172 resultados para sensor classification


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A new radiolarian order - Archaeospicularia - is proposed for some Lower Paleozoic radiolarians previously considered to belong to Spumellaria and to Collodaria. It is characterized by a globular shell made of several spicules which can be free, interlocked, or fused to formed a latticed wall. The present paper gives the definition of this order and proposes a first classification. It is supposed that the Archaeospicularia represents the oldest radiolarian group and that in the Lower Paleozoic it gave rise to the orders Entactinaria, Albaillellaria, and probably Spumellaria by the reduction of the number of initial spicules. The origin of this order and its relationships with other groups of organisms with siliceous skeletons are also briefly discussed. (C) 2000 Academie des sciences / Editions scientifiques et medicales Elsevier SAS.

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Many inflammatory and infectious diseases are characterized by the activation of signaling pathways steaming from the endoplasmic reticulum (ER). These pathways, primarily associated with loss of ER homeostasis, are emerging as key regulators of inflammation and infection. Recent advances shed light on the mechanisms linking ER-stress and immune responses.

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Pseudomonas protegens is a biocontrol rhizobacterium with a plant-beneficial and an insect pathogenic lifestyle, but it is not understood how the organism switches between the two states. Here, we focus on understanding the function and possible evolution of a molecular sensor that enables P. protegens to detect the insect environment and produce a potent insecticidal toxin specifically during insect infection but not on roots. By using quantitative single cell microscopy and mutant analysis, we provide evidence that the sensor histidine kinase FitF is a key regulator of insecticidal toxin production. Our experimental data and bioinformatic analyses indicate that FitF shares a sensing domain with DctB, a histidine kinase regulating carbon uptake in Proteobacteria. This suggested that FitF has acquired its specificity through domain shuffling from a common ancestor. We constructed a chimeric DctB-FitF protein and showed that it is indeed functional in regulating toxin expression in P. protegens. The shuffling event and subsequent adaptive modifications of the recruited sensor domain were critical for the microorganism to express its potent insect toxin in the observed host-specific manner. Inhibition of the FitF sensor during root colonization could explain the mechanism by which P. protegens differentiates between the plant and insect host. Our study establishes FitF of P. protegens as a prime model for molecular evolution of sensor proteins and bacterial pathogenicity.

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In the preceding article, we demonstrated that activation of the hepatoportal glucose sensor led to a paradoxical development of hypoglycemia that was associated with increased glucose utilization by a subset of tissues. In this study, we tested whether GLUT2 plays a role in the portal glucose-sensing system that is similar to its involvement in pancreatic beta-cells. Awake RIPGLUT1 x GLUT2-/- and control mice were infused with glucose through the portal (Po-) or the femoral (Fe-) vein for 3 h at a rate equivalent to the endogenous glucose production rate. Blood glucose and plasma insulin concentrations were continuously monitored. Glucose turnover, glycolysis, and glycogen synthesis rates were determined by the 3H-glucose infusion technique. We showed that portal glucose infusion in RIPGLUT1 x GLUT24-/- mice did not induce the hypoglycemia observed in control mice but, in contrast, led to a transient hyperglycemic state followed by a return to normoglycemia; this glycemic pattern was similar to that observed in control Fe-mice and RIPGLUT1 x GLUT2-/- Fe-mice. Plasma insulin profiles during the infusion period were similar in control and RIPGLUT1 x GLUT2-/- Po- and Fe-mice. The lack of hypoglycemia development in RIPGLUT1 x GLUT2-/- mice was not due to the absence of GLUT2 in the liver. Indeed, reexpression by transgenesis of this transporter in hepatocytes did not restore the development of hypoglycemia after initiating portal vein glucose infusion. In the absence of GLUT2, glucose turnover increased in Po-mice to the same extent as that in RIPGLUT1 x GLUT2-/- or control Fe-mice. Finally, co-infusion of somatostatin with glucose prevented development of hypoglycemia in control Po-mice, but it did not affect the glycemia or insulinemia of RIPGLUT1 x GLUT2-/- Po-mice. Together, our data demonstrate that GLUT2 is required for the function of the hepatoportal glucose sensor and that somatostatin could inhibit the glucose signal by interfering with GLUT2-expressing sensing units.

