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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
DOE OSTI2024

Photoluminescence Excitation Spectroscopy of Monolithic Perovskite/Silicon Tandem Solar Cells

The contributions of each subcell to the total photoluminescence (PL) spectrum of a monolithic perovskite/silicon tandem solar cell are distinguished using a variable wavelength excitation laser source. Here, in the results, a strong overlap of the PL spectrum is shown, originating from the sub‐bandgap region of the perovskite top cell with the emission from the silicon bottom cell, even with near‐infrared excitation wavelengths. Consequently, an excitation laser wavelength of at least 815 nm is required for a dominant PL signal from the silicon bottom cell, and a wavelength no longer than 750 nm is needed for a dominant PL signal from the perovskite top cell in the investigated tandem solar cell. Moreover, a shoulder in the sub‐bandgap emission of the perovskite top cell almost coincides with the PL response region of the silicon bottom cell, which can cause signal confusion in subcell characterization.

14 SOLAR ENERGY↗
DOE OSTI2024

Insight into the autoproteolysis mechanism of the RsgI9 anti‐σ factor from Clostridium thermocellum

Abstract Clostridium thermocellum is a potential microbial platform to convert abundant plant biomass to biofuels and other renewable chemicals. It efficiently degrades lignocellulosic biomass using a surface displayed cellulosome, a megadalton sized multienzyme containing complex. The enzymatic composition and architecture of the cellulosome is controlled by several transmembrane biomass‐sensing RsgI‐type anti‐σ factors. Recent studies suggest that these factors transduce signals from the cell surface via a conserved RsgI extracellular (CRE) domain (also called a periplasmic domain) that undergoes autoproteolysis through an incompletely understood mechanism. Here we report the structure of the autoproteolyzed CRE domain from the C. thermocellum RsgI9 anti‐σ factor, revealing that the cleaved fragments forming this domain associate to form a stable α/β/α sandwich fold. Based on AlphaFold2 modeling, molecular dynamics simulations, and tandem mass spectrometry, we propose that a conserved Asn‐Pro bond in RsgI9 autoproteolyzes via a succinimide intermediate whose formation is promoted by a conserved hydrogen bond network holding the scissile peptide bond in a strained conformation. As other RsgI anti‐σ factors share sequence homology to RsgI9, they likely autoproteolyze through a similar mechanism.

Takayesu, Allen↗
DOE OSTI2024

Insight into molecular basis and dynamics of full-length CRaf kinase in cellular signaling mechanisms

Raf kinases play key roles in signal transduction in cells for regulating proliferation, differentiation, and survival. Despite decades of research into functions and dynamics of Raf kinases with respect to other cytosolic proteins, understanding Raf kinases is limited by the lack of their full-length structures at the atomic resolution. Here, we present the first model of the full-length CRaf kinase obtained from artificial intelligence/machine learning algorithms with a converging ensemble of structures simulated by large-scale temperature replica exchange simulations. Our model is validated by comparing simulated structures with the latest cryo-EM structure detailing close contacts among three key domains and regions of the CRaf. Our simulations identify potentially new epitopes of intramolecule interactions within the CRaf and reveal a dynamical nature of CRaf kinases, in which the three domains can move back and forth relative to each other for regulatory dynamics. The dynamic conformations are then used in a docking algorithm to shed insight into the paradoxical effect caused by vemurafenib in comparison with a paradox breaker PLX7904. In this study, we propose a model of Raf-heterodimer/KRas-dimer as a signalosome based on the dynamics of the full-length CRaf.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Quantitative Bioluminescence Tomography-Guided Conformal Irradiation for Preclinical Radiation Research

