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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Uncultivated Viral Populations Dominate Estuarine Viromes on the Spatiotemporal Scale

Viruses are ubiquitous and abundant in the oceans, and viral metagenomes (viromes) have been investigated extensively via several large-scale ocean sequencing projects. However, there have not been any systematic viromic studies in estuaries. Here, we investigated the viromes of the Delaware Bay and Chesapeake Bay, two Mid-Atlantic estuaries. Deep sequencing generated a total of 48,190 assembled viral sequences (>5 kb) and 26,487 viral populations (9,204 virus clusters and 17,845 singletons), including 319 circular viral contigs between 7.5 kb and 161.8 kb. Unknown viruses represented the vast majority of the dominant populations, while the composition of known viruses, such as pelagiphage and cyanophage, appeared to be relatively consistent across a wide range of salinity gradients and in different seasons. A difference between estuarine and ocean viromes was reflected by the proportions of Myoviridae, Podoviridae, Siphoviridae, Phycodnaviridae, and a few well-studied virus representatives. The difference in viral community between the Delaware Bay and Chesapeake Bay is significantly more pronounced than the difference caused by temperature or salinity, indicating strong local profiles caused by the unique ecology of each estuary. Interestingly, a viral contig similar to phages infecting Acinetobacter baumannii (“Iraqibacter”) was found to be highly abundant in the Delaware Bay but not in the Chesapeake Bay, the source of which is yet to be identified. Highly abundant viruses in both estuaries have close hits to viral sequences derived from the marine single-cell genomes or long-read single-molecule sequencing, suggesting that important viruses are still waiting to be discovered in the estuarine environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

CD206 + Trem2 + macrophage accumulation in the murine knee joint after injury is associated with protection against post-traumatic osteoarthritis in MRL/MpJ mice

Post-traumatic osteoarthritis (PTOA) is a painful joint disease characterized by the degradation of bone, cartilage, and other connective tissues in the joint. PTOA is initiated by trauma to joint-stabilizing tissues, such as the anterior cruciate ligament, medial meniscus, or by intra-articular fractures. In humans, ~50% of joint injuries progress to PTOA, while the rest spontaneously resolve. To better understand molecular programs contributing to PTOA development or resolution, we examined injury-induced fluctuations in immune cell populations and transcriptional shifts by single-cell RNA sequencing of synovial joints in PTOA-susceptible C57BL/6J (B6) and PTOA-resistant MRL/MpJ (MRL) mice. We identified significant differences in monocyte and macrophage subpopulations between MRL and B6 joints. A potent myeloid-driven anti-inflammatory response was observed in MRL injured joints that significantly contrasted the pro-inflammatory signaling seen in B6 joints. Multiple CD206 + macrophage populations classically described as M2 were found enriched in MRL injured joints. These CD206 + macrophages also robustly expressed Trem2 , a receptor involved in inflammation and myeloid cell activation. These data suggest that the PTOA resistant MRL mouse strain displays an enhanced capacity of clearing debris and apoptotic cells induced by inflammation after injury due to an increase in activated M2 macrophages within the synovial tissue and joint space.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Nanoscale resolution of microbial fiber degradation in action

The lives of microbes unfold at the micron scale, and their molecular machineries operate at the nanoscale. Their study at these resolutions is key toward achieving a better understanding of their ecology. We focus on cellulose degradation of the canonical Clostridium thermocellum system to comprehend how microbes build and use their cellulosomal machinery at these nanometer scales. Degradation of cellulose, the most abundant organic polymer on Earth, is instrumental to the global carbon cycle. We reveal that bacterial cells form ‘cellulosome capsules’ driven by catalytic product-dependent dynamics, which can increase the rate of hydrolysis. Biosynthesis of this energetically costly machinery and cell growth are decoupled at the single-cell level, hinting at a division-of-labor strategy through phenotypic heterogeneity. This novel observation highlights intrapopulation interactions as key to understanding rates of fiber degradation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Exploring new frontiers in type 1 diabetes through advanced mass-spectrometry-based molecular measurements

