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At least 505 records · Page 28

Evidence for increased beta-adrenoreceptor responsiveness induced by 14 days of simulated microgravity in humans

We studied hemodynamic responses to alpha- and beta-receptor agonists in eight healthy men before and after 14 days of 6 degrees head-down tilt (HDT) to test the hypothesis that increased adrenoreceptor responsiveness is induced by prolonged exposure to simulated microgravity. Steady-state infusions of isoproterenol (Iso) at rates of 0.005, 0.01, and 0.02 microgram.kg-1.min-1 were used to assess beta 1- and beta 2-adrenoreceptor responsiveness. Infusions of phenylephrine (PE) at rates of 0.25, 0.50, and 1.00 microgram.kg-1.min-1 were used to assess responsiveness of alpha 1-vascular adrenoreceptors. Slopes calculated from linear regressions between Iso and PE doses and changes in beat-to-beat heart rate, blood pressure, and leg vascular resistance (occlusion plethysmography) for each subject were used as an index of alpha- and beta-adrenoreceptor responsiveness. HDT increased the slopes of heart rate (1,056 +/- 107 to 1,553 +/- 83 beats micrograms-1.kg-1.min-1; P = 0.014) and vasodilation (-469 +/- 111 to -1,446 +/- 309 peripheral resistance units.microgram-1.kg-1.min-1; P = 0.0224) to Iso infusion. There was no alteration in blood pressure or vascular resistance responses to PE infusion after HDT. Our results provide evidence that simulated microgravity causes selective increases in beta 1- and beta 2-adrenoreceptor responsiveness without affecting alpha 1-vascular adrenoreceptor responses.

NASA Discipline Cardiopulmonary↗

Determining blood and plasma volumes using bioelectrical response spectroscopy

We hypothesized that an electric field (inductance) produced by charged blood components passing through the many branches of arteries and veins could assess total blood volume (TBV) or plasma volume (PV). Individual (N = 29) electrical circuits (inductors, two resistors, and a capacitor) were determined from bioelectrical response spectroscopy (BERS) using a Hewlett Packard 4284A Precision LCR Meter. Inductance, capacitance, and resistance from the circuits of 19 subjects modeled TBV (sum of PV and computed red cell volume) and PV (based on 125I-albumin). Each model (N = 10, cross validation group) had good validity based on 1) mean differences (-2.3 to 1.5%) between the methods that were not significant and less than the propagated errors (+/- 5.2% for TBV and PV), 2) high correlations (r > 0.92) with low SEE (< 7.7%) between dilution and BERS assessments, and 3) Bland-Altman pairwise comparisons that indicated "clinical equivalency" between the methods. Given the limitation of this study (10 validity subjects), we concluded that BERS models accurately assessed TBV and PV. Further evaluations of the models' validities are needed before they are used in clinical or research settings.

NASA Discipline Number 00-00↗

Role of physical countermaneuvers in the management of orthostatic hypotension: efficacy and biofeedback augmentation

OBJECTIVE: To evaluate the efficacy of various physical countermaneuvers in reducing orthostatic hypotension and its associated symptoms and to assess the efficacy of biofeedback training in enhancing the effectiveness of physical countermaneuvers. MATERIAL AND METHODS: In nine study subjects with neurogenic orthostatic hypotension, four training sessions on physical countermaneuvers were performed after tilt-up, three with visual feedback on the effect of physical countermaneuvers on blood pressure and other cardiovascular variables. Blood pressure change and orthostatic symptoms during tilt-up were determined, as were the changes in total peripheral resistance, stroke index, and heart rate. RESULTS: The five female and four male patients had a mean age of 53 years and a mean duration of symptoms of 4.2 years. On an orthostatic symptom scale of 0 to 10, these patients had a mean symptom score of 7.3. The increment in systolic blood pressure was better for some maneuvers (such as leg crossing and a combination) than others (such as neck flexion and abdominal contraction). Three patterns of responses to biofeedback were found. Simple maneuvers such as squatting did not improve with training; visual feedback was needed for maneuvers such as thigh contraction, and performance declined without biofeedback; the third pattern, seen in maneuvers such as leg crossing, showed continued improvement with training, even without biofeedback. A survey at 3 to 4 months after training revealed continued use of physical maneuvers (3.8 +/- 3.1 per day), increased standing time with each episode of presyncopal symptoms (8.3 +/- 5.8 minutes), and continued global symptomatic improvement. Total peripheral resistance, but not heart rate or stroke index, showed significant regression with blood pressure improvement. CONCLUSION: Physical countermaneuvers are efficacious in reducing orthostatic hypotension, can be augmented by use of biofeedback, and may significantly improve the functional outcome. The major mechanism of improvement is an increase in total peripheral resistance, presumably by reducing the vascular capacitance.