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The first AO comprehensive pediatric long-bone fracture classification system has been proposed following a structured path of development and validation with experienced pediatric surgeons. A Web-based multicenter agreement study involving 70 surgeons in 15 clinics and 5 countries was conducted to assess the reliability and accuracy of this classification when used by a wide range of surgeons with various levels of experience. Training was provided at each clinic before the session. Using the Internet, participants could log in at any time and classify 275 supracondylar, radius, and tibia fractures at their own pace. The fracture diagnosis was made following the hierarchy of the classification system using both clinical terminology and codes. kappa coefficients for the single-surgeon diagnosis of epiphyseal, metaphyseal, or diaphyseal fracture type were 0.66, 0.80, and 0.91, respectively. Median accuracy estimates for each bone and type were all greater than 80%. Depending on their experience and specialization, surgeons greatly varied in their ability to classify fractures. Pediatric training and at least 2 years of experience were associated with significant improvement in reliability and accuracy. Kappa coefficients for diagnosis of specific child patterns were 0.51, 0.63, and 0.48 for epiphyseal, metaphyseal, and diaphyseal fractures, respectively. Identified reasons for coding discrepancies were related to different understandings of terminology and definitions, as well as poor quality radiographic images. Results supported some minor adjustments in the coding of fracture type and child patterns. This classification system received wide acceptance and support among the surgeons involved. As long as appropriate training could be performed, the system classification was reliable, especially among surgeons with a minimum of 2 years of clinical experience. We encourage broad-based consultation between surgeons' international societies and the use of this classification system in the context of clinical practice as well as prospectively for clinical studies.

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The aim of this study was to compare the diagnostic efficiency of plain film and spiral CT examinations with 3D reconstructions of 42 tibial plateau fractures and to assess the accuracy of these two techniques in the pre-operative surgical plan in 22 cases. Forty-two tibial plateau fractures were examined with plain film (anteroposterior, lateral, two obliques) and spiral CT with surface-shaded-display 3D reconstructions. The Swiss AO-ASIF classification system of bone fracture from Muller was used. In 22 cases the surgical plans and the sequence of reconstruction of the fragments were prospectively determined with both techniques, successively, and then correlated with the surgical reports and post-operative plain film. The fractures were underestimated with plain film in 18 of 42 cases (43%). Due to the spiral CT 3D reconstructions, and precise pre-operative information, the surgical plans based on plain film were modified and adjusted in 13 cases among 22 (59%). Spiral CT 3D reconstructions give a better and more accurate demonstration of the tibial plateau fracture and allows a more precise pre-operative surgical plan.

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Comme la classification de Savary-Miller dont elle adopte l'essentiel, la classification de l'oesophagite par refluxen 5 types de Savary-Monnier repose sur une analyse rigoureuse et précise des lésions endoscopiques. Ses principales qualités sont d'être simple, complète, logique et souple. Son impact sur la pratique est certain puisqu'elle a une excellente valeur pronostique et qu'elle permet de choisir la bonne stratégie thérapeutique. De plus, en isolant les cicatrices cylindriques (seules précancéroses à surveiller à long terme) elle permet de les utiliser pour préciser la topographie des oesophagites de reflux.

