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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Diagnostic, Prognostic, and Therapeutic Use of Radiopharmaceuticals in the Context of SARS-CoV-2

The coronavirus disease 2019 (COVID-19) outbreak has devastated the healthcare systems and economies of over 200 countries in just a few months. The etiological agent of COVID-19, SARS-CoV-2, is a highly contagious virus that can be transmitted by asymptomatic and symptomatic carriers alike. While in vitro testing techniques have allowed for population-wide screening, prognostic tools are required to assess the disease severity and therapeutic response, contributing to improve the patient clinical outcomes. Moreover, no specific antiviral against COVID-19 exists at the time of publication, severely limiting treatment against the infection. Hence, there is an urgent clinical need for innovative therapeutic strategies that may contribute to manage the COVID-19 outbreak and prevent future pandemics. In this work, we critically examine recent diagnostic, prognostic, and therapeutic advancements for COVID-19 in the field of radiopharmaceuticals. First, we summarize the gold standard techniques used to diagnose COVID-19, including in vitro assays and imaging techniques, and then discuss how radionuclide-based nuclear imaging provides complementary information for prognosis and treatment management of infected patients. Second, we introduce new emerging types of radiotherapies that employ radioimmunoconjugates, which have shown selective cytotoxic response in oncological studies, and critically analyze how these compounds could be used as therapeutic agents against SARS-CoV-2. Finally, this Perspective further discusses the emerging applications of radionuclides to study the behavior of pulmonary SARS-CoV-2 aerosol particles.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

A robust and interpretable machine learning approach using multimodal biological data to predict future pathological tau accumulation

The early stages of Alzheimer’s disease (AD) involve interactions between multiple pathophysiological processes. Although these processes are well studied, we still lack robust tools to predict individualised trajectories of disease progression. Here, we employ a robust and interpretable machine learning approach to combine multimodal biological data and predict future pathological tau accumulation. In particular, we use machine learning to quantify interactions between key pathological markers (β-amyloid, medial temporal lobe atrophy, tau and APOE 4) at mildly impaired and asymptomatic stages of AD. Using baseline non-tau markers we derive a prognostic index that: (a) stratifies patients based on future pathological tau accumulation, (b) predicts individualised regional future rate of tau accumulation, and (c) translates predictions from deep phenotyping patient cohorts to cognitively normal individuals. Our results propose a robust approach for fine scale stratification and prognostication with translation impact for clinical trial design targeting the earliest stages of AD.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Testing at scale during the COVID-19 pandemic

Assembly and publication of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome in January 2020 enabled the immediate development of tests to detect the new virus. This began the largest global testing programme in history, in which hundreds of millions of individuals have been tested to date. The unprecedented scale of testing has driven innovation in the strategies, technologies and concepts that govern testing in public health. In this Review, we describe the changing role of testing during the COVID-19 pandemic, including the use of genomic surveillance to track SARS-CoV-2 transmission around the world, the use of contact tracing to contain disease outbreaks and testing for the presence of the virus circulating in the environment. Despite these efforts, widespread community transmission has become entrenched in many countries and has required the testing of populations to identify and isolate infected individuals, many of whom are asymptomatic. The diagnostic and epidemiological principles that underpin such population-scale testing are also considered, as are the high-throughput and point-of-care technologies that make testing feasible on a massive scale.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Orthologs of human circulating miRNAs associated with hepatocellular carcinoma are elevated in mouse plasma months before tumour detection

