational change where N-terminal and C-terminal domains separate from each other in a partial unfolding process. The separation distance between these domains was found to correlate with the calcium ion concentration. The experimental data support the simulation results showing that albumin has enhanced conformational heterogeneity upon exposure to intermediate levels of calcium, without any significant secondary structure changes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Suillus : an emerging model for the study of ectomycorrhizal ecology and evolution

Research on mycorrhizal symbiosis has been slowed by a lack of established study systems. To address this challenge, we have been developing Suillus, a widespread ecologically and economically relevant fungal genus primarily associated with the plant family Pinaceae, into a model system for studying ectomycorrhizal (ECM) associations. Over the last decade, we have compiled extensive genomic resources, culture libraries, a phenotype database, and protocols for manipulating Suillus fungi with and without their tree partners. Our efforts have already resulted in a large number of publicly available genomes, transcriptomes, and respective annotations, as well as advances in our understanding of mycorrhizal partner specificity and host communication, fungal and plant nutrition, environmental adaptation, soil nutrient cycling, interspecific competition, and biological invasions. Here, we highlight the most significant recent findings enabled by Suillus, present a suite of protocols for working with the genus, and discuss how Suillus is emerging as an important model to elucidate the ecology and evolution of ECM interactions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1972

Silver stain for electron microscopy

Ammoniacal silver stain used for light microscopy was adapted advantageously for use with very thin biological sections required for electron microscopy. Silver stain can be performed in short time, has more contrast, and is especially useful for low power electron microscopy.

Corbett, R. L.↗
NASA NTRS1994

Unique life sciences research facilities at NASA Ames Research Center

The Life Science Division at NASA's Ames Research Center has a suite of specialized facilities that enable scientists to study the effects of gravity on living systems. This paper describes some of these facilities and their use in research. Seven centrifuges, each with its own unique abilities, allow testing of a variety of parameters on test subjects ranging from single cells through hardware to humans. The Vestibular Research Facility allows the study of both centrifugation and linear acceleration on animals and humans. The Biocomputation Center uses computers for 3D reconstruction of physiological systems, and interactive research tools for virtual reality modeling. Psycophysiological, cardiovascular, exercise physiology, and biomechanical studies are conducted in the 12 bed Human Research Facility and samples are analyzed in the certified Central Clinical Laboratory and other laboratories at Ames. Human bedrest, water immersion and lower body negative pressure equipment are also available to study physiological changes associated with weightlessness. These and other weightlessness models are used in specialized laboratories for the study of basic physiological mechanisms, metabolism and cell biology. Visual-motor performance, perception, and adaptation are studied using ground-based models as well as short term weightlessness experiments (parabolic flights). The unique combination of Life Science research facilities, laboratories, and equipment at Ames Research Center are described in detail in relation to their research contributions.

Mulenburg, G. M.↗