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DOE OSTI2022

Predictive Risk Mapping of Schistosomiasis in Madagascar Using Ecological Niche Modeling and Precision Mapping

Schistosomiasis is a neglected tropical disease (NTD) found throughout tropical and subtropical Africa. In Madagascar, the condition is widespread and endemic in 74% of all administrative districts in the country. Despite the significant burden of the disease, high-resolution risk maps have yet to be produced to guide national control programs. This study used an ecological niche modeling (ENM) and precision mapping approach to estimate environmental suitability and disease transmission risk. The results show that suitability for schistosomiasis is widespread and covers 264,781 km 2 (102,232 sq miles). Covariates of significance to the model were the accessibility to cities, distance to water, enhanced vegetation index (EVI), annual mean temperature, land surface temperature (LST), clay content, and annual precipitation. Disease transmission risk is greatest in the central highlands, tropical east coast, arid-southwest, and northwest. An estimated 14.9 million people could be at risk of schistosomiasis; 11.4 million reside in rural areas, while 3.5 million are in urban areas. This study provides valuable insight into the geography of schistosomiasis in Madagascar and its potential risk to human populations. Because of the focal nature of the disease, these maps can inform national surveillance programs while improving understanding of areas in need of medical interventions.

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 OSTI2024

Site-specific acetylation of polynucleotide kinase 3'-phosphatase regulates its distinct role in DNA repair pathways

Mammalian polynucleotide kinase 3'-phosphatase (PNKP), a DNA end-processing enzyme with 3'-phosphatase and 5'-kinase activities, is involved in multiple DNA repair pathways, including base excision (BER), single-strand break (SSBR), and double-strand break repair (DSBR). However, little is known as to how PNKP functions in such diverse repair processes. Here we report that PNKP is acetylated at K142 (AcK142) by p300 constitutively but at K226 (AcK226) by CBP, only after DSB induction. Co-immunoprecipitation analysis using AcK142 or AcK226 PNKP-specific antibodies showed that AcK142-PNKP associates only with BER/SSBR, and AcK226 PNKP with DSBR proteins. Despite the modest effect of acetylation on PNKP’s enzymatic activity in vitro, cells expressing non-acetylable PNKP (K142R or K226R) accumulated DNA damage in transcribed genes. Intriguingly, in striatal neuronal cells of a Huntington's Disease (HD)-based mouse model, K142, but not K226, was acetylated. This is consistent with the reported degradation of CBP, but not p300, in HD cells. Moreover, transcribed genomes of HD cells progressively accumulated DSBs. Chromatin-immunoprecipitation analysis demonstrated the association of Ac-PNKP with the transcribed genes, consistent with PNKP’s role in transcription-coupled repair. Thus, our findings demonstrate that acetylation at two lysine residues, located in different domains of PNKP, regulates its distinct role in BER/SSBR versus DSBR.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Outbreak analysis from case count and survey data

This code enables fitting a model of an infectious disease outbreak, customized for when available data is a combination of case counts and symptom survey responses. This is just a small bit of code being used only for a publication; we need to release it to fulfill a journal's requirement that our work be reproducible.

Goldberg, Emma↗

DOE OSTI2020

Sandia's Research in Support of COVID-19 Pandemic Response: Computing and Information Sciences

This report summarizes the goals and findings of eight research projects conducted under the Computing and Information Sciences (CIS) Research Foundation and related to the COVID- 19 pandemic. The projects were all formulated in response to Sandia's call for proposals for rapid-response research with the potential to have a positive impact on the global health emergency. Six of the projects in the CIS portfolio focused on modeling various facets of disease spread, resource requirements, testing programs, and economic impact. The two remaining projects examined the use of web-crawlers and text analytics to allow rapid identification of articles relevant to specific technical questions, and categorization of the reliability of content. The portfolio has collectively produced methods and findings that are being applied by a range of state, regional, and national entities to support enhanced understanding and prediction of the pandemic's spread and its impacts.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Plant Bioengineering Atlas: A Knowledge Graph of Genes, DNA Constructs, and Plant Traits.