Type 1 diabetes (T1D) is a devastating autoimmune disease for which advanced mass spectrometry (MS) methods are increasingly used to identify new biomarkers and better understand underlying mechanisms. For example, integration of MS analysis and machine learning has identified multimolecular biomarker panels. In mechanistic studies, MS has contributed to the discovery of neoepitopes, and pathways involved in disease development and identifying therapeutic targets. However, challenges remain in understanding the role of tissue microenvironments, spatial heterogeneity, and environmental factors in disease pathogenesis. Recent advancements in MS, such as ultra-fast ion-mobility separations, and single-cell and spatial omics, can play a central role in addressing these challenges. Here, in this work, we review recent advancements in MS-based molecular measurements and their role in understanding T1D.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

DOE new players Carbon cycle (2016-2021)

The overarching scientific goals of our multidisciplinary grant was to further expand understanding about the key microorganisms (players), metabolic strategies (processes), and interspecies relationships (interactions) involved in the formation and oxidation of methane in the environment. This research applied novel environmental metagenomics, transcriptomics, and proteomic techniques, state-of-the-art analytical imaging, stable isotope geochemistry, and reaction-transport modeling to address these goals and develop an ‘ecosystems level’ understanding of the factors which regulate microbial methane cycling in anoxic sedimentary ecosystems. For decades, it was believed that the obligate step in methanogenesis catalyzed by methyl coenzyme M reductase (Mcr) was limited to a specific branch of the archaeal Domain, formerly known as the Euryarchaeota. Less than a decade ago co-I Tyson’s team published a surprising metagenomic-based discovery of divergent Mcr genes in a novel uncultured phylum (Bathyarchaeota), catalyzing a major shift in thinking about the diversity of microorganisms that encode the potential for methane (or higher alkane) metabolism in anoxic environments (Evans et al., 2015). In our work here, we further expand on the groups of archaea harboring the genomic potential for methane or hydrocarbon metabolism using environmental metagenomics and new gene targeted bioinformatics techniques. We additionally advanced understanding about the terminal electron acceptors and metabolic potential supporting the anaerobic oxidation of methane (AOM) in terrestrial ecosystems, specifically focused on new lineages of ANME archaea capable of respiring manganese oxides with methane presumably using large extracellular multi-heme cytochrome complexes. New details about specific syntrophic mechanisms underlying the exchange of electrons during sulfate-coupled methane oxidation between ANME-2 archaea and their sulfate-reducing bacterial partners were also elucidated as part of this funded project. Through a series of experimental ‘omics and single cell stable isotope probing studies with incubated environmental sediment samples and a cultured model electrogenic microorganism combined with model-based predictions. Combined, this work provides strong support for the hypothesis of direct interspecies electron transfer (DIET) is the dominant syntrophic mechanism controlling the anaerobic oxidation of methane with sulfate over other proposed mechanisms and additionally illustrates important spatial constraints and the underlying physico-chemical factors influencing AOM syntrophic consortia structure for DIET and extracellular metal respiration. This collaborative multi-institutional project successfully advanced several of our milestone goals including the identification of new microbial players containing methyl coenzyme M reductases hypothesized to be central to methane or hydrocarbon cycling in anoxic environments and enhancing fundamental knowledge about the role extracellular electron transfer plays in the ecophysiology of methanotrophic archaea respiring metal oxides and in the physical and metabolic structuring of syntrophic interactions in methane-rich sedimentary ecosystems.

