Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “model compounds”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Effect of particle characteristics, kinetics and transport phenomena on the prediction of particle mass loss and products yields during biomass fast pyrolysis

Here a low computational cost model for the pyrolysis of biomass anisotropic particles was used to study the effect of thermal conductivity of the particle, CRECK kinetic scheme implementation, intraparticle secondary reactions, heats of reaction, and advection on particle conversion prediction. The model considers a shrinking anisotropic cylindrical particle with biomass pseudo-components, the appearance of liquid intermediates, intra-particle mass and heat transport and secondary reactions of volatiles. The model was validated against oak and birchwood single particle experiments. More accurate predictions for mass loss evolution are found when considering the change of the particle thermal conductivity anisotropy with conversion and the temperature dependency of the thermal conductivities of the biomass and the gas phase, compared to ignoring these phenomena. The CRECK biomass pyrolysis reaction scheme provides insights into the effect of biomass composition on the evolution of the liquid intermediate phase allowing future studies about the presence of heavy compounds in the bio-oil and other phenomena such as aerosol ejection. Secondary intraparticle vapor phase reactions showed a negligible effect in volatiles conversion while heterogeneous reactions slightly overestimate its conversion. Heats of reaction and product advection are important for accurate prediction of particle mass loss.

09 BIOMASS FUELS↗
NASA NTRS1993

Physiological water model development

The water of the human body can be categorized as existing in two main compartments: intracellular water and extracellular water. The intracellular water consists of all the water within the cells and constitutes over half of the total body water. Since red blood cells are surrounded by plasma, and all other cells are surrounded by interstitial fluid, the intracellular compartment has been subdivided to represent these two cell types. The extracellular water, which includes all of the fluid outside of the cells, can be further subdivided into compartments which represent the interstitial fluid, circulating blood plasma, lymph, and transcellular water. The interstitial fluid surrounds cells outside of the vascular system whereas plasma is contained within the blood vessels. Avascular tissues such as dense connective tissue and cartilage contain interstitial water which slowly equilibrates with tracers used to determine extracellular fluid volume. For this reason, additional compartments are sometimes used to represent these avascular tissues. The average size of each compartment, in terms of percent body weight, has been determined for adult males and females. These compartments and the forces which cause flow between them are presented. The kidneys, a main compartment, receive about 25 percent of the cardiac output and filters out a fluid similar to plasma. The composition of this filtered fluid changes as it flows through the kidney tubules since compounds are continually being secreted and reabsorbed. Through this mechanism, the kidneys eliminate wastes while conserving body water, electrolytes, and metabolites. Since sodium accounts for over 90 percent of the cations in the extracellular fluid, and the number of cations is balanced by the number of anions, considering the renal handling sodium and water only should sufficiently describe the relationship between the plasma compartment and kidneys. A kidney function model is presented which has been adapted from a previous model of normal renal function in man. To test the validity of the proposed kidney model, results predicted by the model will be compared to actual data involving injected or ingested fluids and subsequent urine flow rates. Comparison of the model simulation to actual data following the ingestion of 1 liter of water is shown. The model simulation is also shown with actual data following the intravenous infusion of hypertonic saline.

Doty, Susan↗
DOE OSTI2026

Predicting river turbidity in Pine Island Bayou using machine learning techniques coupled with variational mode decomposition

Elevated turbidity levels pose significant public health risks by facilitating the transport of harmful pollutants, including metals, organic compounds, and pathogenic microorganisms into the surface water. These conditions create serious challenges for public recreational water use and drinking water treatment, leading to economic losses and health risks. This study utilizes water monitoring data in Pine Island Bayou, Texas, and develops a Sequence-to-Sequence (S2S) model to predict turbidity using Attention-based Gated Recurrent Units with Encoder-Decoder (AT-GRU-ED) and Long Short-Term Memory (LSTM), coupled with Variational Mode Decomposition (VMD). Compared to the model without VMD, the model demonstrates satisfactory 72-hour turbidity prediction performance, achieving MAEs of 2.60 and 3.29 NTU (reductions of 53% and 58%), RMSEs of 21.08 and 31.49 NTU (reductions of 82% and 80%), and R² values of 0.96 and 0.84 on the validation and test sets, respectively. Feature importance analysis reveals that water temperature is the dominant factor influencing seasonal turbidity patterns, while real-time hourly rainfall significantly contributes to short-term variability. Turbidity typically peaks within 48 hours after rainfall events due to lagged effects from surface runoff and upstream flow. Findings suggest suspending recreational water use and water supply pumping for three days after heavy rainfall can benefit public health and improve water treatment processes. Discharges above 100 m3/s are found to accelerate sediment dilution and transport, reducing turbidity levels more quickly after the peak. In conclusion, the proposed model demonstrates reliable 72-hour turbidity prediction, supporting decision-making for water treatment plant operations and providing early warning for public recreational water use.

