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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Studying Host-Pathogen Interactions In 3-D: Organotypic Models For Infectious Disease And Drug Development

Representative, reproducible and high-throughput models of human cells and tissues are critical for a meaningful evaluation of host-pathogen interactions and are an essential component of the research developmental pipeline. The most informative infection models - animals, organ explants and human trials - are not suited for extensive evaluation of pathogenesis mechanisms and screening of candidate drugs. At the other extreme, more cost effective and accessible infection models such as conventional cell culture and static co-culture may not capture physiological and three-dimensional aspects of tissue biology that are important in assessing pathogenesis, and effectiveness and cytotoxicity of therapeutics. Our lab has used innovative bioengineering technology to establish biologically meaningful 3-D models of human tissues that recapitulate many aspects of the differentiated structure and function of the parental tissue in vivo, and we have applied these models to study infectious disease. We have established a variety of different 3-D models that are currently being used in infection studies - including small intestine, colon, lung, placenta, bladder, periodontal ligament, and neuronal models. Published work from our lab has shown that our 3-D models respond to infection with bacterial and viral pathogens in ways that reflect the infection process in vivo. By virtue of their physiological relevance, 3-D cell cultures may also hold significant potential as models to provide insight into the neuropathogenesis of HIV infection. Furthermore, the experimental flexibility, reproducibility, cost-efficiency, and high throughput platform afforded by these 3-D models may have important implications for the design and development of drugs with which to effectively treat neurological complications of HIV infection.

Nickerson, Cheryl A.↗
NASA NTRS2008

Accessing and Utilizing Remote Sensing Data for Vectorborne Infectious Diseases Surveillance and Modeling

Background: The transmission of vectorborne infectious diseases is often influenced by environmental, meteorological and climatic parameters, because the vector life cycle depends on these factors. For example, the geophysical parameters relevant to malaria transmission include precipitation, surface temperature, humidity, elevation, and vegetation type. Because these parameters are routinely measured by satellites, remote sensing is an important technological tool for predicting, preventing, and containing a number of vectorborne infectious diseases, such as malaria, dengue, West Nile virus, etc. Methods: A variety of NASA remote sensing data can be used for modeling vectorborne infectious disease transmission. We will discuss both the well known and less known remote sensing data, including Landsat, AVHRR (Advanced Very High Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectroradiometer), TRMM (Tropical Rainfall Measuring Mission), ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), EO-1 (Earth Observing One) ALI (Advanced Land Imager), and SIESIP (Seasonal to Interannual Earth Science Information Partner) dataset. Giovanni is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center. It provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data. After remote sensing data is obtained, a variety of techniques, including generalized linear models and artificial intelligence oriented methods, t 3 can be used to model the dependency of disease transmission on these parameters. Results: The processes of accessing, visualizing and utilizing precipitation data using Giovanni, and acquiring other data at additional websites are illustrated. Malaria incidence time series for some parts of Thailand and Indonesia are used to demonstrate that malaria incidences are reasonably well modeled with generalized linear models and artificial intelligence based techniques. Conclusions: Remote sensing data relevant to the transmission of vectorborne infectious diseases can be conveniently accessed at NASA and some other websites. These data are useful for vectorborne infectious disease surveillance and modeling.

Kiang, Richard↗
NASA NTRS2005

Three-Dimensional Cell Culture Models for Infectious Disease and Drug Development

Three-dimensional (3-D) cell cultures hold enormous potential to advance our understanding of infectious disease and to effectively translate basic cellular research into clinical applications. Using novel NASA bioreactor technology, the rotating wall vessel (RWV), we have engineered physiologically relevant 3-D human tissue culture models for infectious disease studies. The design of the RWV is based on the understanding that organs and tissues function in a 3-D environment, and that this 3-D architecture is critical for the differentiated form and function of tissues in vivo. The RWV provides large numbers of cells which are amenable to a wide variety of experimental manipulations and provides an easy, reproducible, and cost-effective approach to enhance differentiated features of cell culture models.

Nickerson, Cheryl A.↗
NASA NTRS2004

NASA Classroom Bioreactor

Exploration of space provides a compelling need for cell-based research into the basic mechanisms that underlie the profound changes that occur in terrestrial life that is transitioned to low gravity environments. Toward that end, NASA developed a rotating bioreactor in which cells are cultured while continuously suspended in a cylinder in which the culture medium rotates with the cylinder. The randomization of the gravity vector accomplished by the continuous rotation, in a low shear environment, provides an analog of microgravity. Because cultures grown in bioreactors develop structures and functions that are much closer to those exhibited by native tissue than can be achieved with traditional culture methods, bioreactors have contributed substantially to advancing research in the fields of cancer, diabetes, infectious disease modeling for vaccine production, drug efficacy, and tissue engineering. NASA has developed a Classroom Bioreactor (CB) that is built from parts that are easily obtained and assembled, user-friendly and versatile. It can be easily used in simple school settings to examine the effect cultures of seeds or cells. An educational brief provides assembly instructions and lesson plans that describes activities in science, math and technology that explore free fall, microgravity, orbits, bioreactors, structure-function relationships and the scientific method.