Research examining the potential for circulating miRNA to serve as markers for preneoplastic lesions or early-stage hepatocellular carcinoma (HCC) is hindered by the difficulties of obtaining samples from asymptomatic individuals. As a surrogate for human samples, we identified hub miRNAs in gene co-expression networks using HCC-bearing C3H mice. We confirmed 38 hub miRNAs as associated with HCC in F2 hybrid mice derived from radiogenic HCC susceptible and resistant founders. When compared to a panel of 12 circulating miRNAs associated with human HCC, two had no mouse ortholog and 7 of the remaining 10 miRNAs overlapped with the 38 mouse HCC hub miRNAs. Using small RNA sequencing data generated from serially collected plasma samples in F2 mice, we examined the temporal levels of these 7 circulating miRNAs and found that the levels of 4 human circulating markers, miR-122-5p, miR-100-5p, miR-34a-5p and miR-365-3p increased linearly as the time approaching HCC detection neared, suggesting a correlation of miRNA levels with oncogenic progression. Estimation of change points in the kinetics of the 4 circulating miRNAs suggested the changes started 17.5 to 6.8 months prior to HCC detection. These data establish these 4 circulating miRNAs as potential sentinels for preneoplastic lesions or early-stage HCC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A simple model of COVID-19 explains disease severity and the effect of treatments

Abstract Considerable effort has been made to better understand why some people suffer from severe COVID-19 while others remain asymptomatic. This has led to important clinical findings; people with severe COVID-19 generally experience persistently high levels of inflammation, slower viral load decay, display a dysregulated type-I interferon response, have less active natural killer cells and increased levels of neutrophil extracellular traps. How these findings are connected to the pathogenesis of COVID-19 remains unclear. We propose a mathematical model that sheds light on this issue by focusing on cells that trigger inflammation through molecular patterns: infected cells carrying pathogen-associated molecular patterns (PAMPs) and damaged cells producing damage-associated molecular patterns (DAMPs). The former signals the presence of pathogens while the latter signals danger such as hypoxia or lack of nutrients. Analyses show that SARS-CoV-2 infections can lead to a self-perpetuating feedback loop between DAMP expressing cells and inflammation, identifying the inability to quickly clear PAMPs and DAMPs as the main contributor to hyperinflammation. The model explains clinical findings and reveal conditions that can increase the likelihood of desired clinical outcome from treatment administration. In particular, the analysis suggest that antivirals need to be administered early during infection to have an impact on disease severity. The simplicity of the model and its high level of consistency with clinical findings motivate its use for the formulation of new treatment strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Simulating nationwide coupled disease and fear spread in an agent-based model

Human cognitive responses, behavioral responses, and disease dynamics co-evolve over the course of any disease outbreak, and can result in complex feedbacks. We present a dynamic agent-based model that explicitly couples the spread of disease with the spread of fear surrounding the disease, implemented within the EpiCast simulation framework. EpiCast models transmission within a realistic synthetic population, capturing individual-level interactions. In our model, fear propagates through both in-person contact and broadcast media, prompting individuals to adopt protective behaviors that reduce disease spread. In order to better understand these coupled dynamics, we create and compare a range of compartmental models to ensure that introducing additional disease states does not prevent the emergence of multiple waves in these simpler models. Additionally, we compare a range of behavioral scenarios within EpiCast, varying the level and intensity of fear and behavior change. Our results show that the addition of asymptomatic, exposed, and pre-symptomatic disease states can impact both the rate at which an outbreak progresses and its overall trajectory in compartmental models. In EpiCast, the combination of non-local fear spread via broadcasters and strong behavioral responses by fearful individuals generally leads to multiple epidemic waves, an outcome that occurs only within a narrow parameter range when fear spreads purely through local contact. Accounting for the coupled spread of fear and disease is critical for understanding disease dynamics and designing timely, targeted responses to emerging infectious threats.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Structural basis for Zika envelope domain III recognition by a germline version of a recurrent neutralizing antibody

