58 resultados para INDEPENDENT COMPONENT ANALYSIS


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Functional connectivity (FC) as measured by correlation between fMRI BOLD time courses of distinct brain regions has revealed meaningful organization of spontaneous fluctuations in the resting brain. However, an increasing amount of evidence points to non-stationarity of FC; i.e., FC dynamically changes over time reflecting additional and rich information about brain organization, but representing new challenges for analysis and interpretation. Here, we propose a data-driven approach based on principal component analysis (PCA) to reveal hidden patterns of coherent FC dynamics across multiple subjects. We demonstrate the feasibility and relevance of this new approach by examining the differences in dynamic FC between 13 healthy control subjects and 15 minimally disabled relapse-remitting multiple sclerosis patients. We estimated whole-brain dynamic FC of regionally-averaged BOLD activity using sliding time windows. We then used PCA to identify FC patterns, termed "eigenconnectivities", that reflect meaningful patterns in FC fluctuations. We then assessed the contributions of these patterns to the dynamic FC at any given time point and identified a network of connections centered on the default-mode network with altered contribution in patients. Our results complement traditional stationary analyses, and reveal novel insights into brain connectivity dynamics and their modulation in a neurodegenerative disease.

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Objective: To assess the factorial validity of the Portuguese version of the Maslach Burnout Inventory - Human Services Survey (MBI-HSS). Methods: Between November 2010 and November 2011 a Portuguese version of the MBI-HSS was applied to 151 Portuguese family doctors (55% women, median age 54 years). The factorial structure of the MBI-HSS was examined by principal component analysis (PCA) and confirmatory factor analysis (CFA). Internal consistency estimates of the MBI-HSS were determined with Cronbach's alpha. Results: The fit of the hypothesized three-factor model to the data was superior to the alternative two-factor and four-factor models. CFA supported MBI-HSS as an acceptable measure to evaluate burnout and deletion of items 12 and 16 improved the goodness of fit of the model. In PCA, the three-factor model explained 50.58% of the variance and the four-factor model did not lead to understandable components. Item 12 was also found to be problematic in PCA. The Cronbach's alpha was satisfactory for emotional exhaustion (alpha=0.90), lack of personal accomplishment (alpha=0.73), and depersonalization (alpha=0.64). Conclusion: The Portuguese version of the MBI-HSS was found to be reliable to measure burnout among Portuguese medical doctors. We also recommend the deletion of items 12 and 16 from the MBI-HSS.

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The fatty acids from cocoa butters of different origins, varieties, and suppliers and a number of cocoa butter equivalents (Illexao 30-61, Illexao 30-71, Illexao 30-96, Choclin, Coberine, Chocosine-Illipe, Chocosine-Shea, Shokao, Akomax, Akonord, and Ertina) were investigated by bulk stable carbon isotope analysis and compound specific isotope analysis. The interpretation is based on principal component analysis combining the fatty acid concentrations and the bulk and molecular isotopic data. The scatterplot of the two first principal components allowed detection of the addition of vegetable fats to cocoa butters. Enrichment in heavy carbon isotope (C-13) of the bulk cocoa butter and of the individual fatty acids is related to mixing with other vegetable fats and possibly to thermally or oxidatively induced degradation during processing (e.g., drying and roasting of the cocoa beans or deodorization of the pressed fat) or storage. The feasibility of the analytical approach for authenticity assessment is discussed.

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Understanding the genetic structure of human populations is of fundamental interest to medical, forensic and anthropological sciences. Advances in high-throughput genotyping technology have markedly improved our understanding of global patterns of human genetic variation and suggest the potential to use large samples to uncover variation among closely spaced populations. Here we characterize genetic variation in a sample of 3,000 European individuals genotyped at over half a million variable DNA sites in the human genome. Despite low average levels of genetic differentiation among Europeans, we find a close correspondence between genetic and geographic distances; indeed, a geographical map of Europe arises naturally as an efficient two-dimensional summary of genetic variation in Europeans. The results emphasize that when mapping the genetic basis of a disease phenotype, spurious associations can arise if genetic structure is not properly accounted for. In addition, the results are relevant to the prospects of genetic ancestry testing; an individual's DNA can be used to infer their geographic origin with surprising accuracy-often to within a few hundred kilometres.

