66 resultados para Binary panels
Resumo:
The antennal lobe is the primary olfactory center in the insect brain and represents the anatomical and functional equivalent of the vertebrate olfactory bulb. Olfactory information in the external world is transmitted to the antennal lobe by olfactory sensory neurons (OSNs), which segregate to distinct regions of neuropil called glomeruli according to the specific olfactory receptor they express. Here, OSN axons synapse with both local interneurons (LNs), whose processes can innervate many different glomeruli, and projection neurons (PNs), which convey olfactory information to higher olfactory brain regions. Optical imaging of the activity of OSNs, LNs and PNs in the antennal lobe - traditionally using synthetic calcium indicators (e.g. calcium green, FURA-2) or voltage-sensitive dyes (e.g. RH414) - has long been an important technique to understand how olfactory stimuli are represented as spatial and temporal patterns of glomerular activity in many species of insects. Development of genetically-encoded neural activity reporters, such as the fluorescent calcium indicators G-CaMP and Cameleon, the bioluminescent calcium indicator GFP-aequorin, or a reporter of synaptic transmission, synapto-pHluorin has made the olfactory system of the fruitfly, Drosophila melanogaster, particularly accessible to neurophysiological imaging, complementing its comprehensively-described molecular, electrophysiological and neuroanatomical properties. These reporters can be selectively expressed via binary transcriptional control systems (e.g. GAL4/UAS, LexA/LexAop, Q system) in defined populations of neurons within the olfactory circuitry to dissect with high spatial and temporal resolution how odor-evoked neural activity is represented, modulated and transformed. Here we describe the preparation and analysis methods to measure odor-evoked responses in the Drosophila antennal lobe using G-CaMP. The animal preparation is minimally invasive and can be adapted to imaging using wide-field fluorescence, confocal and two-photon microscopes.
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BACKGROUND: Social support has been found to be protective from adverse health effects of psychological stress. We hypothesized that higher social support would predict a more favorable course of Crohn's disease (CD) directly (main effect hypothesis) and via moderating other prognostic factors (buffer hypothesis). METHODS: Within a multicenter cohort study we observed 597 adults with CD for 18 months. We assessed social support using the ENRICHD Social Support Inventory. Flares, nonresponse to therapy, complications, and extraintestinal manifestations were recorded as a combined endpoint indicating disease deterioration. We controlled for several demographic, psychosocial, and clinical variables of potential prognostic importance. We used multivariate binary logistic regression to estimate the overall effect of social support on the odds of disease deterioration and to explore main and moderator effects of social support by probing interactions with other predictors. RESULTS: The odds of disease deterioration decreased by 1.5 times (95% confidence interval [CI]: 1.2-1.9) for an increase of one standard deviation (SD) of social support. In case of low body mass index (BMI) (i.e., 1 SD below the mean or <19 kg/m(2)), the odds decreased by 1.8 times for an increase of 1 SD of social support. In case of low social support, the odds increased by 2.1 times for a decrease of 1 SD of BMI. Low BMI was not predictive under high social support. CONCLUSIONS: The findings suggest that elevated social support may favorably affect the clinical course of CD, particularly in patients with low BMI. (Inflamm Bowel Dis 2010;).
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Given the very large amount of data obtained everyday through population surveys, much of the new research again could use this information instead of collecting new samples. Unfortunately, relevant data are often disseminated into different files obtained through different sampling designs. Data fusion is a set of methods used to combine information from different sources into a single dataset. In this article, we are interested in a specific problem: the fusion of two data files, one of which being quite small. We propose a model-based procedure combining a logistic regression with an Expectation-Maximization algorithm. Results show that despite the lack of data, this procedure can perform better than standard matching procedures.
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Two genome-wide association studies for meningococcal disease and tuberculosis identify new loci associated with susceptibility to these infectious diseases. They highlight a role for the acquired and innate immune systems in host control of several human pathogens and demonstrate that denser genotyping platforms and population-specific reference panels are necessary for genetic studies in African populations.
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Routine screening of patients at risk of hepatitis C virus (HCV) infection has become a priority given recent improvements in therapeutic options and the asymptomatic nature of most chronic infections. The aim of this study was to evaluate the performance of the Elecsys® Anti-HCV II assay, a new qualitative antibody immunoassay, compared with currently available assays, and assess its suitability for routine diagnostic testing. The sensitivity of the Elecsys® Anti-HCV II, ARCHITECT® Anti-HCV, AxSYM® HCV 3.0, PRISM® HCV, Vitros® ECi Anti-HCV, Elecsys® Anti-HCV, and ADVIA Centaur® HCV assays was compared using commercially available seroconversion panels and samples from patients known to be HCV positive and infected with HCV genotypes 1-6. Specificity was investigated using samples from blood donors, unselected hospitalized patients, and patients with potential cross-reacting factors or from high-risk groups. The Elecsys® Anti-HCV II assay detected more positive bleeds than the comparator assays, was more sensitive in recognizing early HCV infection, and correctly identified all 765 samples known to be HCV positive, regardless of genotype. The overall specificity of the Elecsys(®) Anti-HCV II assay was 99.84% (n = 6,850) using blood donor samples, 99.66% (n = 3,922) using samples from unselected hospitalized patients, and 99.66% (n = 2,397) using samples from patients with potentially cross-reacting factors or from high-risk groups. The specificity of the Elecsys® Anti-HCV II assay was superior or equal to the comparator assays. In conclusion, the Elecsys® Anti-HCV II assay is a sensitive and specific assay suitable for routine use in the reliable detection of anti-HCV antibodies. J. Med. Virol. 85:1362-1368, 2013. © 2013 Wiley Periodicals, Inc.
