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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 163 records · Page 9

Theory of antimotion sickness drug mechanisms.

The results of a series of antimotion sickness drug evaluations indicates that drugs with central anticholinergic actions and drugs that increase central sympathetic activity are effective against motion sickness. The combination of these actions produces a synergistic effect against motion sickness. The effect of these medications on central acetylcholine or on norepinephrine could alter a balance between the neurons in the vestibular and reticular areas which influence motion sickness and also sympathetic and parasympathetic reactions. It is suggested that this could be their mechanism of action in preventing motion sickness.

Wood, D. C.↗

Stress modification of the toxicity of antimotion sickness drugs and Aspirin

The effect of environmental temperature on the toxicity of cyclizine, trimethobenzamide, and Aspirin were studied in mice. LD-50s were compared at 30 C, 22 C, and 15 C. At 30 C the toxicity of all three drugs increased, with that to Aspirin being affected most. Cooling decreased the toxicity of cyclizine and had no significant effect on that of trimethobenzamide or aspirin. These findings indicate that alterations in environmental temperature markedly affect drug toxicity. They emphasize that such alterations, and particularly increases in temperature, do not have to be particularly drastic, but that 'mild' variations in the environment are effective in altering an animal's sensitivity to a drug.

Shields, D.↗

Evaluation of a new antinauseant drug for the prevention of motion sickness

The new drug, AHR 5645B, together with other drugs was evaluated in tests, conducted with eight male subjects, concerning its ability to prevent motion sickness. It was found that AHR 5645B, used in doses of 20, 50, and 100 mg, was not efficacious in preventing experimental motion sickness. A combination of 50 mg meclizine and 25 mg ephedrine sulfate produced the best results. Favorable results were also obtained with a combination of 12.5 mg promethazine hydrochloride and 12.5 mg ephedrine sulfate. The findings in the reported experiment point to the difficulty of identifying a highly efficacious antimotion sickness drug for everyone.

Graybiel, A.↗

Drug Research

NBOD2, a program developed at Goddard Space Flight Center to solve equations of motion coupled N-body systems is used by E.I. DuPont de Nemours & Co. to model potential drugs as a series of elements. The program analyses the vibrational and static motions of independent components in drugs. Information generated from this process is used to design specific drugs to interact with enzymes in designated ways.

Source record↗

Gravisensing, apoptosis, and drug recovery in Taxus cell suspensions

Haploid and diploid cell suspensions of Taxus spp. were examined for their adaptive plasticity in response to simulated microgravity, unit gravity, and hypergravity. Cell suspensions produced the taxane, paclitaxel, (TAXOL (R)), which is useful for the treatment of various cancers. Amyloplasts contributed to taxane ring biosynthesis and to drug release at the cell wall. Drug-producing cells reacted as gravisensing osmotic tensiometers. In stressed cells, amyloplasts docked and fused in clusters to sites on the plasmalemma before taxane discharge into the culture medium. In simulated microgravity and compared to all other treatments, taxane production was reduced nearly 100-fold. The percent paclitaxel of total taxanes remained 3-to 6-fold greater, and biomass doubled. When p53-independent programmed cell death was induced, taxanes were released into the culture medium as free molecules (soluble and insoluble) or bound to membranes, nuclear fragments, xylan residues, and other particulate materials. Unit gravity and especially hypergravity promoted xylogenesis and significant drug overproduction. A model relating families of >touch = (TCH), taxane early response (TER), nuclear cycling, and apoptosis-regulating genes to gravisensing, cell wall modifications, and to taxane recovery accounted for most but not all of the observations.