Recent epidemics demonstrate the global threat of Zika virus (ZIKV), a flavivirus transmitted by mosquitoes. Although infection is usually asymptomatic or mild, newborns of infected mothers can display severe symptoms, including neurodevelopmental abnormalities and microcephaly. Given the large-scale spread, symptom severity, and lack of treatment or prophylaxis, a safe and effective ZIKV vaccine is urgently needed. However, vaccine design is complicated by concern that elicited antibodies (Abs) may cross-react with other flaviviruses that share a similar envelope protein, such as dengue virus, West Nile virus, and yellow fever virus. This cross-reactivity may worsen symptoms of a subsequent infection through Ab-dependent enhancement. To better understand the neutralizing Ab response and risk of Ab-dependent enhancement, further information on germline Ab binding to ZIKV and the maturation process that gives rise to potently neutralizing Abs is needed. In this work, we use binding and structural studies to compare mature and inferred-germline Ab binding to envelope protein domain III of ZIKV and other flaviviruses. We show that affinity maturation of the light-chain variable domain is important for strong binding of the recurrent VH3-23/VK1-5 neutralizing Abs to ZIKV envelope protein domain III, and identify interacting residues that contribute to weak, cross-reactive binding to West Nile virus. These findings provide insight into the affinity maturation process and potential cross-reactivity of VH3-23/VK1-5 neutralizing Abs, informing precautions for protein-based vaccines designed to elicit germline versions of neutralizing Abs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Integrating Public Health Surveillance and Environmental Data to Model Presence of Histoplasma in the United States

In the United States, the true geographic distribution of the environmental fungus Histoplasma capsulatum remains poorly understood but appears to have changed since it was first characterized. Histoplasmosis is caused by inhalation of the fungus and can range in severity from asymptomatic to life-threatening. Due to limited public health surveillance and under detection of infections, it is challenging to directly use reported case data to characterize spatial risk. Using monthly and yearly county-level public health surveillance data and various environmental and socioeconomic characteristics, we use a spatio-temporal occupancy model to estimate latent, or unobserved, presence of H. capsulatum , accounting for imperfect detection of histoplasmosis cases. We estimate areas with higher probabilities of the presence of H. capsulatum in the East North Central states around the Great Lakes, reflecting a shift of the endemic region to the north from previous estimates. The presence of H. capsulatum was strongly associated with higher soil nitrogen levels. In this investigation, we were able to mitigate challenges related to reporting and illustrate a shift in the endemic region from historical estimates. This work aims to help inform future surveillance needs, clinical awareness, and testing decisions for histoplasmosis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Rapid assessment of beech leaf disease in Fagus sylvatica buds

Abstract The European beech (Fagus sylvatica) is threatened by the foliar nematodeLitylenchus crenataesubsp.mccannii(Lcm), the causal agent of beech leaf disease (BLD). Thus far, the majority of studies regarding BLD have focused on American beech (F. grandifolia). To better determine the impact of Lcm in buds of European beech, a total of 54 buds were collected from naturally symptomatic trees. Here, we characterized for the first time the bud scale morphology of two different cultivars ofF. sylvaticainfected with Lcm. Detailed observations of asymptomatic and symptomatic bud scales provided insight into the physical changes and arrangements of cells in the bud scale, shedding light on the dynamic processes occurring during Lcm infection. In addition, we evaluated the suitability of using the bud scale morphology for the early detection of BLD and Lcm in naturally infected buds. The distinct cellular arrangement of symptomatic bud scales cells (i.e., asymmetric pattern of enlarged cells) provides a rapid and visual, user‐friendly methodology to prematurely diagnose BLD symptoms within the buds, as well as the detection of associated nematodes.

Forestry↗
DOE OSTI2024

Spatiotemporal analysis of lung immune dynamics in lethal Coccidioides posadasii infection

