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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Artificial extracellular matrix scaffolds of mobile molecules enhance maturation of human stem cell-derived neurons

Human induced pluripotent stem cell (hiPSC) technologies offer a unique resource for modeling neurological diseases. However, iPSC models are fraught with technical limitations including abnormal aggregation and inefficient maturation of differentiated neurons. These problems are in part due to the absence of synergistic cues of the native extracellular matrix (ECM). We report on the use of three artificial ECMs based on peptide amphiphile (PA) supramolecular nanofibers. All nanofibers display the laminin-derived IKVAV signal on their surface but differ in the nature of their non-bioactive domains. Here, we find that nanofibers with greater intensity of internal supramolecular motion have enhanced bioactivity toward hiPSC-derived motor and cortical neurons. Proteomic, biochemical, and functional assays reveal that highly mobile PA scaffolds caused enhanced β1-integrin pathway activation, reduced aggregation, increased arborization, and matured electrophysiological activity of neurons. Our work highlights the importance of designing biomimetic ECMs to study the development, function, and dysfunction of human neurons.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Differentially Private Map Matching (DPMM) v1.0

Human mobility trajectories provide valuable information for developing mobility applications, as they contain diverse and rich information about the users. User mobility data is valuable for various applications such as intelligent transportation systems (ITS), commercial business models, and disease-spread models. However, such spatio-temporal traces may pose a threat to user privacy. GPS trajectories in their raw form are not suitable for transportation studies, as they require matching locations with nearest road links — a process called map-matching. This software implements a differential privacy (DP)-based map-matching algorithm, called DPMM, that generates link-level location trajectories in a privacy-preserving manner to protect users' origin destinations (OD) and travel paths. OD privacy is achieved by injecting Planar Laplace noise to the user OD GPS points. Travel-path privacy is provided with randomized travel path construction using exponential DP mechanism. The injected noise level is selected adaptively, by considering the link density of the location and the functional category of the localized links. For path privacy, our mechanism samples waypoints and selects candidate paths between waypoints. DPMM provides privacy effectively with respect to link density instead of other trajectory samples in the database compared to other privacy mechanisms. Compared to the different baseline models our DP-based privacy model offers closer query responses to the raw data in terms of individual and aggregate trajectory-level statistics with an average at absolute deviation from the baseline for individual statistics on ϵ = 1.0. Beyond individual trajectory statistics, the DPMM outperforms the other benchmark DP-based mechanisms on different aggregate statistics with up to 8x improvement in utility.

Peisert, Sean [Lawrence Berkeley National Laborato↗
DOE OSTI2021

Drosophila models to study causative genes for human rare intractable neurological diseases

Highlights: • Drosophila models targeting some ALS-causing genes are described. • Drosophila models targeting some CMT-causing genes are described. • Drosophila models targeting some Sotos syndrome-causing genes are described. • Genes and pathways that commonly interact with ALS- and/or CMT-causing genes are described. Drosophila is emerging as a convenient model for investigating human diseases. Functional homologues of almost 75% of human disease-related genes are found in Drosophila. Amyotrophic lateral sclerosis (ALS) is a severe neurodegenerative disease that causes defects in motoneurons. Charcot-Marie-Tooth disease (CMT) is one of the most commonly found inherited neuropathies affecting both motor and sensory neurons. No effective therapy has been established for either of these diseases. In this review, after overviewing ALS, Drosophila models targeting several ALS-causing genes, including TDP-43, FUS and Ubiquilin2, are described with their genetic interactants. Then, after overviewing CMT, examples of Drosophila models targeting several CMT-causing genes, including mitochondria-related genes and FIG 4, are also described with their genetic interactants. In addition, we introduce Sotos syndrome caused by mutations in the epigenetic regulator gene NSD1. Lastly, several genes and pathways that commonly interact with ALS- and/or CMT-causing genes are described. In the case of ALS and CMT that have many causative genes, it may be not practical to perform gene therapy for each of the many disease-causing genes. The possible uses of the common genes and pathways as novel diagnosis markers and effective therapeutic targets are discussed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Comparison of Routes of Administration, Frequency, and Duration of Favipiravir Treatment in Mouse and Guinea Pig Models of Ebola Virus Disease

