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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Disruption of electrostatic contacts in the HNH nuclease from a thermophilic Cas9 rewires allosteric motions and enhances high-temperature DNA cleavage

Allosteric signaling within multidomain proteins is a driver of communication between spatially distant functional sites. Understanding the mechanism of allosteric coupling in large multidomain proteins is the most promising route to achieving spatial and temporal control of the system. The recent explosion of CRISPR-Cas9 applications in molecular biology and medicine has created a need to understand how the atomic level protein dynamics of Cas9, which are the driving force of its allosteric crosstalk, influence its biophysical characteristics. In this study, we used a synergistic approach of nuclear magnetic resonance (NMR) and computation to pinpoint an allosteric hotspot in the HNH domain of the thermostable GeoCas9. We show that mutation of K597 to alanine disrupts a salt-bridge network, which in turn alters the structure, the timescale of allosteric motions, and the thermostability of the GeoHNH domain. This homologous lysine-to-alanine mutation in the extensively studied mesophilic S. pyogenes Cas9 similarly alters the dynamics of the SpHNH domain. We have previously demonstrated that the alteration of allostery via mutations is a source for the specificity enhancement of SpCas9 (eSpCas9). Hence, this may also be true in GeoCas9.

Chemistry↗
DOE OSTI2023

Support for Students, Postdoctoral Fellows and Trainees to Attend Radiochemistry-Related Symposia at Pacifichem 2020

This project was undertaken to help meet the need for training personnel who will be involved in professional careers requiring knowledge of radiochemistry, such as those working in radionuclide production, and in biological, industrial, medical and environmental fields that use radionuclides in their work. The goal of the project was to provide financial assistance to students and trainees from US academic and government institutions to attend selected radiochemistry related symposia at the Pacifichem 2020 meeting, which was to be held in Honolulu, Hawaii in December 2020. The funding, meant to provide a portion of an awardee’s travel cost, was specifically directed at awardees attendance to the following symposia: #190, Advancements in Isotope production-Providing Important Materials for Research and Applications; #180, Advancements in the Chemistry of Targeted Alpha Therapy, and #178, The Chemistry of 18 F, 11 C and Radiometal-based Probes for Molecular Imaging & Precision Medicine. It was/is believed that attendance of students/postdocs at the meeting would point out the critical role radiochemistry and radionuclides can have in the development of future diagnostic and therapeutic agents which would stimulate student interest in radiochemistry, and thus, provide support for making, or an impetus to make, this technical area a career choice.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
NASA NTRS2012

NASA Tech Briefs, March 2012

The topics include: 1) Spectral Profiler Probe for In Situ Snow Grain Size and Composition Stratigraphy; 2) Portable Fourier Transform Spectroscopy for Analysis of Surface Contamination and Quality Control; 3) In Situ Geochemical Analysis and Age Dating of Rocks Using Laser Ablation-Miniature Mass Spectrometer; 4) Physics Mining of Multi-Source Data Sets; 5) Photogrammetry Tool for Forensic Analysis; 6) Connect Global Positioning System RF Module; 7) Simple Cell Balance Circuit; 8) Miniature EVA Software Defined Radio; 9) Remotely Accessible Testbed for Software Defined Radio Development; 10) System-of-Systems Technology-Portfolio-Analysis Tool; 11) VESGEN Software for Mapping and Quantification of Vascular Regulators; 12) Constructing a Database From Multiple 2D Images for Camera Pose Estimation and Robot Localization; 13) Adaption of G-TAG Software for Validating Touch and Go Asteroid Sample Return Design Methodology; 14) 3D Visualization for Phoenix Mars Lander Science Operations; 15) RxGen General Optical Model Prescription Generator; 16) Carbon Nanotube Bonding Strength Enhancement Using Metal Wicking Process; 17) Multi-Layer Far-Infrared Component Technology; 18) Germanium Lift-Off Masks for Thin Metal Film Patterning; 19) Sealing Materials for Use in Vacuum at High Temperatures; 20) Radiation Shielding System Using a Composite of Carbon Nanotubes Loaded With Electropolymers; 21) Nano Sponges for Drug Delivery and Medicinal Applications; 22) Molecular Technique to Understand Deep Microbial Diversity; 23) Methods and Compositions Based on Culturing Microorganisms in Low Sedimental Fluid Shear Conditions; 24) Secure Peer-to-Peer Networks for Scientific Information Sharing; 25) Multiplexer/Demultiplexer Loading Tool (MDMLT); 26) High-Rate Data-Capture for an Airborne Lidar System; 27) Wavefront Sensing Analysis of Grazing Incidence Optical Systems; 28) Foam-on-Tile Damage Model; 29) Instrument Package Manipulation Through the Generation and Use of an Attenuated-Fluent Gas Fold; 30) Multicolor Detectors for Ultrasensitive Long-Wave Imaging Cameras; 31) Lunar Reconnaissance Orbiter (LRO) Command and Data Handling Flight Electronics Subsystem; and 32) Electro-Optic Segment-Segment Sensors for Radio and Optical Telescopes.

