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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Relationship Between Perceived Control and Hypothalamic–Pituitary–Adrenal Axis Reactivity to the Trier Social Stress Test in Healthy Young Adults

Psychological factors can modulate the hypothalamic–pituitary–adrenal (HPA) axis activity toward stressors. Animal studies demonstrated that uncontrollability was one critical factor associated with HPA axis stress response, but the results in human studies were inconsistent. The current study adopted a standardized laboratory stress induction procedure, the Trier Social Stress Test (the TSST), as the stressor to regulate the objective controllability level, and young adult participants were asked to rate their subjectively perceived control level toward the stressor and measured their cortisol stress responses ( N =54; 19 females and 35 males) to address this concern. Results showed that participants’ perceived control on the TSST was related to the cortisol stress response. In other words, under the stress of a certain objective controllability level, the lower the subjectively perceived control level, the greater the HPA axis response. This finding suggested that, in addition to objective controllability, subjectively perceived control is a psychological factor that regulates activation of the HPA axis in young adults.

Liu, Qian↗
DOE OSTI2023

Targeting tissues via dynamic human systems modeling in generative design

Drug discovery is a complex, costly process with high failure rates. A successful drug should bind to a target, be deliverable to an intended site of activity, and promote a desired pharmacological effect without causing toxicity. Typically, these factors are evaluated in series over the course of a pipeline where the number of candidates is sequentially whittled down from a very large initial pool. One promise of AI-driven discovery is the opportunity to evaluate multiple facets of drug performance in parallel. However, despite ML-driven advancements, current models for pharmacological property prediction are exclusively trained to predict molecular properties, ignoring important, dynamic biodistribution and bioactivity effects. Here, we present our progress towards incorporating quantitative systems physiology models into an AI-enabled drug design and molecular generation pipeline. Within a genetic algorithm, we include human-relevant physiologically based pharmacokinetic (PBPK) models. These PBPK models leverage properties that are predicted by a fine-tuned molecular language model. Together, these models will aid in capturing the mapping between molecules and therapeutic outcomes that is necessary to accelerate the drug discovery process.

Fox, Zach↗
DOE OSTI2022

Instantiation of HCML Demonstrating Bayesian Predictive Modeling for Attentional Control

The research team developed models of Attentional Control (AC) that are unique to existing modeling approaches in the literature. The goal was to enable the research team to (1) make predictions about AC and human performance in real-world scenarios and (2) to make predictions about individual characteristics based on human data. First, the team developed a proof-of-concept approach for representing an experimental design and human subjects data in a Bayesian model, then demonstrated an ability to draw inferences about conditions of interest relevant to real-world scenarios. Ultimately, this effort was successful, and we were able to make reasonable (meaning supported by behavioral data) inferences about conditions of interest to develop a risk model for AC (where risk is defined as a mismatch between AC and attentional demand). The team additionally defined a path forward for a human-constrained machine learning (HCML) approach to make predictions about an individual's state based on performance data. The effort represents a successful first step in both modeling efforts and serves as a basis for future work activities. Numerous opportunities for future work have been defined.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Expression Patterns of Energy-Related Genes in Single Cells Uncover Key Isoforms and Enzymes That Gain Priority Under Nanoparticle-Induced Stress

Cellular responses to nanoparticles (NPs) have been largely studied in cell populations, providing averaged values that often misrepresent the true molecular processes that occur in the individual cell. To understand how a cell redistributes limited molecular resources to achieve optimal response and survival requires single-cell analysis. Here we applied multiplex single molecule-based fluorescence in situ hybridization (fliFISH) to quantify the expression of 10 genes simultaneously in individual intact cells, including glycolysis and glucose transporter genes, which are critical for restoring and maintaining energy balance. We focused on individual gill epithelial cell responses to lithium cobalt oxide (LCO) NPs, which are actively pursued as cathode materials in lithium-ion batteries, raising concerns about their impact on the environment and human health. We found large variabilities in the expression levels of all genes between neighboring cells under the same exposure conditions, from only a few transcripts to over 100 copies in individual cells. Gene expression ratios among the 10 genes in each cell uncovered shifts in favor of genes that play key roles in restoring and maintaining energy balance. Among these genes are isoforms that can secure and increase glycolysis rates more efficiently, as well as genes with multiple cellular functions, in addition to glycolysis, including DNA repair, regulation of gene expression, cell cycle progression, and proliferation. Our study uncovered prioritization of gene expression in individual cells for restoring energy balance under LCO NP exposures. Broadly, our study gained insight into single-cell strategies for redistributing limited resources to achieve optimal response and survival under stress.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Nuclear Waste Tank Emission Contributions to Particle Size Distribution