03 NATURAL GAS↗
DOE OSTI2025

Transcription of hepatitis B surface antigen shifts from cccDNA to integrated HBV DNA during treatment

The cornerstone of functional cure for chronic hepatitis B (CHB) is hepatitis B surface antigen (HBsAg) loss from blood. HBsAg is encoded by covalently closed circular DNA (cccDNA) and HBV DNA integrated into the host genome (iDNA). Nucleos(t)ide analogs (NUCs), the mainstay of CHB treatment, rarely lead to HBsAg loss, which we hypothesized was due to continued iDNA transcription despite decreased cccDNA transcription. To test this, we applied a multiplex droplet digital PCR that identifies the dominant source of HBsAg mRNAs to 3,436 single cells from paired liver biopsies obtained from 10 people with CHB and HIV receiving NUCs. With increased NUC duration, cells producing HBsAg mRNAs shifted their transcription from chiefly cccDNA to chiefly iDNA. This shift was due to both a reduction in the number of cccDNA-containing cells and diminished cccDNA-derived transcription per cell; furthermore, it correlated with reduced detection of proteins deriving from cccDNA but not iDNA. Despite this shift in the primary source of HBsAg, rare cells remained with detectable cccDNA-derived transcription, suggesting a source for maintaining the replication cycle. Functional cure must address both iDNA and residual cccDNA transcription. Further research is required to understand the significance of HBsAg when chiefly derived from iDNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Catalytic Activity and Stability of Non-Platinum Group Metal Oxides for the Oxygen Evolution Reaction in Anion Exchange Membrane Electrolyzers

The activities and stabilities of non-platinum group metals (PGMs) in the forms of monometallic (Mn 2 O 3 , Fe 2 O 3 , Co 3 O 4 , NiO) and bimetallic (NiFe 2 O 4 , CoNiO 2 ) oxides were assessed for the oxygen evolution reaction (OER) in alkaline media and compared with IrO 2 . Both half-cell, rotating disc electrode (RDE) apparatus and single-cell, membrane electrode assemblies (MEA) were used to study kinetic and device-level performance in parallel and to provide insights into the use of these materials in anion exchange membrane (AEM) electrolyzers. Normalization of RDE results by geometric and physical surface areas, double layer capacitance, and metal content probed differences in physically vs electrochemically accessible surface areas and ensured reported trends were independent of the normalization method. The results showed that: (i) Ni- and Co- containing materials met or exceeded IrO 2 performance in both RDE and MEA testing, (ii) Co 3 O 4 deactivated over time-on-stream (1.8 V for 13.5 h) due to oxide and, relatedly, particle growth, (iii) NiFe 2 O 4 increased in activity over time-on-stream due to dissolution of Fe and an increased Ni/Fe ratio, and (iv) reduction of catalyst layer resistance is an avenue to further increase device-level performance. These results demonstrated the clear viability for non-PGMs to be used as anode catalysts in AEM devices.

25 ENERGY STORAGE↗
DOE OSTI2024

Inhibition of the eukaryotic initiation factor-2α kinase PERK decreases risk of autoimmune diabetes in mice

Preventing the onset of autoimmune type 1 diabetes (T1D) is feasible through pharmacological interventions that target molecular stress–responsive mechanisms. Cellular stresses, such as nutrient deficiency, viral infection, or unfolded proteins, trigger the integrated stress response (ISR), which curtails protein synthesis by phosphorylating eukaryotic translation initiation factor-2α (eIF2α). In T1D, maladaptive unfolded protein response (UPR) in insulin-producing β cells renders these cells susceptible to autoimmunity. We found that inhibition of the eIF2α kinase PKR-like ER kinase (PERK), a common component of the UPR and ISR, reversed the mRNA translation block in stressed human islets and delayed the onset of diabetes, reduced islet inflammation, and preserved β cell mass in T1D-susceptible mice. Single-cell RNA-Seq of islets from PERK-inhibited mice showed reductions in the UPR and PERK signaling pathways and alterations in antigen-processing and presentation pathways in β cells. Spatial proteomics of islets from these mice showed an increase in the immune checkpoint protein programmed death-ligand 1 (PD-L1) in β cells. Golgi membrane protein 1, whose levels increased following PERK inhibition in human islets and EndoC-βH1 human β cells, interacted with and stabilized PD-L1. Collectively, our studies show that PERK activity enhances β cell immunogenicity and that inhibition of PERK may offer a strategy for preventing or delaying the development of T1D.