Source record↗
DOE OSTI2021

A multimodal and integrated approach to interrogate human kidney biopsies with rigor and reproducibility: guidelines from the Kidney Precision Medicine Project

Comprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate three-dimensional (3-D) molecular atlases of healthy and diseased kidney biopsies by using multiple state-of-the-art omics and imaging technologies across several institutions. Obtaining rigorous and reproducible results from disparate methods and at different sites to interrogate biomolecules at a single-cell level or in 3-D space is a significant challenge that can be a futile exercise if not well controlled. Here we describe a “follow the tissue” pipeline for generating a reliable and authentic single-cell/region 3-D molecular atlas of human adult kidney. Our approach emphasizes quality assurance, quality control, validation, and harmonization across different omics and imaging technologies from sample procurement, processing, storage, shipping to data generation, analysis, and sharing. We established benchmarks for quality control, rigor, reproducibility, and feasibility across multiple technologies through a pilot experiment using common source tissue that was processed and analyzed at different institutions and different technologies. A peer review system was established to critically review quality control measures and the reproducibility of data generated by each technology before their being approved to interrogate clinical biopsy specimens. The process established economizes the use of valuable biopsy tissue for multiomics and imaging analysis with stringent quality control to ensure rigor and reproducibility of results and serves as a model for precision medicine projects across laboratories, institutions and consortia.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Streptococcus pneumoniae HtrA is a dynamic and monomeric virulence factor capable of forming larger oligomeric complexes

Abstract High‐temperature requirement A (HtrA) proteases are a conserved family of serine proteases central to protein quality control and bacterial virulence. While Gram‐negative and human HtrAs are structurally well studied, Gram‐positive homologs remain essentially uncharacterized. Here, we present the first integrated structural and mechanistic analysis of a Gram‐positive HtrA, from Streptococcus pneumoniae , a virulence factor essential for adhesion and infection in vivo. Proteomic profiling of an htrA knockout and cleavage assays demonstrate that S. pneumoniae HtrA is required for protein quality control, with the PDZ domain mediating substrate recognition. Biochemically, S. pneumoniae HtrA exists exclusively as a monomer in solution, a striking divergence from canonical trimeric HtrAs that we show is shared with other Gram‐positive homologs. NMR analyses reveal that the monomer dynamically samples open and closed conformations, while cryo‐EM of a catalytic mutant identifies a hexamer stabilized by a unique LoopA–PDZ interaction. Together, these findings define S. pneumoniae HtrA as a dynamic monomer with interdomain coupling between its protease and PDZ domains, establishing Gram‐positive HtrAs as a mechanistically divergent subgroup within the HtrA family.

Lee, Eunjeong [Department of Biochemistry and Mole↗
NASA NTRS2006

Constellation-X Observatory

Women in Science Conferences are designed to allow young women in grades 7 through 12 to learn first-hand about careers in science, mathematics, and technology from accomplished professional women. Results of an international science and mathematics study conducted in 2000 indicated that "children in the United States were among the leaders in the 4th grade assessment, but by high school graduation, they were almost last." Part of the problem is that many girls and young women in junior and senior high school lose interest in science and technological careers. The goal of the WIS-Conferences held at the University of Wyoming in Laramie, and at Central Wyoming College in Riverton, are to directly address this problem. The conferences will be a cooperative effort supported by local agencies, schools, and businesses, in addition to several state agencies. By presenting positive role models in the science, mathematics, and technological fields, we hope to encourage all students (especially young women and minorities) to pursue higher education and careers in mathematics and science. The workshop topics include: 1) Engineering; 2) Robotics; 3) Physics/Astronomy; 4) Geology; 5) Paleontology; 6) Remote Sensing (GPS/GIS); 7) Molecular Biology; 8) Veterinary Medicine; 9) Optometry; 10) Data Encryption; and 11) Wildlife Biology.