Paclitaxel/biosynthesis↗

Protein Innovations Advance Drug Treatments, Skin Care

Dan Carter carefully layered the sheets of tracing paper on the light box. On each sheet were renderings of the atomic components of an essential human protein, one whose structure had long been a mystery. With each layer Carter laid down, a never-before-seen image became clearer. Carter joined NASA s Marshall Space Flight Center in 1985 and began exploring processes of protein crystal growth in space. By bouncing intense X-rays off the crystals, researchers can determine the electron densities around the thousands of atoms forming the protein molecules, unveiling their atomic structures. Cultivating crystals of sufficient quality on Earth was problematic; the microgravity conditions of space were far more accommodating. At the time, only a few hundred protein structures had been mapped, and the methods were time consuming and tedious. Carter hoped his work would help reveal the structure of human serum albumin, a major protein in the human circulatory system responsible for ferrying numerous small molecules in the blood. More was at stake than scientific curiosity. Albumin has a high affinity for most of the world s pharmaceuticals, Carter explains, and its interaction with drugs can change their safety and efficacy. When a medication enters the bloodstream a cancer chemotherapy drug, for example a majority of it can bind with albumin, leaving only a small percentage active for treatment. How a drug interacts with albumin can influence considerations like the necessary effective dosage, playing a significant role in the design and application of therapeutic measures. In spite of numerous difficulties, including having no access to microgravity following the 1986 Space Shuttle Challenger disaster, the image Carter had hoped to see was finally clarifying. In 1988, his lab had acquired specialized X-ray and detection equipment a tipping point. Carter and his colleagues began to piece together albumin s portrait, the formation of its electron densities coalescing on the sheets of tracing paper he arranged on the light box. While space-grown crystals were ultimately not involved in the achievement, a year later, Carter says, we were on the cover of Science magazine, having determined the atomic structure of albumin.

Source record↗

AI-based language models powering drug discovery and development

The discovery and development of new medicines is expensive, time-consuming, and often inefficient, with many failures along the way. Powered by artificial intelligence (AI), language models (LMs) have changed the landscape of natural language processing (NLP), offering possibilities to transform treatment development more effectively. Here, we summarize advances in AI-powered LMs and their potential to aid drug discovery and development. We highlight opportunities for AI-powered LMs in target identification, clinical design, regulatory decision-making, and pharmacovigilance. We specifically emphasize the potential role of AI-powered LMs for developing new treatments for Coronavirus 2019 (COVID-19) strategies, including drug repurposing, which can be extrapolated to other infectious diseases that have the potential to cause pandemics. Finally, we set out the remaining challenges and propose possible solutions for improvement.

60 APPLIED LIFE SCIENCES↗

Establishing reference ranges for circulating biomarkers of drug‐induced liver injury in healthy human volunteers 1

Aims The potential of mechanistic biomarkers to improve prediction of drug‐induced liver injury (DILI) and hepatic regeneration is widely acknowledged. We sought to determine reference intervals for new biomarkers of DILI and regeneration, as well as to characterize their natural variability and impact of diurnal variation. Methods Serum samples from 227 healthy volunteers were recruited as part of a cross‐sectional study; of these, 25 subjects had weekly serial sampling over 3 weeks, while 23 had intensive blood sampling over a 24h period. Alanine aminotransferase (ALT), MicroRNA‐122 (miR‐122), High Mobility Group Box‐1 (HMGB1), total Keratin‐18 (K18), caspase‐cleaved Keratin‐18 (ccK18), Glutamate Dehydrogenase (GLDH) and Macrophage Colony‐Stimulating Factor‐1 (CSF‐1) were assayed. Results Reference intervals were established for each biomarker based on the 97.5% quantile (90% CI) following the assessment of fixed effects in univariate and multivariable models. Intra‐individual variability was found to be non‐significant, and there was no significant impact of diurnal variation. Conclusion Reference intervals for novel DILI biomarkers have been described. An upper limit of a reference range might represent the most appropriate mechanism to utilize these data. These data can now be used to interpret data from exploratory clinical DILI studies and to assist their further qualification as required by regulatory authorities.