Pollutants from anthropogenic activities including industrial processes are ubiquitous to the environment. To understand the impact from industrial aerosol on climate and human health, industrial aerosol needs to be better characterized. Here, in this study, particle number concentrations were used as a proxy for atmospheric pollutants, which include both particles and gases. Particle concentration and size distribution were measured using a scanning mobility particle sizer (SMPS) approximately 4.5 km from primary industrial areas at the Savannah River Site in Aiken, SC. Industrial areas include numerous nuclear waste storage and processing tanks. The SMPS data were divided into two groups depending on the wind direction measured onsite to categorize transport from the industrial area or from elsewhere. Industrial contributions were found to have a higher concentration of particles with sizes less than 200 nm, 859 ± 564 cm -3 , in comparison to non-industrial attributed particles, 733 ± 495 cm -3 on average from March-July 2021. For sizes larger than 200 nm, industrial and non-industrial particles have a similar concentration, 89 ± 59 cm -3 and 99 ± 61 cm -3 , with non-industrial concentrations being slightly larger. To confirm that industrial particles could travel to the sampling location, air dispersion modeling was completed for specific case studies during the sampling period. The atmospheric dispersion modeling results confirmed that particles released at the industrial areas reached the sampling location when the wind direction was favorable for transport from the industrial areas. The greater concentration of smaller-sized particles in industrial emissions has implications for typical particulate measurements (PM2.5), heath impacts, and climatological influences.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Detection of Chymotrypsin by Optical and Acoustic Methods

Chymotrypsin is an important proteolytic enzyme in the human digestive system that cleaves milk proteins through the hydrolysis reaction, making it an interesting subject to study the activity of milk proteases. In this work, we compared detection of chymotrypsin by spectrophotometric dynamic light scattering (DLS) and quartz crystal microbalance (QCM) methods and determined the limit of chymotrypsin detection (LOD), 0.15 ± 0.01 nM for spectrophotometric, 0.67 ± 0.05 nM for DLS and 1.40 ± 0.30 nM for QCM methods, respectively. The sensors are relatively cheap and are able to detect chymotrypsin in 3035 min. While the optical detection methods are simple to implement, the QCM method is more robust for sample preparation, and allows detection of chymotrypsin in non-transparent samples. We give an overview on methods and instruments for detection of chymotrypsin and other milk proteases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Xanthohumol Alters Gut Microbiota Metabolism and Bile Acid Dynamics in Gastrointestinal Simulation Models of Eubiotic and Dysbiotic States

Xanthohumol (XN), a polyphenol from hops (Humulus lupulus), exhibits antioxidant, anti-inflammatory, antihyperlipidemic, and chemo-preventive activity. Preclinical evidence suggests gut microbiota are critical to mediating some of these bioactivities. Nevertheless, its precise impact on human gut microbiota, particularly at supplemental doses, remains poorly characterized. We evaluated 200 mg/day XN for 3 weeks on human gut microbiota in a eubiotic and dysbiotic model using the Simulator of the Human Intestinal Microbial Ecosystem (SHIME®). Functional assessments of microbiota included quantification of XN metabolites, short-chain fatty acids (SCFAs), and untargeted metabolomics of the digestive metabolome. Bacterial composition was assessed by 16S rRNA gene sequencing. XN reduced alpha-diversity and short-chain fatty acid production in both models, as well as altered taxa abundance variably between models. XN disrupted bile acid metabolism through inhibition of microbial bile salt hydrolase (BSH). The modulation of bile acid metabolism has important implications for host-level bioactivity of XN.

