233 resultados para level-sets

em Université de Lausanne, Switzerland


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1. Statistical modelling is often used to relate sparse biological survey data to remotely derived environmental predictors, thereby providing a basis for predictively mapping biodiversity across an entire region of interest. The most popular strategy for such modelling has been to model distributions of individual species one at a time. Spatial modelling of biodiversity at the community level may, however, confer significant benefits for applications involving very large numbers of species, particularly if many of these species are recorded infrequently. 2. Community-level modelling combines data from multiple species and produces information on spatial pattern in the distribution of biodiversity at a collective community level instead of, or in addition to, the level of individual species. Spatial outputs from community-level modelling include predictive mapping of community types (groups of locations with similar species composition), species groups (groups of species with similar distributions), axes or gradients of compositional variation, levels of compositional dissimilarity between pairs of locations, and various macro-ecological properties (e.g. species richness). 3. Three broad modelling strategies can be used to generate these outputs: (i) 'assemble first, predict later', in which biological survey data are first classified, ordinated or aggregated to produce community-level entities or attributes that are then modelled in relation to environmental predictors; (ii) 'predict first, assemble later', in which individual species are modelled one at a time as a function of environmental variables, to produce a stack of species distribution maps that is then subjected to classification, ordination or aggregation; and (iii) 'assemble and predict together', in which all species are modelled simultaneously, within a single integrated modelling process. These strategies each have particular strengths and weaknesses, depending on the intended purpose of modelling and the type, quality and quantity of data involved. 4. Synthesis and applications. The potential benefits of modelling large multispecies data sets using community-level, as opposed to species-level, approaches include faster processing, increased power to detect shared patterns of environmental response across rarely recorded species, and enhanced capacity to synthesize complex data into a form more readily interpretable by scientists and decision-makers. Community-level modelling therefore deserves to be considered more often, and more widely, as a potential alternative or supplement to modelling individual species.

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The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.

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For the last 2 decades, supertree reconstruction has been an active field of research and has seen the development of a large number of major algorithms. Because of the growing popularity of the supertree methods, it has become necessary to evaluate the performance of these algorithms to determine which are the best options (especially with regard to the supermatrix approach that is widely used). In this study, seven of the most commonly used supertree methods are investigated by using a large empirical data set (in terms of number of taxa and molecular markers) from the worldwide flowering plant family Sapindaceae. Supertree methods were evaluated using several criteria: similarity of the supertrees with the input trees, similarity between the supertrees and the total evidence tree, level of resolution of the supertree and computational time required by the algorithm. Additional analyses were also conducted on a reduced data set to test if the performance levels were affected by the heuristic searches rather than the algorithms themselves. Based on our results, two main groups of supertree methods were identified: on one hand, the matrix representation with parsimony (MRP), MinFlip, and MinCut methods performed well according to our criteria, whereas the average consensus, split fit, and most similar supertree methods showed a poorer performance or at least did not behave the same way as the total evidence tree. Results for the super distance matrix, that is, the most recent approach tested here, were promising with at least one derived method performing as well as MRP, MinFlip, and MinCut. The output of each method was only slightly improved when applied to the reduced data set, suggesting a correct behavior of the heuristic searches and a relatively low sensitivity of the algorithms to data set sizes and missing data. Results also showed that the MRP analyses could reach a high level of quality even when using a simple heuristic search strategy, with the exception of MRP with Purvis coding scheme and reversible parsimony. The future of supertrees lies in the implementation of a standardized heuristic search for all methods and the increase in computing power to handle large data sets. The latter would prove to be particularly useful for promising approaches such as the maximum quartet fit method that yet requires substantial computing power.

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BACKGROUND: Since the emergence of diffusion tensor imaging, a lot of work has been done to better understand the properties of diffusion MRI tractography. However, the validation of the reconstructed fiber connections remains problematic in many respects. For example, it is difficult to assess whether a connection is the result of the diffusion coherence contrast itself or the simple result of other uncontrolled parameters like for example: noise, brain geometry and algorithmic characteristics. METHODOLOGY/PRINCIPAL FINDINGS: In this work, we propose a method to estimate the respective contributions of diffusion coherence versus other effects to a tractography result by comparing data sets with and without diffusion coherence contrast. We use this methodology to assign a confidence level to every gray matter to gray matter connection and add this new information directly in the connectivity matrix. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate that whereas we can have a strong confidence in mid- and long-range connections obtained by a tractography experiment, it is difficult to distinguish between short connections traced due to diffusion coherence contrast from those produced by chance due to the other uncontrolled factors of the tractography methodology.