Plant bioengineering has generated tens of thousands of genotype-to-phenotype relationships, but this knowledge remains fragmented across narrative literature and difficult to use computationally. Inconsistent descriptions of DNA constructs, host species, and traits, including variable species names, omitted regulatory elements, and inconsistent gene symbols, impede data reuse, comparative analysis, and design-build-test-learn cycles. Here, we present the Plant Bioengineering Atlas, a literature-mined, ontology-grounded knowledge base assembled using an artificial intelligence (AI)-aided extraction pipeline. A large language model parsed open-access primary research articles to generate structured, provenance-anchored records of engineered genes, modification types, promoter-gene-terminator constructs, host species, target traits, and reported phenotypes, with every record traceable to its source. The current release contains 14,358 curated records encompassing 6,998 distinct genes across 436 plant species from 6,452 papers published between 2000 and 2026. Corpus analysis reveals that experiments are concentrated in a small group of model and crop species, disease and pathogen resistance is the most frequently engineered trait class, and constitutive regulatory parts (particularly the CaMV 35S promoter and NOS terminator) remain pervasive. Two in five records omit one or both flanking regulatory elements (i.e., promoter and terminator), while only 23.4% describe cassettes in which both elements resolve to named part classes, exposing a systematic reproducibility gap. We organize these data into a knowledge graph linking genes, constructs, species, and traits; provide access through an interactive web portal; and propose an AI-compatible documentation standard for AI-ready reporting. The Plant Bioengineering Atlas provides a foundation for data-driven hypothesis generation and AI-aided plant biodesign.

, Genes, DNA Constructs↗

NASA NTRS1988

Applicability of mathematical modeling to problems of environmental physiology

The paper traces the evolution of mathematical modeling and systems analysis from terrestrial research to research related to space biomedicine and back again to terrestrial research. Topics covered include: power spectral analysis of physiological signals; pattern recognition models for detection of disease processes; and, computer-aided diagnosis programs used in conjunction with a special on-line biomedical computer library.

White, Ronald J.↗

NASA NTRS1988

Terrestrial implications of mathematical modeling developed for space biomedical research

This paper summarizes several related research projects supported by NASA which seek to apply computer models to space medicine and physiology. These efforts span a wide range of activities, including mathematical models used for computer simulations of physiological control systems; power spectral analysis of physiological signals; pattern recognition models for detection of disease processes; and computer-aided diagnosis programs.

Lujan, Barbara F.↗

NASA NTRS1998

Role of Dendritic Cells in Immune Dysfunction

The specific aims of the project were: (1) Application of the NASA bioreactor to enhance cytokine-regulated proliferation and maturation of dendritic cells (DC). (2) Compare the frequency and function of DC in normal donors and immunocompromised cancer patients. (3) Analyze the effectiveness of cytokine therapy and DC-assisted immunotherapy (using bioreactor-expanded DC) in a murine model of experimental fungal disease. Our investigations have provided new insight into DC immunobiology and have led to the development of methodology to evaluate DC in blood of normal donors and patients. Information gained from these studies has broadened our understanding of possible mechanisms involved in the immune dysfunction of space travelers and earth-bound cancer patients, and could contribute to the design of novel therapies to restore/preserve immunity in these individuals. Several new avenues of investigation were also revealed. The results of studies completed during Round 2 are summarized.

Savary, Cherylyn A.↗

NASA NTRS2001

Chronic mitral regurgitation and Doppler estimation of left ventricular filling pressures in patients with heart failure

Previous studies relating Doppler parameters and pulmonary capillary wedge pressures (PCWP) typically exclude patients with severe mitral regurgitation (MR). We evaluated the effects of varying degrees of chronic MR on the Doppler estimation of PCWP. PCWP and mitral Doppler profiles were obtained in 88 patients (mean age 55 +/- 8 years) with severe left ventricular (LV) dysfunction (mean ejection fraction 23% +/- 5%). Patients were classified by severity of MR. Patients with severe MR had greater left atrial areas, LV end-diastolic volumes, and mean PCWPs and lower ejection fractions (each P <.01). In patients with mild MR, multiple echocardiographic parameters correlated with PCWP; however, with worsening MR, only deceleration time strongly related to PCWP. From stepwise multivariate analysis, deceleration time was the best independent predictor of PCWP overall, and it was the only predictor in patients with moderate or severe MR. Doppler-derived early mitral deceleration time reliably predicts PCWP in patients with severe LV dysfunction irrespective of degree of MR.