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For many applications in population genetics, codominant simple sequence repeats (SSRs) may have substantial advantages over dominant anonymous markers such as amplified fragment length polymorphisms (AFLPs). In high polyploids, however, allele dosage of SSRs cannot easily be determined and alleles are not easily attributable to potentially diploidized loci. Here, we argue that SSRs may nonetheless be better than AFLPs for polyploid taxa if they are analyzed as effectively dominant markers because they are more reliable and more precise. We describe the transfer of SSRs developed for diploid Mercurialis huetii to the clonal dioecious M. perennis. Primers were tested on a set of 54 male and female plants from natural decaploid populations. Eight of 65 tested loci produced polymorphic fragments. Binary profiles from 4 different scoring routines were used to define multilocus lineages (MLLs). Allowing for fragment differences within 1 MLL, all analyses revealed the same 14 MLLs without conflicting with merigenet, sex, or plot assignment. For semiautomatic scoring, a combination of as few as 2 of the 4 most polymorphic loci resulted in unambiguous discrimination of clones. Our study demonstrates that microsatellite fingerprinting of polyploid plants is a cost efficient and reliable alternative to AFLPs, not least because fewer loci are required than for diploids.
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Fungalysins are secreted fungal peptidases with the ability to degrade the extracellular matrix proteins elastin and collagen and are thought to act as virulence factors in diseases caused by fungi. Fungalysins constitute a unique family among zinc-dependent peptidases that bears low sequence similarity to known bacterial peptidases of the thermolysin family. The crystal structure of the archetype of the fungalysin family, Aspergillus fumigatus metalloprotease (AfuMep), has been obtained for the first time. The 1.8 Å resolution structure of AfuMep corresponds to that of an autoproteolyzed proenzyme with separate polypeptide chains corresponding to the N-terminal prodomain in a binary complex with the C-terminal zinc-bound catalytic domain. The prodomain consists of a tandem of cystatin-like folds whose C-terminal end is buried into the active-site cleft of the catalytic domain. The catalytic domain harbouring the key catalytic zinc ion and its ligands, two histidines and one glutamic acid, undergoes a conspicuous rearrangement of its N-terminal end during maturation. One key positively charged amino-acid residue and the C-terminal disulfide bridge appear to contribute to its structural-functional properties. Thus, structural, biophysical and biochemical analysis were combined to provide a deeper comprehension of the underlying properties of A. fumigatus fungalysin, serving as a framework for the as yet poorly known metallopeptidases from pathogenic fungi.
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We present a novel filtering method for multispectral satellite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments carried out on multiclass one-against-all classification and target detection show the capabilities of the learned spatial filters.
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Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.
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Using a numerical approach, we explore wave-induced fluid flow effects in partially saturated porous rocks in which the gas-water saturation patterns are governed by mesoscopic heterogeneities associated with the dry frame properties. The link between the dry frame properties and the gas saturation is defined by the assumption of capillary pressure equilibrium, which in the presence of heterogeneity implies that neighbouring regions can exhibit different levels of saturation. To determine the equivalent attenuation and phase velocity of the synthetic rock samples considered in this study, we apply a numerical upscaling procedure, which permits to take into account mesoscopic heterogeneities associated with the dry frame properties as well as spatially continuous variations of the pore fluid properties. The multiscale nature of the fluid saturation is taken into account by locally computing the physical properties of an effective fluid, which are then used for the larger-scale simulations. We consider two sets of numerical experiments to analyse such effects in heterogeneous partially saturated porous media, where the saturation field is determined by variations in porosity and clay content, respectively. In both cases we also evaluate the seismic responses of corresponding binary, patchy-type saturation patterns. Our results indicate that significant attenuation and modest velocity dispersion effects take place in this kind of media for both binary patchy-type and spatially continuous gas saturation patterns and in particular in the presence of relatively small amounts of gas. The numerical experiments also show that the nature of the gas distribution patterns is a critical parameter controlling the seismic responses of these environments, since attenuation and velocity dispersion effects are much more significant and occur over a broader saturation range for binary patchy-type gas-water distributions. This analysis therefore suggests that the physical mechanisms governing partial saturation should be accounted for when analysing seismic data in a poroelastic framework. In this context, heterogeneities associated with the dry frame properties, which do not play important roles in wave-induced fluid flow processes per se, should be taken into account since they may determine the kind of gas distribution pattern taking place in the porous rock.