Source record↗
DOE OSTI2022

Production Review of Accelerator-Based Medical Isotopes

The production of reactor-based medical isotopes is fragile, which has meant supply shortages from time to time. This paper reviews alternative production methods in the form of cyclotrons, linear accelerators and neutron generators. Finally, the status of the production of medical isotopes in China is described.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Titanium-45 (45Ti) Radiochemistry and Applications in Molecular Imaging

Molecular imaging is an important part of modern medicine which enables the non-invasive identification and characterization of diseases. With the advancement of radiochemistry and scanner technology, nuclear medicine is providing insight into efficient treatment options for individual patients. Titanium-45 (45Ti) is a lesser-explored radionuclide that is garnering increasing interest for the development of positron emission tomography (PET) radiopharmaceuticals. This review discusses aspects of this radionuclide including production, purification, radiochemistry development, and molecular imaging studies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project

An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medicine Project are working towards this goal through the collection and integration of large, disparate clinical, biological and imaging data from patients with kidney disease. Ontologies are powerful tools that facilitate these efforts by enabling researchers to organize and make sense of different data elements and the relationships between them. Ontologies are critical to support the types of big data analysis necessary for kidney precision medicine, where heterogeneous clinical, imaging and biopsy data from diverse sources must be combined to define a patient’s phenotype. Here, the development of two new ontologies — the Kidney Tissue Atlas Ontology and the Ontology of Precision Medicine and Investigation — will support the creation of the Kidney Tissue Atlas, which aims to provide a comprehensive molecular, cellular and anatomical map of the kidney. These ontologies will improve the annotation of kidney-relevant data, and eventually lead to new definitions of kidney disease in support of precision medicine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Identification of potent inhibitors of JUN N-terminal kinases for treatment of endometriosis and associated pain

Endometriosis, defined as the ectopic growth of endometrial tissue outside of the uterine cavity, is an inflammatory and hormone-dependent disease that causes excruciating pelvic pain, infertility, and significantly decreases quality of life in affected patients. The JUN N-terminal kinases (JNKs) are a leading class of nonhormonal therapeutic targets that have been validated in preclinical models of endometriosis and in a Phase 1/2 clinical trial. Despite their therapeutic potential, JNK inhibitors with increased potency and specificity are needed to address the inflammatory pathology of endometriosis and to prevent disease progression. Leveraging a DNA-encoded chemical library collection of ~4 billion compounds, we identified lead inhibitor CDD-2428 and optimized derivatives, CDD-2728 and CDD-3013, with excellent binding affinity to JNK1-3 (K d = 0.12 to 3.7 nM), enhanced selectivity, metabolic stability, and cellular permeability. Crystallographic and biochemical studies confirmed that CDD-3013 exhibited superior kinase selectivity with improved efficacy compared to existing JNK inhibitors. In primary endometriosis cell models, CDD-2728 and CDD-3013 suppressed JNK-dependent inflammatory signaling, dampening pathways linked to pain, invasion, angiogenesis, and macrophage recruitment. In an endometriosis mouse model, both CDD-2728 and CDD-3013 reduced endometriotic lesion size, macrophage infiltration, and cellular proliferation, showing in vivo efficacy. When tested in a lipopolysaccharide-induced hyperalgesia model, CDD-2728 and CDD-3013 decreased markers of induced pain, as measured by changes in a dynamic weight bearing test and Grimace scores. These findings nominate CDD-2728 and CDD-3013 as potent, nonhormonal therapeutic candidates for endometriosis with broad anti-inflammatory and analgesic activity, addressing a critical unmet clinical need.

Madasu, Chandrashekhar [Department of Pathology an↗
NASA NTRS2008

NASA Innovation Builds Better Nanotubes

Nanotailor Inc., based in Austin, Texas, licensed Goddard Space Flight Center's unique single-walled carbon nanotube (SWCNT) fabrication process with plans to make high-quality, low-cost SWCNTs available commercially. Carbon nanotubes are being used in a wide variety of applications, and NASA's improved production method will increase their applicability in medicine, microelectronics, advanced materials, and molecular containment. Nanotailor built and tested a prototype based on Goddard's process, and is using this technique to lower the cost and improve the integrity of nanotubes, offering a better product for use in biomaterials, advanced materials, space exploration, highway and building construction, and many other applications.