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In many high income developed countries, obesity is inversely associated with educational level. In some countries, a widening gap of obesity between educational groups has been reported. The aim of this study was to assess trends in body mass index (BMI) and in prevalence of overweight and obesity and their association with educational level in the adult Swiss population. Four cross-sectional National health interview surveys conducted in 1992/93 (n = 14,521), 1997 (n = 12,474), 2002 (n = 18,908) and 2007 (n = 17,879) using representative samples of the Swiss population (age range 18-102 years). BMI was derived from self-reported data. Overweight was defined as BMI > or = 25 and <30 kg/m(2), and obesity as BMI > or = 30 kg/m(2). Mean (+/- standard deviation) BMI increased from 24.7 +/- 3.6 in 1992/3 to 25.4 +/- 3.6 kg/m2 in 2007 in men and 22.8 +/- 3.8 to 23.7 +/- 4.3 kg/m(2) in women. Between 1992/3 and 2007, the prevalence of overweight + obesity increased from 40.4% to 49.5% in men and from 22.3% to 31.3% in women, while the prevalence of obesity increased from 6.3% to 9.4% in men and from 4.9% to 8.5% in women. The rate of increase in the prevalence of obesity was greater between 1992/3 and 2002 (men: +0.26%/year; women: +0.31%/year) than between 2002 and 2007 (men: +0.10%/year; women: +0.10%/year). A sizable fraction (approximately 25%) of the increasing mean BMI was due to increasing age of the participants over time. The increase was larger in low than high education strata of the population. BMI was strongly associated with low educational level among women and this gradient remained fairly constant over time. A weaker similar gradient by educational level was apparent in men, but it tended to increase over time. In Switzerland, overweight and obesity increased between 1992 and 2007 and was associated with low education status in both men and women. A trend towards a stabilization of mean BMI levels was noted in most age categories since 2002. The increase in the prevalence of obesity was larger in low education strata of the population. These findings suggest that obesity preventive measures should be targeted according to educational level in Switzerland.

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Background: T reatment o f chronic hepatitis C i s evolving, a nd direct acting antivirals ( DAAs) are now a dded to p egylated interferon-α ( Peg- INF-α) and ribavirin (RBV) for the treatment o f hepatitis C v irus ( HCV) genotype 1 infection. DAAs c ause d ifferent side effects and can even worsen RBV induced hemolytic anemia. T herefore, identifying host genetic d eterminants of R BV bioavailability and therapeutic e fficacy will remain crucial for individualized treatment. Recent d ata showed associations between R BV induced h emolytic anemia and genetic polymorphisms o f concentrative nucleoside transporters s uch as C NT3 (SLC28A3) and i nosine t riphosphatase (ITPA). T o analyze t he association of genetic variants of SLC28 transporters and ITPA with RBV induced hemolytic anemia and treatment o utcome. Methods: I n our study, 173 patients f rom t he S wiss Hepatitis C C ohort Study and 2 2 patients from Swiss Association for the Study of the Liver study 24 (61% HCV g enotype 1, 3 9% genotypes 2 o r 3) were analyzed for SLC28A2 single nucleotide p olymorphism (SNP) rs11854484, SLC28A3 rs56350726 and SLC28A3 rs10868138 as well as ITPA SNPs rs1127354 and rs7270101. RBV serum levels during treatment were measured in 49 patients. Results: SLC28A2 r s11854484 genotype TT was associated with significantly higher dosage- and body weight-adjusted RBV levels as compared to genotypes TC and CC (p=0.04 and p=0.02 at weeks 4 and 8, respectively). ITPA SNPs rs1127354 and rs7270101 were associated with h emolytic a nemia both in genotype as w ell as i n allelic a nalyses. SLC28A3 rs56350726 genotype TT (vs. AT/AA, RR=2.1; 95% CI 1.1-4.1) as well as the T allele (vs. A; RR=1.8, 95% CI 1.1-3.2) were associated with increased SVR rates. The combined analysis of overall ITPA activity and SLC28 v ariants together revealed n o significant a dditive effects on either treatment-related anemia or SVR. Conclusions: T he newly identified association between RBV serum levels a nd SLC28A2 rs11854484 genotype as well as the replicated association of ITPA and SLC28A3 g enetic p olymorphisms w ith RBV induced hemolytic anemia and treatment r esponse underpin the need for further studies on host genetic d eterminants of R BV bioavailability and therapeutic e fficacy f or individualized treatment of chronic hepatitis C.

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Business ethicists often assume that unethical behavior arises when individuals deviate from the norms and responsibilities that are institutionalized to frame economic activities. People's greed motivates them to violate the rules of the game. In Kohlberg's terms, it is assumed that such actors make decisions in a preconventional way and act opportunistically. In this article, we propose an alternative interpretation of deviant behavior, arguing that such behavior does not result from a lack of conventional moral guidance but rather from the fact that characteristics attributed to preconventional morality by Kohlberg - the purely incentive and punishment driven opportunistic morality - have become the conventionalized morality. The prevailing norms that economic actors have internalized as their yardstick are those of the preconventional Homo economicus. Not the deviation from, but the compliance with the rules of the game explains many forms of harmful and illegal decisions made in corporations.