Deep learning↗
DOE OSTI2023

Vapor and Liquid ( p –ρ– T–x ) Measurements of Binary Refrigerant Blends Containing R-32, R-152a, R-227ea, R-1234yf, and R-1234ze(E)

In this article, The pressure–density–temperature–composition (p–ρ–T–x) data of binary refrigerant mixtures containing R-32 (difluoromethane), R-152a (1,1,-difluoroethane), R-227ea (1,1,1,2,3,3,3-heptafluoropropane), R-1234yf (2,3,3,3-tetrafluoropropene), and R-1234ze(E) (trans-1,3,3,3-tetrafluoropropene) were measured in both the vapor and liquid phases using a two-sinker, magnetic suspension densimeter. The specific samples in this study comprised two compositions of approximately (0.3/0.7) and (0.7/0.3) mole fraction for each of the following four binary refrigerant blends: R-32 + R-1234yf, R-32 + R-1234ze(E), R-1234yf + R-152a, and R-1234ze(E) + R-227ea. Single-phase vapor densities were measured over a temperature range of approximately 253 to 293 K and pressures from 0.05 to 0.98 MPa. Single-phase liquid and supercritical densities were measured over a temperature range of approximately 230 to 400 K and pressures up to 22 MPa; for refrigerant blends containing R-1234yf, the maximum pressure was limited to 14 MPa. Overall relative combined, expanded (k = 2) uncertainties in density ranged from 0.025 to 0.191%, with an average uncertainty of approximately 0.05%. Here, we present measurement results, along with comparisons to available literature data and to default equations of state and mixture models included in REFPROP.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Advances in catalytic production processes of biomass-derived vinyl monomers

Plastic industries currently source the majority of monomers from crude oil substances. Although we have witnessed a significant interest of companies in the utilization of sustainable feedstock materials for bio-based compound synthesis in the past decade, the transition to photosynthetic or chemosynthetic plant-based production in a circular carbon economy is largely slow due to complex biomass processing, costs and related reaction factors. The upgrade of the separated platform chemicals with a deeper supporting understanding of processes, models and a root–cause analysis about the underlying distribution challenges of engineered transformation mechanisms, catalyzed conversion pathways and selectivity would be beneficial to advance applied scientific development, bio-refining and manufacturing output amount. This review provides a summary, assessment and perspective for three important polymer-forming vinyl molecules, i.e. acrylic acid, methacrylic acid and styrene. These provide a backbone to produce acrylates, polystyrene, resins, rubbers, protective surface coatings, adhesives, textiles and other obtained copolymers. A succinct analytical overview on the thermo-catalytic intermediate routes for property-wise drop-in alternatives is presented. Sugars, acrolein, allyl alcohol, ethylbenzene, glycerol, 3-hydroxypropionic acid, isobutene, itaconic acid and lactic acid are considered as the main starting reactants. Catalysts span mixed metal oxides, silicates, native or impregnated zeolite frameworks (HBEA, HZSM, and MFI) and hetero-poly acids as well as homogeneous base hydroxides or platinum group metals, supported on carbon, alumina and sulfates. Finally, the article concludes with a brief state sum-up of the results, topics and opportunities for systematic future research or scaling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Horizontal Gene Transfer to a Defensive Symbiont with a Reduced Genome in a Multipartite Beetle Microbiome