Favipiravir is a ribonucleoside analogue that has been explored as a therapeutic for the treatment of Ebola Virus Disease (EVD). Promising data from rodent models has informed nonhuman primate trials, as well as evaluation in patients during the 2013–2016 West African EVD outbreak of favipiravir treatment. However, mixed results from these studies hindered regulatory approval of favipiravir for the indication of EVD. This study examined the influence of route of administration, duration of treatment, and treatment schedule of favipiravir in immune competent mouse and guinea pig models using rodent-adapted Zaire ebolavirus (EBOV). A dose of 300 mg/kg/day of favipiravir with an 8-day treatment was found to be fully effective at preventing lethal EVD-like disease in BALB/c mice regardless of route of administration (oral, intraperitoneal, or subcutaneous) or whether it was provided as a once-daily dose or a twice-daily split dose. Preclinical data generated in guinea pigs demonstrates that an 8-day treatment of 300 mg/kg/day of favipiravir reduces mortality following EBOV challenge regardless of route of treatment or duration of treatments for 8, 11, or 15 days. This work supports the future translational development of favipiravir as an EVD therapeutic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

New cyclophilin D inhibitor rescues mitochondrial and cognitive function in Alzheimer’s disease

Abstract Mitochondrial dysfunction is an early pathological feature of Alzheimer disease and plays a crucial role in the development and progression of Alzheimer’s disease. Strategies to rescue mitochondrial function and cognition remain to be explored. Cyclophilin D (CypD), the peptidylprolyl isomerase F (PPIase), is a key component in opening the mitochondrial membrane permeability transition pore, leading to mitochondrial dysfunction and cell death. Blocking membrane permeability transition pore opening by inhibiting CypD activity is a promising therapeutic approach for Alzheimer’s disease. However, there is currently no effective CypD inhibitor for Alzheimer’s disease, with previous candidates demonstrating high toxicity, poor ability to cross the blood–brain barrier, compromised biocompatibility and low selectivity. Here, we report a new class of non-toxic and biocompatible CypD inhibitor, ebselen, using a conventional PPIase assay to screen a library of ∼2000 FDA-approved drugs with crystallographic analysis of the CypD-ebselen crystal structure (PDB code: 8EJX). More importantly, we assessed the effects of genetic and pharmacological blockade of CypD on Alzheimer’s disease mitochondrial and glycolytic bioenergetics in Alzheimer’s disease-derived mitochondrial cybrid cells, an ex vivo human sporadic Alzheimer’s disease mitochondrial model, and on synaptic function, inflammatory response and learning and memory in Alzheimer’s disease mouse models. Inhibition of CypD by ebselen protects against sporadic Alzheimer’s disease- and amyloid-β-induced mitochondrial and glycolytic perturbation, synaptic and cognitive dysfunction, together with suppressing neuroinflammation in the brain of Alzheimer’s disease mouse models, which is linked to CypD-related membrane permeability transition pore formation. Thus, CypD inhibitors have the potential to slow the progression of neurodegenerative diseases, including Alzheimer’s disease, by boosting mitochondrial bioenergetics and improving synaptic and cognitive function.

Neurosciences & Neurology↗
DOE OSTI2026

A Multi-Region SEIR Model Incorporating Inter-County Mobility and Time-Dependent Transmission Dynamics: Application to COVID-19 Disease Outbreak Data in North Carolina.

Classical infectious disease compartmental models typically do not incorporate spatial heterogeneity or mobility. We develop a multi-region susceptible-exposed-infected-recovered (SEIR) model in which disease dynamics are coupled via inter-region mobility and the transmission rate is both region and time dependent. We calibrate the model using rolling averages of daily COVID-19 data in all 100 North Carolina counties. Mobility parameters are prescribed using daily inter-county commuter data. The number of transmission rate parameters is substantially reduced by hypothesizing that the dynamics correlate with county-level population density. Parameter estimation is carried out using several objective functions with error terms at different scales. An additive combination of least squares error at the county-level and the state-level, along with a quadratic transmission rate polynomial, yields the lowest overall error at both spatial scales. The calibrated model is used to simulate regional effects of perturbing disease transmission rates in adjacent counties and to illustrate effects of the state’s mobility infrastructure on disease dynamics and spread for a new disease outbreak.