NASA Program Space Physiology and Countermeasures↗

Power law behavior of RR-interval variability in healthy middle-aged persons, patients with recent acute myocardial infarction, and patients with heart transplants

BACKGROUND. The purposes of the present study were (1) to establish normal values for the regression of log(power) on log(frequency) for, RR-interval fluctuations in healthy middle-aged persons, (2) to determine the effects of myocardial infarction on the regression of log(power) on log(frequency), (3) to determine the effect of cardiac denervation on the regression of log(power) on log(frequency), and (4) to assess the ability of power law regression parameters to predict death after myocardial infarction. METHODS AND RESULTS. We studied three groups: (1) 715 patients with recent myocardial infarction; (2) 274 healthy persons age and sex matched to the infarct sample; and (3) 19 patients with heart transplants. Twenty-four-hour RR-interval power spectra were computed using fast Fourier transforms and log(power) was regressed on log(frequency) between 10(-4) and 10(-2) Hz. There was a power law relation between log(power) and log(frequency). That is, the function described a descending straight line that had a slope of approximately -1 in healthy subjects. For the myocardial infarction group, the regression line for log(power) on log(frequency) was shifted downward and had a steeper negative slope (-1.15). The transplant (denervated) group showed a larger downward shift in the regression line and a much steeper negative slope (-2.08). The correlation between traditional power spectral bands and slope was weak, and that with log(power) at 10(-4) Hz was only moderate. Slope and log(power) at 10(-4) Hz were used to predict mortality and were compared with the predictive value of traditional power spectral bands. Slope and log(power) at 10(-4) Hz were excellent predictors of all-cause mortality or arrhythmic death. To optimize the prediction of death, we calculated a log(power) intercept that was uncorrelated with the slope of the power law regression line. We found that the combination of slope and zero-correlation log(power) was an outstanding predictor, with a relative risk of > 10, and was better than any combination of the traditional power spectral bands. The combination of slope and log(power) at 10(-4) Hz also was an excellent predictor of death after myocardial infarction. CONCLUSIONS. Myocardial infarction or denervation of the heart causes a steeper slope and decreased height of the power law regression relation between log(power) and log(frequency) of RR-interval fluctuations. Individually and, especially, combined, the power law regression parameters are excellent predictors of death of any cause or arrhythmic death and predict these outcomes better than the traditional power spectral bands.

Non-NASA Center↗

Evaluation of nearest-neighbor methods for detection of chimeric small-subunit rRNA sequences

Detection of chimeric artifacts formed when PCR is used to retrieve naturally occurring small-subunit (SSU) rRNA sequences may rely on demonstrating that different sequence domains have different phylogenetic affiliations. We evaluated the CHECK_CHIMERA method of the Ribosomal Database Project and another method which we developed, both based on determining nearest neighbors of different sequence domains, for their ability to discern artificially generated SSU rRNA chimeras from authentic Ribosomal Database Project sequences. The reliability of both methods decreases when the parental sequences which contribute to chimera formation are more than 82 to 84% similar. Detection is also complicated by the occurrence of authentic SSU rRNA sequences that behave like chimeras. We developed a naive statistical test based on CHECK_CHIMERA output and used it to evaluate previously reported SSU rRNA chimeras. Application of this test also suggests that chimeras might be formed by retrieving SSU rRNAs as cDNA. The amount of uncertainty associated with nearest-neighbor analyses indicates that such tests alone are insufficient and that better methods are needed.