Source record↗
DOE OSTI2024

Active causal learning for decoding chemical complexities with targeted interventions

Abstract Predicting and enhancing inherent properties based on molecular structures is paramount to design tasks in medicine, materials science, and environmental management. Most of the current machine learning and deep learning approaches have become standard for predictions, but they face challenges when applied across different datasets due to reliance on correlations between molecular representation and target properties. These approaches typically depend on large datasets to capture the diversity within the chemical space, facilitating a more accurate approximation, interpolation, or extrapolation of the chemical behavior of molecules. In our research, we introduce an active learning approach that discerns underlying cause-effect relationships through strategic sampling with the use of a graph loss function. This method identifies the smallest subset of the dataset capable of encoding the most information representative of a much larger chemical space. The identified causal relations are then leveraged to conduct systematic interventions, optimizing the design task within a chemical space that the models have not encountered previously. While our implementation focused on the QM9 quantum-chemical dataset for a specific design task—finding molecules with a large dipole moment—our active causal learning approach, driven by intelligent sampling and interventions, holds potential for broader applications in molecular, materials design and discovery.

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

Active Causal Machine Learning for Molecular Property Prediction

Predicting properties from molecular structures is paramount to design tasks in medicine, materials science, and environmental management. However, design rules derived from the structure-property relationships using correlative data-driven methods fail to elucidate underlying causal mechanisms controlling chemical phenomena. This preliminary work proposes a workflow to actively learn robust cause-effect relations between structural features and molecular property for a broad chemical space utilizing smaller subsets, entailing partial information.

Fox, Zach↗
DOE OSTI2021

Artificial Intelligence for Autonomous Molecular Design: A Perspective

Domain-aware artificial intelligence has been increasingly adopted in recent years to expedite molecular design in various applications, including drug design and discovery. Recent advances in areas such as physics-informed machine learning and reasoning, software engineering, high-end hardware development, and computing infrastructures are providing opportunities to build scalable and explainable AI molecular discovery systems. This could improve a design hypothesis through feedback analysis, data integration that can provide a basis for the introduction of end-to-end automation for compound discovery and optimization, and enable more intelligent searches of chemical space. Several state-of-the-art ML architectures are predominantly and independently used for predicting the properties of small molecules, their high throughput synthesis, and screening, iteratively identifying and optimizing lead therapeutic candidates. However, such deep learning and ML approaches also raise considerable conceptual, technical, scalability, and end-to-end error quantification challenges, as well as skepticism about the current AI hype to build automated tools. To this end, synergistically and intelligently using these individual components along with robust quantum physics-based molecular representation and data generation tools in a closed-loop holds enormous promise for accelerated therapeutic design to critically analyze the opportunities and challenges for their more widespread application. This article aims to identify the most recent technology and breakthrough achieved by each of the components and discusses how such autonomous AI and ML workflows can be integrated to radically accelerate the protein target or disease model-based probe design that can be iteratively validated experimentally. Taken together, this could significantly reduce the timeline for end-to-end therapeutic discovery and optimization upon the arrival of any novel zoonotic transmission event. Our article serves as a guide for medicinal, computational chemistry and biology, analytical chemistry, and the ML community to practice autonomous molecular design in precision medicine and drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Towards verifiable cancer digital twins: tissue level modeling protocol for precision medicine

Cancer exhibits substantial heterogeneity, manifesting as distinct morphological and molecular variations across tumors, which frequently undermines the efficacy of conventional oncological treatments. Developments in multiomics and sequencing technologies have paved the way for unraveling this heterogeneity. Nevertheless, the complexity of the data gathered from these methods cannot be fully interpreted through multimodal data analysis alone. Mathematical modeling plays a crucial role in delineating the underlying mechanisms to explain sources of heterogeneity using patient-specific data. Intra-tumoral diversity necessitates the development of precision oncology therapies utilizing multiphysics, multiscale mathematical models for cancer. This review discusses recent advancements in computational methodologies for precision oncology, highlighting the potential of cancer digital twins to enhance patient-specific decision-making in clinical settings. We review computational efforts in building patient-informed cellular and tissue-level models for cancer and propose a computational framework that utilizes agent-based modeling as an effective conduit to integrate cancer systems models that encode signaling at the cellular scale with digital twin models that predict tissue-level response in a tumor microenvironment customized to patient information. Furthermore, we discuss machine learning approaches to building surrogates for these complex mathematical models. These surrogates can potentially be used to conduct sensitivity analysis, verification, validation, and uncertainty quantification, which is especially important for tumor studies due to their dynamic nature.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Distinct binding conformations of epinephrine with α- and β-adrenergic receptors

