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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 505 records · Page 28

All sources NASA NTRS DOE OSTI

DOE OSTI2015

Agent-based model forecasts aging of the population of people who inject drugs in metropolitan Chicago and changing prevalence of hepatitis C infections

People who inject drugs (PWID) are at high risk for blood-borne pathogens transmitted during the sharing of contaminated injection equipment, particularly hepatitis C virus (HCV). HCV prevalence is influenced by a complex interplay of drug-use behaviors, social networks, and geography, as well as the availability of interventions, such as needle exchange programs. To adequately address this complexity in HCV epidemic forecasting, we have developed a computational model, the Agent-based Pathogen Kinetics model (APK). APK simulates the PWID population in metropolitan Chicago, including the social interactions that result in HCV infection. We used multiple empirical data sources on Chicago PWID to build a spatial distribution of an in silico PWID population and modeled networks among the PWID by considering the geography of the city and its suburbs. APK was validated against 2012 empirical data (the latest available) and shown to agree with network and epidemiological surveys to within 1%. For the period 2010–2020, APK forecasts a decline in HCV prevalence of 0.8% per year from 44(±2)% to 36(±5)%, although some sub-populations would continue to have relatively high prevalence, including Non-Hispanic Blacks, 48(±5)%. The rate of decline will be lowest in Non-Hispanic Whites and we find, in a reversal of historical trends, that incidence among non-Hispanic Whites would exceed incidence among Non-Hispanic Blacks (0.66 per 100 per years vs 0.17 per 100 person years). APK also forecasts an increase in PWID mean age from 35(±1) to 40(±2) with a corresponding increase from 59(±2)% to 80(±6)% in the proportion of the population >30 years old. Our research highlight the importance of analyzing sub-populations in disease predictions, the utility of computer simulation for analyzing demographic and health trends among PWID and serve as a tool for guiding intervention and prevention strategies in Chicago, and other major cities.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Structural Studies of a Rationally Selected Multi-Drug Resistant HIV-1 Protease Reveal Synergistic Effect of Distal Mutations on Flap Dynamics

We report structural analysis of HIV protease variant PR S17 which was rationally selected by machine learning to represent wide classes of highly drug-resistant variants. Crystal structures were solved of PR S17 in the inhibitor-free form and in complex with antiviral inhibitor, darunavir. Despite its 17 mutations, PR S17 has only one mutation (V82S) in the inhibitor/substrate binding cavity, yet exhibits high resistance to all clinical inhibitors. PR S17 has none of the major mutations (I47V, I50V, I54ML, L76V and I84V) associated with darunavir resistance, but has 10,000-fold weaker binding affinity relative to the wild type PR. Comparable binding affinity of 8000-fold weaker than PR is seen for drug resistant mutant PR20, which bears 3 mutations associated with major resistance to darunavir (I47V, I54L and I84V). Inhibitor-free PR S17 shows an open flap conformation with a curled tip correlating with G48V flap mutation. NMR studies on inactive PR S17 D25N unambiguously confirm that the flaps adopt mainly an open conformation in solution very similar to that in the inhibitor-free crystal structure. In PR S17 , the hinge loop cluster of mutations, E35D, M36I and S37D, contributes to the altered flap dynamics by a mechanism similar to that of PR20. An additional K20R mutation anchors an altered conformation of the hinge loop. Flap mutations M46L and G48V in PR S17 /DRV complex alter the Phe53 conformation by steric hindrance between the side chains. Unlike the L10F mutation in PR20, L10I in PR S17 does not break the inter-subunit ion pair or diminish the dimer stability, consistent with a very low dimer dissociation constant comparable to that of wild type PR. Distal mutations A71V, L90M and I93L propagate alterations to the catalytic site of PR S17 . PRS17 exhibits a molecular mechanism whereby mutations act synergistically to alter the flap dynamics resulting in significantly weaker binding yet maintaining active site contacts with darunavir.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Novel antibody reagents for characterization of drug- and tumor microenvironment-induced changes in epithelial-mesenchymal transition and cancer stem cells