NASA Discipline Cardiopulmonary↗

NASA NTRS2011

Contribution of Spaceflight Environmental Factors to Vision Risks

The risk of visual impairment and elevated intracranial pressure as a result of low-earth orbit microgravity exposure has directed our attention and research efforts to the eye. While the alterations observed in astronauts returning from long duration missions include vision and neuroanatomical changes observed by non-invasive methods, other effects and subsequent tissue responses at the molecular and cellular level can only be studied by accessing the tissue itself. As a result of this need, several studies are currently taking place within the Human and Health Countermeasures Element (HHC) that use animal models for eye research. The rodent eye has many similarities to the human eye, and both rats and mice have historically been used as models of human eye disease, aiding in the identification of the disease genes, elucidation of mechanisms of disease, as well as in the assessment of therapeutic treatments. These studies attempt to answer two central questions in the etiology of possible vision alterations in the environment of space exploration missions. The first is: what effects and response mechanisms take place in the different eye structures at the cellular and molecular level? The second question is directed to elucidate the contribution of the various environmental stressors (radiation, nutrition, fluid shift) to these effects. Collaborative approaches with internal and external investigators have allowed performing these studies in a most cost-effective fashion, providing preliminary data and laying the bases for testing further hypotheses in future and specifically designed animal experiments. From a study centered on the radioadaptive response in mice, we have learned that the retina responds to low and high dose gamma radiation by elevating antioxidant-related genes at early time points (4hrs) and that this response returns to control levels after 1 day post-irradiation. We are expanding this research with another collaborative study that investigates the combined effects of radiation exposure and iron overload on sensitivity to radiation injury in rat eyes. All main eye structures will be analyzed in this study: retina, lens and cornea. A study in collaboration with the Space Human Factors and Habitability Element (SHFH) investigates the effects of lunar dust exposure on the rat cornea. It is anticipated that common underlying oxidative stress mechanisms of damage may be observed as a result of these three stressors: radiation, nutritional iron and lunar dust. The contribution of fluid shift is addressed by a study using rats subjected to hindlimb suspension. The hypothesis to be tested in this study is that the mechanical stress imparted by the pressure differential across the optic disc and lamina cribosa will impact oxygenation (therefore causing oxidative stress and hypoxia) and cell survival. This study also includes the assessment of two nutritional antioxidant countermeasures: epigallocatechin gallate (green tea) and resveratrol. Finally, as a result of two successful tissue sharing efforts, we are proceeding with the analysis of eye samples of mice aboard two shuttle missions: STS-133 and STS-135. Results from the STS-133 study are presented in an independent abstract. Briefly, the results show that spaceflight represents a source of environmental stress that directly translates into oxidative and cellular stress in the retina. Similar analysis is also planned for the cornea. These samples add large value to our current vision research as they provide data on the direct effects of low-earth orbit spaceflight on eye structures and physiology.

Zanello, Susana B.↗

NASA NTRS2017

MS Non-Pharmacological Countermeasure to Decrease Landing Sickness and Improve Functional Performance While Disorientad