Research & Experimental Medicine↗
DOE OSTI2021

Use of imaging and mass spectrometry-based capabilities to describe microbiome interactions (Q4 Performance Metric Report, 2021)

The LLNL “Microbes Persist” Soil Microbiome Scientific Focus Area (SFA) seeks to determine how microbial soil ecophysiology, population dynamics, and microbe-mineral-organic matter interactions regulate the persistence of microbial residues and formation of soil carbon (C). In much of our research, we use imaging, mass spectrometry, and related methods to study plantmicrobe-mineral interactions, viral and microbial particles from soil, and the signatures plant and microbial necromass contribute as part of soil organic matter (SOM). Our project’s signature techniques include NanoSIMS-enabled approaches (to understand cell-cell and OM-mineral interactions at the single cell and even viral particle scale), radiocarbon (14C) analyses (to determine both the age and turnover time of soil organic matter), and a suite of soil chemical characterization techniques we describe below, and collectively refer to as ‘Multi- dimensional SOM-mineral characterization’ (SEM, TEM, STXM, NEXAFS, NMR, FTICR-MS, LC-MS). In this report, we focus on how imaging, NMR, beamline and mass spectrometry approaches can deepen our understanding of soil microbiomes and their engagement with the soil matrix.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Battery Life Prediction Using Reduced-Order Physics Models and Machine Learning (CRADA Final Report)

Phase 1 (Original CRADA, plus no-cost extension modifications #1-3, 6/1/2017 to 3/13/2021): The Australian Department of Defence (AUDoD) is performing accelerated aging tests of Li-ion batteries to benchmark their reliability and degradation characteristics. Using its previously developed battery lifetime predictive model framework, the National Laboratory of the Rockies (NLR) will develop analytical models based the AUDoD data to predict lifetime of the multiple Li-ion battery chemistries under real-world use scenarios of interest to AUDoD. The NLR model is based on physical degradation mechanisms encountered by Li-ion batteries and has been previously validated. Phase 2 (CRADA modification #4, plus no-cost extension modification #5, 2/22/2021 to 3/30/2025): Train and support Australian Department of Defence personnel to use NLR software for model-based estimation of Li-ion battery lifetime using accelerated battery aging data collected by the Australian Department of Defence. Under separate DOE funding from 2019 to 2021, NLR enhanced its battery life-prediction software using machine learning algorithms to automate portions of the model-fitting process, requiring significantly less labor and expert judgment and also adding uncertainty quantification, increasing statistical rigor. Under Phase 2, NLR will customize NLR Software and provide it to AuDoD. NLR will enhance its NLR Model to capture aging modes of AuDoD's multi-cell modules, including cell-balancing effects. NLR will develop example single-cell and multi-cell models based on one AuDoD battery aging dataset. NLR will train AuDoD personnel on NLR Software. By the conclusion of the project, NLR will have provided AuDoD the training materials, a user manual and software needed to perform their own analysis of additional and/or future battery aging datasets.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Stochastic journeys of cell progenies through compartments and the role of self-renewal, symmetric and asymmetric division

Abstract Division and differentiation events by which cell populations with specific functions are generated often take place as part of a developmental programme, which can be represented by a sequence of compartments. A compartment is the set of cells with common characteristics; sharing, for instance, a spatial location or a phenotype. Differentiation events are transitions from one compartment to the next. Cells may also die or divide. We consider three different types of division events: (i) where both daughter cells inherit the mother’s phenotype (self-renewal), (ii) where only one of the daughters changes phenotype (asymmetric division), and (iii) where both daughters change phenotype (symmetric division). The self-renewal probability in each compartment determines whether the progeny of a single cell, moving through the sequence of compartments, is finite or grows without bound. We analyse the progeny stochastic dynamics with probability generating functions. In the case of self-renewal, by following one of the daughters after any division event, we may construct lifelines containing only one cell at any time. We analyse the number of divisions along such lines, and the compartment where lines terminate with a death event. Analysis and numerical simulations are applied to a five-compartment model of the gradual differentiation of hematopoietic stem cells and to a model of thymocyte development: from pre-double positive to single positive (SP) cells with a bifurcation to either SP4 or SP8 in the last compartment of the sequence.