Jorgensen, Andrea L. [Department of Health Data Sc↗

MtrA modulates Mycobacterium tuberculosis cell division in host microenvironments to mediate intrinsic resistance and drug tolerance

The success of Mycobacterium tuberculosis (Mtb) is largely attributed to its ability to physiologically adapt and withstand diverse localized stresses within host microenvironments. Here, we present a data-driven model (EGRIN 2.0) that captures the dynamic interplay of environmental cues and genome-encoded regulatory programs in Mtb. Analysis of EGRIN 2.0 shows how modulation of the MtrAB two-component signaling system tunes Mtb growth in response to related host microenvironmental cues. Disruption of MtrAB by tunable CRISPR interference confirms that the signaling system regulates multiple peptidoglycan hydrolases, among other targets, that are important for cell division. Further, MtrA decreases the effectiveness of antibiotics by mechanisms of both intrinsic resistance and drug tolerance. Together, the model-enabled dissection of complex MtrA regulation highlights its importance as a drug target and illustrates how EGRIN 2.0 facilitates discovery and mechanistic characterization of Mtb adaptation to specific host microenvironments within the host.

59 BASIC BIOLOGICAL SCIENCES↗

Low rotational barriers for the most dynamically active methyl groups in the proposed antiviral drugs for treatment of SARS-CoV-2, apilimod and tetrandrine

A recent screening study highlighted a molecular compound, apilimod, for its efficacy against the SARS-CoV-2 virus, while another compound, tetrandrine, demonstrated a remarkable synergy with the benchmark antiviral drug, remdesivir. In this work, we find that because of significantly reduced potential energy barriers, which also give rise to pronounced quantum effects, the rotational dynamics of the most dynamically active methyl groups in apilimod and tetrandrine are much faster than those in remdesivir. Because dynamics of methyl groups are essential for biochemical activity, screening studies based on the computed potential energy profiles may help identify promising candidates within a given class of drugs.

60 APPLIED LIFE SCIENCES↗

Longitudinal Preclinical Imaging Characterizes Extracellular Drug Accumulation After Radiation Therapy in the Healthy and Leukemic Bone Marrow Vascular Microenvironment

Recent initial findings suggest that radiation therapy improves blood perfusion and cellular chemotherapy uptake in mice with leukemia. However, the ability of radiation therapy to influence drug accumulation in the extracellular bone marrow tissue is unknown, due in part to a lack of methodology. This study developed longitudinal quantitative multiphoton microscopy (L-QMPM) to characterize the bone marrow vasculature (BMV) and drug accumulation in the extracellular bone marrow tissue before and after radiation therapy in mice bearing leukemia.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Ambient ion focusing from a field-free region to a detector: enhanced signal for explosives and drug detection with mass spectrometry

This study demonstrates ion focusing at ambient pressure and increased ion signal by creating a voltage gradient from a field-free region to a detector, thereby improving the detection of chemicals, such as explosives and drugs. At ambient pressure, ion loss and resulting signal reduction pose challenges that limit detection sensitivity in analytical instruments. Techniques to increase sensitivity, such as atmospheric flow tube-mass spectrometry (AFT-MS), extend ion-molecule reaction times but result in significant overall ion loss due to diffusion. Ion manipulation techniques, though challenging at ambient pressure, can mitigate these losses by concentrating ions toward the detector inlet. Using SIMION, ion trajectories were modeled with a voltage gradient applied between a flow tube and a detector, revealing ion focusing at ambient pressure. Experimental verification with an atmospheric flow tube employed both mass spectrometry and Faraday plate detectors to measure ion beam profiles across varying flow rates, tube diameters, and voltage gradients. Application of a voltage gradient effectively directed ions to the axial center of the flow tube, narrowed ion beam width, and increased signal intensity by 5 to 10 times compared to conditions without a voltage gradient. This ion focusing approach shows promise for improving sensitivity in ambient-pressure instruments. This technique has the potential to enhance detection levels in security and forensic applications, with particular benefits for field-portable devices used at checkpoints to identify explosives and drugs.

ambient pressure↗

High-throughput screening of the ReFRAME, Pandemic Box, and COVID Box drug repurposing libraries against SARS-CoV-2 nsp15 endoribonuclease to identify small-molecule inhibitors of viral activity

