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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Monitoring and Correcting Autonomic Function Aboard Mir: NASA Technology Used in Space and on Earth to Facilitate Adaptation

The broad objective of the research was to study individual characteristics of human adaptation to long duration spaceflight and possibilities of their correction using autonomic conditioning. The changes in autonomic state during adaptation to microgravity can have profound effects on the operational efficiency of crewmembers and may result in debilitating biomedical symptoms. Ground-based and inflight experiment results showed that certain responses of autonomic nervous system were correlated with, or consistently preceded, reports of performance decrements or the symptoms. Autogenic-Feedback-Training Exercise (AFTE) is a physiological conditioning method that has been used to train people to voluntary control several of their own physiological responses. The specific objectives were: 1) To study human autonomic nervous system (ANS) responses to sustained exposure to microgravity; 2) To study human behavior/performance changes related to physiology; 3) To evaluate the effectiveness of preflight autonomic conditioning (AFTE) for facilitating adaptation to space and readaptation to Earth; and 4) To archive these data for the NASA Life Sciences Data Archive and thereby make this information available to the international scientific community.

Cowings, P.↗
NASA NTRS1975

Biomedical Results of Apollo

The biomedical program developed for Apollo is described in detail. The findings are listed of those investigations which are conducted to assess the effects of space flight on man's physiological and functional capacities, and significant medical events in Apollo are documented. Topics discussed include crew health and inflight monitoring, preflight and postflight medical testing, inflight experiments, quarantine, and life support systems.

Richard S. Johnston↗
NASA NTRS1993

Kennedy Space Center exercise program

The Kennedy Space Center (KSC) Fitness Program began in Feb. 1993. The program is managed by the Biomedical Operations and Research Office and operated by the Bionetics Corporation. The facilities and programs are offered to civil servants, all contractors, temporary duty assignment (TDY) participants, and retirees. All users must first have a medical clearance. A computer-generated check-in system is used to monitor participant usage. Various aspects of the program are discussed.

Hoffman, Cristy↗
NASA NTRS2003

The biomedical challenges of space flight

Space medicine has evolved considerably through past U.S. missions. It has been proven that humans can live and work in space for long durations and that humans are integral to mission success. The space medicine program of the National Aeronautics and Space Administration (NASA) looks toward future long-duration missions. Its goal is to overcome the biomedical challenges associated with maintaining the safety, health, and optimum performance of astronauts and cosmonauts. This program investigates the health effects of adaptation to microgravity: the nature of their pathologies, the effects of microgravity on pathophysiology, and the alterations in pharmacodynamics and treatment. A critical capability in performing research is the monitoring of the health of all astronauts and of the spacecraft environment. These data support the evidence-based approach to space medicine, incorporating past studies of microgravity-related conditions and their terrestrial counterparts. This comprehensive approach will enable safe and effective exploration beyond low Earth orbit.

Mir Project↗
NASA NTRS2004

The ALTEA/ALTEINO projects: studying functional effects of microgravity and cosmic radiation

The ALTEA project investigates the risks of functional brain damage induced by particle radiation in space. A modular facility (the ALTEA facility) is being implemented and will be operated in the International Space Station (ISS) to record electrophysiological and behavioral descriptors of brain function and to monitor their time dynamics and correlation with particles and space environment. The focus of the program will be on abnormal visual perceptions (often reported as "light flashes" by astronauts) and the impact on retinal and brain visual structures of particle in microgravity conditions. The facility will be made available to the international scientific community for human neurophysiological, electrophysiological and psychophysics experiments, studies on particle fluxes, and dosimetry. A precursor of ALTEA (the 'Alteino' project) helps set the experimental baseline for the ALTEA experiments, while providing novel information on the radiation environment onboard the ISS and on the brain electrophysiology of the astronauts during orbital flights. Alteino was flown to the ISS on the Soyuz TM34 as part of mission Marco Polo. Controlled ground experiments using mice and accelerator beams complete the experimental strategy of ALTEA. We present here the status of progress of the ALTEA project and preliminary results of the Alteino study on brain dynamics, particle fluxes and abnormal visual perceptions. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

manned↗
NASA NTRS1972

Miniature biotelemeter gives multichannel wideband biomedical data

A miniature biotelemeter was developed for sensing and transmitting multiple channels of biomedical data over a radio link. The design of this miniature, 10-channel, wideband (5 kHz/channel), pulse amplitude modulation/ frequency modulation biotelemeter takes advantage of modern device technology (e.g., integrated circuit operational amplifiers, complementary symmetry/metal oxide semiconductor logic, and solid state switches) and hybrid packaging techniques. The telemeter is being used to monitor 10 channels of neuron firings from specific regions of the brain in rats implanted with chronic electrodes. Design, fabrication, and testing of an engineering model biotelemeter are described.