Widely used cone beam computed tomography (CBCT)-guided irradiators in preclinical radiation research are limited to localize soft tissue target because of low imaging contrast. Knowledge of target volume is a fundamental need for radiation therapy (RT). Without such information to guide radiation, normal tissue can be overirradiated, introducing experimental uncertainties. This led us to develop high-contrast quantitative bioluminescence tomography (QBLT) for guidance. The use of a 3-dimensional bioluminescence signal, related to cell viability, for preclinical radiation research is one step toward biology-guided RT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Spatially Resolved Top-Down Proteomics of Tissue Sections Based on a Microfluidic Nanodroplet Sample Preparation Platform

Conventional proteomics measures the averaged signal from mixed cell populations or bulk tissues, leading to the dilution of significant changes in subpopulations of cells that might serve as important biomarkers. Recent developments in bottom-up proteomics have enabled spatial mapping of cellular heterogeneity in tissue microenvironments. However, bottom-up proteomics cannot precisely infer the abundance changes of intact proteins, which are presented as proteoforms. Herein, we described a spatially resolved top-down proteomics (TDP) platform for proteoform identification and quantification directly on thin tissue sections. The spatial TDP platform consisted of a nanoPOTS (nanodroplet Processing in One pot for Trace Samples)-based sample preparation system and an LCM (laser capture microdissection)-based cell isolation system. We improved the nanoPOTS sample preparation by adding benzonase in the extraction buffer to enhance the coverage of nucleus proteins. Using ~200 cultured cells as model samples, the improved approach increased proteoform identifications from 493 to 700; newly identified proteoforms primarily corresponded to nuclear proteins. To demonstrate the spatial TDP platform in tissue samples, we analyzed LCM-isolated tissue voxels from rat brain cortex and hypothalamus regions. We quantified 426 proteoforms by combining identifications from TopPIC and TDPortal with the quantitation from ProMex. Several proteoforms corresponding to the same gene exhibited mixed abundance profiles between two tissue regions, suggesting potential PTM-specific spatial distributions. The spatial TDP workflow has prospects for biomarker discovery at proteoform level from small tissue sections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Molecular Glue Discovery: Current and Future Approaches

The intracellular interactions of biomolecules can be maneuvered to redirect signaling, reprogram the cell cycle, or decrease infectivity using only a few dozen atoms. Such "molecular glues," which can drive both novel and known interactions between protein partners, represent an enticing therapeutic strategy. Here, we review the methods and approaches that have led to the identification of small-molecule molecular glues. We first classify current FDA-approved molecular glues to facilitate the selection of discovery methods. We then survey two broad discovery method strategies, where we highlight the importance of factors such as experimental conditions, software packages, and genetic tools for success. In conclusion, we hope that this curation of methodologies for directed discovery will inspire diverse research efforts targeting a multitude of human diseases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

GWAS supported by computer vision identifies large numbers of candidate regulators of in planta regeneration in Populus trichocarpa

Plant regeneration is an important dimension of plant propagation and a key step in the production of transgenic plants. However, regeneration capacity varies widely among genotypes and species, the molecular basis of which is largely unknown. Association mapping methods such as genome-wide association studies (GWAS) have long demonstrated abilities to help uncover the genetic basis of trait variation in plants; however, the performance of these methods depends on the accuracy and scale of phenotyping. To enable a large-scale GWAS of in planta callus and shoot regeneration in the model tree Populus, we developed a phenomics workflow involving semantic segmentation to quantify regenerating plant tissues over time. We found that the resulting statistics were of highly non-normal distributions, and thus employed transformations or permutations to avoid violating assumptions of linear models used in GWAS. We report over 200 statistically supported quantitative trait loci (QTLs), with genes encompassing or near to top QTLs including regulators of cell adhesion, stress signaling, and hormone signaling pathways, as well as other diverse functions. Our results encourage models of hormonal signaling during plant regeneration to consider keystone roles of stress-related signaling (e.g. involving jasmonates and salicylic acid), in addition to the auxin and cytokinin pathways commonly considered. The putative regulatory genes and biological processes we identified provide new insights into the biological complexity of plant regeneration, and may serve as new reagents for improving regeneration and transformation of recalcitrant genotypes and species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

