971 resultados para Linked Data
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Study Design. A clinical study was conducted on 39 patients with acute, first-episode, unilateral low back pain and unilateral, segmental inhibition of the multifidus muscle. Patients were allocated randomly to a control or treatment group. Objectives. To document the natural course of lumbar multifidus recovery and to evaluate the effectiveness of specific, localized, exercise therapy on muscle recovery. Summary of Background Data. Acute low back pain usually resolves spontaneously, but the recurrence rate is high. Inhibition of multifidus occurs with acute, first-episode, low back pain, and pathologic changes in this muscle have been linked with poor outcome and recurrence of symptoms. Methods. Patients in group 1 received medical treatment only. Patients in group 2 received medical treatment and specific, localized, exercise therapy. Outcome measures for both groups included 4 weekly assessments of pain, disability, range of motion, and size of the multifidus cross-sectional area. Independent examiners were blinded to group allocation. Patients were reassessed at a 10-week follow-up examination. Results. Multifidus muscle recovery was not spontaneous on remission of painful symptoms in patients in group 1. Muscle recovery was more rapid and more complete in patients in group 2 who received exercise therapy (P = 0.0001). Other outcome measurements were similar for the two groups at the 4-week examination. Although they resumed normal levels of activity, patients in group 1 still had decreased multifidus muscle size at the 10-week follow-up examination. Conclusions. Multifidus muscle recovery is not spontaneous on remission of painful symptoms. Lack of localized, muscle support may be one reason for the high recurrence rate of low back pain following the initial episode.
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Dherte PM, Negrao MPG, Mori Neto S, Holzhacker R, Shimada V, Taberner P, Carmona MJC - Smart Alerts: Development of a Software to Optimize Data Monitoring. Background and objectives: Monitoring is useful for vital follow-ups and prevention, diagnosis, and treatment of several events in anesthesia. Although alarms can be useful in monitoring they can cause dangerous user`s desensitization. The objective of this study was to describe the development of specific software to integrate intraoperative monitoring parameters generating ""smart alerts"" that can help decision making, besides indicating possible diagnosis and treatment. Methods: A system that allowed flexibility in the definition of alerts, combining individual alarms of the parameters monitored to generate a more elaborated alert system was designed. After investigating a set of smart alerts, considered relevant in the surgical environment, a prototype was designed and evaluated, and additional suggestions were implemented in the final product. To verify the occurrence of smart alerts, the system underwent testing with data previously obtained during intraoperative monitoring of 64 patients. The system allows continuous analysis of monitored parameters, verifying the occurrence of smart alerts defined in the user interface. Results: With this system a potential 92% reduction in alarms was observed. We observed that in most situations that did not generate alerts individual alarms did not represent risk to the patient. Conclusions: Implementation of software can allow integration of the data monitored and generate information, such as possible diagnosis or interventions. An expressive potential reduction in the amount of alarms during surgery was observed. Information displayed by the system can be oftentimes more useful than analysis of isolated parameters.
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We have observed previously that Ca2+ pump-mediated Ca2+ efflux is elevated in cultured aortic smooth muscle cells from spontaneously hypertensive rats compared to those from Wistar-Kyoto rat controls. The objective of this work was to determine if these strains differ in mRNA levels for the PMCA1 isoform of the plasma membrane Ca2+-ATPase and the SERCA2 isoform of the sarcoplasmic reticulum Ca2+-ATPase. mRNA levels were compared in cultured aortic smooth muscle cells from 10-week-old male rats. PMCA1 and SERCA2 mRNA levels were elevated in SHR compared to WKY. Angiotensin II increased the level of PMCA1 and SERCA2 mRNA in both strains. These studies provide further evidence for alterered Ca2+ homeostasis in hypertension at the level of Ca2+ transporting ATPases in the spontaneously hypertensive rat model. These data are also consistent with the hypothesis that the expression of these two Ca2+ pumps may be linked. (C) 1997 Academic Press
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Objective: To illustrate methodological issues involved in estimating dietary trends in populations using data obtained from various sources in Australia in the 1980s and 1990s. Methods: Estimates of absolute and relative change in consumption of selected food items were calculated using national data published annually on the national food supply for 1982-83 to 1992-93 and responses to food frequency questions in two population based risk factor surveys in 1983 and 1994 in the Hunter Region of New South Wales, Australia. The validity of estimated food quantities obtained from these inexpensive sources at the beginning of the period was assessed by comparison with data from a national dietary survey conducted in 1983 using 24 h recall. Results: Trend estimates from the food supply data and risk factor survey data were in good agreement for increases in consumption of fresh fruit, vegetables and breakfast food and decreases in butter, margarine, sugar and alcohol. Estimates for trends in milk, eggs and bread consumption, however, were inconsistent. Conclusions: Both data sources can be used for monitoring progress towards national nutrition goals based on selected food items provided that some limitations are recognized. While data collection methods should be consistent over time they also need to allow for changes in the food supply (for example the introduction of new varieties such as low-fat dairy products). From time to time the trends derived from these inexpensive data sources should be compared with data derived from more detailed and quantitative estimates of dietary intake.
