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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Chronic arsenic increases cell migration in BEAS-2B cells by increasing cell speed, cell persistence, and cell protrusion length

Highlights: • Chronic arsenic exposure primes lung epithelial cells for enhanced cell migration. • Chronic arsenic increases cell motility in an EGFR-dependent manner. • Chronic arsenic increases cell persistence in an EGFR-independent manner. • EGFR is sufficient, but not necessary for increasing cell protrusion length in chronic arsenic treated cells. There is a strong association between arsenic exposure and lung cancer development, however, the mechanism by which arsenic exposure leads to carcinogenesis is not clear. In our previous study, we observed that when BEAS-2B cells are chronically exposed to arsenic, there is an increase in secreted TGFα, as well as an increase in EGFR expression and activity. Further, these changes were broadly accompanied with an increase in cell migration. The overarching goal of this study was to acquire finer resolution of the arsenic-dependent changes in cell migration, as well as to understand the role of increased EGFR expression and activity levels in the underlying mechanisms of cell migration. To do this, we used a combination of biochemical and single cell assays, and observed chronic arsenic treatment enhancing cell migration by increasing cell speed, cell persistence and cell protrusion length. All three parameters were further increased by the addition of TGFα, indicating EGFR activity is sufficient to enhance those aspects of cell migration. In contrast, EGFR activity was necessary for the increase in cell speed, as it was reversed with an EGFR inhibitor, AG1478, but was not necessary to enhance persistence and protrusion length. From these data, we were able to isolate both EGFR-dependent and –independent features of cell migration that were enhanced by chronic arsenic exposure.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Data for The Stem Cell-Type Transcriptome of Bioenergy Sorghum Reveals the Spatial Regulation of Secondary Cell Wall Networks

Bioenergy sorghum is a low-input, drought-resilient, deep-rooting annual crop that has high biomass yield potential enabling the sustainable production of biofuels, biopower, and bioproducts. Bioenergy sorghum’s 4-5 m stems account for ~80% of the harvested biomass. Stems accumulate high levels of sucrose that could be used to synthesize bioethanol and useful biopolymers if information about stem cell-type gene expression and regulation was available to enable engineering. To obtain this information, Laser Capture Microdissection (LCM) was used to isolate and collect transcriptome profiles from five major cell types that are present in stems of the sweet sorghum Wray. Transcriptome analysis identified genes with cell-type specific and cell-preferred expression patterns that reflect the distinct metabolic, transport, and regulatory functions of each cell type. Analysis of cell-type specific gene regulatory networks (GRNs) revealed that unique TF families contribute to distinct regulatory landscapes, where regulation is organized through various modes and identifiable network motifs. Cell-specific transcriptome data was combined with a stem developmental transcriptome dataset to identify the GRN that differentially activates the secondary cell wall (SCW) formation in stem xylem sclerenchyma and epidermal cells. The cell-type transcriptomic dataset provides a valuable source of information about the function of sorghum stem cell types and GRNs that will enable the engineering of bioenergy sorghum stems.

Software↗
DOE OSTI2022

A synthetic cell density signal can drive proliferation in chick embryonic tendon cells and tendon cells from a full size rooster can produce high levels of procollagen in cell culture

Cell density signaling drives tendon morphogenesis by regulating both procollagen production and cell proliferation. The signal is composed of a small, highly conserved protein (SNZR P) tightly bound to a tissue-specific, unique lipid (SNZR L). This allows the complex (SNZR PL) to bind to the membrane of the cell and locally diffuse over a radius of ~1 mm. The cell produces low levels of this signal but the binding to the membrane increases with the number of tendon cells in the local environment. In this article SNZR P was produced in E.coli and SNZR L was chemically synthesized. The two bind together when heated to 60 °C in the presence of Ca ++ and Mg ++ and the synthesized SNZR PL at ng/ml levels can replace serum. Adding SNZR PL to the medium was also tested on primary tendon cells from adult roosters. The older cells were in a maintenance state in vivo and in cell culture they proliferate more slowly than embryonic cells. Nevertheless, after reaching a moderately high cell density, they produced high levels of procollagen similar to the embryonic cells. This data was not expected from older cells but suggests that adult tendon cells can regenerate the tissue after injury when given the correct signals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Improved Primary Reference Cell Calibrations for Higher Accuracy Photovoltaic Cell and Module Performance Measurements