FIRM image analysis: A machine learning workflow for quantifying extracellular matrix components from electron microscopy images

The extracellular matrix (ECM) is a complex network of biomolecules that plays an integral role in the structure, processes, and signaling mechanisms of cells and tissues. Identifying and quantifying changes in these matrix components provides insight into the mechanisms behind specific tissue remodeling processes; however, quantifying these changes is challenging due to difficult imaging conditions, complexity of the ECM, and the subtlety of these changes. Current imaging techniques allow us to visualize these critical remodeling events and developments in image analysis have employed a combination of analysis software and machine learning techniques to improve the efficiency and accuracy with which features are measured. Although image analysis has seen much improvement in recent years, there has been no technique developed to address ambiguity in feature edges in electron microscopy images. Presented here is a new machine learning-based workflow for the analysis of microscopy images named FIRM (Feature Identification from Raw Microscopy) that uses a random forest classifier to identify ECM features of interest and generate binary segmentation masks for quantification with ImageJ-FIJI. FIRM performed with an F1 score of 0.794 and greater than 80% accuracy for number and size of features detected. FIRM had similar deviation from the ground truth in the number of identified fibrils, fibril size, and size distributions when compared to human analyses. The results suggest that FIRM performs as well as manual analysis and requires a fraction of the time. This analysis technique is more efficient, eliminates user bias, and can be easily optimized to identify a variety of features, making it useful for any discipline requiring image analysis.

Science & Technology - Other Topics↗
DOE OSTI2022

Affordable Realtime Viral Detection: Demonstrated with SARS COV-2

The near real-time detection of airborne particles-of-interest is needed for avoiding current/future threats. The incorporation of imprinted particles into a micelle-based electrochemical cell produced a signal when brought into contact with particle analytes (such as SARS-COV-2), previously imprinted onto the structure. Nanoamp scales of signals were generated from what may’ve been individual virus-micelle interactions. The system showed selectivity when tested against similar size and morphology particles. The technology was compatible with airborne aerosol sampling techniques. Overall, the application of imprinted micelle technology could provide near real-time detection methods to a host of possible analytes of interest in the field.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Phloem Exudate Protein Profiles during Drought and Recovery Reveal Abiotic Stress Responses in Tomato Vasculature

Drought is the leading cause of agricultural yield loss among all abiotic stresses, and the link between water deficit and phloem protein contents is relatively unexplored. Here we collected phloem exudates from Solanum lycopersicum leaves during periods of drought stress and recovery. Our analysis identified 2558 proteins, the most abundant of which were previously localized to the phloem. Independent of drought, enrichment analysis of the total phloem exudate protein profiles from all samples suggests that the protein content of phloem sap is complex, and includes proteins that function in chaperone systems, branched-chain amino acid synthesis, trehalose metabolism, and RNA silencing. We observed 169 proteins whose abundance changed significantly within the phloem sap, either during drought or recovery. Proteins that became significantly more abundant during drought include members of lipid metabolism, chaperone-mediated protein folding, carboxylic acid metabolism, abscisic acid signaling, cytokinin biosynthesis, and amino acid metabolism. Conversely, proteins involved in lipid signaling, sphingolipid metabolism, cell wall organization, carbohydrate metabolism, and a mitogen-activated protein kinase are decreased during drought. Our experiment has achieved an in-depth profiling of phloem sap protein contents during drought stress and recovery that supports previous findings and provides new evidence that multiple biological processes are involved in drought adaptation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Seismoacoustic Monitoring of Pyroprocessing Equipment

