942 resultados para Regression To The Mean


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BACKGROUND Quality of life (QoL) is a subjective perception whose components may vary in importance between individuals. Little is known about which domains of QoL older people deem most important. OBJECTIVE This study investigated in community-dwelling older people the relationships between the importance given to domains defining their QoL and socioeconomic, demographic and health status. METHODS Data were compiled from older people enrolled in the Lc65+ cohort study and two additional, population-based, stratified random samples (n = 5,300). Principal components analysis (PCA) was used to determine the underlying domains among 28 items that participants defined as important to their QoL. The components extracted were used as dependent variables in multiple linear regression models to explore their associations with socioeconomic, demographic and health status. RESULTS PCA identified seven domains that older persons considered important to their QoL. In order of importance (highest to lowest): feeling of safety, health and mobility, autonomy, close entourage, material resources, esteem and recognition, and social and cultural life. A total of six and five domains of importance were significantly associated with education and depressive symptoms, respectively. The importance of material resources was significantly associated with a good financial situation (β = 0.16, P = 0.011), as was close entourage with living with others (β = 0.20, P = 0.007) and as was health and mobility with age (β = -0.16, P = 0.014). CONCLUSION The importance older people give to domains of their QoL appears strongly related to their actual resources and experienced losses. These findings may help clinicians, researchers and policy makers better adapt strategies to individuals' needs.

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Many studies investigated solar–terrestrial responses (thermal state, O₃ , OH, H₂O) with emphasis on the tropical upper atmosphere. In this paper the Focus is switched to water vapor in the mesosphere at a mid-latitudinal location. Eight years of water vapor profile measurements above Bern (46.88°N/7.46°E) are investigated to study oscillations with the Focus on periods between 10 and 50 days. Different spectral analyses revealed prominent features in the 27-day oscillation band, which are enhanced in the upper mesosphere (above 0.1 hPa, ∼64 km) during the rising sun spot activity of solar cycle 24. Local as well as zonal mean Aura MLS observations Support these results by showing a similar behavior. The relationship between mesospheric water and the solar Lyman-α flux is studied by comparing thesi-milarity of their temporal oscillations. The H₂O oscillation is negatively correlated to solar Lyman-α oscillation with a correlation coefficient of up to −0.3 to −0.4, and the Phase lag is 6–10 days at 0.04 hPa. The confidence level of the correlation is ≥99%. This finding supports the assumption that the 27-day oscillation in Lyman-α causes a periodical photo dissociation loss in mesospheric water. Wavelet power spectra, cross-wavelet transform and wavelet coherence analysis (WTC)complete our study. More periods of high common wavelet power of H₂O and solar Lyman-α are present when amplitudes of the Lyman-α flux increase. Since this is not a measure of physical correlation a more detailed view on WTC is necessary, where significant (two sigma level)correlations occur intermittently in the 27 and 13-day band with variable Phase lock behavior. Large Lyman-α oscillations appeared after the solar super storm in July 2012 and the H₂O oscillations show a well pronounced anticorrelation. The competition between advective transport and photo dissociation loss of mesospheric water vapor may explain the sometimes variable Phase relationship of mesospheric H₂O and solar Lyman-α oscillations. Generally, the WTC analysis indicates that solar variability causes observable photochemical and dynamical processes in the mid-latitude mesosphere.

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Improvements in the analysis of microarray images are critical for accurately quantifying gene expression levels. The acquisition of accurate spot intensities directly influences the results and interpretation of statistical analyses. This dissertation discusses the implementation of a novel approach to the analysis of cDNA microarray images. We use a stellar photometric model, the Moffat function, to quantify microarray spots from nylon microarray images. The inherent flexibility of the Moffat shape model makes it ideal for quantifying microarray spots. We apply our novel approach to a Wilms' tumor microarray study and compare our results with a fixed-circle segmentation approach for spot quantification. Our results suggest that different spot feature extraction methods can have an impact on the ability of statistical methods to identify differentially expressed genes. We also used the Moffat function to simulate a series of microarray images under various experimental conditions. These simulations were used to validate the performance of various statistical methods for identifying differentially expressed genes. Our simulation results indicate that tests taking into account the dependency between mean spot intensity and variance estimation, such as the smoothened t-test, can better identify differentially expressed genes, especially when the number of replicates and mean fold change are low. The analysis of the simulations also showed that overall, a rank sum test (Mann-Whitney) performed well at identifying differentially expressed genes. Previous work has suggested the strengths of nonparametric approaches for identifying differentially expressed genes. We also show that multivariate approaches, such as hierarchical and k-means cluster analysis along with principal components analysis, are only effective at classifying samples when replicate numbers and mean fold change are high. Finally, we show how our stellar shape model approach can be extended to the analysis of 2D-gel images by adapting the Moffat function to take into account the elliptical nature of spots in such images. Our results indicate that stellar shape models offer a previously unexplored approach for the quantification of 2D-gel spots. ^