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Using one male-inherited and eight biparentally inherited microsatellite markers, we investigate the population genetic structure of the Valais chromosome race of the common shrew (Sorex araneus) in the Central Alps of Europe. Unexpectedly, the Y-chromosome microsatellite suggests nearly complete absence of male gene flow among populations from the St-Bernard and Simplon regions (Switzerland). Autosomal markers also show significant genetic structuring among these two geographical areas. Isolation by distance is significant and possible barriers to gene flow exist in the study area. Two different approaches are used to better understand the geographical patterns and the causes of this structuring. Using a principal component analysis for which testing procedure exists, and partial Mantel tests, we show that the St-Bernard pass does not represent a significant barrier to gene flow although it culminates at 2469 m, close to the highest altitudinal record for this species. Similar results are found for the Simplon pass, indicating that both passes represented potential postglacial recolonization routes into Switzerland from Italian refugia after the last Pleistocene glaciations. In contrast with the weak effect of these mountain passes, the Rhône valley lowlands significantly reduce gene flow in this species. Natural obstacles (the large Rhône river) and unsuitable habitats (dry slopes) are both present in the valley. Moreover, anthropogenic changes to landscape structures are likely to have strongly reduced available habitats for this shrew in the lowlands, thereby promoting genetic differentiation of populations found on opposite sides of the Rhône valley.

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This study represents the most extensive analysis of batch-to-batch variations in spray paint samples to date. The survey was performed as a collaborative project of the ENFSI (European Network of Forensic Science Institutes) Paint and Glass Working Group (EPG) and involved 11 laboratories. Several studies have already shown that paint samples of similar color but from different manufacturers can usually be differentiated using an appropriate analytical sequence. The discrimination of paints from the same manufacturer and color (batch-to-batch variations) is of great interest and these data are seldom found in the literature. This survey concerns the analysis of batches from different color groups (white, papaya (special shade of orange), red and black) with a wide range of analytical techniques and leads to the following conclusions. Colored batch samples are more likely to be differentiated since their pigment composition is more complex (pigment mixtures, added pigments) and therefore subject to variations. These variations may occur during the paint production but may also occur when checking the paint shade in quality control processes. For these samples, techniques aimed at color/pigment(s) characterization (optical microscopy, microspectrophotometry (MSP), Raman spectroscopy) provide better discrimination than techniques aimed at the organic (binder) or inorganic composition (fourier transform infrared spectroscopy (FTIR) or elemental analysis (SEM - scanning electron microscopy and XRF - X-ray fluorescence)). White samples contain mainly titanium dioxide as a pigment and the main differentiation is based on the binder composition (Csingle bondH stretches) detected either by FTIR or Raman. The inorganic composition (elemental analysis) also provides some discrimination. Black samples contain mainly carbon black as a pigment and are problematic with most of the spectroscopic techniques. In this case, pyrolysis-GC/MS represents the best technique to detect differences. Globally, Py-GC/MS may show a high potential of discrimination on all samples but the results are highly dependent on the specific instrumental conditions used. Finally, the discrimination of samples when data was interpreted visually as compared to statistically using principal component analysis (PCA) yielded very similar results. PCA increases sensitivity and could perform better on specific samples, but one first has to ensure that all non-informative variation (baseline deviation) is eliminated by applying correct pre-treatments. Statistical treatments can be used on a large data set and, when combined with an expert's opinion, will provide more objective criteria for decision making.