Coccidioidomycosis, or Valley fever, is a lung disease caused by inhalation of Coccidioides fungi, prevalent in the Southwestern United States, Mexico, and parts of Central and South America. Annually, the United States reports 10,000–20,000 cases, although those numbers are expected to increase as climate change expands the fungal geographic range. While 60% of infections are asymptomatic, 40% symptomatic infections are often misdiagnosed due to similarities with bronchitis or pneumonia. A small subset of infection progress to severe illness, necessitating a better understanding of immune responses during lethal infection. Using single-cell RNA sequencing and spatial transcriptomics, we characterized lung responses during Coccidioides infection. We identified monocyte-derived Spp1-expressing macrophages as potential mediators of tissue remodeling and fibrosis, marked by high expression of profibrotic and proinflammatory transcripts. These macrophages showed elevated TGF-β and IL-6 signaling, pathways involved in fibrosis pathogenesis. Additionally, we observed significant neutrophil infiltration and defective lymphocyte responses, indicating severe adaptive immunity dysregulation in lethal, acute infection. These findings enhance our understanding of Coccidioides infection and suggest new therapeutic targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Field expedient stool collection methods for gut microbiome analysis in deployed military environments

ABSTRACT Field expedient devices and protocols for the collection, storage, and shipment of stool samples in deployed settings are needed for the advancement of microbiome research in military health. Relevant assessments include the evaluation of microbiome signatures associated with susceptibility to travelers’ diarrhea and recovery of gut function following infection. However, inherent biases in microbial measurements due to preservatives and sampling methods are unclear and should be assessed for an accurate evaluation of the microbiome. We performed shotgun metagenomic sequencing and compared the microbiome composition in paired fecal samples collected using Flinters Technology Associates (FTA) cards and OMNIgene (OG) Gut tubes, prior to and during international travel, from 49 adult participants, 39 of whom remained asymptomatic and 10 experienced travelers’ diarrhea. Higher concentrations of nucleic acid and sequencing libraries were observed in OG samples. A majority of genera (82.9%) were detected with both methods, and detections of genera limited to one collection method were not highly prevalent across samples and were present in extremely low relative abundances (<0.01%). Differences in beta diversity were largely explained by inter-individuality of microbiome composition, followed by the effect of collection method and timepoint-disease states. Differential abundance analysis indicated that Corynebacterium and Blautia were consistently higher in abundance across all groups with FTA and OG collection, respectively. The observed differences in microbiome composition between methods suggest the need for consistent and standardized protocols within a study. Overall, the data presented here could help guide the future design of fecal microbiome study protocols in field and military deployment settings. IMPORTANCE The assessment of field-deployable methods for fecal sample collection and storage is required to reliably capture samples collected in remote and austere locations. This study describes a comparative metagenomics analysis between samples collected by two different commercially available methods in a military-deployed setting. The results presented here are foundational for the future design of fecal microbiome study protocols in an operational context.

field study↗
DOE OSTI2025

Early immune response to Coccidioides is characterized by robust neutrophil and fibrotic macrophage recruitment and differentiation

Coccidioidomycosis, or Valley fever, is an emerging respiratory disease caused by soil-dwelling fungi of the Coccidioides genus that is expected to spread from the southwest into the central U.S. by 2050. While 60% of infections are asymptomatic, the other 40% of patients experience a range of symptoms, from self-limiting pneumonia to life-threatening disseminated disease. The immunological events that underlie the progression to severe disease remain underdefined. Here, we probed the early immune response to Coccidioides using a high dose of an attenuated strain of Coccidioides posadasii in a mouse model of infection coupled with single-cell RNA sequencing. At 24 h post-infection, robust immune infiltration is detected in the lung, marked by high levels of inflammatory PD-L1 + neutrophils and fungal-contact-dependent pro-fibrotic Spp1 + macrophages. These findings elucidate the early dynamics of the host response to Coccidioides and provide a deeper understanding of host-pathogen interactions in the lung.

Coccidioides↗
DOE OSTI2024

How do deer respiratory epithelial cells weather the initial storm of SARS-CoV-2 WA1/2020 strain?