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Purpose. The central concepts in pressure ulcer risk are exposure to external pressure caused by inactivity and tissue tolerance to pressure, a factor closely related to blood flow. Inactivity measures are effective in predicting pressure ulcer risk. The purpose of the study is to evaluate whether a physiological measure of skin blood flow improves pressure ulcer risk prediction. Skin temperature regularity and self-similarity, as proxy measures of blood flow, and not previously described, may be undefined pressure ulcer risk factors. The specific aims were to determine whether a sample of nursing facility residents at high risk of pressure ulcers classified using the Braden Scale for Pressure Sore Risk© differ from a sample of low risk residents according to (1) exposure to external pressure as measured by resident activity, (2) tissue tolerance to external pressure as measured by skin temperature, and (3) skin temperature fluctuations and recovery in response to a commonly occurring stressor, bathing and additionally whether (4) scores on the Braden Scale mobility subscale score are related to entropy and the spectral exponent. ^ Methods. A two group observational time series design was used to describe activity and skin temperature regularity and self-similarity, calculating entropy and the spectral exponent using detrended fluctuation analysis respectively. Twenty nursing facility residents wore activity and skin temperature monitors for one week. One bathing episode was observed as a commonly occurring stressor for skin temperature.^ Results. Skin temperature multiscale entropy (MSE), F(1, 17) = 5.55, p = .031, the skin temperature spectral exponent, F(1, 17) = 6.19, p = .023, and the activity mean MSE, F(1, 18) = 4.52, p = .048 differentiated the risk groups. The change in skin temperature entropy during bathing was significant, t(16) = 2.55, p = .021, (95% CI, .04-.40). Multiscale entropy for skin temperature was lowest in those who developed pressure ulcers, F(1, 18) = 35.14, p < .001.^ Conclusions. This study supports the tissue tolerance component of the Braden and Bergstrom conceptual framework and shows differences in skin temperature multiscale entropy between pressure ulcer risk categories, pressure ulcer outcome, and during a commonly occurring stressor. ^

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This study examines Hispanic levels of incorporation and access to health care. Applying the Aday and Andersen framework for the study of access, the study examined the relationship between two levels of Hispanic incorporation into U.S. society, i.e., mainstream versus ethnic, and potential and realized measures of access to health care. Data for the study were drawn from a 1992 telephone survey of 600 randomly selected Hispanics in Houston and Harris County.^ The hypotheses tested were: (1) Hispanics who are incorporated into mainstream society are more likely to have better potential and realized access to health care than those who are incorporated into ethnic-group enclaves regardless of their socioeconomic status (SES), health status and health needs, and (2) there is no interaction between the levels of incorporation (mainstream or ethnic) and SES, health status, and health needs in predicting potential and realized access.^ The data analysis supported Hypothesis One for the two measures of potential access. The results of bivariate and multiple logistic regression analyses indicated that for Hispanics in Houston and Harris County, being in the "mainstream" incorporation category increased their potential access to care, having "health insurance" and a "regular place of care". For the selected measure of realized access, having a "regular check-up", the analysis did not demonstrate statistically significant differences in having a regular check-up among Hispanics incorporated in the ethnic or mainstream incorporation categories.^ Hypothesis Two, that there is no interaction between the levels of incorporation and socioeconomic characteristics, health status, and health needs in predicting potential and realized access among Hispanics was supported by the data. The results of the logistic regression analysis showed that, after adjusting for socioeconomic status, health status, and health needs, the association between "level of incorporation" and the two measures of potential access ("health insurance" and having a "usual place of care") was not modified by the control variables nor by their interaction with level of incorporation. That is, the effect of incorporation on Hispanics' health insurance coverage, and having a usual place of care, was homogenous across Hispanics with different SES and health status.^ The main research implication of this dissertation is the employment of a theoretical framework for the assessment of cultural factors essential to research on migrating heterogeneous subpopulations. It also provided strategies to solve practical and methodological difficulties in the secondary analyses of data on these populations. ^