With the projected increase in world nuclear capacity comes the hurdle of spent nuclear fuel. Pyroprocessing is one method to process irradiated fuel by using high temperatures and electrochemical steps to separate radioactive components. High temperatures, high radiation levels, and equipment confined to a heavily shielded hot cell are a few of the challenges introduced regarding safeguards for pyroprocessing. The first stage of the process utilizes an element chopper to cut irradiated fuel into smaller pieces, offering the potential to identify equipment operation through seismoacoustic monitoring. Eleven seismic and infrasound sensors were deployed at various locations and distances near a pyroprocessing hot cell to evaluate signals emitted from the chopper. Signals were processed using short-time Fourier transforms and manually scanned to locate chopping events. Operator logs were then collected for a ground truth comparison. Results indicate that both infrasound and seismic signals offer the ability to accurately measure this stage of pyroprocessing, though seismic signals are more prominent. Sensor locations are also evaluated to determine where the signal is detectable. This type of monitoring offers a method to aid in safeguards and proliferation detection by validating a pyroprocessing facility’s schedule and identifying activity that does not align with records.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

DYNC1H1 regulates NSCLC cell growth and metastasis by IFN-γ-JAK-STAT signaling and is associated with an aberrant immune response

Highlights: • DYNC1H1 is upregulated and its high expression predicted poor outcomes in NSCLC. • Loss of function of DYNC1H1 inhibits cell growth and metastasis of NSCLC cells in vitro. • DYNC1H1 knockdown inhibited metastasis of NSCLC cells in vivo. • DYNC1H1 loss of function suppresses IFN-γ-JAK-STAT signaling pathway in NSCLC. • DYNC1H1 expression is correlated with aberrant immune response in NSCLC indicated by analysis of TCGA immune data. It is urgent to identify new biomarkers and therapeutic targets to ameliorate the clinical prognosis of patients with lung cancer. The functional significance and molecular mechanism of dynein cytoplasmic 1 heavy chain 1 (DYNC1H1) in nonsmall cell lung cancer (NSCLC) progression is still elusive. In our current study, publicly available data and Western blotting experiments confirmed that DYNC1H1 expression was upregulated in lung cancer samples compared with noncancerous samples. Quantitative real-time PCR (qPCR) results indicated that high DYNC1H1 expression in lung cancer tissues was significantly associated with clinical tumor stage and distal metastasis; moreover, its high expression was negatively correlated with prognosis. Functional experiments demonstrated that DYNC1H1 loss of function caused a significant decrease in cell viability and cell proliferative ability, inhibition of the cell cycle, and promotion of both migration potential and invasion potential in vitro. Animal experiments by tail vein injection of lung cancer cells showed that DYNC1H1 knockdown significantly decreased lung cancer metastasis. Mechanistically, the results from a human protein array showed changes in the IFN-γ-JAK-STAT signaling pathway, and analysis of The Cancer Genome Atlas (TCGA) immune data demonstrated that disturbance of the immune microenvironment might be involved in the impaired growth and metastatic ability mediated by DYNC1H1 loss in NSCLC. DYNC1H1 might serve as a promising biological marker of prognosis and a potential clinical therapeutic target for patients with NSCLC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

A novel regulator of the fungal phosphate starvation response revealed by transcriptional profiling and DNA affinity purification sequencing