Upon return from spaceflight, a majority of crewmembers experience motion sickness (MS) symptoms. The interactions between crewmembers' adaptation to a gravitational transition, the performance decrements resulting from MS and/or use of promethazine (PMZ), and the constraints imposed by mission task demands could significantly challenge and limit an astronaut's ability to perform functional tasks during gravitational transitions. No operational countermeasure currently exists to mitigate the risks associated with these sensorimotor disturbances. Stochastic resonance (SR) can be thought of simply as "noise benefit" or an increase in information transfer by a system when in the presence of a non-zero level of noise. We have shown that low levels of stochastic vestibular stimulation (SVS) improve balance and locomotor performance due to SR (Goel et al. 2015, Mulavara et al. 2011, 2015). Additionally, a study in a 6-hydroxydopamine (6-OHDA) hemi-lesioned rat model of Parkinson's disease demonstrated improvements in locomotor activity after low-level SVS delivery possibly due to an increase in nigral gamma-aminobutyric acid (GABA) release in a dopamine independent way (Samoudi et al. 2012). SVS specifically increased GABA release on the lesioned, but not the intact side. These results suggest that SVS can cause targeted alterations of GABA release to affect performance of functional tasks. Activation of the GABA pathway is important in modulating MS and promoting adaptability (Cohen 2008). Magnusson et al. (2000) supported this finding by showing that the administration of a GABAB agonist caused a reversal of the symptoms that is normally seen after unilateral labyrinthectomy. Thus, GABA could play a significant role in reducing MS and promoting adaptability. We have taken advantage of the SR mechanism as a modulator of neurotransmitters to develop a unique SVS countermeasure system to mitigate MS symptoms and improve functional performance after landing. Healthy subjects (n=20) participated in two test sessions, one in which they received +/-400 microA of SVS and one where they received no stimulation (0 microA); the study design was counterbalanced. Subjects began by performing a series of four functional tasks 3-5 times as baseline measurements of task performance. Then, to induce MS, subjects walked an obstacle course with up-down reversing prisms. If they completed the course before achieving our pre-determined level of MS, they were asked to read a poster while making large up-down head movements to a metronome while still wearing the reversing prism goggles. Subjects were stopped every two minutes and asked to report their MS symptoms. Using the Pensacola Scale for motion sickness, test operators evaluated the level of MS of each subject. Once a subject reached an 8 on this scale, which is equivalent to mild malaise, or 30 minutes had passed since the start of the MS induction, this protocol was stopped. Finally, immediately after MS induction, subjects were asked to complete the four functional tasks again. Although, 100% of our subjects experienced at least one MS symptom, only 55% of our subjects experienced stomach awareness to any degree. Without SVS, only 40% of subjects lasted the full 30-minute MS induction protocol, while 65% of subjects lasted the full 30 minutes with SVS, which is nearly a significant increase (p=0.056). In addition, subjects showed significant improvement from baseline when performing a tandem walk and a prone-to-stand test immediately after the MS induction protocol was stopped but the stimulation level was continued. The results are promising and future work includes comparing MS progression between PMZ and SVS directly in subjects that are provoked to a minimum of nausea. Low levels of SVS stimulation may serve as a non-pharmacological countermeasure to replace or reduce the PMZ dosage requirements and concurrently improve functional performance during transitions to new gravitational environments after spaceflight.

Rosenberg, M. J. F.↗

NASA NTRS2017

Effects of Simulated Microgravity on a Host-Pathogen System

While it has been shown that decades of astronauts and cosmonauts can suffer from illnesses both during and after spaceflight, the underlying causes are still poorly understood, due in part to the fact that there are so many variables to consider when investigating the human immune system in a complex environment. Invertebrates have become popular models for studying human disease because they are cheap, highly amenable to experimental manipulation, and have innate immune systems with a high genetic similarity to humans. Fruit flies (Drosophila melanogaster) have been shown to experience a dramatic shift in immune gene expression following spaceflight, but are still able to fight off infections when exposed to bacteria. However, the common bacterial pathogen Serratia marcescens was shown to become more lethal to fruit flies after being cultured in space, suggesting that not only do we need to consider host changes in susceptibility, but also changes in the pathogen itself after spaceflight conditions. Being able to simulate spaceflight conditions in a controlled environment on the ground gives us the ability to not only evaluate the effects of microgravity on the host immune system, but also how the microorganisms that cause immune disorders are being affected by these drastic environmental shifts. In this study, I use a ground-based simulated microgravity environment to examine the genetic changes associated with increased S. marcescens virulence in order to understand how microgravity is affecting this pathogen, as well as how these genetic changes influence and interact with the host immune system. This study will provide us with more directed approaches to studying the effects of spaceflight on human beings, with the ultimate goal of being able to counteract immune dysfunction in future space exploration.

Immunology↗

NASA NTRS2017

Studying the Effect of Radiation in the Context of Deep Space Travel

Bhattacharya, Sharmila↗

NASA NTRS2018

Effects of Simulated Microgravity on a Host-Pathogen System

While it has been shown that decades of astronauts and cosmonauts suffer from immune disorders both during and after spaceflight, the underlying causes are still poorly understood, due in part to the fact that there are so many variables to consider when investigating the human immune system in a complex environment. Invertebrates have become popular models for studying human disease because they are cheap, highly amenable to experimental manipulation, and have innate immune systems with a high genetic similarity to humans. Fruit flies (Drosophila melanogaster) have been shown to experience a dramatic shift in immune gene expression following spaceflight, but are still able to fight off infections when exposed to bacteria. Furthermore, a recent spaceflight mission showed that flies are more susceptible to infection following exposure to microgravity conditions, compared to ground-reared flies from the same population. Additionally, the common bacterial pathogen Serratia marcescens was shown to become more lethal to fruit flies (both space- and ground-reared) after being cultured in space, suggesting that not only do we need to consider host changes in susceptibility, but also changes in the pathogen itself after spaceflight conditions. Being able to simulate spaceflight conditions in a controlled environment on the ground gives us the ability to not only evaluate the effects of microgravity on the host immune system, but also how the microorganisms that cause immune disorders are being affected by these drastic environmental shifts. In this study, I use both spaceflight and ground-based (simulated microgravity) environments to examine the genetic changes associated with increased S. marcescens virulence in order to understand how microgravity is affecting this pathogen, as well as to evaluate how these genetic changes influence and interact with the host immune system. This study will provide us with more directed approaches to studying the effects of spaceflight on human beings, with the ultimate goal of being able to ameliorate human immune dysfunction in future space exploration.