NASA Discipline Exobiology↗

Adaptive responses of GLUT-4 and citrate synthase in fast-twitch muscle of voluntary running rats

Glucose transporter (GLUT-4) protein, hexokinase, and citrate synthase (proteins involved in oxidative energy production from blood glucose catabolism) increase in response to chronically elevated neuromuscular activity. It is currently unclear whether these proteins increase in a coordinated manner in response to this stimulus. Therefore, voluntary wheel running (WR) was used to chronically overload the fast-twitch rat plantaris muscle and the myocardium, and the early time courses of adaptative responses of GLUT-4 protein and the activities of hexokinase and citrate synthase were characterized and compared. Plantaris hexokinase activity increased 51% after just 1 wk of WR, whereas GLUT-4 and citrate synthase were increased by 51 and 40%, respectively, only after 2 wk of WR. All three variables remained comparably elevated (+50-64%) through 4 wk of WR. Despite the overload of the myocardium with this protocol, no substantial elevations in these variables were observed. These findings are consistent with a coordinated upregulation of GLUT-4 and citrate synthase in the fast-twitch plantaris, but not in the myocardium, in response to this increased neuromuscular activity. Regulation of hexokinase in fast-twitch muscle appears to be uncoupled from regulation of GLUT-4 and citrate synthase, as increases in the former are detectable well before increases in the latter.

Non-NASA Center↗

Prediction of functional aerobic capacity without exercise testing

The purpose of this study was to develop functional aerobic capacity prediction models without using exercise tests (N-Ex) and to compare the accuracy with Astrand single-stage submaximal prediction methods. The data of 2,009 subjects (9.7% female) were randomly divided into validation (N = 1,543) and cross-validation (N = 466) samples. The validation sample was used to develop two N-Ex models to estimate VO2peak. Gender, age, body composition, and self-report activity were used to develop two N-Ex prediction models. One model estimated percent fat from skinfolds (N-Ex %fat) and the other used body mass index (N-Ex BMI) to represent body composition. The multiple correlations for the developed models were R = 0.81 (SE = 5.3 ml.kg-1.min-1) and R = 0.78 (SE = 5.6 ml.kg-1.min-1). This accuracy was confirmed when applied to the cross-validation sample. The N-Ex models were more accurate than what was obtained from VO2peak estimated from the Astrand prediction models. The SEs of the Astrand models ranged from 5.5-9.7 ml.kg-1.min-1. The N-Ex models were cross-validated on 59 men on hypertensive medication and 71 men who were found to have a positive exercise ECG. The SEs of the N-Ex models ranged from 4.6-5.4 ml.kg-1.min-1 with these subjects.(ABSTRACT TRUNCATED AT 250 WORDS).

Oxygen Consumption↗

Homozygous diploid deletion strains of Saccharomyces cerevisiae that determine lag phase and dehydration tolerance

This study identifies genes that determine length of lag phase, using the model eukaryotic organism, Saccharomyces cerevisiae. We report growth of a yeast deletion series following variations in the lag phase induced by variable storage times after drying-down yeast on filters. Using a homozygous diploid deletion pool, lag times ranging from 0 h to 90 h were associated with increased drop-out of mitochondrial genes and increased survival of nuclear genes. Simple linear regression (R2 analysis) shows that there are over 500 genes for which > 70% of the variation can be explained by lag alone. In the genes with a positive correlation, such that the gene abundance increases with lag and hence the deletion strain is suitable for survival during prolonged storage, there is a strong predominance of nucleonic genes. In the genes with a negative correlation, such that the gene abundance decreases with lag and hence the strain may be critical for getting yeast out of the lag phase, there is a strong predominance of glycoproteins and transmembrane proteins. This study identifies yeast deletion strains with survival advantage on prolonged storage and amplifies our understanding of the genes critical for getting out of the lag phase.