Humulus lupulus↗
DOE OSTI2020

Antisense targeting of decoy exons can reduce intron retention and increase protein expression in human erythroblasts

The decoy exon model has been proposed to regulate a subset of intron retention (IR) events involving predominantly larger introns (>1 kb). Splicing reporter studies have shown that decoy splice sites are essential for activity, suggesting that decoys act by engaging intron-terminal splice sites and competing with cross-intron interactions required for intron excision. The decoy model predicts that antisense oligonucleotides may be able to block decoy splice sites in endogenous pre-mRNA, thereby reducing IR and increasing productive gene expression. Indeed, we now demonstrate that targeting a decoy 5' splice site in the O-GlcNAc transferase (OGT) gene reduced IR from ~80% to ~20% in primary human erythroblasts, accompanied by increases in spliced OGT RNA and OGT protein expression. The remaining OGT IR was refractory to antisense treatment and might be mediated by independent mechanism(s). In contrast, other retained introns were strongly dependent on decoy function, since antisense targeting of decoy 5' splice sites greatly reduced (SNRNP70) or nearly eliminated (SF3B1) IR in two widely expressed splicing factors, and also greatly reduced IR in transcripts encoding the erythroid-specific structural protein, α-spectrin (SPTA1). These results show that modulating decoy exon function can dramatically alter IR and suggest that dynamic regulation of decoy exons could be a mechanism to fine-tune gene expression post-transcriptionally in many cell types.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

An elastin-like polymer targeting vascular endothelial growth factor receptor-1 reduces survival in serum-starved endothelial cells

Peptides often exhibit biological activity that depends on the context in which they are displayed and delivered. Understanding and controlling these contextual effects on peptide function is critical for designing targeted and responsive peptide-based biomaterials and therapeutics. Genetically engineered protein polymers such as elastin-like polypeptides (ELPs) can incorporate bioactive peptide motifs and are attractive candidates for biomaterials used in tissue engineering and targeted drug delivery. They also present an opportunity for investigating and modulating cell signaling pathways by presenting a peptide ligand in various defined chemical and physical environments. Vascular endothelial growth factor receptor-1 (VEGFR1) signaling plays important and complex roles in cell survival and angiogenesis, but polymeric materials that interact with this signaling axis are scarce. In this study, a novel genetically engineered elastin-like polymer that targets VEGFR1 is characterized. This polymer, termed R1B-ELP, binds to human endothelial cells in a manner dependent on its VEGFR1-targeting motif and, based on cell proliferation and cytotoxicity assays, demonstrates activity consistent with disrupting pro-survival signaling necessary for endothelial cell function under conditions of environmental stress. Notably, these findings indicate that ELP fusion alters the functional behavior of the targeting peptide. Modulators of VEGFR1 signaling have potential applications in basic studies of angiogenesis as well as in therapeutic applications targeting vascular or inflammatory diseases.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Molecular recognition of a host protein by NS1 of pandemic and seasonal influenza A viruses