The adoption of photovoltaic (PV) modules for clean electricity relies on accurate measurements of their performance, which are essential for estimating their energy production potential. Herein, the calibration chain of PV cells and modules, with particular emphasis on primary reference cell calibrations, is discussed. Also, herein, the direct sunlight method the group has developed for these calibrations is presented and critical improvements and upgrades that lead to calibration uncertainty as low as 0.45% are discussed. The ultimate motivation behind this work is to provide low‐uncertainty performance measurements of PV modules, and lowering the calibration uncertainty of primary reference cells is a key first step toward achieving this goal. As the use of solar electricity continues to grow, the demand for primary reference cell calibrations inevitably increases beyond what the small handful of primary calibration laboratories can provide today. Therefore, this work can serve as a useful guide for implementing primary PV reference cell calibrations using the outdoor method, as well as outlining the critical elements required to make these calibrations highly accurate.

Osterwald, Carl R.↗
DOE OSTI2021

Modification of cell wall polysaccharide guides cell division in Streptococcus mutans

In ovoid-shaped, Gram-positive bacteria, MapZ guides FtsZ-ring positioning at cell equators. The cell wall of the ovococcus Streptococcus mutans contains peptidoglycan decorated with serotype c carbohydrates (SCCs). In the present study, we identify the major cell separation autolysin AtlA as an SCC-binding protein. AtlA binding to SCC is attenuated by the glycerol phosphate (GroP) modification. Using fluorescently labeled AtlA constructs, we mapped SCC distribution on the streptococcal surface, revealing enrichment of GroP-deficient immature SCCs at the cell poles and equators. The immature SCCs co-localize with MapZ at the equatorial rings throughout the cell cycle. In GroP-deficient mutants, AtlA is mislocalized, resulting in dysregulated cellular autolysis. These mutants display morphological abnormalities associated with MapZ mislocalization, leading to FtsZ-ring misplacement. Altogether, our data support a model in which maturation of a cell wall polysaccharide provides the molecular cues for the recruitment of cell division machinery, ensuring proper daughter cell separation and FtsZ-ring positioning.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Reference Cell Performance and Modeling on a One-Axis Tracking Surface: Preprint

Performance of five silicon-based reference cells is examined on a single-axis tracking surface. The reference cells' output are modeled using one-minute sampled spectral irradiance and reference cell temperature measurements. The model also incorporates spectral responsivity data for the reference cell. The transmission of light through the glazing multiplies the sum over all appropriate wavelengths of temperature adjusted reference cell responsivity times the measured spectral irradiance. Modeled reference cell output is compared with measured reference cell output under clear sky and totally cloudy sky conditions. For each reference cell the ratio of modeled to measured output varies by less than 2% over the year.

modeling↗
DOE OSTI2021

Preliminary Cryogenic Cold Test Results of the First 9-Cell LSF Shape Cavity

Following successful prototyping and testing of single- & 5-cell LSF shape cavities *, **, the first 9-cell LSF shape cavity LSF9-1 was successfully constructed using an innovative process at JLab with the in-house facilities. The cavity was then shipped to KEK for post-fabrication mechanical adjustment and ILC TDR style treatment and surface processing. Cold testing was carried out at the JLab VTA facility, instrumented with a suite of Kyoto instruments. Favorable values for the bath pressure detuning sensitivity and Lorentz force detuning coefficient were experimentally measured, validating the design improvement in cell stiffeners. Pass-band measurements indicate 4 out of 9 cells reaching gradient capability of > 45 MV/m, including 2 cells reaching 51 MV/m. Cornell OST detectors identified the cell and location responsible for the current hard quench limit. Multipacting-like barriers observed in end cells are investigated both analytically and numerically. The cavity was shipped to FNAL and received a light EP at the joint ANL/FNAL facility for further cold testing at Jlab. Two new 9-cell LSF cavities are being constructed including one made of large-grain niobium material.

