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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Investigating the role of adipose tissue in mobility and aging: design and methods of the Adipose Tissue ancillary to the Study of Muscle, Mobility, and Aging (SOMMA-AT)

Background Age-related changes in adipose tissue affect chronic medical diseases and mobility disability but mechanism remains poorly understood. The goal of this study is to define methods for phenotyping unique characteristics of adipose tissue from older adults. Methods Older adults enrolled in study of muscle, mobility, and aging selected for the adipose tissue ancillary (SOMMA-AT; N = 210, 52.38% women, 76.12 ± 4.37 years) were assessed for regional adiposity by whole-body magnetic resonance (AMRA) and underwent a needle-aspiration biopsy of abdominal subcutaneous adipose tissue (ASAT). ASAT biopsies were flash frozen, fixed, or processed for downstream applications and deposited at the biorepository. Biopsy yields, qualitative features, adipocyte sizes, and concentration of adipokines secreted in ASAT explant conditioned media were measured. Inter-measure Spearman correlations were determined. Results Regional, but not total, adiposity differed by sex: women had greater ASAT mass (8.20 ± 2.73 kg, p < .001) and biopsy yield (3.44 ± 1.81 g, p < .001) than men (ASAT = 5.95 ± 2.30 kg, biopsy = 2.30 ± 1.40 g). ASAT mass correlated with leptin (r = 0.54, p < .001) and not resistin (p = .248) and adiponectin (p = .353). Adipocyte area correlated with ASAT mass (r = 0.34, p < .001), BMI (r = 0.33, p < .001), adiponectin (r = −0.22, p = .005) and leptin (r = 0.18, p = .024) but not with resistin (p = .490). Conclusion In addition to the detailed ASAT biopsy processing in this report, we found that adipocyte area correlated with ASAT mass, and both measures related to some key adipokines in the explant conditioned media. In conclusion, these results, methods, and biological repositories underscore the potential of this unique cohort to impact the understanding of aging adipose biology on disease, disability, and other aging tissues.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

The First Virtual Human Global Summit: Prepublication Meeting Report

This is the prepublication report for the First Virtual Human Global Summit held in October 2023. Organized collaboratively by Frederick National Laboratory for Cancer Research, Brookhaven National Laboratory, University College London, and Eviden, the 2023 Virtual Human Global Summit convened global thought leaders to bring together multiple perspectives across domains and organizations. The intent of the Summit was to foster collaboration among key leaders internationally whose combined efforts are required to advance patient-focused precision medicine through medical digital twins. Participants represented cancer and biomedical research, industry, infrastructure, clinical research, community health, non-profit organizations, government, and general public interests. The Summit included over 80 attendees across three continents including native American tribes. The Summit was held to share insights about the state of the art for medical digital twins, provide motivating opportunities and identify key challenges along the path to improved health and wellness through virtual human models and personalized digital twins. The Summit included sessions emphasizing the primary areas of research, infrastructure, clinical application, government support, and adoption/sustainability. Several examples of digital twins were referenced or mentioned through the course of the Summit including digital twin approaches in cancer, radiation oncology, molecular scale digital twins, diabetes, and sepsis. The summit report includes perspectives on the current state, challenges and guidance across research, infrastructure, clinical translation and community adoption, as well as multiple key insights from industry perspectives.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

LUCID Thrust 1 - Dataset Identification and Biodata Catalog Creation

The LUCID DOE consortium, part of the Department of Energy’s Biological and Environmental Research (BER) program, advances Low Dose Radiation (LDR) research through multidisciplinary efforts across seven key thrusts. This document focuses on Thrust 1, which centers on the creation of curated multimodal population health datasets and supports broader efforts within the LUCID program, including AI-based hypothesis generation, experimental design, and the study of LDR-induced health risks. Specifically, it describes the identification and cataloging of Thrust 1’s curated LDR datasets and biodata, emphasizing their critical role in supporting various research thrusts within the consortium, with potential applications in healthcare and public policy. In addition, the document includes an evaluation of three Large Language Models (LLMs)—GPT-4, SOLAR-10B, and Mixtral-8x7B—based on their ability to extract features from 25 LDR studies. The results indicate that GPT-4 performed the best, while Mixtral-8x7B demonstrated limited knowledge. Overall, this work advances understanding in radiation protection, risk assessment, and medical treatments, while providing valuable resources for researchers, educators, and policymakers.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2025

