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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Agent-based Disease Surveillance and Transmission Model

The SARS-CoV-2 pandemic has driven a need for models that can predict transmission among populations and test the effectiveness of proposed interventions to control it such as testing, quarantining, vaccinations, and nonpharmaceutical interventions. Some questions of interest include:1. How rapidly will the virus spread if no action is taken? 2. How frequently should people be tested and quarantined if necessary? 3. Should unvaccinated persons be tested more frequently than the vaccinated? 4. If test results are delayed, how will that affect the spread? 5. How do test false negative rates affect the overall efficacy of testing programs? 6. How do constraints on testing resources impact the overall efficacy of testing programs? 7. How does the patient’s failure to recognize COVID symptoms and quarantine affect the spread? 8. What level of vaccination coverage is needed to suppress the epidemic? 9. What is the risk of a large outbreak (probability exceeding x infections)? 10. What is the cost effectiveness of interventions (dollars per avoided infection)? This report describes the structure of a discrete event simulation model that provides actionable information to address these questions. Parameter inputs and results of analyses have been reported in briefings provided to LLNL management and are not discussed here.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Building a Computational and Experimental Rapid Response Pipeline to Counter the Coronavirus Disease 2019 Outbreak and Emerging Biothreats

The COVID-19 pandemic underscored the promise of monoclonal antibody-based prophylactic and therapeutic drugs, especially where protective candidates can be rapidly identified or developed for emerging biothreats and escape variants. Current cutting-edge technologies for this purpose still rely on pathogen-exposed convalescent volunteers and a large screening effort to find a proverbial needle in a haystack. Computational design of protective antibodies based on pre-existing templates skips those requirements and allows for greater control over the breadth and target epitope, while also co-optimizing for potency and developability or other biophysical characteristics. We approached this problem by building and expanding an in vitro experimental rapid antibody production and characterization pipeline to support development of an autonomous, closed loop, active learning software system based on structural simulation and ground truth experimental data to design and evaluate antibody antigen interactions. Starting from early in the pandemic, we targeted SARS-CoV-2, the causative agent of COVID-19, by re-purposing neutralizing antibodies against SARS-CoV-1 that had been identified in the wake of that outbreak in the early 2000’s. We successfully re-targeted three different anti-SARS-CoV-1 antibodies to neutralize SARS-CoV-2 in vitro, where the antibodies were generated externally and tested through conventional binding and neutralization assays internally or with collaborators. As antibodies were identified from the blood of humans infected with SARS-CoV-2, we shifted to collaborate with academic partners to develop improved versions of their human-derived antibodies. This work reached its most important stage in rapid response to the emergence of the Omicron variant of concern (VOC) in late 2021. In a matter of weeks, enabled by on demand innovation to our screening pipeline, we computationally designed and experimentally characterized derivative antibodies of COV2-2130, one of two antibodies from Vanderbilt that form the basis of the AstraZeneca Evusheld prophylactic drug product. This drug product suffers a serious loss of efficacy against Omicron BA.1 and BA.1.1, the first Omicron strains. Due to tight integration of computational design and experimental evaluation, we were able to identify a pair of designs with potent neutralization of the main targets Omicron BA.1 and BA.1.1; but also the earlier Delta variant, and subsequent Omicron strains including BA.2, BA.4, BA.5, and BA.2.75, demonstrating that our multi-target design process can, by its nature, produce robust antibody designs that strictly improve over the parental antibody. These results, recognized by a 2022 Director’s Science and Technology award, have enabled the follow-on GUIDE program, to commence in FY23. While earlier design campaigns were substantially outsourced, we have engineered better and faster processes internally to better compliment, calibrate, and speed computational designs. As part of the follow-on GUIDE program, we will stand up a rapid and high-throughput antibody production and characterization facility staffed with the expertise and capabilities to foster our current collaboration across PLS and ENG as well as other partnerships toward computational design of biologics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Machine learning guided selection of broad-spectrum epitope-specific functional antibodies for "Disease X"

Our project established and demonstrated a transfer learning framework that enables prediction of antibody–antigen interactions across related viruses. The approach focused on three major activities: 1. Conserved region and epitope identification – We compared viral protein structures and sequences to identify shared receptor-binding domains and neutralizing epitope regions across variants and related viruses. These conserved features formed the foundation for discovering broadly functional antibodies. 2. Machine learning model development – We built neural network–based models that integrate epitope features with antibody sequence information. Instead of relying solely on structural or physical properties, the models learned transferable patterns that describe antibody binding potential across different viral families. 3. Transfer learning and validation – Using SARS-CoV-2 and Ebola as source systems, we successfully transferred learned epitope features to predict antibody interactions for SARS CoV-1 and Marburg virus. Iterative cycles of dataset generation, retraining, and evaluation improved generalization and predictive power, ensuring the framework can adapt to new threats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Relating Oxidative Protein Damage to Antioxidant Status in Health and Disease (Full Technical Report for 24-LW-026)

This two-year project evaluated how dietary antioxidants influence oxidative damage in cancer using complementary analytical and in-vivo approaches. We initially developed a protein oxidation labeling workflow and a parallel accelerator and molecular mass spectrometry (PAMMS) quantification method, but ultimately discontinued the labeling strategy due to unresolved separation challenges; PAMMS was instead leveraged to quantify radiolabeled catechol in rat plasma as a methodological benchmark. The biological study used a genetically engineered murine model (GEMM) for breast cancer (n = 40; four groups of 10: cancer/high antioxidant diet, cancer/normal diet, healthy/high-antioxidant diet, healthy/normal diet). In lieu of the abandoned labeling assay, untargeted metabolomics profiled plasma across groups, revealing widespread treatment-dependent changes in metabolites.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Placebo-resistant gut bacteria: Akkermansia muciniphila spp. and Familial Mediterranean fever disease