The potential infectivity of severe acute respiratory syndrome associated coronavirus-2 (SARS-CoV-2) in animals raises a public health and economic concern, particularly the high susceptibility of white-tailed deer (WTD) to SARS-CoV-2. The disparity in the disease outcome between humans and WTD is very intriguing, as the latter are often asymptomatic, subclinical carriers of SARS-CoV-2. To date, no studies have evaluated the innate immune factors responsible for the contrasting SARS-CoV-2-associated disease outcomes in these mammalian species. A comparative transcriptomic analysis in primary respiratory epithelial cells of human (HRECs) and WTD (Deer-RECs) infected with the SARS-CoV-2 WA1/2020 strain was assessed throughout 48 h post inoculation (hpi). Both HRECs and Deer-RECs were susceptible to virus infection, with significantly ( P < 0.001) lower virus replication in Deer-RECs. The number of differentially expressed genes (DEG) gradually increased in Deer-RECs but decreased in HRECs throughout the infection. The ingenuity pathway analysis of DEGs further identified that genes commonly altered during SARS-CoV-2 infection mainly belong to cytokine and chemokine response pathways mediated via interleukin-17 (IL-17) and nuclear factor-κB (NF-κB) signaling pathways. Inhibition of the NF-κB signaling in the Deer-RECs pathway was predicted as early as 6 hpi. The findings from this study could explain the lack of clinical signs reported in WTD in response to SARS-CoV-2 infection as opposed to the severe clinical outcomes reported in humans. IMPORTANCE. This study demonstrated that human and white-tailed deer primary respiratory epithelial cells are susceptible to the SARS-CoV-2 WA1/2020 strain infection. However, the comparative transcriptomic analysis revealed that deer cells could limit viral replication without causing hypercytokinemia by downregulating IL-17 and NF-κB signaling pathways. Identifying differentially expressed genes in human and deer cells that modulate key innate immunity pathways during the early infection will lead to developing targeted therapies toward preventing or mitigating the “cytokine storm” often associated with severe cases of coronavirus disease 19 (COVID-19). Moreover, results from this study will aid in identifying novel prognostic biomarkers in predicting SARS-CoV-2 adaption and transmission in deer and associated cervids.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Comprehensive compartmental model and calibration algorithm for the study of clinical implications of the population-level spread of COVID-19: a study protocol

The complex dynamics of the coronavirus disease 2019 (COVID-19) pandemic has made obtaining reliable long-term forecasts of the disease progression difficult. Simple mechanistic models with deterministic parameters are useful for short-term predictions but have ultimately been unsuccessful in extrapolating the trajectory of the pandemic because of unmodelled dynamics and the unrealistic level of certainty that is assumed in the predictions. We propose a 22-compartment epidemiological model that includes compartments not previously considered concurrently, to account for the effects of vaccination, asymptomatic individuals, inadequate access to hospital care, post-acute COVID-19 and recovery with long-term health complications. Additionally, new connections between compartments introduce new dynamics to the system and provide a framework to study the sensitivity of model outputs to several concurrent effects, including temporary immunity, vaccination rate and vaccine effectiveness. Subject to data availability for a given region, we discuss a means by which population demographics (age, comorbidity, socioeconomic status, sex and geographical location) and clinically relevant information (different variants, different vaccines) can be incorporated within the 22-compartment framework. Considering a probabilistic interpretation of the parameters allows the model's predictions to reflect the current state of uncertainty about the model parameters and model states. We propose the use of a sparse Bayesian learning algorithm for parameter calibration and model selection. This methodology considers a combination of prescribed parameter prior distributions for parameters that are known to be essential to the modelled dynamics and automatic relevance determination priors for parameters whose relevance is questionable. This is useful as it helps prevent overfitting the available epidemiological data when calibrating the parameters of the proposed model. Population-level administrative health data will serve as partial observations of the model states.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Alternative SIAR models for infectious diseases and applications in the study of non-compliance

In this paper, we use modified versions of the SIAR model for epidemics to propose two ways of understanding and quantifying the effect of non-compliance to non-pharmaceutical intervention measures on the spread of an infectious disease. The SIAR model distinguishes between symptomatic infected (I) and asymptomatic infected (A) populations. One modification, which is simpler, assumes a known proportion of the population does not comply with government mandates such as quarantining and social-distancing. In a more sophisticated approach, the modified model treats non-compliant behavior as a social contagion. We theoretically explore different scenarios such as the occurrence of multiple waves of infections. Local and asymptotic analyses for both models are also provided.