43 PARTICLE ACCELERATORS↗
NASA NTRS2001

Response of thyroid follicular cells to gamma irradiation compared to proton irradiation. I. Initial characterization of DNA damage, micronucleus formation, apoptosis, cell survival, and cell cycle phase redistribution

The RBE of protons has been assumed to be equivalent to that of photons. The objective of this study was to determine whether radiation-induced DNA and chromosome damage, apoptosis, cell killing and cell cycling in organized epithelial cells was influenced by radiation quality. Thyroid-stimulating hormone-dependent Fischer rat thyroid cells, established as follicles, were exposed to gamma rays or proton beams delivered acutely over a range of physical doses. Gamma-irradiated cells were able to repair DNA damage relatively rapidly so that by 1 h postirradiation they had approximately 20% fewer exposed 3' ends than their counterparts that had been irradiated with proton beams. The persistence of free ends of DNA in the samples irradiated with the proton beam implies that either more initial breaks or a quantitatively different type of damage had occurred. These results were further supported by an increased frequency of chromosomal damage as measured by the presence of micronuclei. Proton-beam irradiation induced micronuclei at a rate of 2.4% per gray, which at 12 Gy translated to 40% more micronuclei than in comparable gamma-irradiated cultures. The higher rate of micronucleus formation and the presence of larger micronuclei in proton-irradiated cells was further evidence that a qualitatively more severe class of damage had been induced than was induced by gamma rays. Differences in the type of damage produced were detected in the apoptosis assay, wherein a significant lag in the induction of apoptosis occurred after gamma irradiation that did not occur with protons. The more immediate expression of apoptotic cells in the cultures irradiated with the proton beam suggests that the damage inflicted was more severe. Alternatively, the cell cycle checkpoint mechanisms required for recovery from such damage might not have been invoked. Differences based on radiation quality were also evident in the alpha components of cell survival curves (0.05 Gy(-1) for gamma rays, 0.12 Gy(-1) for protons), which suggests that the higher level of survival of gamma-irradiated cells could be attributed to the persistence of nonlethally irradiated thyrocytes and/or the capacity to repair damage more effectively than cells exposed to equal physical doses of protons. The final assessment in this study was radiation-induced cell cycle phase redistribution. Gamma rays and protons produced a similar dose-dependent redistribution toward a predominantly G(2)-phase population. From our cumulative results, it seems likely that a majority of the proton-irradiated cells would not continue to divide. In conclusion, these findings suggest that there are quantitative and qualitative differences in the biological effects of proton beams and gamma rays. These differences could be due to structured energy deposition from the tracks of primary protons and the associated high-LET secondary particles produced in the targets. The results suggest that a simple dose-equivalent approach to dosimetry may be inadequate to compare the biological responses of cells to photons and protons.

NASA Discipline Radiation Health↗
DOE OSTI2025

Single cell RNA sequencing reveals shifts in cell maturity and function of endogenous and infiltrating cell types in response to acute intervertebral disc injury

Intervertebral disc (IVD) degeneration contributes to disabling back pain. Degeneration can be initiated by injury and progressively leads to an irreversible loss of cells and function. IVD function restoration through cell replacement therapies have had limited success due to knowledge gaps in the critical cell populations important for repair. Here, in this study, we used single cell RNA sequencing to identify the transcriptional changes of IVD resident and infiltrating cell populations from Control and Injured coccygeal IVDs extracted from 12-week-old female C57BL/6J mice 7 days post injury. Clustering, gene ontology, and pseudotime trajectory analyses determined transcriptomic divergences with injury, flow cytometry identified they types of infiltrating immune cells, and immunofluorescence was utilized to define mesenchymal stem cell (MSC) localization. We identified 11 distinct clusters that included IVD, immune, vascular cells, and MSCs. Differential gene expression analysis determined that Outer Annulus Fibrosus, Neutrophils, Saa2-High MSCs, Macrophages, and Krt18 + Nucleus Pulposus (NP) cells were the major drivers of transcriptomic differences between Control and Injured cells. Gene ontology revealed that the most upregulated biological pathways were angiogenesis and T cell-related while wound healing and ECM regulation were downregulated. Pseudotime trajectory analyses revealed that IVD injury directed cells towards increased differentiation in all clusters, except for Krt18 + NP cells which remained in a less mature cell state. Saa2-High and Grem1-High MSCs populations shifted towards more differentiated IVD cells profiles with injury and localized distinctly within the IVD. This study revealed novel MSC populations with the potential to be leveraged for future IVD repair studies.

Cartilage↗
NASA NTRS1985

The role of cell size in density gradient electrophoretic separation of mouse leukemia cells according to position in the cell cycle

Cultured mouse leukemia cells line L5178Y were subjected to upward electrophoresis in a density gradient and the slower migrating cell populations were enriched in G2 cells. It is indicated that this cell line does not change electrophoretic mobility through the cell cycle. The possibility that increased sedimentation downward on the part of the larger G2 cells caused this separation was explored. Two different cell populations were investigated. The log phase population was found to migrate upward faster than the G2 population, and a similar difference between their velocities and calculated on the basis of a 1 um diameter difference between the two cell populations. The G2 and G1 enriched populations were isolated by Ficoll density gradient sedimentation. The bottom fraction was enriched in G2 cells and the top fraction was enriched with G1 cells, especially when compared with starting materials. The electrophoretic mobilities of these two cell populations did not differ significantly from one another. Cell diameter dependent migration curves were calculated and were found to be different. Families of migration curves that differ when cell size is considered as a parameter are predicted.