SARS-CoV-2 has caused a global pandemic, and has taken over 1.7 million lives as of mid-December, 2020. Although great progress has been made in the development of effective countermeasures, with several pharmaceutical companies approved or poised to deliver vaccines to market, there is still an unmet need of essential antiviral drugs with therapeutic impact for the treatment of moderate-to-severe COVID-19. Towards this goal, a high-throughput assay was used to screen SARS-CoV-2 nsp15 uracil-dependent endonuclease (endoU) function against 13 thousand compounds from drug and lead repurposing compound libraries. While over 80% of initial hit compounds were pan-assay inhibitory compounds, three hits were confirmed as nsp15 endoU inhibitors in the 1–20 μM range in vitro. Furthermore, Exebryl-1, a ß-amyloid anti-aggregation molecule for Alzheimer’s therapy, was shown to have antiviral activity between 10 to 66 μM, in Vero 76, Caco-2, and Calu-3 cells. Although the inhibitory concentrations determined for Exebryl-1 exceed those recommended for therapeutic intervention, our findings show great promise for further optimization of Exebryl-1 as an nsp15 endoU inhibitor and as a SARS-CoV-2 antiviral.

60 APPLIED LIFE SCIENCES↗

Reducing Sample Size While Improving Equity in Vaccine Clinical Trials: A Machine Learning-Based Recruitment Methodology with Application to Improving Trials of Hepatitis C Virus Vaccines in People Who Inject Drugs

Despite the availability of direct-acting antivirals that cure individuals infected with the hepatitis C virus (HCV), developing a vaccine is critically needed in achieving HCV elimination. HCV vaccine trials have been performed in populations with high incidence of new HCV infection such as people who inject drugs (PWID). Developing strategies of optimal recruitment of PWID for HCV vaccine trials could reduce sample size, follow-up costs and disparities in enrollment. We investigate trial recruitment informed by machine learning and evaluate a strategy for HCV vaccine trials termed PREDICTEE—Predictive Recruitment and Enrichment method balancing Demographics and Incidence for Clinical Trial Equity and Efficiency. PREDICTEE utilizes a survival analysis model applied to trial candidates, considering their demographic and injection characteristics to predict the candidate’s probability of HCV infection during the trial. The decision to recruit considers both the candidate’s predicted incidence and demographic characteristics such as age, sex, and race. We evaluated PREDICTEE using in silico methods, in which we first generated a synthetic candidate pool and their respective HCV infection events using HepCEP, a validated agent-based simulation model of HCV transmission among PWID in metropolitan Chicago. We then compared PREDICTEE to conventional recruitment of high-risk PWID who share drugs or injection equipment in terms of sample size and recruitment equity, with the latter measured by participation-to-prevalence ratio (PPR) across age, sex, and race. Comparing conventional recruitment to PREDICTEE found a reduction in sample size from 802 (95%: 642–1010) to 278 (95%: 264–294) with PREDICTEE, while also reducing screening requirements by 30%. Simultaneously, PPR increased from 0.475 (95%: 0.356–0.568) to 0.754 (95%: 0.685–0.834). Even when targeting a dissimilar maximally balanced population in which achieving recruitment equity would be more difficult, PREDICTEE is able to reduce sample size from 802 (95%: 642–1010) to 304 (95%: 288–322) while improving PPR to 0.807 (95%: 0.792–0.821). PREDICTEE presents a promising strategy for HCV clinical trial recruitment, achieving sample size reduction while improving recruitment equity.

60 APPLIED LIFE SCIENCES↗

Predicting Drug Resistance Using Deep Mutational Scanning

Drug resistance is a major healthcare challenge, resulting in a continuous need to develop new inhibitors. The development of these inhibitors requires an understanding of the mechanisms of resistance for a critical mass of occurrences. Recent genome editing technologies based on high-throughput DNA synthesis and sequencing may help to predict mutations resulting in resistance by testing large mutagenesis libraries. Here we describe the rationale of this approach, with examples and relevance to drug development and resistance in malaria.