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The Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES), a 19-item instrument developed to assess readiness to change alcohol use among individuals presenting for specialized alcohol treatment, has been used in various populations and settings. Its factor structure and concurrent validity has been described for specialized alcohol treatment settings and primary care. The purpose of this study was to determine the factor structure and concurrent validity of the SOCRATES among medical inpatients with unhealthy alcohol use not seeking help for specialized alcohol treatment. The subjects were 337 medical inpatients with unhealthy alcohol use, identified during their hospital stay. Most of them had alcohol dependence (76%). We performed an Alpha Factor Analysis (AFA) and Principal Component Analysis (PCA) of the 19 SOCRATES items, and forced 3 factors and 2 components, in order to replicate findings from Miller and Tonigan (Miller, W. R., & Tonigan, J. S., (1996). Assessing drinkers' motivations for change: The Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES). Psychology of Addictive Behavior, 10, 81-89.) and Maisto et al. (Maisto, S. A., Conigliaro, J., McNeil, M., Kraemer, K., O'Connor, M., & Kelley, M. E., (1999). Factor structure of the SOCRATES in a sample of primary care patients. Addictive Behavior, 24(6), 879-892.). Our analysis supported the view that the 2 component solution proposed by Maisto et al. (Maisto, S.A., Conigliaro, J., McNeil, M., Kraemer, K., O'Connor, M., & Kelley, M.E., (1999). Factor structure of the SOCRATES in a sample of primary care patients. Addictive Behavior, 24(6), 879-892.) is more appropriate for our data than the 3 factor solution proposed by Miller and Tonigan (Miller, W. R., & Tonigan, J. S., (1996). Assessing drinkers' motivations for change: The Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES). Psychology of Addictive Behavior, 10, 81-89.). The first component measured Perception of Problems and was more strongly correlated with severity of alcohol-related consequences, presence of alcohol dependence, and alcohol consumption levels (average number of drinks per day and total number of binge drinking days over the past 30 days) compared to the second component measuring Taking Action. Our findings support the view that the SOCRATES is comprised of two important readiness constructs in general medical patients identified by screening.

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Geographical body size variation has long interested evolutionary biologists, and a range of mechanisms have been proposed to explain the observed patterns. It is considered to be more puzzling in ectotherms than in endotherms, and integrative approaches are necessary for testing non-exclusive alternative mechanisms. Using lacertid lizards as a model, we adopted an integrative approach, testing different hypotheses for both sexes while incorporating temporal, spatial, and phylogenetic autocorrelation at the individual level. We used data on the Spanish Sand Racer species group from a field survey to disentangle different sources of body size variation through environmental and individual genetic data, while accounting for temporal and spatial autocorrelation. A variation partitioning method was applied to separate independent and shared components of ecology and phylogeny, and estimated their significance. Then, we fed-back our models by controlling for relevant independent components. The pattern was consistent with the geographical Bergmann's cline and the experimental temperature-size rule: adults were larger at lower temperatures (and/or higher elevations). This result was confirmed with additional multi-year independent data-set derived from the literature. Variation partitioning showed no sex differences in phylogenetic inertia but showed sex differences in the independent component of ecology; primarily due to growth differences. Interestingly, only after controlling for independent components did primary productivity also emerge as an important predictor explaining size variation in both sexes. This study highlights the importance of integrating individual-based genetic information, relevant ecological parameters, and temporal and spatial autocorrelation in sex-specific models to detect potentially important hidden effects. Our individual-based approach devoted to extract and control for independent components was useful to reveal hidden effects linked with alternative non-exclusive hypothesis, such as those of primary productivity. Also, including measurement date allowed disentangling and controlling for short-term temporal autocorrelation reflecting sex-specific growth plasticity.

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Repetition of environmental sounds, like their visual counterparts, can facilitate behavior and modulate neural responses, exemplifying plasticity in how auditory objects are represented or accessed. It remains controversial whether such repetition priming/suppression involves solely plasticity based on acoustic features and/or also access to semantic features. To evaluate contributions of physical and semantic features in eliciting repetition-induced plasticity, the present functional magnetic resonance imaging (fMRI) study repeated either identical or different exemplars of the initially presented object; reasoning that identical exemplars share both physical and semantic features, whereas different exemplars share only semantic features. Participants performed a living/man-made categorization task while being scanned at 3T. Repeated stimuli of both types significantly facilitated reaction times versus initial presentations, demonstrating perceptual and semantic repetition priming. There was also repetition suppression of fMRI activity within overlapping temporal, premotor, and prefrontal regions of the auditory "what" pathway. Importantly, the magnitude of suppression effects was equivalent for both physically identical and semantically related exemplars. That the degree of repetition suppression was irrespective of whether or not both perceptual and semantic information was repeated is suggestive of a degree of acoustically independent semantic analysis in how object representations are maintained and retrieved.

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Changes in gene expression are thought to underlie many of the phenotypic differences between species. However, large-scale analyses of gene expression evolution were until recently prevented by technological limitations. Here we report the sequencing of polyadenylated RNA from six organs across ten species that represent all major mammalian lineages (placentals, marsupials and monotremes) and birds (the evolutionary outgroup), with the goal of understanding the dynamics of mammalian transcriptome evolution. We show that the rate of gene expression evolution varies among organs, lineages and chromosomes, owing to differences in selective pressures: transcriptome change was slow in nervous tissues and rapid in testes, slower in rodents than in apes and monotremes, and rapid for the X chromosome right after its formation. Although gene expression evolution in mammals was strongly shaped by purifying selection, we identify numerous potentially selectively driven expression switches, which occurred at different rates across lineages and tissues and which probably contributed to the specific organ biology of various mammals.

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Counterfeit pharmaceutical products have become a widespread problem in the last decade. Various analytical techniques have been applied to discriminate between genuine and counterfeit products. Among these, Near-infrared (NIR) and Raman spectroscopy provided promising results.The present study offers a methodology allowing to provide more valuable information fororganisations engaged in the fight against counterfeiting of medicines.A database was established by analyzing counterfeits of a particular pharmaceutical product using Near-infrared (NIR) and Raman spectroscopy. Unsupervised chemometric techniques (i.e. principal component analysis - PCA and hierarchical cluster analysis - HCA) were implemented to identify the classes within the datasets. Gas Chromatography coupled to Mass Spectrometry (GC-MS) and Fourier Transform Infrared Spectroscopy (FT-IR) were used to determine the number of different chemical profiles within the counterfeits. A comparison with the classes established by NIR and Raman spectroscopy allowed to evaluate the discriminating power provided by these techniques. Supervised classifiers (i.e. k-Nearest Neighbors, Partial Least Squares Discriminant Analysis, Probabilistic Neural Networks and Counterpropagation Artificial Neural Networks) were applied on the acquired NIR and Raman spectra and the results were compared to the ones provided by the unsupervised classifiers.The retained strategy for routine applications, founded on the classes identified by NIR and Raman spectroscopy, uses a classification algorithm based on distance measures and Receiver Operating Characteristics (ROC) curves. The model is able to compare the spectrum of a new counterfeit with that of previously analyzed products and to determine if a new specimen belongs to one of the existing classes, consequently allowing to establish a link with other counterfeits of the database.

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Functionally relevant large scale brain dynamics operates within the framework imposed by anatomical connectivity and time delays due to finite transmission speeds. To gain insight on the reliability and comparability of large scale brain network simulations, we investigate the effects of variations in the anatomical connectivity. Two different sets of detailed global connectivity structures are explored, the first extracted from the CoCoMac database and rescaled to the spatial extent of the human brain, the second derived from white-matter tractography applied to diffusion spectrum imaging (DSI) for a human subject. We use the combination of graph theoretical measures of the connection matrices and numerical simulations to explicate the importance of both connectivity strength and delays in shaping dynamic behaviour. Our results demonstrate that the brain dynamics derived from the CoCoMac database are more complex and biologically more realistic than the one based on the DSI database. We propose that the reason for this difference is the absence of directed weights in the DSI connectivity matrix.