Scully, Robert↗
NASA NTRS2012

Use of Giovanni System in Public Health Application

The role of environment and climate in propagating infectious disease has long been recognized since the 5th century. The effect is particularly evident in vector-borne diseases such as malaria where temperature, precipitation and humidity influence the lifecycle of the pathogens and mosquitoes. Likewise, the transmission of respiratory diseases is also often associated with climatic factors. For example, a recent study showed that low humidity and temperature provides efficient condition for seasonal influenza transmission. Understanding of how environment and climate affect infectious diseases would essentially provide guides to prevent and control the spread of disease. Toward this end, our group has developed models for infectious disease risk such as for malaria, dengue and influenza that are driven by climatic and environmental inputs. Results will be presented, especially those that used TRMM data from GIOVANNI.

Soebiyanto, Radina↗
NASA NTRS2020

Ensemble Methodologies for Astronaut Cancer Risk Assessment in the face of Large Uncertainties

A new approach to NASA space radiation risk modeling has successfully extended the current NASA probabilistic cancer risk model to an ensemble framework able to consider sub-model parameter uncertainty (e.g. uncertainty in a radiation quality parameter) as well as model-form uncertainty associated with differing theoretical or empirical formalisms (e.g. combined dose-rate and radiation quality effects). Ensemble methodologies are already widely used in weather prediction, modeling of infectious disease outbreaks, and certain terrestrial radiation protection applications to better understand how uncertainty may influence risk decision-making. Applying ensemble methodologies to space radiation risk projections offers the potential to efficiently incorporate emerging research results, allow for the incorporation of future (including international) models, improve uncertainty quantification for underlying sub-models developed against sparse experimental data, and reduce the impact of subjective bias on risk projections. Moreover, risk forecasting across an ensemble of multiple predictive models can provide stakeholders additional information on risk acceptance if current health/medical standards cannot be met or the level of knowledge doesn’t permit a specific risk or exposure limit to be developed for future space exploration missions. In this work, ensemble risk projections implementing multiple sub-models of radiation quality, dose and dose-rate effectiveness factors, excess risk, and latency as ensemble members are presented. Initial consensus methods for ensemble model weights and correlations to account for individual model bias are discussed. In these analyses, the ensemble forecast compares well to results from NASA's current operational cancer risk projection model used to assess permissible exposure limits and permissible mission durations for astronauts. However, a large range of projected risk values are obtained at the upper 95th confidence level where models must extrapolate beyond available biological data sets; closer agreement is seen at the median + one sigma due to the inherent similarities in available models. Future work, including the addition of new models and methods for statistical correlation between predictive members are discussed to define alternate ways of thinking about risk and ‘acceptable’ uncertainty with respect to NASA’s current permissible exposure limits.

space radiation↗
NASA NTRSDate not supplied

Ensemble Cancer Risk Model for Astronaut Risk Assessment

A new approach to NASA space radiation risk modeling has successfully extended the current NASA probabilistic cancer risk model to an ensemble framework able to consider sub-model parameter uncertainty (e.g. uncertainty in a radiation quality parameter) as well as model-form uncertainty associated with differing theoretical or empirical formalisms (e.g. combined dose-rate and radiation quality effects). Ensemble methodologies are already widely used in weather prediction, modeling of infectious disease outbreaks, and certain terrestrial radiation protection applications to better understand how uncertainty may influence risk decision-making. Applying ensemble methodologies to space radiation risk projections offers the potential to efficiently incorporate emerging research results, allow for the incorporation of future (including international) models, improve uncertainty quantification for underlying sub-models developed against sparse experimental data, and reduce the impact of subjective bias on risk projections. Moreover, risk forecasting across an ensemble of multiple predictive models can provide stakeholders additional information on risk acceptance if current health/medical standards cannot be met or the level of knowledge doesn’t permit a specific risk or exposure limit to be developed for future space exploration missions. In this work, ensemble risk projections implementing multiple sub-models of radiation quality, dose and dose-rate effectiveness factors, excess risk, and latency as ensemble members are presented. Initial consensus methods for ensemble model weights and correlations to account for individual model bias are discussed. In these analyses, the ensemble forecast compares well to results from NASA's current operational cancer risk projection model used to assess permissible exposure limits and permissible mission durations for astronauts. However, a large range of projected risk values are obtained at the upper 95th confidence level where models must extrapolate beyond available biological data sets; closer agreement is seen at the median + one sigma due to the inherent similarities in available models. Future work, including the addition of new models and methods for statistical correlation between predictive members are discussed to define alternate ways of thinking about risk and ‘acceptable’ uncertainty with respect to NASA’s current permissible exposure limits.