COVID-19 modeling↗
DOE OSTI2020

Adaptive Recovery Model: Designing Systems for Testing Tracing and Vaccination to Support COVID-19 Recovery Planning.

This report documents a new approach to designing disease control policies that allocate scarce testing, contact tracing, and vaccination resources to better control community transmission of COVID19 or similar diseases. The Adaptive Recovery Model (ARM) combines a deterministic compartmental disease model with a stochastic network disease propagation model to enable us to simulate COVID-19 community spread through the lens of two complementary modeling motifs. ARM contact networks are derived from cell-phone location data that have been anonymized and interpreted as individual arrivals to specic public locations. Modeling disease spread over these networks allows us to identify locations within communities conducive to rapid disease spread. ARM applies this model- and data-derived abstractions of community transmission to evaluate the effectiveness of disease control measures including targeted social distancing, contact tracing, testing and vaccination. The architecture of ARM provides a unique capacity to help decision makers understand how best to deploy scarce testing, tracing and vaccination resources to minimize disease-spread potential in a community. This document details the novel mathematical formulations underlying ARM, presents a dynamical stability analysis of the deterministic model components, a sensitivity analysis of control parameters and network structure, and summarizes a process for deriving contact networks from cell-phone location data. An example use case steps through applying ARM to evaluate three targeted social distancing policies using Bernalillo County, New Mexico as an exemplar test locale. This step-by-step analysis demonstrates how ARM can be used to measure the relative performance of competing public health policies. Initial scenario tests of ARM shows that ARMs design focus on resource utilization rather than simple incidence prediction can provide decision makers with additional quantitative guidance for managing ongoing public health emergencies and planning future responses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRSDate not supplied

Cardiovascular Disease Spaceflight Equivalent Stressor Risk Modeling Project

The risk of cardiovascular disease (CVD) may be exacerbated by spaceflight hazards including radiation, isolation, distance from the Earth, gravity fields, and closed or confined environments. This project aims to use epidemiologic, scientific research evidence of surrogate spaceflight stressors on analog populations in terrestrial cohorts to model CVD risk for spaceflight conditions. To date, Dr. Butler and the multi-disciplinary CVD Spaceflight Equivalent Stressors (SES) team have conducted a formal systematic literature review on the risk of sleep loss as it relates to cardiovascular disease outcomes and are currently working on a meta-analysis for the data gathered from nearly 100 studies and their various CVD outcomes. The research will continue to examine other surrogate stressors in depth, such as altered gravity, radiation exposure, noise, etc. with cardiovascular outcomes to determine an overall combined spaceflight risk for long term future missions such as Artemis Lunar and Mars missions.

Jennifer Butler↗
DOE OSTI2023

Discovering a reaction–diffusion model for Alzheimer’s disease by combining PINNs with symbolic regression

Misfolded tau proteins play a critical role in the progression and pathology of Alzheimer's disease. Recent studies suggest that the spatio-temporal pattern of misfolded tau follows a reaction-diffusion type equation. However, the precise mathematical model and parameters that characterize the progression of misfolded protein across the brain remain incompletely understood. Here, we use deep learning and artificial intelligence to discover a mathematical model for the progression of Alzheimer's disease using longitudinal tau positron emission tomography from the Alzheimer's Disease Neuroimaging Initiative database. Specifically, we integrate physics informed neural networks (PINNs) and symbolic regression to discover a reaction-diffusion type partial differential equation for tau protein misfolding and spreading. First, we demonstrate the potential of our model and parameter discovery on synthetic data. Then, we apply our method to discover the best model and parameters to explain tau imaging data from 46 individuals who are likely to develop Alzheimer's disease and 30 healthy controls. Our symbolic regression discovers different misfolding models f(c) for two groups, with a faster misfolding for the Alzheimer's group, f(c) = 0.23c 3 – 1.34c 2 + 1.11c, than for the healthy control group, f(c) = –c 3 + 0.62c 2 + 0.39c. Our results suggest that PINNs, supplemented by symbolic regression, can discover a reaction-diffusion type model to explain misfolded tau protein concentrations in Alzheimer's disease. Furthermore, we expect our study to be the starting point for a more holistic analysis to provide image-based technologies for early diagnosis, and ideally early treatment of neurodegeneration in Alzheimer's disease and possibly other misfolding-protein based neurodegenerative disorders.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2009

