185 research outputs found

    Quand les entreprises produisent du capital social

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    Le présent article fait suite à une étude d’un cas de coopération interentreprises entre des boucanières de la région rurale de Cap-Pelé, au Nouveau-Brunswick (Canada). Les auteurs ont voulu examiner la période de transition entre une situation fortement concurrentielle et une situation de coopération. Cette transition s’est opérée grâce à la création d’une agence de commercialisation des produits marins des boucanières. L’examen a porté principalement sur le rôle du contrat, de l’intérêt et de la dimension symbolique dans la réalisation de cette transition. L’étude fait apparaître les conditions nécessaires à la formation du capital social dans les pratiques économiques à l’étude tout en soulignant l’effet déterminant des facteurs utilitaristes, contractualistes, symboliques et normatifs dans la réalisation de l’entente de coopération entre entreprises.In this article, we present the results of our case study on inter-business cooperation involving smokehouses in the rural area of Cap-Pelé, New Brunswick, Canada. Our aim was to trace the evolution from a highly competitive business situation to a cooperative situation, which resulted from the creation of a smoked fish product marketing agency. We examine the role of contract development, interest and the symbolic dimension of the transition to a cooperative model. Our study brings into light the necessary conditions for creating social capital within the economic practices examined, underlining the determining effect of utilitarian, contractarian, symbolic, and normative factors in achieving a cooperative agreement between businesses

    Measuring Outcome in an Early Intervention Program for Toddlers with Autism Spectrum Disorder: Use of a Curriculum-Based Assessment

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    Measuring progress of children with autism spectrum disorder (ASD) during intervention programs is a challenge faced by researchers and clinicians. Typically, standardized assessments of child development are used within research settings to measure the effects of early intervention programs. However, the use of standardized assessments is not without limitations, including lack of sensitivity of some assessments to measure small or slow progress, testing constraints that may affect the child's performance, and the lack of information provided by the assessments that can be used to guide treatment planning. The utility of a curriculum-based assessment is discussed in comparison to the use of standardized assessments to measure child functioning and progress throughout an early intervention program for toddlers with risk for ASD. Scores derived from the curriculum-based assessment were positively correlated with standardized assessments, captured progress masked by standardized assessments, and early scores were predictive of later outcomes. These results support the use of a curriculum-based assessment as an additional and appropriate method for measuring child progress in an early intervention program. Further benefits of the use of curriculum-based measures for use within community settings are discussed

    Preprocessing and Quality Control Strategies for Illumina DASL Assay-Based Brain Gene Expression Studies with Semi-Degraded Samples

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    Available statistical preprocessing or quality control analysis tools for gene expression microarray datasets are known to greatly affect downstream data analysis, especially when degraded samples, unique tissue samples, or novel expression assays are used. It is therefore important to assess the validity and impact of the assumptions built in to preprocessing schemes for a dataset. We developed and assessed a data preprocessing strategy for use with the Illumina DASL-based gene expression assay with partially degraded postmortem prefrontal cortex samples. The samples were obtained from individuals with autism as part of an investigation of the pathogenic factors contributing to autism. Using statistical analysis methods and metrics such as those associated with multivariate distance matrix regression and mean inter-array correlation, we developed a DASL-based assay gene expression preprocessing pipeline to accommodate and detect problems with microarray-based gene expression values obtained with degraded brain samples. Key steps in the pipeline included outlier exclusion, data transformation and normalization, and batch effect and covariate corrections. Our goal was to produce a clean dataset for subsequent downstream differential expression analysis. We ultimately settled on available transformation and normalization algorithms in the R/Bioconductor package lumi based on an assessment of their use in various combinations. A log2-transformed, quantile-normalized, and batch and seizure-corrected procedure was likely the most appropriate for our data. We empirically tested different components of our proposed preprocessing strategy and believe that our results suggest that a preprocessing strategy that effectively identifies outliers, normalizes the data, and corrects for batch effects can be applied to all studies, even those pursued with degraded samples

    Abnormal microglial-neuronal spatial organization in the dorsolateral prefrontal cortex in autism