Introduction: Despite numerous investigations into the impact of drugs/probiotics on the gut microbiota composition in Familial Mediterranean Fever (FMF) patients, the question as to whether there exists a significant bacterial diversity(ies) independent of the placebo effect that can be reliably considered in clinical and nutritional trials remains unresolved. Methods: This study represents the in augural analysis of the placebo’s influence on the gut microbiota of both healthy individuals and FMF afflicted men, utilizing previously collected data from PhyloChip™ DNA microarray experiments. A total of 15 healthy and 15 FMF male volunteers, aged 18 to 50, participated in this partially randomized placebo trial, which is accessible through the GEO Series accession number GSE111835. Results and Discussion: Key findings from current investigations include i. the anticipated divergence in gut bacteria resistance to placebo between healthy and FMF individuals, ii. the minor impact of placebo on gut bacterial diversities in healthy individuals, with Enterobacteriaceae diversities identified as placebo-resistant among “healthy” gut bacteria, and iii. the comprehensive influence of placebo on all bacterial phyla in the gut microbiome of FMF patients, extending to nearly all bacterial genera, except for the resilience of gut Akkermansia muciniphila spp. to placebo in FMF patients. This study underscores the susceptibility of Faecalibacterium, Blautia, and Clostridium genera to placebo. Consequently, this investigation holds significance for the proper design of placebo-controlled trials and establishes a foundation for further exploration of the gut-brain axis. Furthermore, it contributes valuable insights to discussions regarding proposals for probiotic therapies, particularly focusing on Faecalibacterium spp., Blautia spp., and Clostridium spp.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Application of prophage sequence analysis to investigate a disease outbreak involving Salmonella Adjame, a rare serovar and implications for the population structure

Introduction Outbreak investigation of foodborne salmonellosis is hindered when the food source is contaminated by multiple strains of Salmonella , creating difficulties matching an incriminated organism recovered from patients with the specific strain in the suspect food. An outbreak of the rare Salmonella Adjame was caused by multiple strains of the organism as revealed by single-nucleotide polymorphism (SNP) variation. The use of highly discriminatory prophage analysis to characterize strains of Salmonella should enable a more precise strain characterization and aid the investigation of foodborne salmonellosis. Methods We have carried out genomic analysis of S. Adjame strains recovered during the course of a recent outbreak and compared them with other strains of the organism ( n = 38 strains), using SNPs to evaluate strain differences present in the core genome, and prophage sequence typing (PST) to evaluate the accessory genome. Phylogenetic analyses were performed using both total prophage content and conserved prophages. Results The PST analysis of the S. Adjame isolates showed a high degree of strain heterogeneity. We observed small clusters made up of 2-6 isolates ( n = 27) and singletons ( n = 11) in stark contrast with the three clusters observed by SNP analysis. In total, we detected 24 prophages of which only four were highly prevalent, namely: Entero_p88 (36/38 strains), Salmon_SEN34 (35/38 strains), Burkho_phiE255 (33/38 strains) and Edward_GF (28/38 strains). Despite the marked strain diversity seen with prophage analysis, the distribution of the four most common prophages matched the clustering observed using core genome. Discussion Mutations in the core and accessory genomes of S. Adjame have shed light on the evolutionary relationships among the Adjame strains and demonstrated a convergence of the variations observed in both fractions of the genome. We conclude that core and accessory genomes analyses should be adopted in foodborne bacteria outbreak investigations to provide a more accurate strain description and facilitate reliable matching of isolates from patients and incriminated food sources. The outcomes should translate to a better understanding of the microbial population structure and an 46 improved source attribution in foodborne illnesses.

Gao, Ruimin↗
DOE OSTI2020

Single-Atom Nanozymes Linked Immunosorbent Assay for Sensitive Detection of A β 1-40: A Biomarker of Alzheimer’s Disease

Single-atom nanozymes (SANs) possess unique features of maximum atomic utilization and present highly assembled enzyme-like structure and remarkable enzyme-like activity. By introducing SANs into immunoassay, limitations of ELISA such as low stability of horseradish peroxidase (HRP) can be well addressed, thereby improving the performance of the immunoassays. In this work, we have developed novel Fe-N-C single-atom nanozymes (Fe-N x SANs) derived from Fe-doped polypyrrole (PPy) nanotube and substituted the enzymes in ELISA kit for enhancing the detection sensitivity of amyloid beta 1-40. Results indicate that the Fe-N x SANs contain high density of single-atom active sites and comparable enzyme-like properties as HRP, owing to the maximized utilization of Fe atoms and their abundant active sites, which could mimic natural metalloproteases structures. Further designed SAN-linked immunosorbent assay (SAN-LISA) demonstrates the ultralow limit of detection (LOD) of 0.88 pg/mL, much more sensitive than that of commercial ELISA (9.98 pg/mL). The results confirm that the Fe-N x SANs can serve as a satisfactory replacement of enzyme labels, which show great potential as an ultrasensitive colorimetric immunoassay.

60 APPLIED LIFE SCIENCES↗