Lisa C Simonsen↗
NASA NTRS2009

Spatial Analysis of West Nile Virus: Predictive Risk Modeling of a Vector-borne Infectious Disease in Illinois by Means of NASA Earth Observation Systems

West Nile Virus is a mosquito-borne virus of the family Flaviviridae. It infects birds and various mammals, including humans, and can cause encephalitis that may prove fatal, notably among vulnerable populations. Since its identification in New York City in 1999, WNV has become established in a broad range of ecological settings throughout North America, infecting more than 25,300 people and killing 1133 as of 2008 (CDC,2009). WNV is transmitted by mosquitoes that feed on infected birds. As a result, the degree of human infection depends on local ecology and human exposure. This study hypothesizes that remote sensing and GIS can be used to analyze environmental determinants of WNV transmission, such as climate, elevation, land cover, and vegetation densities, to map areas of WNV risk for surveillance and intervention.

Renneboog, Nathan↗
NASA NTRS2021

Climate Predicts Geographic and Temporal Variation in Mosquito-Borne Disease Dynamics on Two Continents

Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For climate-sensitive diseases such as dengue, chikungunya, and Zika, climate appears to have opposing effects in different contexts. Here we show that a model, parameterized with laboratory measured climate-driven mosquito physiology, captures three key epidemic characteristics across ecologically and culturally distinct settings in Ecuador and Kenya: the number, timing, and duration of outbreaks. The model generates a range of disease dynamics consistent with observed Aedes aegypti abundances and laboratory-confirmed arboviral incidence with variable accuracy (28–85% for vectors, 44–88%for incidence). The model predicted vector dynamics better in sites with a smaller proportion of young children in the population, lower mean temperature, and homes with piped water and made of cement. Models with limited calibration that robustly capture climate-virus relationships can help guide intervention efforts and climate change disease projections.

Climate-change ecology↗
NASA NTRS2018

Satellite and Reanalysis Air Quality Data and Services at NASA GES DISC for Public Health Study

Outbreaks of infectious diseases and health can be influenced by airborne and water-borne pollutants. Furthermore, air and water quality are associated with climate variability, industrialization, land use and land cover change, and water resource management. It is therefore crucial to understand environment-disease connections with existing long-term observed and modeled data, particularly for development of early warning systems for infectious disease outbreaks. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) (https://disc.gsfc.nasa.gov) archives large volumes of global environment data that are useful for research and applications regarding environmental factors and public health. Examples of air quality measurements are: Daily satellite remotely sensed data, including Aerosol Index (AI), O3, SO2, CO, and NO2 from Aura/OMI (October 2014 to present), and OMPS-NPP (January 2012 to present, currently research data products only) Hourly and monthly reanalysis modeled data, including PM2.5, O3, CO, SO2, BC, dust, AOD, and aerosol types from MERRA-2 (January 1980 to present) Examples of surface meteorology and land surface measurements are: hourly, daily, and monthly satellite precipitation from TRMM (December 1997 to March 2015) 30-minute and monthly satellite precipitation from GPM (March 2014 to present); Hourly and monthly modeled surface meteorology and land surface condition from MERRA-2 (January 1980 to present) and land surface assimilation models (January 1948 to present), including precipitation, surface temperature, relative humidity, wind, and soil moisture.This presentation will give an overview of relevant environmental data at the NASA GES DISC. Through a number of use cases, such as dust events and active fires, we will introduce data services that assist in finding the right data, enable visualization and analysis of the data online, and allow downloading of data in user-preferred format.

remote sensing data↗
NASA NTRS2000

Remote sensing and human health: new sensors and new opportunities

Since the launch of Landsat-1 28 years ago, remotely sensed data have been used to map features on the earth's surface. An increasing number of health studies have used remotely sensed data for monitoring, surveillance, or risk mapping, particularly of vector-borne diseases. Nearly all studies used data from Landsat, the French Systeme Pour l'Observation de la Terre, and the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer. New sensor systems are in orbit, or soon to be launched, whose data may prove useful for characterizing and monitoring the spatial and temporal patterns of infectious diseases. Increased computing power and spatial modeling capabilities of geographic information systems could extend the use of remote sensing beyond the research community into operational disease surveillance and control. This article illustrates how remotely sensed data have been used in health applications and assesses earth-observing satellites that could detect and map environmental variables related to the distribution of vector-borne and other diseases.

Satellite Communications↗
NASA NTRSDate not supplied

Moving With Parasites: Relationships Between Animal Movement and Infectious Disease Across Systems and Scales

Animal movement patterns are important for ecological processes such as population dynamics and infectious disease transmission. Because animals move in response to environmental cues like temperature and precipitation, changes to the environment – whether they are seasonal, interannual, or long-term – can change these processes, leading to changes in population sizes or infectious disease prevalence across space and time. My work uses a combination of simulation modeling and data analysis at multiple spatial and temporal scales to understand the environment-movement-disease connection in diverse animal taxa and environments. In this seminar, I will highlight the diverse ways that the environment can influence infectious disease dynamics via changes to animal movement patterns, including through a global study of migration in ungulate populations, a study of American White Ibis adapting to urban environments in South Florida, and examples of avian influenza prevalence in wild waterfowl. Together, these examples highlight that understanding environment-movement interactions can help predict how infectious disease dynamics might change in the future, as changes to climate, land use, and habitats alter animal movement patterns.

Animal movement↗
NASA NTRS2010

Next Generation Respiratory Viral Vaccine System: Advanced and Emerging Bioengineered Human Lung Epithelia Model (HLEM) Organoid Technology

Acute respiratory infections, including pneumonia and influenza, are the S t" leading cause of United States and worldwide deaths. Newly emerging pathogens signaled the need for an advanced generation of vaccine technology.. Human bronchial-tracheal epithelial tissue was bioengineered to detect, identify, host and study the pathogenesis of acute respiratory viral disease. The 3-dimensional (3D) human lung epithelio-mesechymal tissue-like assemblies (HLEM TLAs) share characteristics with human respiratory epithelium: tight junctions, desmosomes, microvilli, functional markers villin, keratins and production of tissue mucin. Respiratory Syntial Virus (RSV) studies demonstrate viral growth kinetics and membrane bound glycoproteins up to day 20 post infection in the human lung-orgainoid infected cell system. Peak replication of RSV occurred on day 10 at 7 log10 particles forming units per ml/day. HLEM is an advanced virus vaccine model and biosentinel system for emergent viral infectious diseases to support DoD global surveillance and military readiness.

Goodwin, Thomas J.↗
NASA NTRS1996

From Individuals to Epidemics

Heterogeneous mixing fundamentally changes the dynamics of infectious diseases; finding ways to incorporate it into models represents a critical challenge. Phenomenological approaches are deficient in their lack of attention to underlying processes; individual-based models, on the other hand, may obscure the essential interactions in a sea of detail. The challenge then is to find ways to bridge these levels of description, starting from individual-based models and deriving macroscopic descriptions from them that retain essential detail, and filter out the rest. In this paper, attempts to achieve this transformation are described for a class of models where non-random mixing arises from the spatial localization of interactions. In general, the epidemic threshold is found to be larger owing to spatial localization than for a homogeneous mixing population. An improved estimate of the dynamics is developed by the use of moment equations, and a simple estimate of the threshold in terms of a 'dyad heuristic'. For more general models in which local infection is not described by mass action, the connection with related partial differential equations is investigated.

Levin, Simon A.↗
NASA NTRS2009

Predicting and Mitigating Outbreaks of Vector-Borne Disease Utilizing Satellite Remote Sensing Technology and Models

The Public Health application area focuses on Earth science applications to public health and safety, particularly regarding infectious disease, emergency preparedness and response, and environmental health issues. The application explores issues of toxic and pathogenic exposure, as well as natural and man-made hazards and their effects, for risk characterization/mitigation and improvements to health and safety. The program elements of the NASA Applied Sciences Program are: Agricultural Efficiency, Air Quality, Climate, Disaster Management, Ecological Forecasting, Water Resources, Weather, and Public Health.

