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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Regulatory helix plays a key role in genetic ON-OFF switching for the 2’-deoxyguanosine sensing mRNA element

Transcriptional riboswitches, noncoding mRNA elements that operate in cis to regulate gene expression, have a promising potential in medicine, synthetic biology and directed evolution. They bind to cellular metabolites or metal ions with high specificity, leading to conformational rearrangements that facilitate the activation or premature termination of transcription for downstream genes. This elegant mechanism for feedback regulation of metabolic pathways has been identified in prokaryotes and a few in eukaryotes. Our chemical probing of the 2’-deoxyguanosine (2’-dG)-sensing riboswitch demonstrates that the overall conformational state of the full-length riboswitch (dGsw-fl) is unresponsive to the 2’-dG. Although binding proceeds as expected, dGsw-fl exclusively populates an OFF state of transcriptional inhibition. We chemically probed the structure of a known dGsw transcriptional intermediate (dGsw-int) to evaluate the possibility of a cotranscriptional regulatory role. Interestingly, apo dGsw-int adopts an alternative conformation in which a stable anti-terminator helix is formed, leading to an ON state where transcription can proceed. In the presence of 2’-dG, this anti-terminator helix is destabilized to produce a conformation reminiscent of the full-length, OFF-state dGsw. Using a fluorescence quenching assay, we demonstrate that binding 2’-dG to early transcriptional intermediates can inhibit the formation of the anti-terminator helix, locking dGsw in an OFF state. These data suggest that metabolite sensing occurs during a brief window of time between the synthesis of two transcriptional intermediates. Our studies indicate that dGsw does not function as a binary ON−OFF switch, but instead fine-tunes the transcription of downstream genes during RNA synthesis using key intermediates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Comments on “Failure analysis of corroded hydrogen-blended natural gas pipelines based on finite element analysis and genetic algorithm-back propagation neural network” [262 (2025) 111174]

This is a brief commentary paper to highlight and discuss the determination of hydrogen concentration in pipeline steel, effect of hydrogen embrittlement (HE) on the mechanical properties of the material, burst strength of corroded pipelines using finite element analysis (FEA) simulations, and curve-fit models for assessing remaining strength of X80 corroded pipelines for transporting hydrogen blended natural gas. Recently, Xie et al. [1] proposed a methodology to quantify the impact of HE on material properties and numerically determined burst pressure of X80 corroded pipelines. However, their HE quantification overestimated the degradation of tensile strength for hydrogen blending ratios beyond the original data range, and their FEA results of burst pressure are nonconservative. This work thus recharacterized the hydrogen concentration in the steel pipeline and the effect of HE on tensile strength, and then redetermined burst pressures for a set of typical corrosion defect cases considered by Xie et al. [1] based on an experimentally validated FEA modelling method. With the new FEA results, two empirical corrosion models were proposed for X80 corroded pipelines for hydrogen service. At zero hydrogen blending ratio, the novel empirical models predict burst pressures to be consistent with the industry-accepted corrosion models. Furthermore, both the numerical simulation method and the novel corrosion models are significant contributions to the pipeline industry and the hydrogen community. Application of these results will enhance the safety, reliability, and integrity of natural gas pipelines when used to transport hydrogen.

Burst pressure prediction↗
DOE OSTI2025

Reduction of Exciton Diffusion Length with Genetically Tuned Non-Photochemical Quenching in Plant Thylakoid Membranes

Non-photochemical quenching (NPQ) protects plants from excess light by dissipating excitation energy as heat. Limited exciton migration is a key feature of NPQ, reducing the energy flux to reaction centers; however, quantitative evidence for this mechanism in native thylakoid membranes has been lacking. Here, we investigate the correlation between NPQ activity and exciton diffusion length (LD) using Nicotiana benthamiana mutants with distinct NPQ capacities. NPQ under both light- and dark-acclimated conditions was quantified for each genotype via fluorescence lifetime snapshots, and exciton mobility was probed using transient absorption spectroscopy with exciton-exciton annihilation analysis. By comparing the relationship between chlorophyll fluorescence lifetime and LD across mutants, we observed that NPQ activation quantitatively limits the spatial range of exciton migration, thereby reducing the access to reaction centers. Our findings provide direct experimental evidence that NPQ modulates the dynamics of energy transport, advancing our understanding of photoprotective regulation in photosynthetic systems.

Diffusion↗
DOE OSTI2024

Applying MALDI-TOF MS to resolve morphologic and genetic similarities between two Dermacentor tick species of public health importance

Abstract Hard ticks (Acari: Ixodidae) have been historically identified by morphological methods which require highly specialized expertise and more recently by DNA-based molecular assays that involve high costs. Although both approaches provide complementary data for tick identification, each method has limitations which restrict their use on large-scale settings such as regional or national tick surveillance programs. To overcome those obstacles, the matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been introduced as a cost-efficient method for the identification of various organisms, as it balances performance, speed, and high data output. Here we describe the use of this technology to validate the distinction of two closely relatedDermacentortick species based on the development of the first nationwide MALDI-TOF MS reference database described to date. The dataset obtained from this protein-based approach confirms that tick specimens collected from United States regions west of the Rocky Mountains and identified previously asDermacentor variabilisare the recently described species,Dermacentor similis. Therefore, we propose that this integrative taxonomic tool can facilitate vector and vector-borne pathogen surveillance programs in the United States and elsewhere.