Science & Technology - Other Topics↗
DOE OSTI2023

Second-Phase Hepatitis C Plasma Viral Kinetics Directly Reflects Reduced Intrahepatic Burden of Hepatitis C Virus

Mathematical models explain how antivirals control viral infections. Hepatitis C virus (HCV) treatment results in at least 2 phases of decline in viremia. Here, the first phase reflects clearance of rapidly produced virions. The second phase is hypothesized to derive from loss of infected cells but has been challenging to prove. Using single-cell methods, we quantified the number of hepatitis C virus (HCV)-infected hepatocytes in liver biopsies taken before and within 7 days of initiating direct-acting antivirals (DAAs) in a double-blinded randomized controlled trial testing 2 (sofosbuvir-velpatasvir) versus 3 (sofosbuvir-velpatasvir-voxilaprevir) DAAs. We employed thousands of intrahepatic measurements in 10 persons with chronic genotype 1a HCV infection: median proportion of infected hepatocytes declined from 11.3% (range, 1.3%–59%) to 0.6% (range, <0.3%–5.8%), a loss of 75%–95% infected hepatocytes. Plasma viremia correlated with numbers of HCV-infected hepatocytes (r = 0.77; P < .0001). Second-phase plasma dynamics and changes in infected hepatocytes were indistinct (P = .16), demonstrating that second-phase viral dynamics derive from loss of infected cells. DAAs led to a decline in intracellular HCV RNA and interferon-stimulated gene expression (P < .05 for both). We proved that second-phase viral dynamics reflect decay of intrahepatic burden of HCV, partly due to clearance of HCV RNA from hepatocytes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Efficient, stable silicon tandem cells enabled by anion-engineered wide-bandgap perovskites

Maximizing the power conversion efficiency (PCE) of perovskite/silicon tandem solar cells that can exceed the Shockley-Queisser single-cell limit requires a high-performing, stable perovskite top cell with a wide bandgap. We developed a stable perovskite solar cell with a bandgap of ~1.7 electron volts that retained more than 80% of its initial PCE of 20.7% after 1000 hours of continuous illumination. Anion engineering of phenethylammonium-based two-dimensional (2D) additives was critical for controlling the structural and electrical properties of the 2D passivation layers based on a lead iodide framework. The high PCE of 26.7% of a monolithic two-terminal wide-bandgap perovskite/silicon tandem solar cell was made possible by the ideal combination of spectral responses of the top and bottom cells.

14 SOLAR ENERGY↗
DOE OSTI2025

Sempervirens: A Fast Reconstruction Algorithm for Noisy and Incomplete Binary Matrix Representations of Trees

Applications such as reconstructing cell lineage trees (represented as phylogenetic trees) from single-cell sequencing data require reconstructing a {0,1}-matrix that has many errors and missing entries. We introduce Sempervirens, a very fast matrix reconstruction algorithm for noisy and incomplete matrix representations of phylogenetic trees. Sempervirens uses an iterative maximum-likelihood approach to determine the topology tree represented by the corrupted data. We show that Sempervirens is at least three orders of magnitude faster than other methods on thousand by thousand matrices, with the speed gap widening with larger matrices. We also show that Sempervirens matches state-of-the-art methods in reconstruction accuracy. The speed of Sempervirens enables it to be tractably applied to reconstructing much larger matrices than those that other methods can reconstruct. In addition to experimental results, we justify the algorithm with a mathematical treatment of its subprocedures.

