355 resultados para functional programming
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The project "Quantification and qualification of ambulatory health care", financed by the Swiss National Science Foundation and covering the Cantons of Vaud and Fribourg, has two main goals: --a structural study of the elements of the ambulatory care sector. This is done through inventories of the professions concerned (physicians, public health nurses, physiotherapists, pharmacists, medical laboratories), allowing to better characterize the "offer". This inventory work includes the collect and analysis of existing statistical data as well as surveys, by questionnaires sent (from September 1980) to the different professions and by interviews. --a functional study, inspired from the US National Ambulatory Medical Care Survey and from similar studies elsewhere, in order to investigate the modes of practice of various providers, with particular regard to interprofessional collaboration (through studying referrals from the ones to the others). The first months of the project have been used for a methodological research in this regard, centered on the use of systems analysis, and for the elaboration of adequate instruments.
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PurposeThe purpose of this study was to report the 2-year outcome of an individually tailored 'observe-and-plan' treatment regimen for neovascular age-related macular degeneration (nAMD), and to investigate its clinical value in terms of functional outcome. This regimen aimed to reduce the clinical burden (visits) by employing individually fixed injection intervals, based on the predictability of an individual's need for retreatment.MethodsThis prospective case series included 104 patients (115 eyes) with nAMD. Following three loading doses of ranibizumab, the disease recurrence interval was determined in monthly observation visits. Retreatment was applied in a series of three injections with individually fixed intervals (2 weeks shorter than the recurrence interval), combined with periodic adjustment of the intervals. The allowed injection intervals in treatment plans ranged from 1 to 3 months. If there was no recurrence at 3 months, the patient could change to monitoring alone.ResultsMean visual acuity (VA) improved by 8.7, 9.7, and 9.2 letters at months 3, 12, and 24, respectively. The mean number of injections was 7.8 and 5.8 during years 1 and 2, respectively, whereas the mean number of ophthalmic examinations was 4.0 and 2.9, respectively. The mean treatment interval (after the loading doses) was 2.0 months during year 1, and 2.2 months during year 2.ConclusionThe observe-and-plan regimen significantly improved and maintained VA over the course of 2 years. This favourable functional outcome was achieved with fewer clinic visits compared with other regimens. Therefore, this observe-and-plan regimen has the potential to alleviate the clinical burden of nAMD treatment.Eye advance online publication, 7 November 2014; doi:10.1038/eye.2014.258.
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The current state of empirical investigations refers to consciousness as an all-or-none phenomenon. However, a recent theoretical account opens up this perspective by proposing a partial level (between nil and full) of conscious perception. In the well-studied case of single-word reading, short-lived exposure can trigger incomplete word-form recognition wherein letters fall short of forming a whole word in one's conscious perception thereby hindering word-meaning access and report. Hence, the processing from incomplete to complete word-form recognition straightforwardly mirrors a transition from partial to full-blown consciousness. We therefore hypothesized that this putative functional bottleneck to consciousness (i.e. the perceptual boundary between partial and full conscious perception) would emerge at a major key hub region for word-form recognition during reading, namely the left occipito-temporal junction. We applied a real-time staircase procedure and titrated subjective reports at the threshold between partial (letters) and full (whole word) conscious perception. This experimental approach allowed us to collect trials with identical physical stimulation, yet reflecting distinct perceptual experience levels. Oscillatory brain activity was monitored with magnetoencephalography and revealed that the transition from partial-to-full word-form perception was accompanied by alpha-band (7-11 Hz) power suppression in the posterior left occipito-temporal cortex. This modulation of rhythmic activity extended anteriorly towards the visual word form area (VWFA), a region whose selectivity for word-forms in perception is highly debated. The current findings provide electrophysiological evidence for a functional bottleneck to consciousness thereby empirically instantiating a recently proposed partial perspective on consciousness. Moreover, the findings provide an entirely new outlook on the functioning of the VWFA as a late bottleneck to full-blown conscious word-form perception.
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Understanding the relative importance of historical and environmental processes in the structure and composition of communities is one of the longest quests in ecological research. Increasingly, researchers are relying on the functional and phylogenetic β-diversity of natural communities to provide concise explanations on the mechanistic basis of community assembly and the drivers of trait variation among species. The present study investigated how plant functional and phylogenetic β-diversity change along key environmental and spatial gradients in the Western Swiss Alps. Methods Using the quadratic diversity measure based on six functional traits: specific leaf area (SLA), leaf dry matter content (LDMC), plant height (H), leaf carbon content (C), leaf nitrogen content (N), and leaf carbon to nitrogen content (C/N) alongside a species-resolved phylogenetic tree, we relate variations in climate, spatial geographic, land use and soil gradients to plant functional and phylogenetic turnover in mountain communities of the Western Swiss Alps. Important findings Our study highlights two main points. First, climate and land use factors play an important role in mountain plant community turnover. Second, the overlap between plant functional and phylogenetic turnover along these gradients correlates with the low phylogenetic signal in traits, suggesting that in mountain landscapes, trait lability is likely an important factor in driving plant community assembly. Overall, we demonstrate the importance of climate and land use factors in plant functional and phylogenetic community turnover, and provide valuable complementary insights into understanding patterns of β-diversity along several ecological gradients.