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Pteropods are a group of holoplanktonic gastropods for which global biomass distribution patterns remain poorly resolved. The aim of this study was to collect and synthesize existing pteropod (Gymnosomata, Thecosomata and Pseudothecosomata) abundance and biomass data, in order to evaluate the global distribution of pteropod carbon biomass, with a particular emphasis on its seasonal, temporal and vertical patterns. We collected 25 902 data points from several online databases and a number of scientific articles. The biomass data has been gridded onto a 360 x 180° grid, with a vertical resolution of 33 WOA depth levels. Data has been converted to NetCDF format. Data were collected between 1951-2010, with sampling depths ranging from 0-1000 m. Pteropod biomass data was either extracted directly or derived through converting abundance to biomass with pteropod specific length to weight conversions. In the Northern Hemisphere (NH) the data were distributed evenly throughout the year, whereas sampling in the Southern Hemisphere was biased towards the austral summer months. 86% of all biomass values were located in the NH, most (42%) within the latitudinal band of 30-50° N. The range of global biomass values spanned over three orders of magnitude, with a mean and median biomass concentration of 8.2 mg C l-1 (SD = 61.4) and 0.25 mg C l-1, respectively for all data points, and with a mean of 9.1 mg C l-1 (SD = 64.8) and a median of 0.25 mg C l-1 for non-zero biomass values. The highest mean and median biomass concentrations were located in the NH between 40-50° S (mean biomass: 68.8 mg C l-1 (SD = 213.4) median biomass: 2.5 mg C l-1) while, in the SH, they were within the 70-80° S latitudinal band (mean: 10.5 mg C l-1 (SD = 38.8) and median: 0.2 mg C l-1). Biomass values were lowest in the equatorial regions. A broad range of biomass concentrations was observed at all depths, with the biomass peak located in the surface layer (0-25 m) and values generally decreasing with depth. However, biomass peaks were located at different depths in different ocean basins: 0-25 m depth in the N Atlantic, 50-100 m in the Pacific, 100-200 m in the Arctic, 200-500 m in the Brazilian region and >500 m in the Indo-Pacific region. Biomass in the NH was relatively invariant over the seasonal cycle, but more seasonally variable in the SH. The collected database provides a valuable tool for modellers for the study of ecosystem processes and global biogeochemical cycles.

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This study presents a newly compiled dataset of modern pollen and climate data from 798 sites across Japan and the Russian Far East. This comprehensive reference dataset combined with the modern analogue technique (MAT) provides a powerful tool for pollen-based reconstruction of the Quaternary Northwest Pacific climate. Pollen-derived reconstruction of the modern climate at the reference pollen-sampling sites matches well with the estimated modern climate values (R2 values vary between 0.79 and 0.95, and RMSEP values vary between 5.8 and 9.7% of the modern climatic range for all nine tested variables). The successful testing of the method encourages its application to the fossil pollen records. We used a coarse-resolution pollen record from Lake Biwa to reconstruct glacial-interglacial climate dynamics in central Japan since ~438 kyr and compared it to the earlier reconstruction based on a less representative reference dataset. The current and earlier results consistently demonstrate that the coldest glacial intervals experienced pronounced cooling in winter and moderate cooling in summer, supporting the growth of cool mixed forest (COMX) where warm mixed forest (WAMX) predominates today. During the last glacial, maximum (~24 kyr BP) mean temperatures of the coldest (MTCO) and warmest (MTWA) month were about -13 °C (RMSEP = 2.34 °C) and 21 °C (RMSEP = 1.66 °C) respectively, and annual precipitation (PANN) was about 800 mm (RMSEP = 158.06 mm). During the thermal optimums of the interglacial intervals, the temperatures of the coldest and warmest month were above 0 °C and 25 °C respectively, leading to the reconstruction of WAMX and temperate conifer forest (TECO). Although both these vegetation types grow in the southern part of Japan today, WAMX requires warmer space. The presence of WAMX during marine isotope stages (MIS) 11 and 1, and its absence during MIS 9 and MIS 5 contradict the marine isotope and Antarctic ice records, suggesting that the latter two interglacials were the warmest of the last 800 kyr. The apparent contradiction allows at least three different explanations including low temporal resolution of the pollen record; different trends in CO2 concentrations during 'short' and 'long' interglacials; and regional climate variability and non-linear response of different regions to the global forcing. More definitive conclusions will be possible on the basis of forthcoming high-resolution pollen records from central Japan.