Symbiotic mutualisms of bacteria and animals are ubiquitous in nature, running a continuum from facultative to obligate from the perspectives of both partners. The loss of functions required for living independently but not within a host gives rise to reduced genomes in many symbionts. Although the phenomenon of genome reduction can be explained by existing evolutionary models, the initiation of the process is not well understood. Here, we describe the microbiome associated with the eggs of the beetle Lagria villosa, consisting of multiple bacterial symbionts related to Burkholderia gladioli, including a reduced-genome symbiont thought to be the exclusive producer of the defensive compound lagriamide. We show that the putative lagriamide-producing symbiont is the only member of the microbiome undergoing genome reduction and that it has already lost the majority of its primary metabolism and DNA repair pathways. The key step preceding genome reduction in the symbiont was likely the horizontal acquisition of the putative lagriamide lga biosynthetic gene cluster. Unexpectedly, we uncovered evidence of additional horizontal transfers to the symbiont’s genome while genome reduction was occurring and despite a current lack of genes needed for homologous recombination. These gene gains may have given the genome-reduced symbiont a selective advantage in the microbiome, especially given the maintenance of the large lga gene cluster despite ongoing genome reduction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Reviews and syntheses: Ironing out wrinkles in the soil phosphorus cycling paradigm

Soil phosphorus (P) management remains a critical challenge for agriculture worldwide, and yet we are still unable to predict soil P dynamics as confidently as that of carbon (C) or nitrogen (N). This is due to both the complexity of inorganic P (P i ) and organic P (P o ) cycling and the methodological constraints that have limited our ability to trace P dynamics in the soil–plant system. In this review, we describe the challenges for building parsimonious, accurate, and useful biogeochemical models that represent P dynamics and explore the potential of new techniques to usher P biogeochemistry research and modeling forward. We conclude that research efforts should focus on the following: (1) updating the McGill and Cole (1981) model of P o mineralization by clarifying the role and prevalence of biochemical and biological P o mineralization, which we suggest are not mutually exclusive and may co-occur along a continuum of P o substrate stoichiometry; (2) further understanding the dynamics of phytate, a six C compound that can regulate the poorly understood stoichiometry of soil P; (3) exploring the effects of C and P o saturation on P sorption and P o mineralization; and (4) resolving discrepancies between hypotheses about P cycling and the methods used to test these hypotheses.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Electronic characterization of defects in narrow gap semiconductors

We use a Green's function technique to calculate the position of deep defects in narrow gap semiconductors. We consider substitutional (including antisite), vacancy, and interstitial (self and foreign) deep defects. We also use perturbation theory to look at the effect of nonparabolic bands on shallow defect energies and find nonparabolicity can increase the binding by 10 percent or so. We consider mercury cadmium telluride (MCT), mercury zinc telluride (MZT), and mercury zinc selenide (MZS). For substitutional and interstitial defects we look at the situation with and without relaxation. For substitutional impurities in MCT, MZT, and MZS, we consider x (the concentration of Cd or Zn) in the range 0.1 less than x less than 0.3 and also consider appropriate x so E(sub g) = 0.1 eV for each of the three compounds. We consider several cation site s-like deep levels and anion site p-like levels. For E(sub g) = 0.1 eV, we also consider the effects of relaxation. Similar comments apply to the interstitial deep levels whereas no relaxation is considered for the ideal vacancy model. Relaxation effects can be greater for the interstitial than the substitutional cases. Specific results are given in figures and tables and comparison to experiment is made in a limited number of cases. We find, for example, that I, Se, S, Rn, and N are possible cation site, s-like deep levels in MCT and Zn and Mg are for anion site, p-like levels (both levels for substitutional cases). The corresponding cation and anion site levels for interstitial deep defects are (Au, Ag, Hg, Cd, Cu, Zn) and (N, Ar, O, F). For the substitutional cases we have some examples of relaxation moving the levels into the band gap, whereas for the interstitial case we have examples where relaxation moves it out of the band gap. Future work involves calculating the effects of charge state interaction and seeing the effect of relaxation on vacancy levels.

Patterson, James D.↗
NASA NTRS2002

Norfolk State University Research Experience in Earth System Science

The truly interdisciplinary nature of Earth System Science lends itself to the creation of research teams comprised of people with different scientific and technical backgrounds. In the annals of Earth System Science (ESS) education, the lack of an academic major in the discipline might be seen as a barrier to the involvement of undergraduates in the overall ESS-enterprise. This issue is further compounded at minority-serving institutions by the rarity of departments dedicated to Atmospheric Science, Oceanography or even the geosciences. At Norfolk State University, a Historically Black College, a six week, NASA-supported, summer undergraduate research program (REESS - Research Experience in Earth System Science) is creating a model that involves students with majors in diverse scientific disciplines in authentic ESS research coupled with a structured education program. The project is part of a wider effort at the University to enhance undergraduate education by identifying specific areas of student weaknesses regarding the content and process of science. A pre- and post-assessment test, which is focused on some fundamental topics in global climate change, is given to all participants as part of the evaluation of the program. Student attitudes towards the subject and the program's approach are also surveyed at the end of the research experience. In 2002, 11 undergraduates participated in REESS and were educated in the informed use of some of the vast remote sensing resources available through NASA's Earth Science Enterprise (ESE). The program ran from June 3rd through July 12, 2002. This was the final year of the project.