Carraway, J. B.↗
NASA NTRS1992

Metabolic response of environmentally isolated microorganisms to industrial effluents: Use of a newly described cell culture assay

An environmental application using a microtiter culture assay to measure the metabolic sensitivity of microorganisms to petrochemical effluents will be tested. The Biomedical Operations and Research Branch at NASA JSC has recently developed a rapid and nondestructive method to measure cell growth and metabolism. Using a colorimetric procedure the uniquely modified assay allows the metabolic kinetics of prokaryotic and eukaryotic cells to be measured. Use of such an assay if adapted for the routine monitoring of waste products, process effluents, and environmentally hazardous substances may prove to be invaluable to the industrial community. The microtiter method as described will be tested using microorganisms isolated from the Galveston Bay aquatic habitat. The microbial isolates will be identified prior to testing using the automated systems available at JSC. Sodium dodecyl sulfate (SDS), cadmium, and lead will provide control toxic chemicals. The toxicity of industrial effluent from two industrial sites will be tested. An effort will be made to test the efficacy of this assay for measuring toxicity in a mixed culture community.

Ferebee, Robert N.↗
NASA NTRS1971

Future needs for biomedical transducers

In summary there are three major classes of transducer improvements required: improvements in existing transducers, needs for unexploited physical science phenomena in transducer design, and needs for unutilized physiological phenomena in transducer design. During the next decade, increasing emphasis will be placed on noninvasive measurement in all of these areas. Patient safety, patient comfort, and the need for efficient utilization of the time of both patient and physician requires that noninvasive methods of monitoring be developed.

Wooten, F. T.↗
NASA NTRS1971

Medically related activities of application team program

Application team methodology identifies and specifies problems in technology transfer programs to biomedical areas through direct contact with users of aerospace technology. The availability of reengineering sources increases impact of the program on the medical community and results in broad scale application of some bioinstrumentation systems. Examples are given that include devices adapted to the rehabilitation of neuromuscular disorders, power sources for artificial organs, and automated monitoring and detection equipment in clinical medicine.

Source record↗
NASA NTRS2016

Multidimensional Processing and Visual Rendering of Complex 3D Biomedical Images

The proposed technology uses advanced image analysis techniques to maximize the resolution and utility of medical imaging methods being used during spaceflight. We utilize COTS technology for medical imaging, but our applications require higher resolution assessment of the medical images than is routinely applied with nominal system software. By leveraging advanced data reduction and multidimensional imaging techniques utilized in analysis of Planetary Sciences and Cell Biology imaging, it is possible to significantly increase the information extracted from the onboard biomedical imaging systems. Year 1 focused on application of these techniques to the ocular images collected on ground test subjects and ISS crewmembers. Focus was on the choroidal vasculature and the structure of the optic disc. Methods allowed for increased resolution and quantitation of structural changes enabling detailed assessment of progression over time. These techniques enhance the monitoring and evaluation of crew vision issues during space flight.

Sams, Clarence F.↗
NASA NTRSDate not supplied

High School Citizen Scientists Use AI/ML to Predict Intra-Ocular Pressure From Gene Expression Data for Spaceflown Mice

Artificial Intelligence (AI) and Machine Learning (ML) have increasingly become pivotal in biological and biomedical research, largely due to the culture of open data sharing and its associated benefits. The methodologies inherent in AI/ML are particularly adept at identifying and forecasting biological phenotypes from the vast amounts of data generated by next-generation sequencing technologies. These techniques offer substantial promise for advancing research in space biosciences and for the development of automated systems for monitoring space health. Nevertheless, there are crucial aspects to consider when training, validating, and testing machine learning models in both biological research and clinical contexts. It is essential that Open Science principles, including data sharing and the availability of open-source code, are complemented by high-quality, publicly accessible training resources. These resources should focus on best practices and include modules based on real-world scientific cases and data to ensure that future AI/ML practitioners gain practical experience with genuine problems. Addressing this knowledge gap, we have designed, developed, and delivered both interactive and self-paced training programs for citizen scientists worldwide, enabling them to utilize AI/ML for space biology research. This initiative was made possible through generous funding from a Transformation to Open Science Training grant. The interactive training sessions, conducted this summer, utilized AI/ML techniques to analyze data from the Open Science Data Repository, specifically targeting the effects of spaceflight on ocular structure and function. The dataset OSD-583, from the Rodent Research 9 mission, provides experimental data detailing the ocular responses of mice subjected to a 35-day spaceflight, compared with ground control counterparts. Using OSD-583 as observational data, our summer training participants applied AI/ML methods to predict intraocular pressure from RNA-seq data and identify the genes most predictive of the observed responses. Further analysis through pathway enrichment and gene set enrichment revealed that these genes are involved in molecular and cellular processes contributing to retinal degeneration.

James Casaletto↗
NASA NTRS2010

Telescience Support Center Data System Software

The Telescience Support Center (TSC) team has developed a databasedriven, increment-specific Data Require - ment Document (DRD) generation tool that automates much of the work required for generating and formatting the DRD. It creates a database to load the required changes to configure the TSC data system, thus eliminating a substantial amount of labor in database entry and formatting. The TSC database contains the TSC systems configuration, along with the experimental data, in which human physiological data must be de-commutated in real time. The data for each experiment also must be cataloged and archived for future retrieval. TSC software provides tools and resources for ground operation and data distribution to remote users consisting of PIs (principal investigators), bio-medical engineers, scientists, engineers, payload specialists, and computer scientists. Operations support is provided for computer systems access, detailed networking, and mathematical and computational problems of the International Space Station telemetry data. User training is provided for on-site staff and biomedical researchers and other remote personnel in the usage of the space-bound services via the Internet, which enables significant resource savings for the physical facility along with the time savings versus traveling to NASA sites. The software used in support of the TSC could easily be adapted to other Control Center applications. This would include not only other NASA payload monitoring facilities, but also other types of control activities, such as monitoring and control of the electric grid, chemical, or nuclear plant processes, air traffic control, and the like.

Rahman, Hasan↗
NASA NTRS1971

Apollo 15 Mission Report

A detailed discussion is presented of the Apollo 15 mission, which conducted exploration of the moon over longer periods, greater ranges, and with more instruments of scientific data acquisition than previous missions. The topics include trajectory, lunar surface science, inflight science and photography, command and service module performance, lunar module performance, lunar surface operational equipment, pilot's report, biomedical evaluation, mission support performance, assessment of mission objectives, launch phase summary, anomaly summary, and vehicle and equipment descriptions. The capability of transporting larger payloads and extending time on the moon were demonstrated. The ground-controlled TV camera allowed greater real-time participation by earth-bound personnel. The crew operated more as scientists and relied more on ground support team for systems monitoring. The modified pressure garment and portable life support system provided better mobility and extended EVA time. The lunar roving vehicle and the lunar communications relay unit were also demonstrated.

Source record↗
NASA NTRS1972

Biomedical engineering tasks

Electrocardiographic and vectorcardiographic bioinstrumentation work centered on the development of a new electrode system harness for Project Skylab. Evaluation of several silver electrode configurations proved superior impedance voltage performance for silver/silver chloride electrodes mounted flush by using a paste adhesive. A portable ECG processor has been designed and a breadboard unit has been built to sample ECG input data at a rate of 500 samples per second for arrhythmia detection. A small real time display driver program has been developed for statistical analysis on selected QPS features. Engineering work on a sleep monitoring cap assembly continued.

Source record↗
NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields, in part due to a culture of open data sharing and reuse. AI/ML methodology is well-suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Inexperienced researchers can produce models that perform poorly outside of the training dataset. Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Casaletto↗
NASA NTRSDate not supplied

Biological Data for Deep Space Mission Support

Increased biomedical risks and challenges associated with deep space missions (cis-Lunar, Mars transit, Mars surface) require new knowledge discovery and development of novel ecosystem and biomedical support capabilities. This paradigm shift supporting distant and long-duration missions requires biological data to be findable, accessible, interoperable, reusable (FAIR), and maximally open-access (i.e., there is a data governance continuum from closed to mediated to embargoed to open). The NASA “Open Science Data Repositories” (OSDR) aims to meet scientific, technical, and operational spaceflight needs, and offers the ability to upload, download, search, share, analyze, and visualize data across physiological, behavioral, ‘omics, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive (ALSDA), and NASA Biological Institutional Scientific Collection (NBISC). In the past year, ALSDA has undergone a transformation in its data collection, curation, and architecture methods. Standardizing non-genomic (phenotypic) datasets was, and will continue to be, a challenge because of their diverse nature (e.g., molecular, cellular, tissue, whole organism behavior; micro-computed tomography, intraocular pressure, fluorescence microscopy, western blot, ultrasonography; tabular, images, video). This year ALSDA, alongside GeneLab, introduced the Biological Data Management Environment (BDME) with the purpose to accept submission of data from space relevant experiments including spaceflight, radiation, simulated gravity, gravitropism, isolation and confinement, hostile closed environments and/or distance from Earth. In addition to bringing together omics, phenotypic, physiological, bioimaging, and behavioral data into one repository. By integrating with GeneLab a multi-project submission portal aims to reduce the burden on PIs submitting data and enabling the discovery of both omics and phenotypic data. The purpose of ALSDA is to collect, curate, and make all non-human space-relevant biological data maximally findable, accessible, interoperable, and reusable (FAIR). These scope of ALSDA data collected and submitted by PIs include study design metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). In 2021, a community of researchers rallied to form the ALSDA Analysis Working Group (AWG) and provided scientific consensus on dataset sample and assay metadata. The community and excitement around the ALSDA/OSDR system has already led to several data reuse studies, demonstrating value using machine learning (ML), knowledge graphs, and meta-analysis approaches.

space biology↗
NASA NTRSDate not supplied

Biological Data for Deep Space Mission Support

Increased biomedical risks and challenges associated with deep space missions (cis-Lunar, Mars transit, Mars surface) require new knowledge discovery and development of novel ecosystem and biomedical support capabilities. This paradigm shift supporting distant and long-duration missions requires biological data to be findable, accessible, interoperable, reusable (FAIR), and maximally open-access (i.e., there is a data governance continuum from closed to mediated to embargoed to open). The NASA “Open Science Data Repositories” (OSDR) aims to meet scientific, technical, and operational spaceflight needs, and offers the ability to upload, download, search, share, analyze, and visualize data across physiological, behavioral, ‘omics, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive (ALSDA), and NASA Biological Institutional Scientific Collection (NBISC). In the past year, ALSDA has undergone a transformation in its data collection, curation, and architecture methods. Standardizing non-genomic (phenotypic) datasets was, and will continue to be, a challenge because of their diverse nature (e.g., molecular, cellular, tissue, whole organism, behavior; micro-computed tomography, intraocular pressure, fluorescence microscopy, western blot, ultrasonography; tabular, images, video). This year ALSDA, alongside GeneLab, introduced the Biological Data Management Environment (BDME) with the purpose to accept submission of data from space relevant experiments including spaceflight, radiation, simulated gravity, gravitropism, isolation and confinement, hostile closed environments and/or distance from Earth. In addition to bringing together omics, phenotypic, physiological, bioimaging, and behavioral data into one repository. By integrating with GeneLab a multi-project submission portal aims to reduce the burden on PIs submitting data and enabling the discovery of both omics and phenotypic data. The purpose of ALSDA is to collect, curate, and make all non-human space-relevant biological data maximally findable, accessible, interoperable, and reusable (FAIR). These scope of ALSDA data collected and submitted by PIs include study design metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). In 2021, a community of researchers rallied to form the ALSDA Analysis Working Group (AWG) and provided scientific consensus on dataset sample and assay metadata. The community and excitement around the ALSDA/OSDR system has already led to several data reuse studies, demonstrating value using machine learning (ML), knowledge graphs, and meta-analysis approaches.

space biology↗
NASA NTRS1977

Metabolic and cardiovascular adaptation, monkey. NASA SMD 3, project 76, experiment 44 conducted at NASA/JSC, 14-25 May 1977

The biomedical results from an experiment on a monkey subjected to space flight conditions are reported. A background history of the development and testing of an experiment system designed to permit measurement of physiological parameters in subhuman primates during continuous, comfortable, couch restraint for periods of up to 30 days is reviewed. Of major importance in the experimental design of the system was the use of a fiberglass pod, which could be sealed and subdivided into upper and lower parts, to monitor and control the physiological responses for various parts of the animal's body. The experiment was conducted within the Spacelab Simulator for a period of 11 days. Data recorded includes: Spacelab Simulator cabin temperature; ventilation rate; pod internal temperature; fraction percent oxygen; fraction percent carbon dioxide; oxygen consumption rate; carbon dioxide production rate; respiratory quotient; intrathoracic temperature; heart rate; mean aortic pressure; mean ventricular pressure; diurnal variation of parameters measured; comparison of mean preflight, flight, and postflight values of the parameters measured; and correlation matrix for the parameters measured.

Pace, N.↗