Mathematics↗
DOE OSTI2024

Machine learning mathematical models for incidence estimation during pandemics

Accurate estimates of the incidence of infectious diseases are key for the control of epidemics. However, healthcare systems are often unable to test the population exhaustively, especially when asymptomatic and paucisymptomatic cases are widespread; this leads to significant and systematic under-reporting of the real incidence. Here, we propose a machine learning approach to estimate the incidence of a pandemic in real-time, using reported cases and the overall test rate. In particular, we use Bayesian symbolic regression to automatically learn the closed-form mathematical models that most parsimoniously describe incidence. We develop and validate our models using COVID-19 incidence values for nine different countries, confirming their ability to accurately predict daily incidence. Remarkably, despite the differences in epidemic trajectories and dynamics across countries, we find that a single model for all countries offers a more parsimonious description and is more predictive of actual incidence compared to separate models for each country. Our results show the potential to accurately model incidence in real-time using closed-form mathematical models, providing a valuable tool for public health decision-makers.

Fajardo-Fontiveros, Oscar (ORCID:0000000207058972)↗
DOE OSTI2021

Launching a saliva-based SARS-CoV-2 surveillance testing program on a university campus

Regular surveillance testing of asymptomatic individuals for SARS-CoV-2 has been center to SARS-CoV-2 outbreak prevention on college and university campuses. Here we describe the voluntary saliva testing program instituted at the University of California, Berkeley during an early period of the SARS-CoV-2 pandemic in 2020. The program was administered as a research study ahead of clinical implementation, enabling us to launch surveillance testing while continuing to optimize the assay. Results of both the testing protocol itself and the study participants’ experience show how the program succeeded in providing routine, robust testing capable of contributing to outbreak prevention within a campus community and offer strategies for encouraging participation and a sense of civic responsibility.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Temporal serum neurofilament light chain concentrations in sheep inoculated with the agent of classical scrapie

Objective: Neurofilament light chain (Nf-L) has been used to detect neuroaxonal damage in the brain caused by physical injury or disease. The purpose of this study was to determine if serum Nf-L could be used as a biomarker for pre-symptomatic detection of scrapie in sheep. Methods: Four sheep with prion protein genotype AVQQ were intranasally inoculated with the classical scrapie strain x124. Blood was collected every 4 weeks until 44 weeks post-inoculation, at which point weekly collection commenced. Serum was analyzed using single molecule array (Quanterix SR-X) to evaluate Nf-L concentrations. Results: Scrapie was confirmed in each sheep by testing homogenized brainstem at the level of the obex with a commercially available enzyme immunoassay. Increased serum Nf-L concentrations were identified above the determined cutoff during the last tenth of the respective incubation period for each sheep. Throughout the time course study, PrP Sc accumulation was not detected antemortem by immunohistochemistry in rectal tissue at any timepoint for any sheep. RT-QuIC results were inconsistently positive throughout the timepoints tested for each sheep; however, each sheep had at least one timepoint detected positive. When assessing serum Nf-L utility using receiver operator characteristic curves against different clinical parameters, such as asymptomatic and symptomatic (pruritus or neurologic signs), results showed that Nf-L was most useful at being an indicator of disease only late in disease progression when neurologic signs were present. Conclusion: Serum Nf-L concentrations in the cohort of sheep increased as disease progressed; however, serum Nf-L did not increase during the presymptomatic window. The levels increased substantially throughout the final 10% of the animals’ scrapie incubation period when other clinical signs were present. Serum Nf-L is not a reliable biomarker for pre-clinical detection of scrapie.

59 BASIC BIOLOGICAL SCIENCES↗