Immunology↗

NASA NTRS2022

Present-Day and Future PM 2.5 and O 3 -Related Global and Regional Premature Mortality in the EVAv6.0 Health Impact Assessment Model

We used the EVAv6.0 system to estimate the present (2015) and future (2015–2050) global PM 2.5 and O 3 -related premature mortalities, using simulated surface concentrations from the GISS-E2.1-G Earth system model. The PM 2.5 -related global premature mortality is estimated to be 4.3 and 4.4 million by the non-linear and linear models, respectively. Ischemic heart diseases are found to be the leading cause of PM 2.5 -related premature deaths, contributing by 35% globally. Both long-term and short-term O 3 -related premature deaths are estimated to be around 1 million, globally. Overall, PM 2.5 and O 3 -related premature mortality leads to 5.3–5.4 million premature deaths, globally. The global burden of premature deaths is mainly driven by the Asian region, which in 2015 contributes by 75% of the total global premature deaths. An increase from 6.2% to 8% in the PM 2.5 relative risk as recommended by the WHO leads to an increase of PM 2.5 -related premature mortality by 28%, to 5.7 million. Finally, bias correcting the simulated PM 2.5 concentrations in 2015 leads to an increase of up to 73% in the global PM 2.5 -related premature mortality, leading to a total number of global premature deaths of up to 7.7 million, implying the necessity of bias correction to get more robust health burden estimates. PM 2.5 and O 3 -related premature mortality in 2050 decreases by up to 57% and 18%, respectively, due to emission reductions alone. However, the projected increase and aging of the population leads to increases of premature mortality by up to a factor of 2, showing that the population exposed to air pollution is more important than the level of air pollutants, highlighting that the population dynamics should be considered when setting up health assessment systems.

Premature mortality↗

DOE OSTI2021

Spatio-temporal Estimates of Disease Transmission Parameters for COVID-19 with a Fully-Coupled, County-Level Model of the United States

Sandia National Laboratories has developed a capability to estimate parameters of epidemiological models from case reporting data to support responses to the COVID-19 pandemic. A differentiating feature of this work is the ability to simultaneously estimate county-specific disease transmission parameters in a nation-wide model that considers mobility between counties. The approach is focused on estimating parameters in a stochastic SEIR model that considers mobility between model patches (i.e., counties) as well as additional infectious compartments. The inference engine developed by Sandia includes (1) reconstruction and (2) transmission parameter inference. Reconstruction involves estimating current population counts within each of the compartments in a modified SEIR model from reported case data. Reconstruction produces input for the inference formulations, and it provides initial conditions that can be used in other modeling and planning efforts. Inference involves the solution of a large-scale optimization problem to estimate the time profiles for the transmission parameters in each county. These provide quantification of changes in the transmission parameter over time (e.g., due to impact of intervention strategies). This capability has been implemented in a Python-based software package, epi_inference, that makes extensive use of Pyomo [5] and IPOPT [10] to formulate and solve the inference formulations.

42 ENGINEERING↗

DOE OSTI2021

PastoralScape: An Environment-Driven Model of Vaccination Decision Making Within Pastoralist Groups in East Africa

Economic and cultural resilience among pastoralists in East Africa is threatened by the interconnected forces of climate change, contagious diseases spread and evolving national and international trade. A key factor in the resilience of livestock that communities depend on is human decision making regarding vaccination against prevalent diseases such as Rift Valley fever and Contagious Bovine Pleuropneumonia. This paper describes an agent-based model that couples models of disease propagation, animal health, human decision making, and external GIS data sources capturing measures of foraging condition. We describe the design of the sub-models, their coupling, and demonstrate the sensitivity of the model to parameters that relate to controllable factors such as government and NGO information sources that can influence human decision making patterns. This model is intended to form the basis upon which richer economic and human factor models can be built.

97 MATHEMATICS AND COMPUTING↗