Plank, L. D.↗
DOE OSTI2023

Reassembly of Peptide Nanofibrils on Live Cell Surfaces Promotes Cell–Cell Interactions

Nature regulates cellular interactions through the cell-surface molecules and plasma membranes. Despite advances in cell-surface engineering with diverse ligands and reactive groups, modulating cell–cell interactions through scaffolds of the cell-binding cues remains a challenging endeavor. Here, we assembled peptide nanofibrils on live cell surfaces to present the ligands that bind to the target cells. Surprisingly, with the same ligands, reducing the thermal stability of the nanofibrils promoted cellular interactions. Characterizations of the system revealed a thermally induced fibril disassembly and reassembly pathway that facilitated the complexation of the fibrils with the cells. Using the nanofibrils of varied stabilities, the cell–cell interaction was promoted to different extents with free-to-bound cell conversion ratios achieved at low (31%), medium (54%), and high (93%) levels. Further, this study expands the toolbox to generate desired cell behaviors for applications in many areas and highlights the merits of thermally less stable nanoassemblies in designing functional materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS2024

DNA Break Clustering as a Predictor of Cell Death across Various Radiation Qualities: Influence of Cell Size, Cell Asymmetry, and Beam Orientation

Cosmic radiation, composed of high charge and energy (HZE) particles, causes cellular DNA damage that can result in cell death or mutation that can evolve into cancer. In this work, a cell death model is applied to several cell lines exposed to HZE ions spanning a broad range of linear energy transfer (LET) values. We hypothesize that chromatin movement leads to the clustering of multiple double strand breaks (DSB) within one radiation-induced foci (RIF). The survival probability of a cell population is determined by averaging the survival probabilities of individual cells, which is function of the number of pairwise DSB interactions within RIF. The simulation code RITCARD was used to compute DSB. Two clustering approaches were applied to determine the number of RIF per cell. RITCARD outputs were combined with experimental data from four normal human cell lines to derive the model parameters and expand its predictions in response to ions with LET ranging from ∼0.2keV/μmto∼3000keV/μm. Spherical and ellipsoidal nuclear shapes and two ion beam orientations were modeled to assess the impact of geometrical properties on cell death. The calculated average number of RIF per cell reproduces the saturation trend for high doses and high-LET values that is usually experimentally observed. The cell survival model generates the recognizable bell shape of LET dependence for the relative biological effectiveness (RBE). At low LET, smaller nuclei have lower survival due to increased DNA density and DSB clustering. At high LET, nuclei with a smaller irradiation area either because of a smaller size or a change in beam orientation have a higher survival rate due to a change in the distribution of DSB/RIF per cell. If confirmed experimentally, the geometric characteristics of cells would become a significant factor in predicting radiation-induced biological effects.

cell survival↗
DOE OSTI2020

Predicting cell-to-cell failure propagation and limits of propagation in lithium-ion cell stacks

Thermal runaway of lithium-ion batteries is a risk that is magnified when stacks of lithium-ion cells are used for large scale energy storage. When limits of propagation can be identified so that systems can be designed to prevent large scale cascading failure even if a failure does occur, these systems will be safer. This work addresses the prediction of cell-to-cell failure propagation and the propagation limits in lithium-ion cell stacks to better understand and identify safe designs. A thermal-runaway model is presented based on recent developments in thermochemical source terms. It is noted that propagating failure is characterized by temperatures above which calorimetry data is available. Results show high temperature propagating failure predictions are too rapid unless an intra-particle diffusion limit is included, introducing a Damköhler number limiter into the rate expression. This new model form is evaluated against cell-to-cell failure propagation where the end cell of a stack is forced into thermal runaway through a nail-induced short circuit. Limits of propagation for this configuration are identified. Results show cell-to-cell propagation predictions are consistent with measurements over a range of cell states of charge and with the introduction of metal plates between cells to add system heat capacity representative of structural members. This consistency extends from scenarios where propagation occurs through scenarios where propagation is prevented.