The 1918 influenza A virus (IAV) caused the most severe flu pandemic in recorded human history. Nonstructural protein 1 (NS1) is an important virulence factor of the 1918 IAV. NS1 antagonizes host defense mechanisms through interactions with multiple host factors. One pathway by which NS1 increases virulence is through the activation of phosphoinositide 3-kinase (PI3K) by binding to its p85β subunit. Here we present the mechanism underlying the molecular recognition of the p85β subunit by 1918 NS1. Using X-ray crystallography, we determine the structure of 1918 NS1 complexed with p85β of human PI3K. We find that the 1918 NS1 effector domain (1918 NS1 ED ) undergoes a conformational change to bind p85β. Using NMR relaxation dispersion and molecular dynamics simulation, we identify that free 1918 NS1 ED exists in a dynamic equilibrium between p85β-binding–competent and –incompetent conformations in the submillisecond timescale. Moreover, we discover that NS1 ED proteins of 1918 (H1N1) and Udorn (H3N2) strains exhibit drastically different conformational dynamics and binding kinetics to p85β. These results provide evidence of strain-dependent conformational dynamics of NS1. Using kinetic modeling based on the experimental data, we demonstrate that 1918 NS1 ED can result in the faster hijacking of p85β compared to Ud NS1 ED , although the former has a lower affinity to p85β than the latter. Our results suggest that the difference in binding kinetics may impact the competition with cellular antiviral responses for the activation of PI3K. We anticipate that our findings will increase the understanding of the strain-dependent behaviors of influenza NS1 proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Interpreting machine learning prediction of fire emissions and comparison with FireMIP process-based models

Annual burned areas in the United States have increased 2-fold during the past decades. With more large fires resulting in more emissions of fine particulate matter, an accurate prediction of fire emissions is critical for quantifying the impacts of fires on air quality, human health, and climate. This study aims to construct a machine learning (ML) model with game-theory interpretation to predict monthly fire emissions over the contiguous US (CONUS) and to understand the controlling factors of fire emissions. The optimized ML model is used to diagnose the process-based models in the Fire Modeling Intercomparison Project (FireMIP) to inform future development. Results show promising performance for the ML model, Community Land Model (CLM), and Joint UK Land Environment Simulator-Interactive Fire And Emission Algorithm For Natural Environments (JULES-INFERNO) in reproducing the spatial distributions, seasonality, and interannual variability of fire emissions over the CONUS. Regional analysis shows that only the ML model and CLM simulate the realistic interannual variability of fire emissions for most of the subregions (r >0.95 for ML and r =0.14~0.70 for CLM), except for Mediterranean California, where all the models perform poorly (r =0.74 for ML and r <0.30 for the FireMIP models). Regarding seasonality, most models capture the peak emission in July over the western US. However, all models except for the ML model fail to reproduce the bimodal peaks in July and October over Mediterranean California, which may be explained by the smaller wind speeds of the atmospheric forcing data during Santa Ana wind events and limitations in model parameterizations for capturing the effects of Santa Ana winds on fire activity. Furthermore, most models struggle to capture the spring peak in emissions in the southeastern US, probably due to underrepresentation of human effects and the influences of winter dryness on fires in the models. As for extreme events, both the ML model and CLM successfully reproduce the frequency map of extreme emission occurrence but overestimate the number of months with extremely large fire emissions. Comparing the fire PM 2.5 emissions from the ML model with process-based fire models highlights their strengths and uncertainties for regional analysis and prediction and provides useful insights into future directions for model improvements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

CryoEM structures of the human CLC-2 voltage-gated chloride channel reveal a ball-and-chain gating mechanism

CLC-2 is a voltage-gated chloride channel that contributes to electrical excitability and ion homeostasis in many different tissues. Among the nine mammalian CLC homologs, CLC-2 is uniquely activated by hyperpolarization, rather than depolarization, of the plasma membrane. The molecular basis for the divergence in polarity of voltage gating among closely related homologs has been a long-standing mystery, in part because few CLC channel structures are available. Here, we report cryoEM structures of human CLC-2 at 2.46 – 2.76 Å, in the presence and absence of the selective inhibitor AK-42. AK-42 binds within the extracellular entryway of the Cl – -permeation pathway, occupying a pocket previously proposed through computational docking studies. In the apo structure, we observed two distinct conformations involving rotation of one of the cytoplasmic C-terminal domains (CTDs). In the absence of CTD rotation, an intracellular N-terminal 15-residue hairpin peptide nestles against the TM domain to physically occlude the Cl – -permeation pathway. This peptide is highly conserved among species variants of CLC-2 but is not present in other CLC homologs. Previous studies suggested that the N-terminal domain of CLC-2 influences channel properties via a “ball-and-chain” gating mechanism, but conflicting data cast doubt on such a mechanism, and thus the structure of the N-terminal domain and its interaction with the channel has been uncertain. Through electrophysiological studies of an N-terminal deletion mutant lacking the 15-residue hairpin peptide, we support a model in which the N-terminal hairpin of CLC-2 stabilizes a closed state of the channel by blocking the cytoplasmic Cl – -permeation pathway.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Robust T cell activation requires an eIF3-driven burst in T cell receptor translation