The presence of cancer stem cells (CSCs) and the induction of epithelial-to-mesenchymal transition (EMT) in tumors are associated with tumor aggressiveness, metastasis, drug resistance, and poor prognosis, necessitating the development of reagents for unambiguous detection of CSC- and EMT-associated proteins in tumor specimens. To this end, we generated novel antibodies to EMT- and CSC-associated proteins, including Goosecoid, Sox9, Slug, Snail, and CD133. Importantly, unlike several widely used antibodies to CD133, the anti-CD133 antibodies we generated recognize epitopes distal to known glycosylation sites, enabling analyses that are not confounded by differences in CD133 glycosylation. For all target proteins, we selected antibodies that yielded the expected target protein molecular weights by Western analysis and the correct subcellular localization patterns by immunofluorescence microscopy assay (IFA); binding selectivity was verified by immunoprecipitation-mass spectrometry and by immunohistochemistry and IFA peptide blocking experiments. Finally, we applied these reagents to assess modulation of the respective markers of EMT and CSCs in xenograft tumor models by IFA. We observed that the constitutive presence of human hepatocyte growth factor (hHGF) in the tumor microenvironment of H596 non-small cell lung cancer tumors implanted in homozygous hHGF knock-in transgenic mice induced a more mesenchymal-like tumor state (relative to the epithelial-like state when implanted in control SCID mice), as evidenced by the elevated expression of EMT-associated transcription factors detected by our novel antibodies. Similarly, our new anti-CD133 antibody enabled detection and quantitation of drug-induced reductions in CD133-positive tumor cells following treatment of SUM149PT triple-negative breast cancer xenograft models with the CSC/focal adhesion kinase (FAK) inhibitor VS-6063. Thus, our novel antibodies to CSC- and EMT-associated factors exhibit sufficient sensitivity and selectivity for immunofluorescence microscopy studies of these processes in preclinical xenograft tumor specimens and the potential for application with clinical samples.

Science & Technology - Other Topics↗

DOE OSTI2022

People who inject drugs in metropolitan Chicago: A meta-analysis of data from 1997-2017 to inform interventions and computational modeling toward hepatitis C microelimination

Progress toward hepatitis C virus (HCV) elimination in the United States is not on track to meet targets set by the World Health Organization, as the opioid crisis continues to drive both injection drug use and increasing HCV incidence. A pragmatic approach to achieving this is using a microelimination approach of focusing on high-risk populations such as people who inject drugs (PWID). Computational models are useful in understanding the complex interplay of individual, social, and structural level factors that might alter HCV incidence, prevalence, transmission, and treatment uptake to achieve HCV microelimination. However, these models need to be informed with realistic sociodemographic, risk behavior and network estimates on PWID. We conducted a meta-analysis of research studies spanning 20 years of research and interventions with PWID in metropolitan Chicago to produce parameters for a synthetic population for realistic computational models (e.g., agent-based models). We then fit an exponential random graph model (ERGM) using the network estimates from the meta-analysis in order to develop the network component of the synthetic population.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Aging and drug discovery

Multiple interventions in the aging process have been discovered to extend the healthspan of model organisms. Both industry and academia are therefore exploring possible transformative molecules that target aging and age-associated diseases. In this overview, we summarize the presented talks and discussion points of the 5th Annual Aging and Drug Discovery Forum 2018 in Basel, Switzerland. Here academia and industry came together, to discuss the latest progress and issues in aging research. The meeting covered talks about the mechanistic cause of aging, how longevity signatures may be highly conserved, emerging biomarkers of aging, possible interventions in the aging process and the use of artificial intelligence for aging research and drug discovery. Importantly, a consensus is emerging both in industry and academia, that molecules able to intervene in the aging process may contain the potential to transform both societies and healthcare.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Structural basis of mutant-selectivity and drug-resistance related to CO-1686

Non-small-cell lung cancers (NSCLCs) caused by activating mutations in the kinase domain of epidermal growth factor receptor (EGFR) initially respond to first-generation reversible drugs gefitinib and erlotinib. However, clinical efficacy is limited due to the development of drug-resistance that in more than half of the cases are driven by the secondary T790M mutation. CO-1686 is one of the third generation irreversible inhibitors that inhibits EGFR activating mutants, including those with concurrent T790M, while avoiding the off-target toxicity owing to inhibition of wild-type EGFR in treating EGFR mutation-positive NSCLCs. Despite the remarkable success, the experimentally determined structure of this agent in complex with EGFR T790M remains unknown. In this study, we determined crystal structures of EGFR T790M or L858R mutants covalently bound by CO-1686. Based on these structural data, we can explain why CO-1686 irreversibly inhibits EGFR and selectively prefers T790M, which may help improving this or similar compounds, and explain why EGFR L718Q and L844V mutations incur resistance to this agent.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Catching Villains: Finding single cells responsible for cancer drug resistance and metastasis

Despite the widespread acceptance that cell-to-cell variability is a defining feature of cancer, much remains unknown about stem-cell like cancer cells that are hypothesized to be responsible for both metastasis and drug resistance (Marusyk, Almendro, and Polyak 2012). Few analytical techniques exist that can quantify single cell drug uptake, hindering progress towards decoding how cancer cells evade therapeutics. This project aims to address the dearth of analytical chemical methods available for single cell analysis, by employing accelerator mass spectrometry (AMS) to directly quantify chemotherapeutic uptake in single cells.