Biophysics Representation of the Two-Hit Model of Alzheimer's Disease for the Exploration of Late CNS Risks from Space Radiation

A concern for long-term space travel outside the Earth s magnetic field is the late effects to the central nervous system (CNS) from galactic cosmic ray (GCR) or solar particle events (SPE). Human epidemiology data is severely limited for making CNS risk estimates and it is not clear such effects occur following low LET exposures. We are developing systems biology models based on biological information on specific diseases, and experimental data for proton and heavy ion radiation. A two-hit model of Alzheimer s disease (AD) has been proposed by Zhu et al.(1), which is the framework of our model. Of importance is that over 50% of the US population over the age of 75-y have mild to severe forms of AD. Therefore we recommend that risk assessment for a potential AD risk from space radiation should focus on the projection of an earlier age of onset of AD and the prevention of this possible acceleration through countermeasures. In the two-hit model, oxidative stress and aberrant cell cycle-related abnormalities leading to amyloid-beta plaques and neurofibrillary tangles are necessary and invariant steps in AD. We have formulated a stochastic cell kinetics model of the two-hit AD model. In our model a population of neuronal cells is allowed to undergo renewal through neurogenesis and is susceptible to oxidative stress or cell cycle abnormalities with age-specific accumulation of damage. Baseline rates are fitted to AD population data for specific ages, gender, and for persons with an apolipoprotein 4 allele. We then explore how low LET or heavy ions may increase either of the two-hits or neurogenesis either through persistent oxidative stress, direct mutation, or through changes to the micro-environment, and suggest possible ways to develop accurate quantitative estimates of these processes for predicting AD risks following long-term space travel.

Cucinotta, Francis A.↗
DOE OSTI2024

A Simplified Model of Adenine-Induced Chronic Kidney Disease Using SKH1 Mice

Commonly used adenine-induced chronic kidney disease (CKD) murine models often employ C57BL/6 mice; however, this strain has inherent limitations due to its natural resistance to developing key pathological features of CKD, such as tubulointerstitial fibrosis and inflammation. There have been attempts to overcome these barriers by using multiple concentrations of adenine-supplemented diets or by performing prolonged experiments up to 20 weeks. Here, we demonstrate that SKH1 Elite mice develop clinically relevant CKD phenotypes (e.g., polyuria, proteinuria, inflammation, and renal fibrosis) over the course of only 6 weeks of low-dose (0.15%) adenine supplementation. As a docile, immunocompetent, and hairless strain, SKH1 Elite mice offer several logistical advantages over C57BL/6 mice, including ease of handling and the ability to study dermal conditions, which are often secondary to CKD.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2001

Parvalbumin overexpression alters immune-mediated increases in intracellular calcium, and delays disease onset in a transgenic model of familial amyotrophic lateral sclerosis

Intracellular calcium is increased in vulnerable spinal motoneurons in immune-mediated as well as transgenic models of amyotrophic lateral sclerosis (ALS). To determine whether intracellular calcium levels are influenced by the calcium-binding protein parvalbumin, we developed transgenic mice overexpressing parvalbumin in spinal motoneurons. ALS immunoglobulins increased intracellular calcium and spontaneous transmitter release at motoneuron terminals in control animals, but not in parvalbumin overexpressing transgenic mice. Parvalbumin transgenic mice interbred with mutant SOD1 (mSOD1) transgenic mice, an animal model of familial ALS, had significantly reduced motoneuron loss, and had delayed disease onset (17%) and prolonged survival (11%) when compared with mice with only the mSOD1 transgene. These results affirm the importance of the calcium binding protein parvalbumin in altering calcium homeostasis in motoneurons. The increased motoneuron parvalbumin can significantly attenuate the immune-mediated increases in calcium and to a lesser extent compensate for the mSOD1-mediated 'toxic-gain-of-function' in transgenic mice.