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The reconstruction of the stable carbon isotope evolution in atmospheric CO2 (d13Catm ), as archived in Antarctic ice cores, bears the potential to disentangle the contributions of the different carbon cycle fluxes causing past CO2 variations. Here we present a new record of d13Catm before, during and after the Marine Isotope Stage 5.5 (155 000 to 105 000 years BP). The record was derived with a well established sublimation method using ice from the EPICA Dome C (EDC) and the Talos Dome ice cores in East Antarctica. We find a 0.4 permil shift to heavier values between the mean d13Catm level in the Penultimate (~ 140 000 years BP) and Last Glacial Maximum (~ 22 000 years BP), which can be explained by either (i) changes in the isotopic composition or (ii) intensity of the carbon input fluxes to the combined ocean/atmosphere carbon reservoir or (iii) by long-term peat buildup. Our isotopic data suggest that the carbon cycle evolution along Termination II and the subsequent interglacial was controlled by essentially the same processes as during the last 24 000 years, but with different phasing and magnitudes. Furthermore, a 5000 years lag in the CO2 decline relative to EDC temperatures is confirmed during the glacial inception at the end of MIS 5.5 (120 000 years BP). Based on our isotopic data this lag can be explained by terrestrial carbon release and carbonate compensation.

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To understand the validity of d18O proxy records as indicators of past temperature change, a series of experiments was conducted using an atmospheric general circulation model fitted with water isotope tracers (Community Atmosphere Model version 3.0, IsoCAM). A pre-industrial simulation was performed as the control experiment, as well as a simulation with all the boundary conditions set to Last Glacial Maximum (LGM) values. Results from the pre-industrial and LGM simulations were compared to experiments in which the influence of individual boundary conditions (greenhouse gases, ice sheet albedo and topography, sea surface temperature (SST), and orbital parameters) were changed each at a time to assess their individual impact. The experiments were designed in order to analyze the spatial variations of the oxygen isotopic composition of precipitation (d18Oprecip) in response to individual climate factors. The change in topography (due to the change in land ice cover) played a significant role in reducing the surface temperature and d18Oprecip over North America. Exposed shelf areas and the ice sheet albedo reduced the Northern Hemisphere surface temperature and d18Oprecip further. A global mean cooling of 4.1 °C was simulated with combined LGM boundary conditions compared to the control simulation, which was in agreement with previous experiments using the fully coupled Community Climate System Model (CCSM3). Large reductions in d18Oprecip over the LGM ice sheets were strongly linked to the temperature decrease over them. The SST and ice sheet topography changes were responsible for most of the changes in the climate and hence the d18Oprecip distribution among the simulations.