Cells must accurately sense and respond to nutrients to compete for resources and establish growth. Phosphate is a critical nutrient source necessary for signaling, energy metabolism, and synthesis of nucleic acids, phospholipids, and cellular metabolites. During phosphate limitation, fungi import phosphate from the environment and liberate phosphate from phosphate-containing molecules in the cell. In the model filamentous fungus Neurospora crassa, the phosphate starvation response is regulated by the conserved transcription factor NUC-1. The activity of NUC-1 is repressed by a complex of the cyclin-dependent kinase MDK-1 and the cyclin PREG when phosphate is plentiful. When phosphate is limiting, NUC-1 repression by MDK-1/PREG is relieved by the cyclin-dependent kinase inhibitor NUC-2. We investigated the global response of N. crassa to phosphate starvation. During phosphate starvation, NUC-1 directly activated the expression of genes encoding phosphatases, nucleases, and a phosphate transporter and directly repressed genes associated with the ribosome. Additionally, NUC-1 indirectly activated the expression of an uncharacterized transcription factor, which we named nuc-3. NUC-3 directly repressed the expression of genes involved in phosphate acquisition and liberation after an extended period of phosphate starvation. Additionally, NUC-3 directly repressed the expression of the cyclin-dependent kinase inhibitor nuc-2. Thus, through the combination of NUC-3 direct repression of genes in the phosphate starvation response and nuc-2, an activator of the phosphate starvation response, NUC-3 serves to act as a brake on the phosphate starvation response after an extended period of phosphate starvation. This braking mechanism could reduce transcription, a phosphate-intensive process, under conditions of extended phosphate limitation.IMPORTANCEFungi have evolved regulatory networks to respond to available nutrients. Phosphate is often a limiting nutrient for fungi that is critical for many cellular functions, including nucleic acid and phospholipid biosynthesis, cell signaling, and energy metabolism. The fungal response to phosphate limitation is important in interactions with plants and animals. We investigated the global transcriptional response to phosphate starvation and the role of a major transcriptional regulator, NUC-1, in the model filamentous fungus Neurospora crassa. Our data show that NUC-1 is a bifunctional transcription factor that directly activates phosphate acquisition genes, while directly repressing genes associated with phosphate-intensive processes. NUC-1 indirectly regulates an uncharacterized transcription factor, which we named nuc-3. NUC-3 directly represses phosphate acquisition genes and nuc-2, an activator of the phosphate starvation response, during extended periods of phosphate starvation. Thus, NUC-3 acts as a brake on the phosphate starvation response to reduce phosphate-intensive activities, like transcriptional activation, when phosphate starvation persists.

DNA affinity purification sequencing↗
DOE OSTI2020

Clostridioides difficile Toxin A Remodels Membranes and Mediates DNA Entry Into Cells to Activate Toll-Like Receptor 9 Signaling

Background & Aims: Clostridioides difficile toxin A (TcdA) activates the innate immune response. TcdA co-purifies with DNA. Toll-like receptor 9 (TLR9) recognizes bacterial DNA to initiate inflammation. We investigated whether DNA bound to TcdA activates an inflammatory response in murine models of C difficile infection via activation of TLR9. Methods: We performed studies with human colonocytes and monocytes and macrophages from wild-type and TLR9 knockout mice incubated with TcdA or its antagonist (ODN TTAGGG) or transduced with vectors encoding TLR9 or small-interfering RNAs. Cytokine production was measured with enzyme-linked immunosorbent assay. We studied a transduction domain of TcdA (TcdA 57-80 ), which was predicted by machine learning to have cell-penetrating activity and confirmed by synchrotron small-angle X-ray scattering. Intestines of CD1 mice, C57BL6J mice, and mice that express a form of TLR9 that is not activated by CpG DNA were injected with TcdA, TLR9 antagonist, or both. Enterotoxicity was estimated based on loop weight to length ratios. A TLR9 antagonist was tested in mice infected with C difficile. We incubated human colon explants with an antagonist of TLR9 and measured TcdA-induced production of cytokines. Results: The TcdA 57-80 protein transduction domain had membrane remodeling activity that allowed TcdA to enter endosomes. TcdA-bound DNA entered human colonocytes. TLR9 was required for production of cytokines by cultured cells and in human colon explants incubated with TcdA. TLR9 was required in TcdA-induced mice intestinal secretions and in the survival of mice infected by C difficile. Even in a protease-rich environment, in which only fragments of TcdA exist, the TcdA 57-80 domain organized DNA into a geometrically ordered structure that activated TLR9. Conclusions: TcdA from C difficile can bind and organize bacterial DNA to activate TLR9. TcdA and TcdA fragments remodel membranes, which allows them to access endosomes and present bacterial DNA to and activate TLR9. Rather than inactivating the ability of DNA to bind TLR9, TcdA appears to chaperone and organize DNA into an inflammatory, spatially periodic structure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Quantitative modeling of carcinogenesis induced by single beams or mixtures of space radiations using targeted and non-targeted effects