Abstract Agonists targeting α 2 -adrenergic receptors (ARs) are used to treat diverse conditions, including hypertension, attention-deficit/hyperactivity disorder, pain, panic disorders, opioid and alcohol withdrawal symptoms, and cigarette cravings. These receptors transduce signals through heterotrimeric Gi proteins. Here, we elucidated cryo-EM structures that depict α 2A -AR in complex with Gi proteins, along with the endogenous agonist epinephrine or the synthetic agonist dexmedetomidine. Molecular dynamics simulations and functional studies reinforce the results of the structural revelations. Our investigation revealed that epinephrine exhibits different conformations when engaging with α-ARs and β-ARs. Furthermore, α 2A -AR and β 1 -AR (primarily coupled to Gs, with secondary associations to Gi) were compared and found to exhibit different interactions with Gi proteins. Notably, the stability of the epinephrine–α 2A -AR–Gi complex is greater than that of the dexmedetomidine–α 2A -AR–Gi complex. These findings substantiate and improve our knowledge on the intricate signaling mechanisms orchestrated by ARs and concurrently shed light on the regulation of α-ARs and β-ARs by epinephrine.

Biochemistry & Molecular Biology↗
NASA NTRS1997

Optical Characterization and 2,525 micron Lasing of Cr(2+):Cd(0.85)Mn(0.15)Te

Transition metal doped solids are of significant current interest for the development of tunable solid-state lasers for the near and mid-infrared (1-4 pm) spectral region. Applications of these lasers include basic research in atomic, molecular, and solid-state physics, optical communication, medicine, and environmental studies of the atmosphere. In transition metal based laser materials, absorption and emission of light arises from electronic transitions between crystal field split energy levels of 3d transition metal ions. The optical spectra generally exhibit broad bands due to the strong interaction between dopant and host (electron-phonon coupling). Broad emission bands offer the prospect of tunable laser activity over a wide wavelength range, e.g. the tuning range of Ti:Sapphire extends from 700-1100 run. The only current transition metal laser operating in the mid-infrared wavelength region (1.8-2.4 micro-m) is CO(2+):MgF2, but its performance is severely limited due to strong nonradiative decay at room temperature. Based on lifetime data, the quantum efficiency is estimated to be less than 3 deg/0 11,21. In general, the probability for non-radiative decay via multi-phonon relaxation increases with decreasing energy gap between ground and excited state. Therefore, efficient transition metal lasers beyond -1.6 micro-m are rare. Recently, tunable laser activity around 2.3 micro-m was observed from Cr doped ZnS and ZnSe. The new lasing center in these materials was identified as Cr(2+) occupying the tetrahedral Zn site. Tetrahedrally coordinated optical centers are rather unusual among transition metal lasers. Their potential usefulness, however, has been demonstrated by the recent development of near infrared laser materials such as Cr:forsterite and Cr:YAG, which are based on tetrahedrally coordinated Cr(4+) ions. According to the Laporte selection rule, electric-dipole transition within the optically active 3d-electron shells are parity forbidden. However, a static acentric electric crystal field or the coupling of asymmetric phonons can force electric-dipole transitions by the admixture of wave functions with opposite parity. Tetrahedral sites lack inversion symmetry which provides the odd-parity field necessary to relax the parity selection rule. Therefore, high absorption and emission cross sections are observed. An enhanced radiative emission rate is also expected to reduce the detrimental effect of non-radiative decay. Motivated by the initial results on Cr doped ZnS and ZnSe, we have started a comprehensive effort to study Cr(2+) doped II-VI semiconductors for solid-state laser applications. In this paper we present the optical properties and the demonstration of mid-infrared lasing from Cr doped Cd(0.85)Mn(0.15)Te.

Davis, V. R.↗
NASA NTRS2000

Fluid Physics and Macromolecular Crystal Growth in Microgravity

The molecular structure of biological macromolecules is important in understanding how these molecules work and has direct application to rational drug design for new medicines and for the improvement and development of industrial enzymes. In order to obtain the molecular structure, large, well formed, single macromolecule crystals are required. The growth of macromolecule crystals is a difficult task and is often hampered on the ground by fluid flows that result from the interaction of gravity with the crystal growth process. One such effect is the bulk movement of the crystal through the fluid due to sedimentation. A second is buoyancy driven convection close to the crystal surface. On the ground the crystallization process itself induces both of these flows.

Pusey, M.↗