59 BASIC BIOLOGICAL SCIENCES↗

Do Molecular Fingerprints Identify Diverse Active Drugs in Large-Scale Virtual Screening? (No)

Computational approaches for small-molecule drug discovery now regularly scale to the consideration of libraries containing billions of candidate small molecules. One promising approach to increased the speed of evaluating billion-molecule libraries is to develop succinct representations of each molecule that enable the rapid identification of molecules with similar properties. Molecular fingerprints are thought to provide a mechanism for producing such representations. Here, we explore the utility of commonly used fingerprints in the context of predicting similar molecular activity. We show that fingerprint similarity provides little discriminative power between active and inactive molecules for a target protein based on a known active—while they may sometimes provide some enrichment for active molecules in a drug screen, a screened data set will still be dominated by inactive molecules. We also demonstrate that high-similarity actives appear to share a scaffold with the query active, meaning that they could more easily be identified by structural enumeration. Furthermore, even when limited to only active molecules, fingerprint similarity values do not correlate with compound potency. In sum, these results highlight the need for a new wave of molecular representations that will improve the capacity to detect biologically active molecules based on their similarity to other such molecules.

59 BASIC BIOLOGICAL SCIENCES↗

Molecular Epidemiology of HIV-1 in Ghana: Subtype Distribution, Drug Resistance and Coreceptor Usage

The greatest HIV-1 genetic diversity is found in West/Central Africa due to the pandemic’s origins in this region, but this diversity remains understudied. We characterized HIV-1 subtype diversity (from both sub-genomic and full-genome viral sequences), drug resistance and coreceptor usage in 103 predominantly (90%) antiretroviral-naive individuals living with HIV-1 in Ghana. Full-genome HIV-1 subtyping confirmed the circulating recombinant form CRF02_AG as the dominant (53.9%) subtype in the region, with the complex recombinant 06_cpx (4%) present as well. Unique recombinants, most of which were mosaics containing CRF02_AG and/or 06_cpx, made up 37% of sequences, while “pure” subtypes were rare (<6%). Pretreatment resistance to at least one drug class was observed in 17% of the cohort, with NNRTI resistance being the most common (12%) and INSTI resistance being relatively rare (2%). CXCR4-using HIV-1 sequences were identified in 23% of participants. Overall, our findings advance our understanding of HIV-1 molecular epidemiology in Ghana. Extensive HIV-1 genetic diversity in the region appears to be fueling the ongoing creation of novel recombinants, the majority CRF02_AG-containing, in the region. The relatively high prevalence of pretreatment NNRTI resistance but low prevalence of INSTI resistance supports the use of INSTI-based first-line regimens in Ghana.

59 BASIC BIOLOGICAL SCIENCES↗

The development of Nanosota-1 as anti-SARS-CoV-2 nanobody drug candidates

Combating the COVID-19 pandemic requires potent and low-cost therapeutics. We identified a series of single-domain antibodies (i.e., nanobody), Nanosota-1, from a camelid nanobody phage display library. Structural data showed that Nanosota-1 bound to the oft-hidden receptor-binding domain (RBD) of SARS-CoV-2 spike protein, blocking viral receptor angiotensin-converting enzyme 2 (ACE2). The lead drug candidate possessing an Fc tag (Nanosota-1C-Fc) bound to SARS-CoV-2 RBD ~3000 times more tightly than ACE2 did and inhibited SARS-CoV-2 pseudovirus ~160 times more efficiently than ACE2 did. Administered at a single dose, Nanosota-1C-Fc demonstrated preventive and therapeutic efficacy against live SARS-CoV-2 infection in both hamster and mouse models. Unlike conventional antibodies, Nanosota-1C-Fc was produced at high yields in bacteria and had exceptional thermostability. Pharmacokinetic analysis of Nanosota-1C-Fc documented an excellent in vivo stability and a high tissue bioavailability. As effective and inexpensive drug candidates, Nanosota-1 may contribute to the battle against COVID-19.

60 APPLIED LIFE SCIENCES↗