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We examine variations in the ice-rafted sources for sediments in the Iceland/East Greenland offshore marine archives by utilizing a sediment unmixing model and link the results to a coupled iceberg-ocean model. Surface samples from around Iceland and along the E/NE Greenland shelf are used to define potential sediment sources, and these are examined within the context of the down-core variations in mineralogy in the <2 mm sediment fraction from a transect of cores across Denmark Strait. A sediment unmixing model is used to estimate the fraction of sediment <2 mm off NW and N Iceland exported across Denmark Strait; this averaged between 10 and 20%. Both the sediment unmixing model and the coupled iceberg-ocean model are consistent in finding that the fraction of "far-travelled" sediments in the Denmark Strait environs is overwhelmingly of local, mid-East Greenland, provenance, and therefore with a significant cross-channel component to their travel. The Holocene record of ice-rafted sediments denotes a three-part division of the Holocene in terms of iceberg sediment transport with a notable increase in the process starting ca 4000 cal yr BP. This latter increase may represent the re-advance during the Neoglacial period of land-terminating glaciers on the Geikie Plateau to become marine-terminating. The contrast in spectral signals between these cores and the 1500-yr cycle at VM28-14, just south of the Denmark Strait, combined with the coupled iceberg-model results, leads us to speculate that the signal at VM28-14 reflects pulses in overflow waters, rather than an ice-rafted signal.

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We present results from a field study of inorganic carbon (C) acquisition by Ross Sea phytoplankton during Phaeocystis-dominated early season blooms. Isotope disequilibrium experiments revealed that HCO3? was the primary inorganic C source for photosynthesis in all phytoplankton assemblages. From these experiments, we also derived relative enhancement factors for HCO3?/CO2 interconversion as a measure of extracellular carbonic anhydrase activity (eCA). The enhancement factors ranged from 1.0 (no apparent eCA activity) to 6.4, with an overall mean of 2.9. Additional eCA measurements, made using membrane inlet mass spectrometry (MIMS), yielded activities ranging from 2.4 to 6.9 U/[?g chl a] (mean 4.1). Measurements of short-term C-fixation parameters revealed saturation kinetics with respect to external inorganic carbon, with a mean half-saturation constant for inorganic carbon uptake (K1/2) of ~380 ?M. Comparison of our early springtime results with published data from late-season Ross Sea assemblages showed that neither HCO3? utilization nor eCA activity was significantly correlated to ambient CO2 levels or phytoplankton taxonomic composition. We did, however, observe a strong negative relationship between surface water pCO2 and short-term 14C-fixation rates for the early season survey. Direct incubation experiments showed no statistically significant effects of pCO2 (10 to 80 Pa) on relative HCO3? utilization or eCA activity. Our results provide insight into the seasonal regulation of C uptake by Ross Sea phytoplankton across a range of pCO2 and phytoplankton taxonomic composition.

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Macrozooplankton are an important link between higher and lower trophic levels in the oceans. They serve as the primary food for fish, reptiles, birds and mammals in some regions, and play a role in the export of carbon from the surface to the intermediate and deep ocean. Little, however, is known of their global distribution and biomass. Here we compiled a dataset of macrozooplankton abundance and biomass observations for the global ocean from a collection of four datasets. We harmonise the data to common units, calculate additional carbon biomass where possible, and bin the dataset in a global 1 x 1 degree grid. This dataset is part of a wider effort to provide a global picture of carbon biomass data for key plankton functional types, in particular to support the development of marine ecosystem models. Over 387 700 abundance data and 1330 carbon biomass data have been collected from pre-existing datasets. A further 34 938 abundance data were converted to carbon biomass data using species-specific length frequencies or using species-specific abundance to carbon biomass data. Depth-integrated values are used to calculate known epipelagic macrozooplankton biomass concentrations and global biomass. Global macrozooplankton biomass has a mean of 8.4 µg C l-1, median of 0.15 µg C l-1 and a standard deviation of 63.46 µg C l-1. The global annual average estimate of epipelagic macrozooplankton, based on the median value, is 0.02 Pg C. Biomass is highest in the tropics, decreasing in the sub-tropics and increasing slightly towards the poles. There are, however, limitations on the dataset; abundance observations have good coverage except in the South Pacific mid latitudes, but biomass observation coverage is only good at high latitudes. Biomass is restricted to data that is originally given in carbon or to data that can be converted from abundance to carbon. Carbon conversions from abundance are restricted in the most part by the lack of information on the size of the organism and/or the absence of taxonomic information. Distribution patterns of global macrozooplankton biomass and statistical information about biomass concentrations may be used to validate biogeochemical models and Plankton Functional Type models.