Activation of T cells requires a rapid surge in cellular protein synthesis. However, the role of translation initiation in the early induction of specific genes remains unclear. Here, we show human translation initiation factor eIF3 interacts with select immune system related mRNAs including those encoding the T cell receptor (TCR) subunits TCRA and TCRB. Binding of eIF3 to the TCRA and TCRB mRNA 3’-untranslated regions (3’-UTRs) depends on CD28 coreceptor signaling and regulates a burst in TCR translation required for robust T cell activation. Use of the TCRA or TCRB 3’-UTRs to control expression of an anti-CD19 chimeric antigen receptor (CAR) improves the ability of CAR-T cells to kill tumor cells in vitro. These results identify a new mechanism of eIF3-mediated translation control that can aid T cell engineering for immunotherapy applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Characterization of the procoagulant phenotype of amniotic fluid across gestation in rhesus macaques and humans

Background: Amniotic fluid (AF) plays a key role in fetal development, yet the evolving composition of AF and its effects of hemostasis and thrombosis are poorly understood. Objectives: Here, we aim to determine how the evolving molecular composition of AF relates to its procoagulant properties. Methods: We analyzed the proteomes, lipidomes and procoagulant properties of AF obtained by amniocentesis from rhesus macaque and human pregnancies at gestational-age matched timepoints. Results When added to human plasma, both rhesus and human AF accelerated clotting time and fibrin generation. We identified proteomic modules associated with clotting time and enriched for coagulation-related pathways. Proteins known to be involved in hemostasis were highly correlated with each other and their intensity of expression varied across gestation in both rhesus and humans. Inhibition of contact pathway did not affect the procoagulant effect of AF. Blocking tissue factor pathway inhibitor reversed the ability of AF to block the generation of FXa. The prothrombinase activity of AF was inhibited by phospholipid inhibitors. The levels of phosphatidylserine in AF were inversely correlated with clotting time. AF promoted platelet activation and secretion in plasma. Conclusions: The addition of AF to plasma enhances coagulation in a manner dependent on phospholipids as well as the presence of proteases and other proteins that directly regulate coagulation. We describe a correlation between clotting time and expression of coagulation proteins and phosphatidylserine in both rhesus and human AF, supporting the use rhesus models for future studies of AF biology.

amniotic fluid↗
DOE OSTI2023

Disruption of Z-Disc Function Promotes Mechanical Dysfunction in Human Myocardium: Evidence for a Dual Myofilament Modulatory Role by Alpha-Actinin 2

The ACTN2 gene encodes α-actinin 2, located in the Z-disc of the sarcomeres in striated muscle. In this study, we sought to investigate the effects of an ACTN2 missense variant of unknown significance (p.A868T) on cardiac muscle structure and function. Left ventricular free wall samples were obtained at the time of cardiac transplantation from a heart failure patient with the ACTN2 A868T heterozygous variant. This variant is in the EF 3–4 domain known to interact with titin and α-actinin. At the ultrastructural level, ACTN2 A868T cardiac samples presented small structural changes in cardiomyocytes when compared to healthy donor samples. However, contractile mechanics of permeabilized ACTN2 A868T variant cardiac tissue displayed higher myofilament Ca 2+ sensitivity of isometric force, reduced sinusoidal stiffness, and faster rates of tension redevelopment at all Ca 2+ levels. Small-angle X-ray diffraction indicated increased separation between thick and thin filaments, possibly contributing to changes in muscle kinetics. Molecular dynamics simulations indicated that while the mutation does not significantly impact the structure of α-actinin on its own, it likely alters the conformation associated with titin binding. Our results can be explained by two Z-disc mediated communication pathways: one pathway that involves α-actinin’s interaction with actin, affecting thin filament regulation, and the other pathway that involves α-actinin’s interaction with titin, affecting thick filament activation. This work establishes the role of α-actinin 2 in modulating cross-bridge kinetics and force development in the human myocardium as well as how it can be involved in the development of cardiac disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Hazard-Based Model of Activity Generation Using Vehicle Trajectory Data