42 ENGINEERING↗

DOE OSTI2024

Annual Report for Structure-Aware Unsupervised, Transformational Machine Learning for Drug Discovery

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Assessment of Naturally Occurring Radioactive Material (NORM) in Illicit Drugs Using High-Resolution Gamma Spectroscopy

This report documents results assessing the presence of Naturally Occurring Radioactive Material (NORM) in illicit drugs using high-resolution gamma spectroscopy. Specifically, high-purity germanium (HPGe) measurements were conducted at the Drug Enforcement Administration (DEA) South Central Laboratory on 11 samples (referred to as exhibits) including cocaine, fentanyl, heroin, ketamine, LSD, marijuana, methamphetamines, psilocybin mushrooms, and synthetic cannabinoids.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2026

Structure-Aware Unsupervised, Transformational Machine Learning for Drug Discovery (DTRA Basic Research Final Report)

The major goal of this project is to develop machine learning (ML) methods to enable improved predictive power on real drug discovery for novel targets. More specifically, we planned to demonstrate the capability and effectiveness of ML tools utilizing unlabeled large-volume protein-ligand datasets. We investigated multiple pre-training approaches for 3D protein-ligand structure-based foundation models, without relying on experimental binding data. We also addressed scenarios in which crystal structures are unavailable or binding data are limited. We also planned to develop a complete pipeline to screen novel compounds as well as to demonstrate the capability and effectiveness of the developed methods by testing on a realistic drug discovery task such as SARS-CoV-2. While the major goals and milestones remain consistent with the original proposal, certain technical details have been adjusted, based on the experimental results and related outcomes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

Global LC/MS Metabolomics Profiling of Calcium Stressed and Immunosuppressant Drug Treated Saccharomyces cerevisiae

Previous studies have shown that calcium stressed Saccharomyces cerevisiae , challenged with immunosuppressant drugs FK506 and Cyclosporin A, responds with comprehensive gene expression changes and attenuation of the generalized calcium stress response. Here, we describe a global metabolomics workflow for investigating the utility of tracking corresponding phenotypic changes. This was achieved by efficiently analyzing relative abundance differences between intracellular metabolite pools from wild-type and calcium stressed cultures, with and without prior immunosuppressant drugs exposure. We used pathway database content from WikiPathways and YeastCyc to facilitate the projection of our metabolomics profiling results onto biological pathways. A key challenge was to increase the coverage of the detected metabolites. This was achieved by applying both reverse phase (RP) and aqueous normal phase (ANP) chromatographic separations, as well as electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) sources for detection in both ion polarities. Unsupervised principle component analysis (PCA) and ANOVA results revealed differentiation between wild-type controls, calcium stressed and immunosuppressant/calcium challenged cells. Untargeted data mining resulted in 247 differentially expressed, annotated metabolites, across at least one pair of conditions. A separate, targeted data mining strategy identified 187 differential, annotated metabolites. All annotated metabolites were subsequently mapped onto curated pathways from YeastCyc and WikiPathways for interactive pathway analysis and visualization. Dozens of pathways showed differential responses to stress conditions based on one or more matches to the list of annotated metabolites or to metabolites that had been identified further by MS/MS. The purine salvage, pantothenate and sulfur amino acid pathways were flagged as being enriched, which is consistent with previously published literature for transcriptomics analysis. Thus, broad discovery-based data mining combined with targeted pathway projections can be an important asset for rapidly distilling, testing and evaluating a large amount of information for further investigation.

calcineurin↗

DOE OSTI2023

Utility of Physiologically Based Pharmacokinetic Modeling to Investigate the Impact of Physiological Changes of Pregnancy and Cancer on Oncology Drug Pharmacokinetics

