79 research outputs found

    Evaluation of machine learning models in psychiatry

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    The biogeochemistry of carbon across a gradient of streams and rivers within the Congo Basin

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    Author Posting. © American Geophysical Union, 2014. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Biogeosciences 119 (2014): 687–702, doi:10.1002/2013JG002442.Dissolved organic carbon (DOC) and inorganic carbon (DIC, pCO2), lignin biomarkers, and theoptical properties of dissolved organic matter (DOM) were measured in a gradient of streams and rivers within the Congo Basin, with the aim of examining how vegetation cover and hydrology influences the composition and concentration of fluvial carbon (C). Three sampling campaigns (February 2010, November 2010, and August 2011) spanning 56 sites are compared by subbasin watershed land cover type (savannah, tropical forest, and swamp) and hydrologic regime (high, intermediate, and low). Land cover properties predominately controlled the amount and quality of DOC, chromophoric DOM (CDOM) and lignin phenol concentrations (∑8) exported in streams and rivers throughout the Congo Basin. Higher DIC concentrations and changing DOM composition (lower molecular weight, less aromatic C) during periods of low hydrologic flow indicated shifting rapid overland supply pathways in wet conditions to deeper groundwater inputs during drier periods. Lower DOC concentrations in forest and swamp subbasins were apparent with increasing catchment area, indicating enhanced DOC loss with extended water residence time. Surface water pCO2 in savannah and tropical forest catchments ranged between 2,600 and 11,922 µatm, with swamp regions exhibiting extremely high pCO2 (10,598–15,802 µatm), highlighting their potential as significant pathways for water-air efflux. Our data suggest that the quantity and quality of DOM exported to streams and rivers are largely driven by terrestrial ecosystem structure and that anthropogenic land use or climate change may impact fluvial C composition and reactivity, with ramifications for regional C budgets and future climate scenarios.This work was supported by the National Science Foundation as part of the ETBC Collaborative Research: Controls on the Flux, Age, and Composition of Terrestrial Organic Carbon Exported by Rivers to the Ocean (0851101 and 0851015).2014-10-3

    High-resolution 7-Tesla fMRI data on the perception of musical genres – an extension to the studyforrest dataset

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    Here we present an extension to the studyforrest dataset – a versatile resource for studying the behavior of the human brain in situations of real-life complexity (http://studyforrest.org). This release adds more high-resolution, ultra high-field (7 Tesla) functional magnetic resonance imaging (fMRI) data from the same individuals. The twenty participants were repeatedly stimulated with a total of 25 music clips, with and without speech content, from five different genres using a slow event-related paradigm. The data release includes raw fMRI data, as well as precomputed structural alignments for within-subject and group analysis. In addition to fMRI, simultaneously recorded cardiac and respiratory traces, as well the complete implementation of the stimulation paradigm, including stimuli, are provided. An initial quality control analysis reveals distinguishable patterns of response to individual genres throughout a large expanse of areas known to be involved in auditory and speech processing. The present data can be used to, for example, generate encoding models for music perception that can be validated against the previously released fMRI data from stimulation with the “Forrest Gump” audio-movie and its rich musical content. In order to facilitate replicative and derived works, only free and open-source software was utilized

    Use of bubble continuous positive airway pressure (bCPAP) in the management of critically ill children in a Malawian paediatric unit: An observational study

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    INTRODUCTION: In low-resource countries, respiratory failure is associated with a high mortality risk among critically ill children. We evaluated the role of bubble continuous positive airway pressure (bCPAP) in the routine care of critically ill children in Lilongwe, Malawi. // METHODS: We conducted an observational study between 26 February and 15 April 2014, in an urban paediatric unit with approximately 20 000 admissions/year (in-hospital mortality <5% approximately during this time period). Modified oxygen concentrators or oxygen cylinders provided humidified bCPAP air/oxygen flow. Children up to the age of 59 months with signs of severe respiratory dysfunction were recruited. Survival was defined as survival during the bCPAP-treatment and during a period of 48 hours following the end of the bCPAP-weaning process. // RESULTS: 117 children with signs of respiratory failure were included in this study and treated with bCPAP. Median age: 7 months. Malaria rapid diagnostic tests were positive in 25 (21%) cases, 15 (13%) had severe anaemia (Hb < 7.0 g/dL); 55 (47%) children had multiorgan failure (MOF); 22 (19%) children were HIV-infected/exposed. 28 (24%) were severely malnourished. Overall survival was 79/117 (68%); survival was 54/62 (87%) in children with very severe pneumonia (VSPNA) but without MOF. Among the 19 children with VSPNA (single-organ failure (SOF)) and negative HIV tests, all children survived. Survival rates were lower in children with MOF (including shock) (45%) as well as in children with severe malnutrition (36%) and proven HIV infection or exposure (45%). // CONCLUSIONS: Despite the limitations of this study, the good outcome of children with signs of severe respiratory dysfunction (SOF) suggests that it is feasible to use bCPAP in the hospital management of critically ill children in resource-limited settings. The role of bCPAP and other forms of non-invasive ventilatory support as a part of an improved care package for critically ill children with MOF at tertiary and district hospital level in low-resource countries needs further evaluation. Critically ill children with nutritional deficiencies and/or HIV infection/exposure need further study to determine bCPAP efficacy

    Subcortical shape alterations in major depressive disorder: findings from the ENIGMA major depressive disorder working group

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    First published:21 March 2020Alterations in regional subcortical brain volumes have been investigated as part of the efforts of an international consortium, ENIGMA, to identify reliable neural correlates of major depressive disorder (MDD). Given that subcortical structures are comprised of distinct subfields, we sought to build significantly from prior work by precisely mapping localized MDD-related differences in subcortical regions using shape analysis. In this meta-analysis of subcortical shape from the ENIGMA-MDD working group, we compared 1,781 patients with MDD and 2,953 healthy controls (CTL) on individual measures of shape metrics (thickness and surface area) on the surface of seven bilateral subcortical structures: nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. Harmonized data processing and statistical analyses were conducted locally at each site, and findings were aggregated by meta-analysis. Relative to CTL, patients with adolescent-onset MDD (≤ 21 years) had lower thickness and surface area of the subiculum, cornu ammonis (CA) 1 of the hippocampus and basolateral amygdala (Cohen's d = -0.164 to -0.180). Relative to first-episode MDD, recurrent MDD patients had lower thickness and surface area in the CA1 of the hippocampus and the basolateral amygdala (Cohen's d = -0.173 to -0.184). Our results suggest that previously reported MDD-associated volumetric differences may be localized to specific subfields of these structures that have been shown to be sensitive to the effects of stress, with important implications for mapping treatments to patients based on specific neural targets and key clinical features.Tiffany C. Ho ... Bernhard Baune ... et al

    Evaluation of machine learning models in psychiatry

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