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BACKGROUND: Alpha-dystroglycan (alpha-DG) is a cell surface receptor providing a molecular link between the extracellular matrix (ECM) and the actin-based cytoskeleton. During its biosynthesis, alpha-DG undergoes specific and unusual O-glycosylation crucial for its function as a high-affinity cellular receptor for ECM proteins. METHODOLOGY/PRINCIPAL FINDINGS: We report that expression of functionally glycosylated alpha-DG during thymic development is tightly regulated in developing T cells and largely confined to CD4(-)CD8(-) double negative (DN) thymocytes. Ablation of DG in T cells had no effect on proliferation, migration or effector function but did reduce the size of the thymus due to a significant loss in absolute numbers of thymocytes. While numbers of DN thymocytes appeared normal, a marked reduction in CD4(+)CD8(+) double positive (DP) thymocytes occurred. In the periphery mature naïve T cells deficient in DG showed both normal proliferation in response to allogeneic cells and normal migration, effector and memory T cell function when tested in acute infection of mice with either lymphocytic choriomeningitis virus (LCMV) or influenza virus. CONCLUSIONS/SIGNIFICANCE: Our study demonstrates that DG function is modulated by glycosylation during T cell development in vivo and that DG is essential for normal development and differentiation of T cells.
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Plasmodium sporozoites make a remarkable journey from the mosquito midgut to the mammalian liver. The sporozoite's major surface protein, circumsporozoite protein (CSP), is a multifunctional protein required for sporozoite development and likely mediates several steps of this journey. In this study, we show that CSP has two conformational states, an adhesive conformation in which the C-terminal cell-adhesive domain is exposed and a nonadhesive conformation in which the N terminus masks this domain. We demonstrate that the cell-adhesive domain functions in sporozoite development and hepatocyte invasion. Between these two events, the sporozoite must travel from the mosquito midgut to the mammalian liver, and N-terminal masking of the cell-adhesive domain maintains the sporozoite in a migratory state. In the mammalian host, proteolytic cleavage of CSP regulates the switch to an adhesive conformation, and the highly conserved region I plays a critical role in this process. If the CSP domain architecture is altered such that the cell-adhesive domain is constitutively exposed, the majority of sporozoites do not reach their target organs, and in the mammalian host, they initiate a blood stage infection directly from the inoculation site. These data provide structure-function information relevant to malaria vaccine development.
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Fas ligand (FasL, Apo-1L) is a member of the tumor necrosis factor protein family and binding to its receptor (Fas, Apo-1, CD95) triggers cell death through apoptosis. Ligand expression is restricted to cells with known cytolytic activity and found on hematopoietic cells of the T cell and natural killer lineage. Here we provide evidence that B lymphocytes can express FasL. Flow cytometric analysis revealed that FasL is expressed on the surface of B cells upon stimulation with either lipopolysaccharide or phorbol 12-myristate 13-acetate/ionomycin. FasL expression on activated B cells was confirmed by western blot and reverse transcriptase polymerase chain reaction analysis. FasL on B cells is functional since lipopolysaccharide-activated B lymphocytes derived from wild type, but not from gld mutant mice, were able to kill Fas-sensitive target cells. Our data suggest that the Fas system may contribute to the control of B cell homeostasis.
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BACKGROUND: Recently, it was shown that the relation between admission glucose and functional outcome after ischemic stroke is described by a J-shaped curve, with a glucose range of 3.7-7.3 mmol/l associated with a favorable outcome. We tested the hypothesis that persistence of hyperglycemia above this threshold at 24-48 h after stroke onset impairs 3-month functional outcome. METHODS: We analyzed all patients with glucose >7.3 mmol/l on admission from the Acute STroke Registry and Analysis of Lausanne (ASTRAL). Patients were divided into two groups according to their subacute glucose level at 24-48 h after last well-being time (group 1: ≤7.3 mmol/l, group 2: >7.3 mmol/l). A favorable functional outcome was defined as a modified Rankin Score (mRS) ≤2 at 3 months. A multiple logistic regression analysis of multiple demographic, clinical, laboratory and neuroimaging covariates was performed to assess predictors of an unfavorable outcome. RESULTS: A total of 1,984 patients with ischemic stroke were admitted between January 1, 2003 and October 20, 2009, within 24 h after last well-being time. In the 421 patients (21.2%) with admission glucose >7.3 mmol/l, the proportion of patients with a favorable outcome was not statistically significantly different between the two groups (59.2 vs. 48.7%, respectively). In multiple logistic regression analysis, unfavorable outcome was significantly associated with age (odds ratio, OR: 1.06, 95% confidence interval, 95% CI: 1.03-1.08 for every 10-year increase), National Institute of Health Stroke Score, NIHSS score, on admission (OR: 1.16, 95% CI: 1.11-1.21), prehospital mRS (OR: 12.63, 95% CI: 2.61-61.10 for patients with score >0), antidiabetic drug usage (OR: 0.36, 95% CI: 0.15-0.86) and glucose on admission (OR: 1.16, 95% CI: 1.02-1.31 for every 1 mmol/l increase). No association was found between persistent hyperglycemia at 24-28 h and outcome in either diabetics or nondiabetics. CONCLUSIONS: In ischemic stroke patients with acute hyperglycemia, persistent hyperglycemia (>7.3 mmol/l) at 24-48 h after stroke onset is not associated with a worse functional outcome at 3 months whether the patient was previously diabetic or not.