NASA Discipline Cell Biology↗

Trends and Solar Cycle Effects in Temperature Versus Altitude From the Halogen Occultation Experiment for the Mesosphere and Upper Stratosphere

Fourteen-year time series of mesospheric and upper stratospheric temperatures from the Halogen Occultation Experiment (HALOE) are analyzed and reported. The data have been binned according to ten-degree wide latitude zones from 40S to 40N and at 10 altitudes from 43 to 80 km-a total of 90 separate time series. Multiple linear regression (MLR) analysis techniques have been applied to those time series. This study focuses on resolving their 11-yr solar cycle (or SC-like) responses and their linear trend terms. Findings for T(z) from HALOE are compared directly with published results from ground-based Rayleigh lidar and rocketsonde measurements. SC-like responses from HALOE compare well with those from lidar station data at low latitudes. The cooling trends from HALOE also agree reasonably well with those from the lidar data for the concurrent decade. Cooling trends of the lower mesosphere from HALOE are not as large as those from rocketsondes and from lidar station time series of the previous two decades, presumably because the changes in the upper stratospheric ozone were near zero during the HALOE time period and did not affect those trends.

Remsberg, Ellis E.↗

Skill in Retrievals

Retrieval Skill quantifies the ability of one retrieval from a sounder to be more accurate than the best forecast relative to another with the same of another sounder. This is summarized using a Retrieval Anomaly Skill Score (RASS) which is the cor (retrieved-background, truth-background) * sqrt(f), Where f is defined as the ratio of accepted to the possible retrievals. Charts show various features and comparisons of RASS to other methods of retrieval.

forecasting↗

Decadal-Scale Responses in Middle and Upper Stratospheric Ozone From SAGE II Version 7 Data

Stratospheric Aerosol and Gas Experiment (SAGE II) version 7 (v7) ozone profiles are analyzed for their decadal-scale responses in the middle and upper stratosphere for 1991 and 1992-2005 and compared with those from its previous version 6.2 (v6.2). Multiple linear regression (MLR) analysis is applied to time series of its ozone number density vs. altitude data for a range of latitudes and altitudes. The MLR models that are fit to the time series data include a periodic 11 yr term, and it is in-phase with that of the 11 yr, solar UV (Ultraviolet)-flux throughout most of the latitude/ altitude domain of the middle and upper stratosphere. Several regions that have a response that is not quite in-phase are interpreted as being affected by decadal-scale, dynamical forcings. The maximum minus minimum, solar cycle (SClike) responses for the ozone at the low latitudes are similar from the two SAGE II data versions and vary from about 5 to 2.5% from 35 to 50 km, although they are resolved better with v7. SAGE II v7 ozone is also analyzed for 1984-1998, in order to mitigate effects of end-point anomalies that bias its ozone in 1991 and the analyzed results for 1991-2005 or following the Pinatubo eruption. Its SC-like ozone response in the upper stratosphere is of the order of 4%for 1984-1998 vs. 2.5 to 3%for 1991-2005. The SAGE II v7 results are also recompared with the responses in ozone from the Halogen Occultation Experiment (HALOE) that are in terms of mixing ratio vs. pressure for 1991-2005 and then for late 1992- 2005 to avoid any effects following Pinatubo. Shapes of their respective response profiles agree very well for 1992-2005. The associated linear trends of the ozone are not as negative in 1992-2005 as in 1984-1998, in accord with a leveling off of the effects of reactive chlorine on ozone. It is concluded that the SAGE II v7 ozone yields SC-like ozone responses and trends that are of better quality than those from v6.2.

Remsberg, E. E.↗

Algorithm Development and Validation of CDOM Properties for Estuarine and Continental Shelf Waters Along the Northeastern U.S. Coast