Chaudhury, Raj↗
NASA NTRS2014

Organics Exposure in Orbit (OREOcube): A Next-Generation Space Exposure Platform

The OREOcube (ORganics Exposure in Orbit cube) experiment on the International Space Station (ISS) will investigate the effects of solar and cosmic radiation on organic thin films supported on inorganic substrates. Probing the kinetics of structural changes and photomodulated organic− inorganic interactions with real-time in situ UV−visible spectroscopy, this experiment will investigate the role played by solid mineral surfaces in the (photo)chemical evolution, transport, and distribution of organics in our solar system and beyond. In preparation for the OREOcube ISS experiment, we report here laboratory measurements of the photostability of thin films of the 9,10-anthraquinone derivative anthrarufin (51 nm thick) layered upon ultrathin films of iron oxides magnetite and hematite (4 nm thick), as well as supported directly on fused silica. During irradiation with UV and visible light simulating the photon flux and spectral distribution on the surface of Mars, anthrarufin/iron oxide bilayer thin films were exposed to CO2 (800 Pa), the main constituent (and pressure) of the martian atmosphere. The time-dependent photodegradation of anthrarufin thin films revealed the inhibition of degradation by both types of underlying iron oxides relative to anthrarufin on bare fused silica. Interactions between the organic and inorganic thin films, apparent in spectral shifts of the anthrarufin bands, are consistent with presumed free-electron quenching of semiquinone anion radicals by the iron oxide layers, electively protecting the organic compound from photodegradation. Combining such in situ real-time kinetic measurements of thin films in future space exposure experiments on the ISS with postflight sample return and analysis will provide time-course studies complemented by in-depth chemical analysis. This will facilitate the characterization and modeling of the chemistry of organic species associated with mineral surfaces in astrobiological contexts.

Organics↗
NASA NTRS2020

First Results From an Uncooled LWIR Polarimeter for Cubesat Deployment

A compact long-wave infrared (LWIR) channeled spectro-polarimeter (IRCSP) has been developed for integration into the NASA Earth Science Technology Office (ESTO) funded submm-wave and LWIR polarimeters project to measure the microphysical properties of cloud ice. Once deployed, the IRCSP will produce the first linear Stokes measurements ( S0 , S1 , S2 ) of upper-tropospheric cirrus clouds from 8.5 to 12.5 μm. For the first time, a compact, light-weight, and uncooled LWIR polarimeter with off-the-shelf thermal optical components is demonstrated. We report narrowband calibration measurements which quantify metrics of polarimetric system performance. The response of the system to linearly polarized light is shown to agree with both a Mueller matrix model and modulation function for narrowband calibration measurements with an R2 > 0.98 from 8 to 11 μm. The polarimetric efficiency is >0.8 from 8 to 11 μm for narrowband measurements indicating satisfactory performance of the polarization optics. Beyond 11 μm, the agreement is significantly reduced as thermal noise compounds with reduced detector response. Ultimately, the observed system performance is limited by the spectral response of the detector past 11 μm in addition to the thermal noise inherent for the measurements at room temperature.