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In this study, blood serum trace elements, biochemical and hematological parameters were obtained to assess the health status of an elderly population residing in So Paulo city, SP, Brazil. Results obtained showed that more than 93% of the studied individuals presented most of the serum trace element concentrations and of the hematological and biochemical data within the reference values used in clinical laboratories. However, the percentage of elderly presenting recommended low density lipoprotein (LDL) cholesterol concentrations was low (70%). The study indicated positive correlation between the concentrations of Zn and LDL-cholesterol (p < 0.06).
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Objective: To evaluate the importance of receptor activator of nuclear factor kappa B (RANK)/receptor activator of nuclear factor kappa B ligand (RANKL)/osteoprotegerin (OPG) modulation in active polyarticular juvenile idiopathic arthritis (pJIA) patients with and without bone erosions. Methods: Thirty female patients (mean age 11.07 +/- 3.77 years, range 4-17 years) with active pJIA and 30 healthy gender-and age-matched controls were consecutively selected for this study. All involved articulations were assessed by X-ray and examined for the presence of bone erosions. The serum levels of RANKL and OPG were measured using an enzyme-linked immunosorbent assay (ELISA). Results: Patients with active pJIA had higher levels of serum RANKL than controls [2.90 (0.1-37.4) vs. 0.25 (0.1-5.7) pg/mL, p=0.007] and a lower OPG/RANKL ratio [21.25 (1.8-897.6) vs. 347.5 (9-947.8), p=0.005]. However, levels of OPG were comparable in both groups [55.24 (28.34-89.76) vs. 64.42 (30.68-111.28) pg/mL, p=0.255]. Higher levels of serum RANKL and a lower OPG/RANKL ratio were also observed in active pJIA patients with bone erosions compared to controls [3.49 (0.1-37.4) vs. 0.25 (0.1-5.7) pg/mL, p=0.0115 and 14.3 (1.8-897.6) vs. 347.5 (9-947.8), p=0.016]. However, RANKL levels and OPG/RANKL ratio were similar in pJIA patients without bone erosion and controls [1.75 (0.1-10.9) vs. 0.25 (0.1-5.7) pg/mL, p=0.055 and 29.2 (3.3-756.8) vs. 347.5 (9-947.8), p=0.281]. Conclusion: These data suggest that active pJIA with bone erosions is associated with high serum levels of RANKL and a low OPG/RANKL ratio, indicating that these alterations may reflect bone damage in this disease.
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Breast cancer five-year relative survival was calculated for 16 urban and rural regions in New South Wales (NSW) for cases incident in 1980-1991. Survival analysis employed cancer registry data linked with the death register, and age- and period-matched regional mortality of NSW women, Proportional hazard regression analysis was used to compare excess mortality in breast cancer cases in each region. The effect of region was significant (P < 0.05) in the analysis, after age and the follow-up variable (and their intel action) were adjusted for, although no region was significantly different from the referent group (chosen because of average relative five-year survival). When degree of spread and its interactions were entered into che model, the effect of region became nonsignificant. A significant linear trend (P < 0.05) in the adjusted relative risk for excess mortality in breast cancer cases was noted when regions were divided into quartiles based on socioeconomic status, with higher relative risk in low-socioeconomic-status groups; this effect also disappeared with adjustment for degree of spread at diagnosis. There was no general effect of rurality versus capital city or other metropolitan centres. This study demonstrates a small effect of region of residence and implied socioeconomic status on breast cancer survival in NSW women, but this becomes nonsignificant when the data are adjusted for degree of spread at diagnosis, This suggests that earlier diagnosis would he of benefit in reducing minor inequalities in breast cancer survival in NSW women.
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Angiotensinogen (AGT) gene polymorphisms have been linked to increased risk of hypertension, but the data remain controversial. In this study we review the most commonly investigated polymorphisms at the AGT locus (other than M235T) and provide summary estimates regarding their association with essential hypertension, while addressing heterogeneity, as well as publication biases. Data on 26 818 subjects from 46 studies for the 4 most-studied AGT variants (T174M in exon 2 and 3 promoter variants: A-6G, A-20C, and G-217A) were meta-analyzed. Statistically significant associations with hypertension were identified for the T174M ( odds ratio [OR]: 1.19; 95% CI: 1.07 to 1.33; P = 0.002) and G-217A (OR: 1.37; 95% CI: 1.17 to 1.59; P = 0.00006) polymorphisms. A dual but consistent effect was observed for the -20C allele, which was associated with a decreased risk of hypertension in populations of mixed and European ancestries (OR: 0.64; 95% CI: 0.44 to 0.92; P = 0.02 and OR: 0.77; 95% CI: 0.65 to 0.91; P = 0.003, respectively), but with a 24% increase in the odds of hypertension in Asian subjects (OR: 1.24; 95% CI: 1.04 to 1.48; P = 0.02). No association of the A-6G variant with hypertension was detected. Current studies support the notion that single variants at the AGT might modulate the risk of hypertension but indicate caution in interpreting these results because of the putative presence of publication bias and gene-environment interactions.
Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI
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Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.
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The present study aimed to investigate the presence of corpus callosum (CC) volume deficits in a population-based recent-onset psychosis (ROP) sample, and whether CC volume relates to interhemispheric communication deficits. For this purpose, we used voxel-based morphometry comparisons of magnetic resonance imaging data between ROP (n = 122) and healthy control (n = 94) subjects. Subgroups (38 ROP and 39 controls) were investigated for correlations between CC volumes and performance on the Crossed Finger Localization Test (CFLT). Significant CC volume reductions in ROP subjects versus controls emerged after excluding substance misuse and non-right-handedness. CC reductions retained significance in the schizophrenia subgroup but not in affective psychoses subjects. There were significant positive correlations between CC volumes and CFLT scores in ROP subjects, specifically in subtasks involving interhemispheric communication. From these results, we can conclude that CC volume reductions are present in association with ROP. The relationship between such deficits and CFLT performance suggests that interhemispheric communication impairments are directly linked to CC abnormalities in ROP. (C) 2010 Elsevier Ireland Ltd. All rights reserved.
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The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.
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Resting state functional magnetic resonance imaging (fMRI) reveals a distinct network of correlated brain function representing a default mode state of the human brain The underlying structural basis of this functional connectivity pattern is still widely unexplored We combined fractional anisotropy measures of fiber tract integrity derived from diffusion tensor imaging (DTI) and resting state fMRI data obtained at 3 Tesla from 20 healthy elderly subjects (56 to 83 years of age) to determine white matter microstructure e 7 underlying default mode connectivity We hypothesized that the functional connectivity between the posterior cingulate and hippocampus from resting state fMRI data Would be associated with the white matter microstructure in the cingulate bundle and fiber tracts connecting posterior cingulate gyrus With lateral temporal lobes, medial temporal lobes, and precuneus This was demonstrated at the p<0001 level using a voxel-based multivariate analysis of covariance (MANCOVA) approach In addition, we used a data-driven technique of joint independent component analysis (ICA) that uncovers spatial pattern that are linked across modalities. It revealed a pattern of white matter tracts including cingulate bundle and associated fiber tracts resembling the findings from the hypothesis-driven analysis and was linked to the pattern of default mode network (DMN) connectivity in the resting state fMRI data Out findings support the notion that the functional connectivity between the posterior cingulate and hippocampus and the functional connectivity across the entire DMN is based oil distinct pattern of anatomical connectivity within the cerebral white matter (C) 2009 Elsevier Inc All rights reserved
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Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.
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Analysis of a major multi-site epidemiologic study of heart disease has required estimation of the pairwise correlation of several measurements across sub-populations. Because the measurements from each sub-population were subject to sampling variability, the Pearson product moment estimator of these correlations produces biased estimates. This paper proposes a model that takes into account within and between sub-population variation, provides algorithms for obtaining maximum likelihood estimates of these correlations and discusses several approaches for obtaining interval estimates. (C) 1997 by John Wiley & Sons, Ltd.
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The reactions between novolac resins and hexamethylenetetramine (HMTA) which occur on curing have been studied by C-13 and N-15 high-resolution n.m.r. in both solution and the solid state. Strong evidence for the existence of many curing intermediates is obtained. New curing intermediates are reported along with experimental data to support previously postulated intermediates. The initial curing reactions between novolac and HMTA produce various substituted benzoxazines and benzylamines. Thermal decomposition/oxidation and further reactions of these initial intermediates generate methylene linkages between phenolic rings for chain extension and cross-linking. Among the three kinds of methylene linkages, the para-para methylene linkages are formed at relatively lower temperatures. Various imine, amide and imide side-products also concurrently appear during the process. The initial amount of HMTA plays a critical role in the curing reactivity and chemical structures of the cured resins. The lower the amount of HMTA, the lower the temperature at which curing occurs, and the lower the amount of the nitrogen-containing side-products in the finally cured resins. The ortho-linked intermediates are relatively stable, and can remain in the cured resins up to higher temperatures. The study provides an extensive description of the curing reactions of novolac resins. (C) 1997 Elsevier Science Ltd.