The treatment of cancer during pregnancy remains challenging with knowledge gaps in drug dosage, safety, and efficacy due to the under-representation of this population in clinical trials. Our aim was to investigate physiological changes reported in both pregnancy and cancer populations into a PBPK modeling framework that allows for a more accurate estimation of PK changes in pregnant patients with cancer. Methods: Paclitaxel and docetaxel were selected to validate a population model using clinical data from pregnant patients with cancer. The validated population model was subsequently used to predict the PK of acalabrutinib in pregnant patients with cancer. Results: The Simcyp pregnancy population model reasonably predicted the PK of docetaxel in pregnant patients with cancer, while a modified model that included a 2.5-fold increase in CYP2C8 abundance, consistent with the increased expression during pregnancy, was needed to reasonably predict the PK of paclitaxel in pregnant patients with cancer. Changes in protein binding levels of patients with cancer had a minimal impact on the predicted clearance of paclitaxel and docetaxel. PBPK modeling predicted approximately 60% lower AUC and Cmax for acalabrutinib in pregnant versus non-pregnant patients with cancer. Conclusions: Our results suggest that PBPK modeling is a promising approach to investigate the effects of pregnancy and cancer on the PK of oncology drugs and potentially inform dosing for pregnant patients with cancer. Further evaluation and refinement of the population model are needed for pregnant patients with cancer with additional compounds and clinical PK data.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1972

Technology assessment and the Food and Drug Administration

The statutory standards underlying the activities of the FDA, and the problems the Agency faces in decision making are discussed from a legal point of view. The premarketing clearance of new drugs and of food additives, the two most publicized and criticized areas of FDA activity, are used as illustrations. The importance of statutory standards in technology assessment in a regulatory setting is developed. The difficulties inherent in the formulation of meaningful standards are recognized. For foods, the words of the statute are inadequate, and for drugs, a statutory recognition of the various other objectives would be useful to the regulator and the regulated.

Kaplan, A. H.↗

NASA NTRS1973

Automated method for study of drug metabolism

Commercially available equipment can be modified to provide automated system for assaying drug metabolism by continuous flow-through. System includes steps and devices for mixing drug with enzyme and cofactor in the presence of pure oxygen, dialyzing resulting metabolite against buffer, and determining amount of metabolite by colorimetric method.

Furner, R. L.↗

NASA NTRS1974

Automated drug identification system

System speeds up analysis of blood and urine and is capable of identifying 100 commonly abused drugs. System includes computer that controls entire analytical process by ordering various steps in specific sequences. Computer processes data output and has readout of identified drugs.

Campen, C. F., Jr.↗

NASA NTRS1973

Evaluation of possible interaction among drugs contemplated for use during manned space flights

Possible interactions among drugs contemplated for use during manned spaceflights have been studied in several animal species. The following seven drugs were investigated: nitrofurantoin, chloral hydrate, hexobarbital, phenobarbital, flurazepam, diphenoxylate, and phenazopyridine. Particular combinations included: chloral hydrate, hexabarbital or flurazepam with nitrofurantoin; phenobarbital or flurazepam with phenazopyridine; and diphenoxylate with two does formulations of nitrofurantoin. Studies were carried out in several species to determine whether induction of liver microsomal enzymes would increase the tendency of phenazopyridine to produce methemoglobin in vivo. Animals were premedicated with phenobarbital, a known inducer of azoreductase, and in a separate experiment with flurazepam, before administration of phenazopyridine. Methemoglobin production was determined in each animal after receiving phenazopyridine. No evidence was found for increased production of methemoglobin in the rat, dog, or rabbit that could be attributed to increased amounts of microsomal enzymes.

Source record↗

NASA NTRS1974

Evaluation of possible interaction among drugs contemplated for use during manned space flights. Part 1: Summary from progress report dated 31 October 1973. Part 2: Progress report for the period November 1973 to June 1974

Possible interactions among drugs contemplated for use during manned spaceflights have been studied in several animal species. The following seven drugs were investigated: nitrofurantoin, chloral hydrate, hexobarbital, phenobarbital, flurazepam, diphenoxylate, and phenazopyridine. Particular combinations included: chloral hydrate, hexobarbital or flurazepam with nitrofurantoin; phenobarbital or flurazepam with phenazopyridine; and diphenoxylate with two dose formulations of nitrofurantoin. The mechanism of action and an explanation of the interaction between diphenoxylate and nitrofurantoin still remains unclear. In man, the interaction does not appear to be significant, affecting only two subjects out of six and with only one dose formulation (Furadantin).

Source record↗

NASA NTRS1983

Implantable Drug Dispenser

Drugs such as insulin are injected as needed directly into bloodstream by compact implantable dispensing unit. Two vapor cavities produce opposing forces on drug-chamber diaphragm. Heaters in cavities allow control of direction and rate of motion of bellows. Dispensing capsule fitted with coil so batteries can be recharged by induction.

Collins, E. R. J.↗