LWIR↗
DOE OSTI2025

Mapping Rare Earths and Toxics in E-Waste via Hyperspectral Imaging and Machine Learning

Electronic waste (e-waste) presents a mounting challenge to environmental sustainability due to its complex composition, which includes high-value rare earth elements, hazardous organic compounds, and non-recyclable plastics. Accurate and scalable material classification is essential for enabling efficient resource recovery and safe recycling practices. This study introduces a confidence-aware classification pipeline that combines mid-infrared hyperspectral imaging (HSI), spectral angle mapping (SAM), and iterative machine learning to perform pixel-level material identification across e-waste devices. A curated spectral library encompassing artificial materials (e.g., plastic iron oxide, galvanized metals), minerals (e.g., allanite, hematite), and organic compounds (e.g., benzanthracene, toluene) was used to generate pseudo-labels, each assigned a confidence score based on SAM-derived spectral similarity. High-confidence samples from seven consumer electronics—digital cameras, keyboards, laptop fans, modems, motherboards, TV remotes, and speakers—were iteratively expanded and classified using models such as Support Vector Machine (SVM), Random Forest, Gradient Boosting Classifier, Partial Least Squares Discriminant Analysis (PLSDA) and Logistic Regression. The best-performing classifiers achieved macro F1 scores approaching 1.0. Results revealed widespread plastic content (dominated by plastic iron oxide), the presence of rare earth-bearing minerals like cerium-containing allanite, and pervasive detection of hazardous organics such as benzanthracene. Principal Component Analysis (PCA) visualizations and confusion matrices confirmed high separability and robust classification performance. This methodology enables precise, non-destructive, and scalable classification of heterogeneous e-waste streams. It supports automated, hazard-aware sorting in recycling workflows, facilitating selective recovery of critical materials and compliance with circular economy goals. The confidence-aware framework provides a foundation for real-time deployment in industrial settings, offering significant implications for smart e-recycling infrastructure and policy-driven material stewardship.

Circular economy↗
NASA NTRS1992

Theoretical model for frequency locking a diode laser with a Faraday cell

A new method was developed for frequency locking a diode lasers, called 'the Faraday anomalous dispersion optical transmitter (FADOT) laser locking', which is much simpler than other known locking schemes. The FADOT laser locking method uses commercial laser diodes with no antireflection coatings, an atomic Faraday cell with a single polarizer, and an output coupler to form a compound cavity. The FADOT method is vibration insensitive and exhibits minimal thermal expansion effects. The system has a frequency pull in the range of 443.2 GHz (9 A). The method has potential applications in optical communication, remote sensing, and pumping laser excited optical filters.

Wanninger, P.↗
DOE OSTI2021

Quasi-one-dimensional magnetism in the spin-12 antiferromagnet BaNa 2 Cu(VO 4 ) 2

Here, we report synthesis and magnetic properties of quasi-one-dimensional spin- 1 2 Heisenberg antiferromagnetic chain compound BaNa 2 Cu ( VO 4 ) 2 . This orthovanadate has a centrosymmetric crystal structure, C 2 / c , where the magnetic Cu 2 + ions form spin chains. These chains are arranged in layers, with the chain direction changing by 62 ° between the two successive layers. Alternatively, the spin lattice can be viewed as anisotropic triangular layers upon taking the interchain interactions into consideration. Despite this potential structural complexity, temperature-dependent magnetic susceptibility, heat capacity, electron spin resonance intensity, and nuclear magnetic resonance (NMR) shift agree well with the uniform spin- 1 / 2 Heisenberg chain model with an intrachain coupling of J / k B ≃ 5.6 K. The saturation field obtained from the magnetic isotherm measurement consistently reproduces the value of J / k B . Further, the V 51 NMR spin-lattice relaxation rate mimics the one-dimensional character in the intermediate temperature range, whereas magnetic long-range order sets in below T N ≃ 0.25 K. The effective interchain coupling is estimated to be J ⊥ / k B ≃ 0.1 K. The theoretical estimation of exchange couplings using band-structure calculations reciprocate our experimental findings and unambiguously establish the one-dimensional character of the compound. Finally, the spin lattice of BaNa 2 Cu ( VO 4 ) 2 is compared with the chemically similar but not isostructural compound BaAg 2 Cu ( VO 4 ) 2 .

36 MATERIALS SCIENCE↗
NASA NTRS2021

Machine Learning Models to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

This research uses machine-learned computational analyses to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is from a rodent model exposed to ≤ 15 cGy of individual Galactic Cosmic Radiation (GCR) ions: 4He, 16O, 28Si, 48Ti, or 56Fe, expected for a Lunar or Mars mission. This work investigates rats at a subject-based level and uses performance scores taken before irradiation to predict impairment in Attentional Set-shifting (ATSET) data post-irradiation. Here, the worst performing rats of the control group define the impairment thresholds based on population analyses via cumulative distribution functions, leading to the labeling of impairment for each subject. A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the Simple Discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the Compound Discrimination (CD) stage. On a subject-based level, implementing Machine Learning (ML) classifiers such as the Gaussian Naïve Bayes, Support Vector Machine, and Artificial Neural Networks identifies rats that have a higher tendency for impairment after GCR exposure. The algorithms employ the experimental prescreenperformance scores as multidimensional input features to predict each rodent’s susceptibility to cognitive impairment due to space radiation exposure. The receiver operating characteristic and the precision-recall curves of the ML models show a better prediction of impairment when 56Feis the ion in question in both SD and CD stages. They, however, do not depict impairment due to 4Hein SD and 28Siin CD, suggesting no dose-dependent impairment response in these cases. One key finding of our study is that prescreen performance scores can be used to predict the ATSET performance impairments. This result is significant to crewed space missions as it supports the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. Future research can focus on constructing ML ensemble methods to integrate the findings from the methodologies implemented in this study for morerobust predictionsof cognitive decrements due to space radiation exposure.

space radiation↗
DOE OSTI2023

The HTAP_v3 emission mosaic: merging regional and global monthly emissions (2000–2018) to support air quality modelling and policies

This study, performed under the umbrella of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP), responds to the global and regional atmospheric modelling community's need of a mosaic emission inventory of air pollutants that conforms to specific requirements: global coverage, long time series, spatially distributed emissions with high time resolution, and a high sectoral resolution. The mosaic approach of integrating official regional emission inventories based on locally reported data, with a global inventory based on a globally consistent methodology, allows modellers to perform simulations of high scientific quality while also ensuring that the results remain relevant to policymakers. HTAP_v3, an ad hoc global mosaic of anthropogenic inventories, has been developed by integrating official inventories over specific areas (North America, Europe, Asia including Japan and South Korea) with the independent Emissions Database for Global Atmospheric Research (EDGAR) inventory for the remaining world regions. The results are spatially and temporally distributed emissions of SO 2 , NO $x$ , CO, non-methane volatile organic compounds (NMVOCs), NH 3 , PM 10 , PM 2.5 , black carbon (BC), and organic carbon (OC), with a spatial resolution of 0.1º × 0.1º and time intervals of months and years, covering the period 2000–2018. The emissions are further disaggregated into 16 anthropogenic emitting sectors. This paper describes the methodology applied to develop such an emission mosaic, reports on source allocation, differences among existing inventories, and best practices for the mosaic compilation. One of the key strengths of the HTAP_v3 emission mosaic is its temporal coverage, enabling the analysis of emission trends over the past 2 decades. The development of a global emission mosaic over such long time series represents a unique product for global air quality modelling and for better-informed policymaking, reflecting the community effort expended by the TF-HTAP to disentangle the complexity of transboundary transport of air pollution.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

A comparative bear model for immobility-induced osteopenia

The National Institutes of Health (NIH) and the National Aeronautics and Space Administration (NASA) are seeking solutions to the human problem of osteopenia, or immobility-induced bone loss. Bears, during winter dormancy, appear uniquely exempted from the debilitating effects of immobility osteopenia. NIH and ESA, Inc. are creating a large database of metabolic information on human ambulatory and bedrest plasma samples for comparison with metabolic data obtained from bear plasma samples collected in different seasons. The database generated from NASA's HR113 human bedrest study showed a clear difference between plasma samples of ambulatory and immobile subjects through cluster analysis using compounds determined by high performance liquid chromatography with coulometric electrochemical array detection (HPLC-EC). We collected plasma samples from black bears (Ursus americanus) across 4 seasons and from 3 areas and subjected them to similar analysis, with particular attention to compounds that changed significantly in the NASA human study. We found seasonal differences in 28 known compounds and 33 unknown compounds. A final database contained 40 known and 120 unknown peaks that were reliably assayed in all bear and human samples; these were the primary data set for interspecies comparison. Six unidentified compounds changed significantly but differentially in wintering bears and immobile humans. The data are discussed in light of current theories regarding dormancy, starvation, and anabolic metabolism. Work is in progress by ESA Laboratories on a larger database to confirm these findings prior to a chemical isolation and identification effort. This research could lead to new pharmaceuticals or dietary interventions for the treatment of immobility osteopenia.

NASA Discipline Musculoskeletal↗