Non-NASA Center↗
NASA NTRS2000

Forecasting disease risk for increased epidemic preparedness in public health

Emerging infectious diseases pose a growing threat to human populations. Many of the world's epidemic diseases (particularly those transmitted by intermediate hosts) are known to be highly sensitive to long-term changes in climate and short-term fluctuations in the weather. The application of environmental data to the study of disease offers the capability to demonstrate vector-environment relationships and potentially forecast the risk of disease outbreaks or epidemics. Accurate disease forecasting models would markedly improve epidemic prevention and control capabilities. This chapter examines the potential for epidemic forecasting and discusses the issues associated with the development of global networks for surveillance and prediction. Existing global systems for epidemic preparedness focus on disease surveillance using either expert knowledge or statistical modelling of disease activity and thresholds to identify times and areas of risk. Predictive health information systems would use monitored environmental variables, linked to a disease system, to be observed and provide prior information of outbreaks. The components and varieties of forecasting systems are discussed with selected examples, along with issues relating to further development.

Disease Outbreaks↗
DOE OSTI2021

Oral delivery of a functional algal-expressed TGF-β mimic halts colitis in a murine DSS model

Inflammatory bowel disease (IBD) is a set of immunological disorders which can generate chronic pain and fatigue associated with the inflammatory symptoms. The treatment of IBD remains a significant hurdle with current therapies being only partially effective or having significant side effects, suggesting that new therapies that elicit different modes of action and delivery strategies are required. TGM1 is a TGF-β mimic that was discovered from the intestinal helminth parasite Heligmosomoides polygyrus and is thought to be produced by the parasite to suppress the intestinal inflammation response to help evade host immunity, making it an ideal candidate to be developed as a novel anti-inflammatory bio-therapeutic. Here we utilized the expression system of the edible green algae Chlamydomonas reinhardtii in order to recombinantly produce active TGM1 in a form that could be ingested. C. reinhardtii robustly expressed TGM1, and the resultant recombinant protein is biologically active as measured by regulatory T cell induction. When delivered orally to mice, the algal expressed TGM1 is able to ameliorate weight loss, lymphadenopathy, and disease symptoms in a mouse model of DSS-induced colitis, demonstrating the potential of this biologic as a novel treatment of IBD.

09 BIOMASS FUELS↗
DOE OSTI2021

Modulation of Neuroinflammation by Low-Dose Radiation Therapy in an Animal Model of Alzheimer's Disease

Recently, several studies have reported that low-dose radiation therapy (RT) suppresses the release of proinflammatory cytokines in inflammatory-degenerative disorders, including Alzheimer disease (AD). AD is the most common cause of dementia, and neuroinflammation is one of the major contributing factors in AD pathogenesis. Therefore, low-dose RT may be used clinically for treating AD. However, the appropriate doses, effects, and underlying mechanisms of RT in AD have not been determined. In this study, we aimed to determine the appropriate RT dose and schedule for AD treatment and to investigate the therapeutic effects and mechanisms of low-dose RT in AD.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Heterogeneous estimations of non-pharmaceutical mitigation behavior during the COVID-19 pandemic

The COVID-19 pandemic highlighted the importance of human behavior in mitigating the spread of disease. Nonetheless, human behavior is often overlooked in models of disease spread, particularly by underutilizing real-world data. We address this by estimating probabilities that individuals engage in behaviors that influence SARS-CoV-2 transmission risk during the COVID-19 pandemic, between September 2020 and June 2022. These behaviors include wearing a mask, using public transportation, spending time with others, avoiding contact with others, and going to work. Our estimates account for the age and sex of individuals and are generated for every county in the United States. We utilized multiple open-source datasets and United States Census data to produce these estimates. Multiple datasets were used for validation, showing our estimates demonstrated comparable accuracy and robustness. Our estimates aid in understanding human behavior dynamics during the COVID-19 pandemic and could be used to inform monthly or longer-term behavior in simulations of COVID-19. Moreover, the methods presented can be applied to other behaviors and features for future simulations of infectious disease.

97 MATHEMATICS AND COMPUTING↗