Science & Technology - Other Topics↗
DOE OSTI2025

Genetic control of morphological transitions in a coacervating protein template

Nature routinely exploits liquid–liquid phase separation (LLPS) of proteins to control the assembly and mineralization of hybrid materials. Here, we show that fusion of the Car9 silica-binding peptide to an elastin-like polypeptide (ELP) yields temperature- and sequence-programmable soft matter templates for the synthesis of silicified architectures ranging in size from nanometers to micrometers. Specifically, we demonstrate unprecedented control over the diameter of silica nanoparticles (SiNP) in the 30–60 nm range with 4 nm precision, show that a single arginine residue (R4) in the Car9 sequence underpins the transition from micelles to proteinosomes, and find that substitutions in other basic residues modulate electrostatic repulsion and solvation to enable access to kinetically trapped species. These structures, which include interconnected micelles, small (∼200 nm) and large (>5 µm) vesicles, are readily visualized by SEM imaging following silicification. Molecular dynamics (MD) simulations and AlphaFold predictions reveal that mutations in positively charged residues alter interfacial packing, hydration, and conformational freedom of the silica-binding segments. Overall, our results establish sequence and thermal energy as synergistic levers for morphological control across length scales using solid-binding ELPs and establish mineralization as a powerful tool to visualize the structure of dynamic soft matter assemblies.

hierarchy↗
DOE OSTI2026

Knowledge-guided learning with curated prior genetic biomarkers for robust model interpretation

Abstract Motivation Knowledge-guided learning offers effective and robust model training strategies in data-scarce settings by incorporating established domain knowledge, thereby enhancing generalization, robustness, and interpretability. By contrast, conventional deep learning approaches rely purely on data-driven learning, which can limit robust model interpretability, particularly in high-dimensional settings with limited size samples. In computational biology, knowledge-guided learning has primarily leveraged network- and structural-based knowledge, leading to biologically interpretable representations and enhanced predictive performance compared to conventional approaches. However, curated biomarkers, one of the most accessible forms of biological knowledge, remain largely unexplored within knowledge-guided paradigms. Results In this study, we propose a model-agnostic training paradigm, Biomarker-driven Explainable Prior-guided Learning (BioExPL), that can be applied to any neural networks that incorporates curated prior knowledge. BioExPL enforces neural networks to reflect curated biomarker priors in their latent representations through a novel knowledge-alignment loss. BioExPL consistently demonstrated significantly improved predictive performance and enhanced model interpretability with minimized computational overhead in simulation studies and intensive experiments on multiple cancer datasets. BioExPL not only integrates prior curated knowledge into the model but also accurately identifies unknown associated signals additionally. BioExPL is model-agnostic and domain-independent, enabling its integration into diverse neural network architectures. Availability and implementation The open-source is publicly available at: https://github.com/datax-lab/BioExPL.

Baek, Beomsu [Department of Computer Science, Univ↗
DOE OSTI2024

Genetically manipulated chloroplast stromal phosphate levels alter photosynthetic efficiency

Abstract The concentration of inorganic phosphate (Pi) in the chloroplast stroma must be maintained within narrow limits to sustain photosynthesis and to direct the partitioning of fixed carbon. However, it is unknown if these limits or the underlying contributions of different chloroplastic Pi transporters vary throughout the photoperiod or between chloroplasts in different leaf tissues. To address these questions, we applied live Pi imaging to Arabidopsis (Arabidopsis thaliana) wild-type plants and 2 loss-of-function transporter mutants: triose phosphate/phosphate translocator (tpt), phosphate transporter 2;1 (pht2;1), and tpt pht2;1. Our analyses revealed that stromal Pi varies spatially and temporally, and that TPT and PHT2;1 contribute to Pi import with overlapping tissue specificities. Further, the series of progressively diminished steady-state stromal Pi levels in these mutants provided the means to examine the effects of Pi on photosynthetic efficiency without imposing nutritional deprivation. ΦPSII and nonphotochemical quenching (NPQ) correlated with stromal Pi levels. However, the proton efflux activity of the ATP synthase (gH+) and the thylakoid proton motive force (pmf) were unaltered under growth conditions, but were suppressed transiently after a dark to light transition with return to wild-type levels within 2 min. These results argue against a simple substrate-level limitation of ATP synthase by depletion of stromal Pi, favoring more integrated regulatory models, which include rapid acclimation of thylakoid ATP synthase activity to reduced Pi levels.

54 ENVIRONMENTAL SCIENCES↗