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There is growing interest in understanding the role of the non-injured contra-lateral hemisphere in stroke recovery. In the experimental field, histological evidence has been reported that structural changes occur in the contra-lateral connectivity and circuits during stroke recovery. In humans, some recent imaging studies indicated that contra-lateral sub-cortical pathways and functional and structural cortical networks are remodeling, after stroke. Structural changes in the contra-lateral networks, however, have never been correlated to clinical recovery in patients. To determine the importance of the contra-lateral structural changes in post-stroke recovery, we selected a population of patients with motor deficits after stroke affecting the motor cortex and/or sub-cortical motor white matter. We explored i) the presence of Generalized Fractional Anisotropy (GFA) changes indicating structural alterations in the motor network of patientsâeuro? contra-lateral hemisphere as well as their longitudinal evolution ii) the correlation of GFA changes with patientsâeuro? clinical scores, stroke size and demographics data iii) and a predictive model.
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Abstract : This work is concerned with the development and application of novel unsupervised learning methods, having in mind two target applications: the analysis of forensic case data and the classification of remote sensing images. First, a method based on a symbolic optimization of the inter-sample distance measure is proposed to improve the flexibility of spectral clustering algorithms, and applied to the problem of forensic case data. This distance is optimized using a loss function related to the preservation of neighborhood structure between the input space and the space of principal components, and solutions are found using genetic programming. Results are compared to a variety of state-of--the-art clustering algorithms. Subsequently, a new large-scale clustering method based on a joint optimization of feature extraction and classification is proposed and applied to various databases, including two hyperspectral remote sensing images. The algorithm makes uses of a functional model (e.g., a neural network) for clustering which is trained by stochastic gradient descent. Results indicate that such a technique can easily scale to huge databases, can avoid the so-called out-of-sample problem, and can compete with or even outperform existing clustering algorithms on both artificial data and real remote sensing images. This is verified on small databases as well as very large problems. Résumé : Ce travail de recherche porte sur le développement et l'application de méthodes d'apprentissage dites non supervisées. Les applications visées par ces méthodes sont l'analyse de données forensiques et la classification d'images hyperspectrales en télédétection. Dans un premier temps, une méthodologie de classification non supervisée fondée sur l'optimisation symbolique d'une mesure de distance inter-échantillons est proposée. Cette mesure est obtenue en optimisant une fonction de coût reliée à la préservation de la structure de voisinage d'un point entre l'espace des variables initiales et l'espace des composantes principales. Cette méthode est appliquée à l'analyse de données forensiques et comparée à un éventail de méthodes déjà existantes. En second lieu, une méthode fondée sur une optimisation conjointe des tâches de sélection de variables et de classification est implémentée dans un réseau de neurones et appliquée à diverses bases de données, dont deux images hyperspectrales. Le réseau de neurones est entraîné à l'aide d'un algorithme de gradient stochastique, ce qui rend cette technique applicable à des images de très haute résolution. Les résultats de l'application de cette dernière montrent que l'utilisation d'une telle technique permet de classifier de très grandes bases de données sans difficulté et donne des résultats avantageusement comparables aux méthodes existantes.