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Microsatellite instability (MSI) testing in clinics is becoming increasingly widespread; therefore, there is an urgent need for methodology standardization and the availability of quality control. This study is aimed to assess the interlaboratory reproducibility of MSI testing in archive samples by using a panel of 5 recently introduced, mononucleotide repeats (MNR). The quality control involved 8 European institutions. Participants were supplied with DNA extracted from 15 archive colon carcinoma samples and from the corresponding normal tissues. Every group was asked to assess the MSI status of the samples by using the BAT25, BAT26, NR21, NR24, and NR27 mononucleotide markers. Four institutions repeated the analysis using the NCI reference panel to confirm the results obtained with the MNR markers. The overall concordance among institutions for MSI analyses at single locus level was 97.7% when using the MNR panel and 95.0% with the NCI one. The laboratories obtained a full agreement in scoring the MSI status of each patient sample, both using the mononucleotide and the NCI marker sets. With the NCI marker set, however, concordance was lowered to 85.7% when considering the MSI-Low phenotype. Concordance between the 2 panels in scoring the MSI status of each sample was complete if no discrimination was made between MSI-Stable and MSI-L, whereas it dropped to 76.7% if MSI-L was considered. In conclusion, the use of the MNR panel seems to be a robust approach that yields a very high level of reproducibility. The results obtained with the 5 MNR are diagnostically consistent with those obtained by the use of the NCI markers, except for the MSI-Low phenotype.
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The present study constitutes an investigation of tobacco consumption, related attitudes and individual differences in smoking or non-smoking behaviors in a sample of adolescents of different ages in the French-speaking part of Switzerland. We investigated three school-age groups (7th-grade, 9th-grade, and the second-year of high school) for differences in attitude and social and cognitive dimensions. We present both descriptive and inferential statistics. On an inferential level, we present a binary logistic regression-based model predicting risk of smoking. The resulting model most importantly suggests a strong relationship between smoking and alcohol consumption (both regular and sporadic). We interpret this result in terms of both the impact of the actual campaigns and the cognitive processes associated with adolescence.
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Many regions of the world, including inland lakes, present with suboptimal conditions for the remotely sensed retrieval of optical signals, thus challenging the limits of available satellite data-processing tools, such as atmospheric correction models (ACM) and water constituent-retrieval (WCR) algorithms. Working in such regions, however, can improve our understanding of remote-sensing tools and their applicabil- ity in new contexts, in addition to potentially offering useful information about aquatic ecology. Here, we assess and compare 32 combinations of two ACMs, two WCRs, and three binary categories of data quality standards to optimize a remotely sensed proxy of plankton biomass in Lake Kivu. Each parameter set is compared against the available ground-truth match-ups using Spearman's right-tailed ρ. Focusing on the best sets from each ACM-WCR combination, their performances are discussed with regard to data distribution, sample size, spatial completeness, and seasonality. The results of this study may be of interest both for ecological studies on Lake Kivu and for epidemio- logical studies of disease, such as cholera, the dynamics of which has been associated with plankton biomass in other regions of the world.
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BACKGROUND: This study examined the reliability of explicit guidelines developed using the RAND-UCLA appropriateness method. METHODS: The appropriateness of over 400 indications for colonoscopy was rated by two multispecialty expert panels (United States and Switzerland). A nine-point scale was used, which was consolidated into three categories of appropriateness: appropriate, uncertain, inappropriate. The distribution of appropriateness ratings between the two panels and the intrapanel and interpanel agreement for categories of appropriateness were calculated for all possible indications. Similar statistics were calculated for a series of 577 primary care patients referred for colonoscopy in Switzerland. RESULTS: Over 80% of all indications (348) could be directly compared. The proportions of indications classified as appropriate, uncertain, or inappropriate were 28.4%, 24.7%, 46.6% and 33.0%, 23.0%, 44.0% for the U.S. and the Swiss panels, respectively. Interpanel agreement was excellent for all the possible indications (kappa value: 0.75) and lower for actual cases (kappa value: 0.51) because of lower agreement for the most frequently encountered indications. CONCLUSIONS: Good agreement between the two sets of criteria was found, pointing to the reliability of the method. Partial disagreement occurred essentially for a few, albeit frequently encountered, indications for use of colonoscopy in cases of uncomplicated lower abdominal pain or constipation.
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Our understanding of the distribution of worldwide human genomic diversity has greatly increased over recent years thanks to the availability of large data sets derived from short tandem repeats (STRs), insertion deletion polymorphisms (indels) and single nucleotide polymorphisms (SNPs). A concern, however, is that the current picture of worldwide human genomic diversity may be inaccurate because of biases in the selection process of genetic markers (so-called 'ascertainment bias'). To evaluate this problem, we first compared the distribution of genomic diversity between these three types of genetic markers in the populations from the HGDP-CEPH panel for evidence of bias or incongruities. In a second step, using a very relaxed set of criteria to prevent the intrusion of bias, we developed a new set of unbiased STR markers and compared the results against those from available panels. Contrarily to recent claims, our results show that the STR markers suffer from no discernible bias, and can thus be used as a baseline reference for human genetic diversity and population differentiation. The bias on SNPs is moderate compared to that on the set of indels analysed, which we recommend should be avoided for work describing the distribution of human genetic diversity or making inference on human settlement history.