25 ENERGY STORAGE↗
DOE OSTI2026

Multimodal framework for the joint analysis of single-cell RNA and T cell receptor sequencing data predicts T cell response to cancer immunotherapy

T cell states are prognostic in different cancer types. Recent technologies enable joint profiling of T cell RNA and T cell receptor (TCR) sequences at single-cell resolution. Here we present the TCR-RNA Integrating Model (TRIM), a multi-modal variational autoencoder framework that integrates RNA-TCR data and predicts T cell clonality and transcriptional states. TRIM learns a shared representation of the data conditioned on patient, tissue source, and treatment timepoint. We applied TRIM to three independent datasets that included T cells collected before and after checkpoint inhibitor treatment, sourced either from blood and tumor biopsies in patients with head and neck squamous cell carcinoma and colorectal cancer, or from tumor and adjacent tissue in a pan-cancer dataset. In all settings, TRIM accurately predicted intra-tumor T cell clonal expansion and transcriptional status based on T cells from blood or normal tissue before treatment, demonstrating its utility in modeling multimodal T cell data and predicting T cell response to treatment and disease progression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Decoding crops one cell at a time: from cell atlases to single-cell genetics

Understanding the mechanisms underlying key agricultural traits remains a central challenge in crop research, but recent advances in technologies are providing powerful tools to address this issue. Among these, single-cell and spatial transcriptomics have revealed tissue heterogeneity and spatial organization, offering unique insights into cellular gene expression dynamics and the coordinated activity of multiple cell types. These approaches help uncover how specific cell types contribute to agricultural traits and refine candidate loci lists through integration with trait-associated loci. Additionally, single-cell and spatial transcriptomics have the potential to serve as cell-level readout platforms integrating cellular perturbations, enabling high-throughput discovery of causal relationships between genotype and gene expression at the cellular level in plants. Successful implementation will accelerate the identification of key genetic variants for crop improvement. Furthermore we review lessons learned from application of single-cell screening in mammalian cells, highlight major technical and biological barriers to its use in plants, and outline potential strategies to overcome these challenges. Together, the widespread application and integration of single-cell and spatial transcriptomics with other technologies enable not only the descriptive cataloging of cell states but also the causal interrogation of sequence functions and regulatory networks at cell type resolution, ultimately advancing gene function studies and accelerating crop improvement.

Cellular heterogeneity↗
DOE OSTI2025

Cell surface crowding is a tunable energetic barrier to cell-cell fusion

Abstract Cell-cell fusion is fundamental to processes such as muscle formation and viral infection. An essential step in fusion is close membrane apposition, but cell membranes are crowded with proteins, glycoproteins, and glycolipids, which must be cleared before a fusion pore can be nucleated. Here, we find that cell surface crowding reduces fusogenicity independent of how fusion is driven. We estimate that crowding presents an energetic barrier to membrane apposition on the scale of ~$${100k}_{{\mbox{B}}}T$$ 100 k B T , greater than that of bare membrane fusion alone. We show that increasing cell surface crowding reduces fusion efficiency of PEG-mediated and fusogen-mediated cell-cell fusion, as well as synthetic membranes under force. Interestingly, we find that differentiating myoblasts naturally decrease their surface crowding prior to fusion. In this work, we show that cell surface crowding presents an underappreciated biophysical barrier that may be tuned developmentally and could be targeted externally to control tissue-specific cell-cell fusion.

Science & Technology - Other Topics↗
DOE OSTI2023

Inference of cell type-specific gene regulatory networks on cell lineages from single cell omic datasets

Abstract Cell type-specific gene expression patterns are outputs of transcriptional gene regulatory networks (GRNs) that connect transcription factors and signaling proteins to target genes. Single-cell technologies such as single cell RNA-sequencing (scRNA-seq) and single cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq), can examine cell-type specific gene regulation at unprecedented detail. However, current approaches to infer cell type-specific GRNs are limited in their ability to integrate scRNA-seq and scATAC-seq measurements and to model network dynamics on a cell lineage. To address this challenge, we have developed single-cell Multi-Task Network Inference (scMTNI), a multi-task learning framework to infer the GRN for each cell type on a lineage from scRNA-seq and scATAC-seq data. Using simulated and real datasets, we show that scMTNI is a broadly applicable framework for linear and branching lineages that accurately infers GRN dynamics and identifies key regulators of fate transitions for diverse processes such as cellular reprogramming and differentiation.

59 BASIC BIOLOGICAL SCIENCES↗