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According to the hypothesis of Traub, also known as the 'formula of Traub', postmortem values of glucose and lactate found in the cerebrospinal fluid or vitreous humor are considered indicators of antemortem blood glucose levels. However, because the lactate concentration increases in the vitreous and cerebrospinal fluid after death, some authors postulated that using the sum value to estimate antemortem blood glucose levels could lead to an overestimation of the cases of glucose metabolic disorders with fatal outcomes, such as diabetic ketoacidosis. The aim of our study, performed on 470 consecutive forensic cases, was to ascertain the advantages of the sum value to estimate antemortem blood glucose concentrations and, consequently, to rule out fatal diabetic ketoacidosis as the cause of death. Other biochemical parameters, such as blood 3-beta-hydroxybutyrate, acetoacetate, acetone, glycated haemoglobin and urine glucose levels, were also determined. In addition, postmortem native CT scan, autopsy, histology, neuropathology and toxicology were performed to confirm diabetic ketoacidosis as the cause of death. According to our results, the sum value does not add any further information for the estimation of antemortem blood glucose concentration. The vitreous glucose concentration appears to be the most reliable marker to estimate antemortem hyperglycaemia and, along with the determination of other biochemical markers (such as blood acetone and 3-beta-hydroxybutyrate, urine glucose and glycated haemoglobin), to confirm diabetic ketoacidosis as the cause of death.

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Clenbuterol is a β2 agonist agent with anabolic properties given by the increase in the muscular mass in parallel to the decrease of the body fat. For this reason, the use of clenbuterol is forbidden by the World Anti-Doping Agency (WADA) in the practice of sport. This compound is of particular interest for anti-doping authorities and WADA-accredited laboratories due to the recent reporting of risk of unintentional doping following the eating of meat contaminated with traces of clenbuterol in some countries. In this work, the development and the validation of an ultra-high pressure liquid chromatography coupled to electrospray ionization tandem mass spectrometry (UHPLC-ESI-MS/MS) method for the quantification of clenbuterol in human urine is described. The analyte was extracted from urine samples by liquid-liquid extraction (LLE) in basic conditions using tert butyl-methyl ether (TBME) and analyzed by UHPLC-MS/MS with a linear gradient of acetonitrile in 9min only. The simple and rapid method presented here was validated in compliance with authority guidelines and showed a limit of quantification at 5pg/mL and a linearity range from 5pg/mL to 300pg/mL. Good trueness (85.8-105%), repeatability (5.7-10.6% RSD) and intermediate precision (5.9-14.9% RSD) results were obtained. The method was then applied to real samples from eighteen volunteers collecting urines after single oral doses administration (1, 5 and 10μg) of clenbuterol-enriched yogurts.

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In 1903, the eastern slope of Turtle Mountain (Alberta) was affected by a 30 M m3-rockslide named Frank Slide that resulted in more than 70 casualties. Assuming that the main discontinuity sets, including bedding, control part of the slope morphology, the structural features of Turtle Mountain were investigated using a digital elevation model (DEM). Using new landscape analysis techniques, we have identified three main joint and fault sets. These results are in agreement with those sets identified through field observations. Landscape analysis techniques, using a DEM, confirm and refine the most recent geology model of the Frank Slide. The rockslide was initiated along bedding and a fault at the base of the slope and propagated up slope by a regressive process following a surface composed of pre-existing discontinuities. The DEM analysis also permits the identification of important geological structures along the 1903 slide scar. Based on the so called Sloping Local Base Level (SLBL) an estimation was made of the present unstable volumes in the main scar delimited by the cracks, and around the south area of the scar (South Peak). The SLBL is a method permitting a geometric interpretation of the failure surface based on a DEM. Finally we propose a failure mechanism permitting the progressive failure of the rock mass that considers gentle dipping wedges (30°). The prisms or wedges defined by two discontinuity sets permit the creation of a failure surface by progressive failure. Such structures are more commonly observed in recent rockslides. This method is efficient and is recommended as a preliminary analysis prior to field investigation.