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Our current knowledge of the general factor requirement in transcription by the three mammalian RNA polymerases is based on a small number of model promoters. Here, we present a comprehensive chromatin immunoprecipitation (ChIP)-on-chip analysis for 28 transcription factors on a large set of known and novel TATA-binding protein (TBP)-binding sites experimentally identified via ChIP cloning. A large fraction of identified TBP-binding sites is located in introns or lacks a gene/mRNA annotation and is found to direct transcription. Integrated analysis of the ChIP-on-chip data and functional studies revealed that TAF12 hitherto regarded as RNA polymerase II (RNAP II)-specific was found to be also involved in RNAP I transcription. Distinct profiles for general transcription factors and TAF-containing complexes were uncovered for RNAP II promoters located in CpG and non-CpG islands suggesting distinct transcription initiation pathways. Our study broadens the spectrum of general transcription factor function and uncovers a plethora of novel, functional TBP-binding sites in the human genome.

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BACKGROUND: The criteria for choosing relevant cell lines among a vast panel of available intestinal-derived lines exhibiting a wide range of functional properties are still ill-defined. The objective of this study was, therefore, to establish objective criteria for choosing relevant cell lines to assess their appropriateness as tumor models as well as for drug absorption studies. RESULTS: We made use of publicly available expression signatures and cell based functional assays to delineate differences between various intestinal colon carcinoma cell lines and normal intestinal epithelium. We have compared a panel of intestinal cell lines with patient-derived normal and tumor epithelium and classified them according to traits relating to oncogenic pathway activity, epithelial-mesenchymal transition (EMT) and stemness, migratory properties, proliferative activity, transporter expression profiles and chemosensitivity. For example, SW480 represent an EMT-high, migratory phenotype and scored highest in terms of signatures associated to worse overall survival and higher risk of recurrence based on patient derived databases. On the other hand, differentiated HT29 and T84 cells showed gene expression patterns closest to tumor bulk derived cells. Regarding drug absorption, we confirmed that differentiated Caco-2 cells are the model of choice for active uptake studies in the small intestine. Regarding chemosensitivity we were unable to confirm a recently proposed association of chemo-resistance with EMT traits. However, a novel signature was identified through mining of NCI60 GI50 values that allowed to rank the panel of intestinal cell lines according to their drug responsiveness to commonly used chemotherapeutics. CONCLUSIONS: This study presents a straightforward strategy to exploit publicly available gene expression data to guide the choice of cell-based models. While this approach does not overcome the major limitations of such models, introducing a rank order of selected features may allow selecting model cell lines that are more adapted and pertinent to the addressed biological question.

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Kinematic functional evaluation with body-worn sensors provides discriminative and responsive scores after shoulder surgery, but the optimal movements' combination has not yet been scientifically investigated. The aim of this study was the development of a simplified shoulder function kinematic score including only essential movements. The P Score, a seven-movement kinematic score developed on 31 healthy participants and 35 patients before surgery and at 3, 6 and 12 months after shoulder surgery, served as a reference.Principal component analysis and multiple regression were used to create simplified scoring models. The candidate models were compared to the reference score. ROC curve for shoulder pathology detection and correlations with clinical questionnaires were calculated.The B-B Score (hand to the Back and hand upwards as to change a Bulb) showed no difference to the P Score in time*score interaction (P > .05) and its relation with the reference score was highly linear (R(2) > .97). Absolute value of correlations with clinical questionnaires ranged from 0.51 to 0.77. Sensitivity was 97% and specificity 94%.The B-B and reference scores are equivalent for the measurement of group responses. The validated simplified scoring model presents practical advantages that facilitate the objective evaluation of shoulder function in clinical practice.