Abstract Ionizing radiations encountered by astronauts on deep space missions produce biological damage by two main mechanisms: (1) Targeted effects (TE) due to direct traversals of cells by ionizing tracks. (2) Non-targeted effects (NTE) caused by release of signals from directly hit cells. The combination of these mechanisms generates non-linear dose response shapes, which need to be modeled quantitatively to predict health risks from space exploration. Here we used a TE + NTE model to analyze data on APC (1638N/+) mouse tumorigenesis induced by space-relevant doses of protons, 4 He, 12 C, 16 O, 28 Si or 56 Fe ions, or γ rays. A customized weighted Negative Binomial distribution was used to describe the radiation type- and dose-dependent data variability. This approach allowed detailed quantification of dose–response shapes, NTE- and TE-related model parameters, and radiation quality metrics (relative biological effectiveness, RBE, and radiation effects ratio, RER, relative to γ rays) for each radiation type. Based on the modeled responses for each radiation type, we predicted the tumor yield for a Mars-mission-relevant mixture of these radiations, using the recently-developed incremental effect additivity (IEA) synergy theory. The proposed modeling approach can enhance current knowledge about quantification of space radiation quality effects, dose response shapes, and ultimately the health risks for astronauts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Single-cell RNA-seq revealed diverse cell types in the mouse placenta at mid-gestation

The mammalian placenta consists of a set of cells to ensure normal placental functions throughout gestation. Dysfunctional placentae are considered as the origin of a series of pregnancy complications. Therefore, it is urgent for detailed information about the molecular recipes of the cell types within the normal placenta. In the past years, gene expression analysis via single-cell RNA-seq (scRNA-seq) offers opportunities to identify new cell types in a variety of organs and tissues. In this study, scRNA-seq was used to explore the cell heterogeneity within the E10.5 mouse placenta and unravel their discrepancies in cell composition and communications. We identified sixteen cell clusters, including some cell clusters that originated from the maternal tissue. Moreover, we traced the developmental trajectories of trophoblasts and Hofbauer-like cells. Further analysis revealed cell connections between the endothelial cells and pericytes, syncytiotrophoblasts, as well as decidual cells. Besides, we highlighted several signaling pathways, such as the EGF, FGF, canonical, and non-canonical WNT signaling pathways, which mediated the potential crosstalk between different cell types within placenta. Our research provides an in-depth understanding of placental development, cellular composition, and communications at the maternal-fetal interface.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Oxygen Vacancy Evolution at Li x V 2 O 5 /LiPON Solid State Electrochemical Interfaces Using Depth Resolved Cathodoluminescence Spectroscopy

The formation of oxygen vacancies at buried LiPON/ Li x V 2 O 5 interfaces has been observed on a near-nanometer scale and nondestructively using depth-resolved cathodoluminescence spectroscopy (DRCLS) and interfacial markers. Before electrochemical cycling, as-deposited LiPON/Li x V 2 O 5 exhibits a 1.6 eV defect optical emission, which density functional theory calculations identify as originating from oxygen vacancies. This defect appears first within a few nanometers of the buried LiPON/Li x V 2 O 5 interface without cycling, indicating that spontaneous O diffusion from the Li x V 2 O 5 lattice into LiPON may have caused these interface-localized oxygen vacancy defects. DRCLS measured the intensity and spatial distribution of this oxygen vacancy signal as a function of electrochemical cycling in a LiPON/Li x V 2 O 5 half-cell, showing oxygen vacancy signal increasing and moving deeper into the electrode with increased cycle number. Significant electrochemical irreversibility was also observed, with poor Coulombic efficiency and a 15% drop in capacity over 50 cycles. Theoretical simulations predict that the presence of oxygen vacancies increases the energy barrier for lithium diffusion significantly, indicating that this aggregation of oxygen vacancies could be another battery degradation mechanism accompanying lithiation induced phase changes.

36 MATERIALS SCIENCE↗