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The InterPro database (http://www.ebi.ac.uk/interpro/) is a freely available resource that can be used to classify sequences into protein families and to predict the presence of important domains and sites. Central to the InterPro database are predictive models, known as signatures, from a range of different protein family databases that have different biological focuses and use different methodological approaches to classify protein families and domains. InterPro integrates these signatures, capitalizing on the respective strengths of the individual databases, to produce a powerful protein classification resource. Here, we report on the status of InterPro as it enters its 15th year of operation, and give an overview of new developments with the database and its associated Web interfaces and software. In particular, the new domain architecture search tool is described and the process of mapping of Gene Ontology terms to InterPro is outlined. We also discuss the challenges faced by the resource given the explosive growth in sequence data in recent years. InterPro (version 48.0) contains 36 766 member database signatures integrated into 26 238 InterPro entries, an increase of over 3993 entries (5081 signatures), since 2012.

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The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

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BACKGROUND AND PURPOSE: MCI was recently subdivided into sd-aMCI, sd-fMCI, and md-aMCI. The current investigation aimed to discriminate between MCI subtypes by using DTI. MATERIALS AND METHODS: Sixty-six prospective participants were included: 18 with sd-aMCI, 13 with sd-fMCI, and 35 with md-aMCI. Statistics included group comparisons using TBSS and individual classification using SVMs. RESULTS: The group-level analysis revealed a decrease in FA in md-aMCI versus sd-aMCI in an extensive bilateral, right-dominant network, and a more pronounced reduction of FA in md-aMCI compared with sd-fMCI in right inferior fronto-occipital fasciculus and inferior longitudinal fasciculus. The comparison between sd-fMCI and sd-aMCI, as well as the analysis of the other diffusion parameters, yielded no significant group differences. The individual-level SVM analysis provided discrimination between the MCI subtypes with accuracies around 97%. The major limitation is the relatively small number of cases of MCI. CONCLUSIONS: Our data show that, at the group level, the md-aMCI subgroup has the most pronounced damage in white matter integrity. Individually, SVM analysis of white matter FA provided highly accurate classification of MCI subtypes.

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This paper presents 3-D brain tissue classificationschemes using three recent promising energy minimizationmethods for Markov random fields: graph cuts, loopybelief propagation and tree-reweighted message passing.The classification is performed using the well knownfinite Gaussian mixture Markov Random Field model.Results from the above methods are compared with widelyused iterative conditional modes algorithm. Theevaluation is performed on a dataset containing simulatedT1-weighted MR brain volumes with varying noise andintensity non-uniformities. The comparisons are performedin terms of energies as well as based on ground truthsegmentations, using various quantitative metrics.

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Introduction: Quantitative measures of degree of lumbar spinal stenosis (LSS) such as antero-posterior diameter of the canal or dural sac cross sectional area vary widely and do not correlate with clinical symptoms or results of surgical decompression. In an effort to improve quantification of stenosis we have developed a grading system based on the morphology of the dural sac and its contents as seen on T2 axial images. The grading comprises seven categories ranging form normal to the most severe stenosis and takes into account the ratio of rootlet/CSF content. Material and methods: Fifty T2 axial MRI images taken at disc level from twenty seven symptomatic lumbar spinal stenosis patients who underwent decompressive surgery were classified into seven categories by five observers and reclassified 2 weeks later by the same investigators. Intra- and inter-observer reliability of the classification were assessed using Cohen's and Fleiss' kappa statistics, respectively. Results: Generally, the morphology grading system itself was well adopted by the observers. Its success in application is strongly influenced by the identification of the dural sac. The average intraobserver Cohen's kappa was 0.53 ± 0.2. The inter-observer Fleiss' kappa was 0.38 ± 0.02 in the first rating and 0.3 ± 0.03 in the second rating repeated after two weeks. Discussion: In this attempt, the teaching of the observers was limited to an introduction to the general idea of the morphology grading system and one example MRI image per category. The identification of the dimension of the dural sac may be a difficult issue in absence of complete T1 T2 MRI image series as it was the case here. The similarity of the CSF to possibly present fat on T2 images was the main reason of mismatch in the assignment of the cases to a category. The Fleiss correlation factors of the five observers are fair and the proposed morphology grading system is promising.