Results of a Geant4 benchmarking study for bio‐medical applications, performed with the G4‐Med system

Geant4, a Monte Carlo Simulation Toolkit extensively used in bio-medical physics, is in continuous evolution to include newest research findings to improve its accuracy and to respond to the evolving needs of a very diverse user community. In 2014, the G4-Med benchmarking system was born from the effort of the Geant4 Medical Simulation Benchmarking Group, to benchmark and monitor the evolution of Geant4 for medical physics applications. The G4-Med system was first described in our Medical Physics Special Report published in 2021. Results of the tests were reported for Geant4 10.5. Purpose In this work, we describe the evolution of the G4-Med benchmarking system. Methods The G4-Med benchmarking suite currently includes 23 tests, which benchmark Geant4 from the calculation of basic physical quantities to the simulation of more clinically relevant set-ups. New tests concern the benchmarking of Geant4-DNA physics and chemistry components for regression testing purposes, dosimetry for brachytherapy with a 125 I source, dosimetry for external x-ray and electron FLASH radiotherapy, experimental microdosimetry for proton therapy, and in vivo PET for carbon and oxygen beams. Regression testing has been performed between Geant4 10.5 and 11.1. Finally, a simple Geant4 simulation has been developed and used to compare Geant4 EM physics constructors and physics lists in terms of execution times. Results In summary, our EM tests show that the parameters of the multiple scattering in the Geant4 EM constructor G4EmStandardPhysics_option3 in Geant4 11.1, while improving the modeling of the electron backscattering in high atomic number targets, are not adequate for dosimetry for clinical x-ray and electron beams. Therefore, these parameters have been reverted back to those of Geant4 10.5 in Geant4 11.2.1. The x-ray radiotherapy test shows significant differences in the modeling of the bremsstrahlung process, especially between G4EmPenelopePhysics and the other constructors under study (G4EmLivermorePhysics, G4EmStandardPhysics_option3, and G4EmStandardPhysics_option4). These differences will be studied in an in-depth investigation within our Group. Improvement in Geant4 11.1 has been observed for the modeling of the proton and carbon ion Bragg peak with energies of clinical interest, thanks to the adoption of ICRU90 to calculate the low energy proton stopping powers in water and of the Linhard–Sorensen ion model, available in Geant4 since version 11.0. Nuclear fragmentation tests of interest for carbon ion therapy show differences between Geant4 10.5 and 11.1 in terms of fragment yields. In particular, a higher production of boron fragments is observed with Geant4 11.1, leading to a better agreement with reference data for this fragment. Conclusions Based on the overall results of our tests, we recommend to use G4EmStandardPhysics_option4 as EM constructor and QGSP_BIC_HP with G4EmStandardPhysics_option4, for hadrontherapy applications. The Geant4-DNA physics lists report differences in modeling electron interactions in water, however, the tests have a pure regression testing purpose so no recommendation can be formulated.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Acoustics at the nanoscale (nanoacoustics): A comprehensive literature review. Part II: Nanoacoustics for biomedical imaging and therapy

We report in the past decade, acoustics at the nanoscale (i.e., nanoacoustics) has evolved rapidly with continuous and substantial expansion of capabilities and refinement of techniques. Motivated by research innovations in the last decade, for the first time, recent advancements of acoustics-associated nanomaterials/nanostructures and nanodevices for different applications are outlined in this comprehensive review, which is written in two parts. As part II of this two-part review, this paper concentrates on nanoacoustics in biomedical imaging and therapy applications, including molecular ultrasound imaging, photoacoustic imaging, ultrasound-mediated drug delivery and therapy, and photoacoustic drug delivery and therapy. Firstly, the recent developments of nanosized ultrasound and photoacoustic contrast agents as well as their various imaging applications are examined. Secondly, different types of nanomaterials/nanostructures as nanocarriers for ultrasound and photoacoustic therapies are discussed. Finally, a discussion of challenges and future research directions are provided for nanoacoustics in medical imaging and therapy.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Protein Data Bank (PDB): Fifty-three years young and having a transformative impact on science and society

This review article describes the co-evolution of structural biology as a discipline and the Protein Data Bank (PDB), established in 1971 as the first open-access data resource in biology by like-minded structural scientists. As the PDB archive grew in size and scope to encompass macromolecular crystallography, NMR spectroscopy, and cryo-electron microscopy, new technologies were developed to ingest, validate, curate, store, and distribute the information. Community engagement ensured that the needs of structural biologists (data depositors) and data consumers were met. Today, the archive houses more than 230,000 experimentally determined structures of proteins, nucleic acids, and macromolecular machines and their complexes with one another and small-molecule ligands. Aggregate costs of PDB data preservation are ~1% of the cost of structure determination. The enormous impact of PDB data on basic and applied research and education across the natural and medical sciences is presented and highlighted with illustrative examples. Enablement of de novo protein structure prediction (AlphaFold2, RoseTTAfold, OpenFold, etc.) is the most widely appreciated benefit of having a corpus of rigorously validated, expertly curated 3D biostructure data.

bioinformatics↗
DOE OSTI2024

Monte Carlo Simulation with CAD Interface for Calculation of 3D Maps of Residual Dose (CRADA)

Objective: To develop an easy-to-use software application to predict and mitigate radiation effects in research environment, space instruments, nuclear plants and medical facilities and help nonproliferation and national security efforts. Tech-X will develop standalone software libraries and command-line tools for ( 1) translating CAD into tessellated surfaces and tetrahedral meshes in GDML (for Geant4 and MARS 15), ROOT (for MARS 15) and HDF5 (for compact representation and for the visualization) formats, (2) healing CAD geometries to make them suitable for Monte Carlo simulations; (3) creating uniform and variable Cartesian and cylindrical meshes for detailed scoring; and ( 4) efficient Monte Carlo navigation in CAD geometries. JLAB will finish automation of simulations of residual dose in CAD geometries and integrate Tech-X software into Geant4 and MARS15. Finally, Tech-X will develop a Graphical User Interface to set up and heal CAD geometries, create input files, run and visualize simulations for residual dose. This application will run on local desktops, local and remote clusters and supercomputers and will be made available through public clouds, such as Amazon Web Services.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

The United States Department of Energy and National Institutes of Health Collaboration: Medical Care Advances via Discovery in Physical Sciences

Over several months, representatives from the U.S. Department of Energy (DOE) Office of Science and National Institutes of Health (NIH) had a number of meetings that lead to the conclusion that innovations in the Nation's health care could be realized by more directed interactions between NIH and DOE. It became clear that the expertise amassed and instrumentation advances developed at the DOE physical science laboratories to enable cutting-edge research in particle physics could also feed innovation in medical healthcare. To meet their scientific mission, the DOE laboratories created advances in such technologies as particle beam generation, radioisotope production, high-energy particle detection and imaging, superconducting particle accelerators, superconducting magnets, cryogenics, high-speed electronics, artificial intelligence, and big data. To move forward, NIH and DOE initiated the process of convening a joint work- shop which occurred on July 12th and 13th, 2021. Here, this Special Report presents a summary of the findings of the collaborative workshop and introduces the goals of the next one.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Laser-driven x-ray and proton micro-source and application to simultaneous single-shot bi-modal radiographic imaging

Radiographic imaging with x-rays and protons is an omnipresent tool in basic research and applications in industry, material science and medical diagnostics. The information contained in both modalities can often be valuable in principle, but difficult to access simultaneously. Laser-driven solid-density plasma-sources deliver both kinds of radiation, but mostly single modalities have been explored for applications. Their potential for bi-modal radiographic imaging has never been fully realized, due to problems in generating appropriate sources and separating image modalities. Here, we report on the generation of proton and x-ray micro-sources in laser-plasma interactions of the focused Texas Petawatt laser with solid-density, micrometer-sized tungsten needles. We apply them for bi-modal radiographic imaging of biological and technological objects in a single laser shot. Thereby, advantages of laser-driven sources could be enriched beyond their small footprint by embracing their additional unique properties, including the spectral bandwidth, small source size and multi-mode emission.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

2D perovskite-based high spatial resolution X-ray detectors

Abstract X-ray radiography is the most widely used imaging technique with applications encompassing medical and industrial imaging, homeland security, and materials research. Although a significant amount of research and development has gone into improving the spatial resolution of the current state-of-the-art indirect X-ray detectors, it is still limited by the detector thickness and microcolumnar structure quality. This paper demonstrates high spatial resolution X-ray imaging with solution-processable two-dimensional hybrid perovskite single-crystal scintillators grown inside microcapillary channels as small as 20 µm. These highly scalable non-hygroscopic detectors demonstrate excellent spatial resolution similar to the direct X-ray detectors. X-ray imaging results of a camera constructed using this scintillator show Modulation Transfer Function values significantly better than the current state-of-the-art X-ray detectors. These structured detectors open up a new era of low-cost large-area ultrahigh spatial resolution high frame rate X-ray imaging with numerous applications.

2D perovskite↗
DOE OSTI2025

Incubating advances in integrated photonics with emerging sensing and computational capabilities

As photonic technologies grow in multidimensional aspects, integrated photonics holds a unique position and continuously presents enormous possibilities for research communities. Applications include data centers, environmental monitoring, medical diagnosis, and highly compact communication components, with further possibilities continuously growing. Herein, we review state-of-the-art integrated photonic on-chip sensors that operate in the visible to mid-infrared wavelength region on various material platforms. Among the different materials, architectures, and technologies leading the way for on-chip sensors, we discuss the optical sensing principles that are commonly applied to biochemical and gas sensing. Our focus is on passive optical waveguides, including dispersion-engineered metamaterial-based structures, which are essential for enhancing the interaction between light and analytes in chip-scale sensors. We harness a diverse array of cutting-edge sensing technologies, heralding a revolutionary on-chip sensing paradigm. Our arsenal includes refractive-index-based sensing, plasmonics, and spectroscopy, which forge an unparalleled foundation for innovation and precision. Furthermore, we include a brief discussion of recent trends and computational concepts, incorporating Artificial Intelligence & Machine Learning (AI/ML) and deep learning approaches over the past few years to improve the qualitative and quantitative analysis of sensor measurements.

Jain, Sourabh (ORCID:0000000279923275)↗
DOE OSTI2023

FrESCO: Framework for Exploring Scalable Computational Oncology

The National Cancer Institute (NCI) monitors population level cancer trends as part of its Surveillance, Epidemiology, and End Results (SEER) program. This program consists of state or regional level cancer registries which collect, analyze, and annotate cancer pathology reports. From these annotated pathology reports, each individual registry aggregates cancer phenotype information from electronic health records. This data is then used to create summary statistics about cancer incidence and mortality to facilitate population health monitoring. Extracting phenotypic information from these reports is a labor intensive task, requiring specialized knowledge about the reports and cancer. Automating the information extraction process from cancer pathology reports has the potential to improve data quality by extracting information in a consistent manner across registries. It can also improve patient outcomes by reducing the time from diagnosis, enabling rapid case ascertainment for clinical trials. Here we present FrESCO, a modular deep-learning natural language processing (NLP) library initially designed for extracting pathology information from clinical text documents. This repository is not solely limited to clinical medical text, but may also be used by researchers just getting started with NLP methods and those looking for a robust solution for their classification problems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Developing a Facility NMAC Plan

The table presented below suggests the basic information that should be covered in a facility NMAC Plan for an NMAC program that is designed for nuclear security. The topics are appropriate for and should be addressed by all facilities in their NMAC Plans. They are appropriate for NMAC Plans for nuclear power plants, research reactors, fuel manufacturing facilities, facilities that produce medical isotopes, and other facilities. The difference is in the intensity with which the various measures are applied and the thoroughness of the description of the application (i.e., the program requirements). The robustness of a facility NMAC program and the content of its NMAC Plan should be graded in accordance with the type of facility and the category of its nuclear material.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

The effect of anxiety on sleep disorders in medical students: a moderated mediation model

The relationship between anxiety and sleep disorders is a key research topic in the academic community. However, evidence on the mechanism through which anxiety influences sleep disorders remains limited. The purpose of this study was to investigate the roles of flourishing and neuroticism in the mechanism through which anxiety influences sleep disorders in medical students. We constructed a moderated mediation model and tested the mediating role of flourishing and the moderating role of neuroticism in medical college students. The results showed that: (1) anxiety was significantly and positively related to sleep disorders and significantly and negatively related to flourishing; flourishing was significantly and negatively related to sleep disorders; neuroticism was significantly and positively related to sleep disorders; (2) flourishing had a mediation effect on the relationship between anxiety and sleep disorders; (3) neuroticism moderated the process through which flourishing mediated the effect of anxiety on sleep disorders. Our research expands the literature on the mechanism underlying the effects of anxiety on sleep disorders and provides insights into the potential prevention and intervention of sleep and emotional problems in medical students.

Yu, Chuang↗
DOE OSTI2022

Evaluation Challenges for the Application of Extended Reality Devices in Medicine

Augmented and virtual reality devices are being actively investigated and implemented for a wide range of medical uses. However, significant gaps in the evaluation of these medical devices and applications hinder their regulatory evaluation. Addressing these gaps is critical to demonstrating the devices’ safety and effectiveness. We outline the key technical and clinical evaluation challenges discussed during the US Food and Drug Administration’s public workshop, “Medical Extended Reality: Toward Best Evaluation Practices for Virtual and Augmented Reality in Medicine” and future directions for evaluation method development. Evaluation challenges were categorized into several key technical and clinical areas. Finally, we highlight current efforts in the standards communities and illustrate connections between the evaluation challenges and the intended uses of the medical extended reality (MXR) devices. Participants concluded that additional research is needed to assess the safety and effectiveness of MXR devices across the use cases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Advances in metal–organic framework-based hydrogel materials: preparation, properties and applications

Although metal–organic frameworks (MOFs) with intriguing physiochemical properties have recently attracted increasing attention of researchers, MOFs have not adequately achieved various applications due to their instability and unsatisfactory processability. Hence, MOF-based composites as well as structurally novel MOFs have been established to solve this challenge. Recently, some efforts have been made for the development of MOF-based hydrogels. They exhibit excellent properties compared to initial MOFs in many ways (e.g., mechanical strength, absorption capacity and total pore volume). In this review, the up-to-date research progress of MOF-based hydrogels will be briefly summarized. Here, we mainly focus on expounding the classification of MOF-based hydrogels and their related synergistic effects. As to details, we will provide a conspectus of laconic and latest approaches for the synthesis of MOF-based hydrogels, focusing on composite systems, mechanism research, and stability. In addition, the applications of MOF-based hydrogels have been widely discussed, particularly in the environmental, energy and medical aspects. It is hoped that the detailed description of this review can help researchers working on MOF-based hydrogels to develop more novel composite materials and investigate their wider application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The Suisun Summit 2022: Emerging Themes and Open Questions in qEEG and Neurotherapies

The Suisun Summit 2022 was a gathering of 70 clinicians, educators, and researchers in quantitative electroencephalography and neurofeedback. During this 5-day event, several themes emerged in talks or discussion groups: EEG/qEEG Reading Skills; Medication Effects and Pharmaco-EEG; Technological Advancements; Emerging Concerns; and Growing Community Prestige through Research. Participants were asked to summarize what they believed to be the most important messages from the event to share with colleagues who were not in attendance, resulting in this review. A unifying concept for all the themes was a desire for higher quality, standardized EEG/qEEG education that provides depth as well as breadth. Models of clinical care that encourage open communication with prescribers and functional medicine specialists were strongly emphasized. Abstracts from all presentations are attached in Addendum B.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Low responsiveness of machine learning models to critical or deteriorating health conditions

Machine learning (ML) based mortality prediction models can be immensely useful in intensive care units. Such a model should generate warnings to alert physicians when a patient’s condition rapidly deteriorates, or their vitals are in highly abnormal ranges. Before clinical deployment, it is important to comprehensively assess a model’s ability to recognize critical patient conditions. We develop multiple medical ML testing approaches, including a gradient ascent method and neural activation map. We systematically assess these machine learning models’ ability to respond to serious medical conditions using additional test cases, some of which are time series. Guided by medical doctors, our evaluation involves multiple machine learning models, resampling techniques, and four datasets for two clinical prediction tasks. We identify serious deficiencies in the models’ responsiveness, with the models being unable to recognize severely impaired medical conditions or rapidly deteriorating health. For in-hospital mortality prediction, the models tested using our synthesized cases fail to recognize 66% of the injuries. In some instances, the models fail to generate adequate mortality risk scores for all test cases. Our study identifies similar kinds of deficiencies in the responsiveness of 5-year breast and lung cancer prediction models. Using generated test cases, we find that statistical machine-learning models trained solely from patient data are grossly insufficient and have many dangerous blind spots. Most of the ML models tested fail to respond adequately to critically ill patients. How to incorporate medical knowledge into clinical machine learning models is an important future research direction.

60 APPLIED LIFE SCIENCES↗