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    Microglial activation and alterations in neuron number have been reported in autism. However, it is unknown whether microglial activation in the disorder includes a neurondirected microglial response that might reflect neuronal dysfunction, or instead indicates a non-directed, pro-activation brain environment. To address this question, we examined microglial and neuronal organization in the dorsolateral prefrontal cortex, a region of pronounced early brain overgrowth in autism, via spatial pattern analysis of 13 male postmortem autism subjects and 9 controls. We report that microglia are more frequently present near neurons in the autism cases at a distance interval of 25 μm, as well as 75 and 100 μm. Many interactions are observed between near-distance microglia and neurons that appear to involve encirclement of the neurons by microglial processes. Analysis of a young subject subgroup preliminarily suggests that this alteration may be present from an early age in autism. We additionally observed that neuron-neuron clustering, although normal in cases with autism as a whole, increases with advancing age in autism, suggesting a gradual loss of normal neuronal organization in the disorder. Microglia-microglia organization is normal in autism at all ages, indicating that aberrantly close microglia-neuron association in the disorder is not a result of altered microglial distribution. Our findings confirm that at least some microglial activation in the dorsolateral prefrontal cortex in autism is associated with a neuron-specific reaction, and suggest that neuronal organization may degrade later in life in the disorder

    Atypical genomic cortical patterning in autism with poor early language outcome.

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    Cortical regionalization develops via genomic patterning along anterior-posterior (A-P) and dorsal-ventral (D-V) gradients. Here, we find that normative A-P and D-V genomic patterning of cortical surface area (SA) and thickness (CT), present in typically developing and autistic toddlers with good early language outcome, is absent in autistic toddlers with poor early language outcome. Autistic toddlers with poor early language outcome are instead specifically characterized by a secondary and independent genomic patterning effect on CT. Genes involved in these effects can be traced back to midgestational A-P and D-V gene expression gradients and different prenatal cell types (e.g., progenitor cells and excitatory neurons), are functionally important for vocal learning and human-specific evolution, and are prominent in prenatal coexpression networks enriched for high-penetrance autism risk genes. Autism with poor early language outcome may be explained by atypical genomic cortical patterning starting in prenatal development, which may detrimentally affect later regional functional specialization and circuit formation

    Electroencephalographic Brain Dynamics Following Manually Responded Visual Targets

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    Scalp-recorded electroencephalographic (EEG) signals produced by partial synchronization of cortical field activity mix locally synchronous electrical activities of many cortical areas. Analysis of event-related EEG signals typically assumes that poststimulus potentials emerge out of a flat baseline. Signals associated with a particular type of cognitive event are then assessed by averaging data from each scalp channel across trials, producing averaged event-related potentials (ERPs). ERP averaging, however, filters out much of the information about cortical dynamics available in the unaveraged data trials. Here, we studied the dynamics of cortical electrical activity while subjects detected and manually responded to visual targets, viewing signals retained in ERP averages not as responses of an otherwise silent system but as resulting from event-related alterations in ongoing EEG processes. We applied infomax independent component analysis to parse the dynamics of the unaveraged 31-channel EEG signals into maximally independent processes, then clustered the resulting processes across subjects by similarities in their scalp maps and activity power spectra, identifying nine classes of EEG processes with distinct spatial distributions and event-related dynamics. Coupled two-cycle postmotor theta bursts followed button presses in frontal midline and somatomotor clusters, while the broad postmotor “P300” positivity summed distinct contributions from several classes of frontal, parietal, and occipital processes. The observed event-related changes in local field activities, within and between cortical areas, may serve to modulate the strength of spike-based communication between cortical areas to update attention, expectancy, memory, and motor preparation during and after target recognition and speeded responding

    Large-scale associations between the leukocyte transcriptome and BOLD responses to speech differ in autism early language outcome subtypes.

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    Heterogeneity in early language development in autism spectrum disorder (ASD) is clinically important and may reflect neurobiologically distinct subtypes. Here, we identified a large-scale association between multiple coordinated blood leukocyte gene coexpression modules and the multivariate functional neuroimaging (fMRI) response to speech. Gene coexpression modules associated with the multivariate fMRI response to speech were different for all pairwise comparisons between typically developing toddlers and toddlers with ASD and poor versus good early language outcome. Associated coexpression modules were enriched in genes that are broadly expressed in the brain and many other tissues. These coexpression modules were also enriched in ASD-associated, prenatal, human-specific, and language-relevant genes. This work highlights distinctive neurobiology in ASD subtypes with different early language outcomes that is present well before such outcomes are known. Associations between neuroimaging measures and gene expression levels in blood leukocytes may offer a unique in vivo window into identifying brain-relevant molecular mechanisms in ASD
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