An extensive set of field measurements have been collected throughout the continental margin of the northeastern U.S. from 2004 to 2011 to develop and validate ocean color satellite algorithms for the retrieval of the absorption coefficient of chromophoric dissolved organic matter (aCDOM) and CDOM spectral slopes for the 275:295 nm and 300:600 nm spectral range (S275:295 and S300:600). Remote sensing reflectance (Rrs) measurements computed from in-water radiometry profiles along with aCDOM() data are applied to develop several types of algorithms for the SeaWiFS and MODIS-Aqua ocean color satellite sensors, which involve least squares linear regression of aCDOM() with (1) Rrs band ratios, (2) quasi-analytical algorithm-based (QAA based) products of total absorption coefficients, (3) multiple Rrs bands within a multiple linear regression (MLR) analysis, and (4) diffuse attenuation coefficient (Kd). The relative error (mean absolute percent difference; MAPD) for the MLR retrievals of aCDOM(275), aCDOM(355), aCDOM(380), aCDOM(412) and aCDOM(443) for our study region range from 20.4-23.9 for MODIS-Aqua and 27.3-30 for SeaWiFS. Because of the narrower range of CDOM spectral slope values, the MAPD for the MLR S275:295 and QAA-based S300:600 algorithms are much lower ranging from 9.9 and 8.3 for SeaWiFS, respectively, and 8.7 and 6.3 for MODIS, respectively. Seasonal and spatial MODIS-Aqua and SeaWiFS distributions of aCDOM, S275:295 and S300:600 processed with these algorithms are consistent with field measurements and the processes that impact CDOM levels along the continental shelf of the northeastern U.S. Several satellite data processing factors correlate with higher uncertainty in satellite retrievals of aCDOM, S275:295 and S300:600 within the coastal ocean, including solar zenith angle, sensor viewing angle, and atmospheric products applied for atmospheric corrections. Algorithms that include ultraviolet Rrs bands provide a better fit to field measurements than algorithms without the ultraviolet Rrs bands. This suggests that satellite sensors with ultraviolet capability could provide better retrievals of CDOM. Because of the strong correlations between CDOM parameters and DOM constituents in the coastal ocean, satellite observations of CDOM parameters can be applied to study the distributions, sources and sinks of DOM, which are relevant for understanding the carbon cycle, modeling the Earth system, and to discern how the Earth is changing.

CDOM Properties↗

Simultaneous Development and Robust Optimization of a Microstructure Dependent Material

Recent microstructure characterization techniques combined with Symbolic Regression(SR)analysis has been proven to generate white box plasticity models well suited for incorporation into FEA software.The current work builds upon those efforts and demonstrates the applicability of Sequential Monte-Carlo (SMC) methods within SR analysis to condense model development and robust optimization into a single, co-dependent process. In this project, SMC methods provide a mechanism through which the observed microstructure features and associated variability can be incorporated into the discovery phase of model development and simultaneously recover approximate parameter distributions through SR analysis. The demonstration utilized a data set consisting of tensile test results from a limited number of sample specimens with corresponding EBSD data from which microstructure features were characterized.The maximum threshold stress model in the Visco-Plastic Self-Consistent (VPSC) code developed by Los Alamos National Laboratories was calibrated using mechanical test data.Synthetic volume elements with statistically equivalent microstructure were generated with DREAM3Dbased on the observed EBSD data. VPSC was used to simulate the corresponding tensile test response for each of the synthetic volume elements. The simulated microstructure and tensile test data was used astraining datafor SMC-SR algorithm and the resulting model was validated with data from the original empirical data set.

Karl Garbrecht↗

Geometric Sensitivity of Residual Fields in Metal Additive Manufacturing

The sensitivity of geometrical parameters on the residual stress and distortion as computed by a metal additive manufacturing simulation is presented. A nozzle-like geometry was chosen with its length, wall thickness, and outer radius varied. A Latin hypercube sampling of 300 specimens produced the combinations of the geometrical parameters. Full thermomechanical simulations predicted the residual fields. Statistical analysis including regression curves shows that there is a strong correlation between these residual fields and the geometry, hinting that it may be possible to predictably influence the residual displacements and residual stresses by varying the overall geometry.

Multiscale Modeling↗

Decoding diffraction and spectroscopy data with machine learning: A tutorial

This Tutorial provides a step-by-step guide on how to apply supervised machine-learning techniques to analyze diffraction and spectroscopy data. This Tutorial details four models—a reconstruction-focused model, a regression-focused model, a hybrid reconstruction/regression model, and a multimodal model—that use x-ray diffraction profiles and vibrational density of states spectra to predict various microstructural descriptors. In this Tutorial, we cover data pre-processing steps, constructions of the models via dimensionality reduction and regression, training, and analysis of these models. Comparisons of the model’s performance are provided, highlighting the strength and weakness of the various approaches utilized.