Travel behavior modeling suffers from lack of longitudinal data due to the high cost of procurement and difficulty with ensuring data quality. In the recent years ubiquitous data intercepted from social media, cell detail record, GPS traces are increasingly being explored to analyze human mobility. However, these data lack key demographic information which limits their use for developing causal models of traveler behavior. The primary contribution of the paper lies in using vehicle trajectory data from Ann Arbor along with multiple other data sources for developing a hazard-based activity generation model. The different category of data used in the analysis include (i) vehicle trajectory data (VTD), (ii) American Census Survey (ACS), (iii) land use data, (iv) household travel survey (HTS) data, and (v) smart location data from Environmental Protection Agency (EPA). Home and work are identified as the two most frequently visited locations from the VTD and validated against land use categories of the region. Next a random utility-based model is developed using HTS data to identify other activity purposes as a function of the polynomials of distance from home, activity duration and departure time. The developed model is then applied to identify the non-home activity purposes in the VTD. Demographic and accessibility information are appended to the VTD from ACS and smart location databases respectively. The fmal database is then used to develop a hazard-based activity generation model. (C) 2020 The Authors. Published by Elsevier B.V.

activity generation↗
DOE OSTI2021

Viral Inhibitors Derived from Macroalgae, Microalgae, and Cyanobacteria: A review of antiviral potential throughout pathogenesis

Viruses are abiotic obligate parasites utilizing complex mechanisms to hijack cellular machinery and reproduce, causing multiple harmful effects in the process. Viruses represent a growing global health concern; at the time of writing, COVID-19 has killed at least two million people around the world and devastated global economies. Lingering concern regarding the virus’ prevalence yet hampers return to normalcy. While catastrophic in and of itself, COVID-19 further heralds in a new era of human-disease interaction characterized by the emergence of novel viruses from natural sources with heretofore unseen frequency. Due to deforestation, population growth, and climate change, we are encountering more viruses that can infect larger groups of people with greater ease and increasingly severe outcomes. The devastation of COVID-19 and forecasts of future human/disease interactions call for a creative reconsideration of global response to infectious disease. There is an urgent need for accessible, cost-effective antiviral (AV) drugs that can be mass-produced and widely distributed to large populations. Development of AV drugs should be informed by a thorough understanding of viral structure and function as well as human biology. To maximize efficacy, minimize cost, and reduce development of drug-resistance, these drugs would ideally operate through a varied set of mechanisms at multiple stages throughout the course of infection. Due to their abundance and diversity, natural compounds are ideal for such comprehensive therapeutic interventions. Promising sources of such drugs are found throughout nature; especially remarkable are the algae, a polyphyletic grouping of phototrophs that produce diverse bioactive compounds. While not much literature has been published on the subject, studies have shown that these compounds exert antiviral effects at different stages of viral pathogenesis. In this review, we follow the course of viral infection in the human body and evaluate the AV effects of algae-derived compounds at each stage. Specifically, we examine the AV activities of algae-derived compounds at the entry of viruses into the body, transport through the body via the lymph and blood, infection of target cells, and immune response. We discuss what is known about algae-derived compounds that may interfere with the infection pathways of SARS-CoV-2; and review which algae are promising sources for AV agents or AV precursors that, with further investigation, may yield life-saving drugs due to their diversity of mechanisms and exceptional pharmaceutical potential.

Algae, antiviral, SARS-CoV-2, seaweed, cyanobacter↗