Estes, Sue M.↗
NASA NTRS2025

Influence of Microgravity on Bacterial Pathogen Virulence and Immune Cell Function—Relevance for Infectious Disease Risk During Spaceflight

Spaceflight has measurable impacts on astronaut immune profiles as well as the virulence patterns of bacterial pathogens. Data with respect to human immunity indicate diminished T and NK cell function, altered cytokine profiles, persistent inflammation, and latent herpesvirus reactivation. Furthermore, evaluation of International Space Station (ISS) crewmembers gives evidence of compromised immunity, including atypical allergy, infectious disease, and dermatitis. Data with respect to certain human bacterial pathogens suggest modified virulence that may be enhanced. It is therefore critical to examine this interaction of immune dysregulation and increased microbial virulence and whether it might synergistically increase the risk of infectious disease to crew members. The goal of this study is to use modeled microgravity to study the impact of medically significant ISS bacteria that may have altered virulence on the immune response of the host. This study consists of two primary aims to assess this relationship. First, immune cells will be collected from healthy test subjects and cultured in static or in modeled microgravity conditions together with either control pathogens or with microgravity conditioned pathogens that were grown in bioreactors. Second, immune cells will be collected from astronauts before, during, and after flight and co-cultured with the control or the microgravity conditioned bacteria. Three pathogens were selected for this investigation: Pseudomonas aeruginosa , Salmonella enterica serovar Enteritidis and Burkholderia cepacia . Previously, the optimal cell to bacteria ratios that produce the greatest immune cell responses have been derived for these three bacteria. Cellular activation, as determined by the induction of cell surface activation markers and cytokine profiles, will be measured. Interactions between cells and bacteria will be assessed using fluorescent and electron microscopy techniques. This study will provide critical information to help understand how microgravity alters microbial virulence and the associated infectious disease risk to crewmembers during spaceflight missions. Over the past year, the Immunology and Microbiology laboratories at NASA Johnson Space Center have collaborated to process the astronaut subject samples to complete the last year of the flight portion of this study. This included the completion of four astronaut subjects full mission sampling sets. Sample processing included innate and adaptive cell flow cytometry as well as analysis of cytokine concentrations in the supernatant. The ground control segment of the study will take place during FY25 which involves parallel infections run under static and clinostat conditions. The acquired data sets over this 3-year study are now being analyzed to provide a comprehensive set of results and conclusions that will contribute to a more effective risk assessment for astronauts during spaceflight regarding this host-pathogen context.

Immunology↗
NASA NTRSDate not supplied

Effects of Low Dose Radiation and Radiation Countermeasures on Infection By Spaceflight Analogue Cultured Salmonella Using 3-D Biomimetic Human Tissue Models

While both microgravity and radiation are major biological stressors associated with the spaceflight environment, their cumulative impact on host-pathogen interactions and infectious disease risks are rarely considered. This is critical to address, since the cumulative effects of these stressors during spaceflight may result in unexpected negative impacts on crew health and performance that neither condition alone would predict, thus limiting the ability to develop effective countermeasures. Previously, we showed that both spaceflight and spaceflight analogue culture increased the virulence and pathogenesis-related characteristics of the foodborne pathogen, Salmonella Typhimurium (S. Typhimurium), which is responsible for disqualification of food destined for the International Space Station and Salmonella spp. have been found aboard NASA spacecraft. Recently, we demonstrated that spaceflight-analogue culture of S. Typhimurium increased its ability to infect 3-D biomimetic human intestinal tissue models. In a separate study, we showed low dose radiation damaged our 3-D intestinal models. The primary objective of this proposal is to evaluate the possibility that low dose radiation will exacerbate the already increased bacterial pathogenicity of S. Typhimurium observed following spaceflight analogue culture. In addition, we will determine the impact of a radiation countermeasure to provide protection against both radiation and pathogen-induced tissue damage and inflammation. Hypothesis: The already enhanced infection potential of spaceflight analogue cultured S. Typhimurium will be further exacerbated when used to infect host cells exposed to low dose radiation and this enhanced pathogenicity can be mitigated by a radioprotective compound. Aims: 1.Characterize the impact of spaceflight-analogue culture on the ability of S. Typhimurium to infect 3-D biomimetic intestinal tissue models before and after exposure to low dose radiation. 2. Evaluate the ability of the radioprotective compound, EC-18, to protect 3-D intestinal models from low dose radiation, S. Typhimurium infection, and the cumulative impact of these stressors. Significance: Current infectious disease risk assessments for spaceflight do not consider the potential for increased susceptibility to infection and disease resulting from exposure to low dose radiation, which is a critical consideration. This study will provide key evidence to determine if exposure to low dose radiation may be a factor in astronaut susceptibility to infection during long duration exploration missions and the impact of selected countermeasures to mitigate that risk to crew health. We have completed infection studies of the 3-D biomimetic intestinal tissue models and are currently analyzing the data.

Jennifer Barrila↗