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Circulating monocytes, as dendritic cell and macrophage precursors, exhibit several functions usually associated with antigen-presenting cells, such as phagocytosis and presence of endosomal/lysosomal degradative compartments particularly enriched in Lamp-1, MHC class II molecules, and other proteins related to antigen processing and MHC class II loading [MHC class II compartments (MIICs)]. Ultrastructural analysis of these organelles indicates that, differently from the multivesicular bodies present in dendritic cells, in monocytes the MIICs are characterized by a single perimetral membrane surrounding an electron-dense core. Analysis of their content reveals enrichment in myeloperoxidase, an enzyme classically associated with azurophilic granules in granulocytes and mast cell secretory lysosomes. Elevation in intracellular free calcium levels in monocytes induced secretion of beta-hexosaminidase, cathepsins, and myeloperoxidase in the extracellular milieu; surface up-regulation of MHC class II molecules; and appearance of lysosomal resident proteins. The Ca(2+)-regulated surface transport mechanism of MHC class II molecules observed in monocytes is different from the tubulovesicular organization of the multivesicular bodies previously reported in dendritic cells and macrophages. Hence, in monocytes, MHC class II-enriched organelles combine degradative functions typical of lysosomes and regulated secretion typical of secretory lysosomes. More important, Ca(2+)-mediated up-regulation of surface MHC class II molecules is accompanied by extracellular release of lysosomal resident enzymes.
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Abstract : The human body is composed of a huge number of cells acting together in a concerted manner. The current understanding is that proteins perform most of the necessary activities in keeping a cell alive. The DNA, on the other hand, stores the information on how to produce the different proteins in the genome. Regulating gene transcription is the first important step that can thus affect the life of a cell, modify its functions and its responses to the environment. Regulation is a complex operation that involves specialized proteins, the transcription factors. Transcription factors (TFs) can bind to DNA and activate the processes leading to the expression of genes into new proteins. Errors in this process may lead to diseases. In particular, some transcription factors have been associated with a lethal pathological state, commonly known as cancer, associated with uncontrolled cellular proliferation, invasiveness of healthy tissues and abnormal responses to stimuli. Understanding cancer-related regulatory programs is a difficult task, often involving several TFs interacting together and influencing each other's activity. This Thesis presents new computational methodologies to study gene regulation. In addition we present applications of our methods to the understanding of cancer-related regulatory programs. The understanding of transcriptional regulation is a major challenge. We address this difficult question combining computational approaches with large collections of heterogeneous experimental data. In detail, we design signal processing tools to recover transcription factors binding sites on the DNA from genome-wide surveys like chromatin immunoprecipitation assays on tiling arrays (ChIP-chip). We then use the localization about the binding of TFs to explain expression levels of regulated genes. In this way we identify a regulatory synergy between two TFs, the oncogene C-MYC and SP1. C-MYC and SP1 bind preferentially at promoters and when SP1 binds next to C-NIYC on the DNA, the nearby gene is strongly expressed. The association between the two TFs at promoters is reflected by the binding sites conservation across mammals, by the permissive underlying chromatin states 'it represents an important control mechanism involved in cellular proliferation, thereby involved in cancer. Secondly, we identify the characteristics of TF estrogen receptor alpha (hERa) target genes and we study the influence of hERa in regulating transcription. hERa, upon hormone estrogen signaling, binds to DNA to regulate transcription of its targets in concert with its co-factors. To overcome the scarce experimental data about the binding sites of other TFs that may interact with hERa, we conduct in silico analysis of the sequences underlying the ChIP sites using the collection of position weight matrices (PWMs) of hERa partners, TFs FOXA1 and SP1. We combine ChIP-chip and ChIP-paired-end-diTags (ChIP-pet) data about hERa binding on DNA with the sequence information to explain gene expression levels in a large collection of cancer tissue samples and also on studies about the response of cells to estrogen. We confirm that hERa binding sites are distributed anywhere on the genome. However, we distinguish between binding sites near promoters and binding sites along the transcripts. The first group shows weak binding of hERa and high occurrence of SP1 motifs, in particular near estrogen responsive genes. The second group shows strong binding of hERa and significant correlation between the number of binding sites along a gene and the strength of gene induction in presence of estrogen. Some binding sites of the second group also show presence of FOXA1, but the role of this TF still needs to be investigated. Different mechanisms have been proposed to explain hERa-mediated induction of gene expression. Our work supports the model of hERa activating gene expression from distal binding sites by interacting with promoter bound TFs, like SP1. hERa has been associated with survival rates of breast cancer patients, though explanatory models are still incomplete: this result is important to better understand how hERa can control gene expression. Thirdly, we address the difficult question of regulatory network inference. We tackle this problem analyzing time-series of biological measurements such as quantification of mRNA levels or protein concentrations. Our approach uses the well-established penalized linear regression models where we impose sparseness on the connectivity of the regulatory network. We extend this method enforcing the coherence of the regulatory dependencies: a TF must coherently behave as an activator, or a repressor on all its targets. This requirement is implemented as constraints on the signs of the regressed coefficients in the penalized linear regression model. Our approach is better at reconstructing meaningful biological networks than previous methods based on penalized regression. The method is tested on the DREAM2 challenge of reconstructing a five-genes/TFs regulatory network obtaining the best performance in the "undirected signed excitatory" category. Thus, these bioinformatics methods, which are reliable, interpretable and fast enough to cover large biological dataset, have enabled us to better understand gene regulation in humans.