36 MATERIALS SCIENCE↗

Multilevel Probit Regression for 3-Alternative Forced Choice Audibility Testing

A recent psychoacoustic test at NASA Langley generated a dataset of 3-alternative forced-choice responses for 40 subjects that measured the audibility of a tone complex in a shaped broadband masker. The task was completed by 4 subjects at a time in a small theatre-like environment using predetermined stimuli levels. These data were subject to 4 forms of probit regression: a “complete pooling” analysis in which all data from the test was fit with one curve, two forms of “no pooling” analyses in which subjects’ data were treated individually (using both packaged and custom software), and a “partial pooling” analysis in which multilevel-regression software fit both individual curves as well as population-level parameters at the same time. The results of the analyses are compared in terms of both individual- and population-level parameters. Partial pooling appears to give the most consistent results at both levels, as well as provide the most robustness among the packaged approaches (albeit with added complexity over single-level regression). These results are also contained in a recent NASA technical memorandum entitled “Comparisons of Analysis Methods Applied to Alternative Forced Choice Audibility Data.”

Psychoacoustics↗

Statistical Analysis of Factors Riving Surface Ozone Variability over Continental South Africa

Statistical relationships between surface ozone (O3) concentration, precursor species and meteorological conditions in continental South Africa were examined from data obtained from measurement stations in north-eastern South Africa. Three multivariate statistical methods were applied in the investigation, i.e. multiple linear regression (MLR), principal component analysis (PCA) and –regression (PCR), and generalised additive model (GAM) analysis. The daily maximum 8-h moving average O3 concentrations were considered in these statistical models (dependent variable). MLR models indicated that meteorology and precursor species concentrations are able to explain ~50% of the variability in daily maximum O3 levels. MLR analysis revealed that atmospheric carbon monoxide (CO), temperature and relative humidity were the strongest factors affecting the daily O3 variability. In summer, daily O3 variances were mostly associated with relative humidity, while winter O3 levels were mostly linked to temperature and CO. PCA indicated that CO, temperature and relative humidity were not strongly collinear. GAM also identified CO, temperature and relative humidity as the strongest factors affecting the daily variation of O3. Partial residual plots found that temperature, radiation and nitrogen oxides most likely have a non-linear relationship with O3,while the relationship with relative humidity and CO is probably linear. An inter-comparison between O3 levels modelled with the three statistical models compared to measured O3 concentrations showed that the GAM model offered a slight improvement over the MLR model. These findings emphasise the critical role of regional-scale O3 precursors coupled with meteorological conditions in daily variances of O3 levels in continental South Africa.

multiple linear regression (MLR)↗

Comparison of Electrical Output Format Options for the Analysis of Strain-Gage Balance Calibration Data

Fundamental characteristics of three gage output formats are discussed that may be used to both interpret and analyze wind tunnel strain-gage balance data. The first output format uses raw outputs, i.e., absolute voltage measurements, for the analysis. This choice requires an intercept term in the regression model of the outputs if the Iterative Method is chosen for the load prediction. Raw outputs can be used for the analysis of all known output characteristics as long as the Iterative Method is applied. However, raw outputs cannot be used to analyze data of a balance with bi-directional outputs if the Non-Iterative Method is chosen for the analysis. The second output format, i.e., difference type 1, uses the difference between raw outputs and the natural zeros of the balance gages for the analysis. In this case, the use of the intercept term becomes optional. Analysis results for difference type 1 will exactly match analysis results obtained by using raw outputs as long as identical math models are used for the regression analysis. In addition, difference type 1 may be used to analyze data of a balance with bi directional outputs if an analyst prefers to process data using the Non-Iterative Method. The third output format, i.e., difference type 2, uses the difference between raw outputs and the outputs of the zero load point of a load series for the data analysis. The application of this format is only recommended if the maximum magnitude of all tare loads of a given balance calibration data set is less than two percent of capacity. Data from the calibration of a force balance is used to illustrate the application of the three gage output formats.

Wind Tunnel Strain-Gage Balance↗