algorithms↗
DOE OSTI2020

Azobenzene-based sinusoidal surface topography drives focal adhesion confinement and guides collective migration of epithelial cells

Surface topography is a key parameter in regulating the morphology and behavior of single cells. At multicellular level, coordinated cell displacements drive many biological events such as embryonic morphogenesis. However, the effect of surface topography on collective migration of epithelium has not been studied in detail. Mastering the connection between surface features and collective cellular behaviour is highly important for novel approaches in tissue engineering and repair. Herein, we used photopatterned microtopographies on azobenzene-containing materials and showed that smooth topographical cues with proper period and orientation can efficiently orchestrate cell alignment in growing epithelium. Furthermore, the experimental system allowed us to investigate how the orientation of the topographical features can alter the speed of wound closure in vitro. Our findings indicate that the extracellular microenvironment topography coordinates their focal adhesion distribution and alignment. These topographic cues are able to guide the collective migration of multicellular systems, even when cell–cell junctions are disrupted.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

SBML Level 3: an extensible format for the exchange and reuse of biological models

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Large-Scale Image Analysis for Investigating Spatio-Temporal Changes in Nuclear DNA Damage Caused by Nitrogen Atmospheric Pressure Plasma Jets

The effective clinical application of atmospheric pressure plasma jet (APPJ) treatments requires a well-founded methodology that can describe the interactions between the plasma jet and a treated sample and the temporal and spatial changes that result from the treatment. In this study, we developed a large-scale image analysis method to identify the cell-cycle stage and quantify damage to nuclear DNA in single cells. The method was then tested and used to examine spatio-temporal distributions of nuclear DNA damage in two cell lines from the same anatomic location, namely the oral cavity, after treatment with a nitrogen APPJ. One cell line was malignant, and the other, nonmalignant. The results showed that DNA damage in cancer cells was maximized at the plasma jet treatment region, where the APPJ directly contacted the sample, and declined radially outward. As incubation continued, DNA damage in cancer cells decreased slightly over the first 4 h before rapidly decreasing by approximately 60% at 8 h post-treatment. In nonmalignant cells, no damage was observed within 1 h after treatment, but damage was detected 2 h after treatment. Notably, the damage was 5-fold less than that detected in irradiated cancer cells. Moreover, examining damage with respect to the cell cycle showed that S phase cells were more susceptible to DNA damage than either G1 or G2 phase cells. The proposed methodology for large-scale image analysis is not limited to APPJ post-treatment applications and can be utilized to evaluate biological samples affected by any type of radiation, and, more so, the cell-cycle classification can be used on any cell type with any nuclear DNA staining.

cellular imaging↗
DOE OSTI2022

A Polymer Canvas with the Stiffness of the Bone Matrix to Study and Control Mesenchymal Stem Cell Response

Reproducing in vitro the complex multiscale physical features of human tissues creates novel biomedical opportunities and fundamental understanding of cell–environment interfaces and interactions. While stiffness has been recognized as a key driver of cell behavior, systematic studies on the role of stiffness have been limited to values in the KPa–MPa range, significantly below the stiffness of bone. Here, in this work, a platform enabling the tuning of the stiffness of a biocompatible polymeric interface up to values characteristic of human bone is reported, which are in the GPa range, by using extremely thin polymer films on glass and cross-linking the films using ultraviolet (UV) light irradiation. It is shown that a higher stiffness is related to better adhesion, proliferation, and osteogenic differentiation, and that it is possible to switch on/off cell attachment and growth by solely tuning the stiffness of the interface, without any surface chemistry or topography modification. Since the stiffness is tuned directly by UV irradiation, this platform is ideal for rapid and simple fabrication of stiffness patterns and gradients, thus representing an innovative tool for combinatorial studies of the synergistic effect of tissue environmental cues on cell behavior, and creates new opportunities for next-generation biosensors, single-cell patterning, and lab-on-a-chip devices.

60 APPLIED LIFE SCIENCES↗