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BACKGROUND: The goal of antiretroviral therapy (ART) is to reduce HIV-related morbidity and mortality by suppressing HIV replication. The prognostic value of persistent low-level viremia (LLV), particularly for clinical outcomes, is unknown. OBJECTIVE: Assess the association of different levels of LLV with virological failure, AIDS event, and death among HIV-infected patients receiving combination ART. METHODS: We analyzed data from 18 cohorts in Europe and North America, contributing to the ART Cohort Collaboration. Eligible patients achieved viral load below 50 copies/ml within 3-9 months after ART initiation. LLV50-199 was defined as two consecutive viral loads between 50 and 199 copies/ml and LLV200-499 as two consecutive viral loads between 50 and 499 copies/ml, with at least one between 200 and 499 copies/ml. We used Cox models to estimate the association of LLV with virological failure (two consecutive viral loads at least 500 copies/ml or one viral load at least 500 copies/ml, followed by a modification of ART) and AIDS event/death. RESULTS: Among 17 902 patients, 624 (3.5%) experienced LLV50-199 and 482 (2.7%) LLV200-499. Median follow-up was 2.3 and 3.1 years for virological and clinical outcomes, respectively. There were 1903 virological failure, 532 AIDS events and 480 deaths. LLV200-499 was strongly associated with virological failure [adjusted hazard ratio (aHR) 3.97, 95% confidence interval (CI) 3.05-5.17]. LLV50-199 was weakly associated with virological failure (aHR 1.38, 95% CI 0.96-2.00). LLV50-199 and LLV200-499 were not associated with AIDS event/death (aHR 1.19, 95% CI 0.78-1.82; and aHR 1.11, 95% CI 0.72-1.71, respectively). CONCLUSION: LLV200-499 was strongly associated with virological failure, but not with AIDS event/death. Our results support the US guidelines, which define virological failure as a confirmed viral load above 200 copies/ml.

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To directly assess the binding of exogenous peptides to cell surface-associated MHC class I molecules at the single cell level, we examined the possibility of combining the use of biotinylated peptide derivatives with an immunofluorescence detection system based on flow cytometry. Various biotinylated derivatives of the adenovirus 5 early region 1A peptide 234-243, an antigenic peptide recognized by CTL in the context of H-2Db, were first screened in functional assays for their ability to bind efficiently to Db molecules on living cells. Suitable peptide derivatives were then tested for their ability to generate positive fluorescence signals upon addition of phycoerythrin-labeled streptavidin to peptide derivative-bearing cells. Strong fluorescent staining of Db-expressing cells was achieved after incubation with a peptide derivative containing a biotin group at the C-terminus. Competition experiments using the unmodified parental peptide as well as unrelated peptides known to bind to Kd, Kb, or Db, respectively, established that binding of the biotinylated peptide to living cells was Db-specific. By using Con A blasts derived from different H-2 congenic mouse strains, it could be shown that the biotinylated peptide bound only to Db among &gt; 20 class I alleles tested. Moreover, binding of the biotinylated peptide to cells expressing the Dbm13 and Dbm14 mutant molecules was drastically reduced compared to Db. Binding of the biotinylated peptide to freshly isolated Db+ cells was readily detectable, allowing direct assessment of the relative amount of peptide bound to distinct lymphocyte subpopulations by three-color flow cytometry. While minor differences between peripheral T and B cells could be documented, thymocytes were found to differ widely in their peptide binding activity. In all cases, these differences correlated positively with the differential expression of Db at the cell surface. Finally, kinetic studies at different temperatures strongly suggested that the biotinylated peptide first associated with Db molecules available constitutively at the cell surface and then with newly arrived Db molecules.

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Migmatization of gabbroic rocks at 2-3 kbar has occurred in the metamorphic contact aureole of a mafic pluton in the Fuerteventura Basal Complex (Canary Island;). Migmatites are characterized by a dense network: of closely spaced millimetre-wide leucocratic veins with perfectly preserved igneous textures. They are all relatively enriched in Al, Na I: Sr Ba, Nb, Y and the rare earth elements compared with the unaffected country rock beyond the aureole. Migmatization under such low-pressure conditions war possible because of the unusual tectonic and magmatic contact in which ii occurred. Multiple basic intrusions associated with extrusive volcanic activity created high heat flow in a small area. Alkaline and metasomatized rocks present in the country rock of the intruding pluton were leached by high-temperature fluids during contact metamorphism. These enriched fluids then favoured partial melting of the host gabbroic rocks, and contaminated both the leucosomes and melanosomes. A transpressive tectonic setting at the time of intrusion created shearing along the contact between the intrusion and its host rock. This shearing enhanced circulation of the fluids and allowed segregation of the nea-formed melts from their restite by opening tension veins into which the melts migrated. Depending on the relative timing of melt segregation and recrystallization leucosomes range in composition from a 40-60% mixture of clinopyroxene (+/- amphibole) and plagioclase to almost pure feldspathic veins. Comparable occurrences of gabbros migmatized at low pressure are expected only at a snail scale in localized areas of high heat flow in the presence of fluids, such as in. mid-ocean ridges or ocean-islands.

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Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem.