Landscape-scale drivers of glacial ecosystem change in the montane forests of the eastern Andean flank, Ecuador

Understanding the impact of landscape-scale disturbance events during the last glacial period is vital in accu- rately reconstructing the ecosystem dynamics of montane environments. Here, a sedimentary succession from the tropical montane cloud forest of the eastern Andean flank of Ecuador provides evidence of the role of non- climate drivers of vegetation change (volcanic events, fire regime and herbivory) during the late-Pleistocene. Multiproxy analysis (pollen, non-pollen palynomorphs, charcoal, geochemistry and carbon content) of the se- diments, radiocarbon dated to ca. 45–42 ka, provide a snap shot of the depositional environment, vegetation community and non-climate drivers of ecosystem dynamics. The geomorphology of the Vinillos study area, along with the organic‐carbon content, and aquatic remains suggest deposition took place near a valley floor in a swamp or shallow water environment. The pollen assemblage initially composed primarily of herbaceous types (Poaceae-Asteraceae-Solanaceae) is replaced by assemblages characterised by Andean forest taxa, (first Melastomataceae-Weinmannia-Ilex, and later, Alnus-Hedyosmum-Myrica). The pollen assemblages have no modern analogues in the tropical montane cloud forest of Ecuador. High micro-charcoal and rare macro-charcoal abundances co-occur with volcanic tephra deposits suggesting transportation from extra-local regions and that volcanic eruptions were an important source of ignition in the wider glacial landscape. The presence of the coprophilous fungi Sporormiella reveals the occurrence of herbivores in the glacial montane forest landscape. Pollen analysis indicates a stable regional vegetation community, with changes in vegetation population co- varying with large volcanic tephra deposits suggesting that the structure of glacial vegetation at Vinillos was driven by volcanic activity

The genetic landscape and clinical spectrum of nephronophthisis and related ciliopathies

Nephronophthisis (NPH) is an autosomal-recessive ciliopathy representing one of the most frequent causes of kidney failure in childhood characterized by a broad clinical and genetic heterogeneity. Applied to one of the worldwide largest cohorts of patients with NPH, genetic analysis encompassing targeted and whole exome sequencing identified disease-causing variants in 600 patients from 496 families with a detection rate of 71%. Of 788 pathogenic variants, 40 known ciliopathy genes were identified. However, the majority of patients (53%) bore biallelic pathogenic variants in NPHP1. NPH-causing gene alterations affected all ciliary modules defined by structural and/or functional subdomains. Seventy six percent of these patients had progressed to kidney failure, of which 18% had an infantile form (under five years) and harbored variants affecting the Inversin compartment or intraflagellar transport complex A. Forty eight percent of patients showed a juvenile (5-15 years) and 34% a late-onset disease (over 15 years), the latter mostly carrying variants belonging to the Transition Zone module. Furthermore, while more than 85% of patients with an infantile form presented with extra-kidney manifestations, it only concerned half of juvenile and late onset cases. Eye involvement represented a predominant feature, followed by cerebellar hypoplasia and other brain abnormalities, liver and skeletal defects. The phenotypic variability was in a large part associated with mutation types, genes and corresponding ciliary modules with hypomorphic variants in ciliary genes playing a role in early steps of ciliogenesis associated with juvenile-to-late onset NPH forms. Thus, our data confirm a considerable proportion of late-onset NPH suggesting an underdiagnosis in adult chronic kidney disease

Conselhos da comunidade: controle social e interlocução para a saúde prisional

This article aims to analyze the performance of Community Councils in penal institutions in Rio Grande do Sul State, related to prison health. This is an exploratory and descriptive research, with a qualitative approach, using Bardin’s data triangulation strategy and Content Analysis. Eight Community Councils participated in the study. The analysis of the collected data resulted in five thematic categories for discussion: Public Policies; Tuberculosis control; Infrastructure; Actions by Community Councils; Difficulties in the performance of Community Councils. It was identified that the Community Councils are potent devices of social control and dialogue for health in the prison system. In this way the presence of health professionals as effective members of Community Councils could qualify the actions focused at the health of prisoners and the professionals of these institutions.  Este artigo tem por objetivo analisar a atuação dos Conselhos da Comunidade nas instituições penais do Rio Grande do Sul, em questões da saúde prisional. Trata-se de uma pesquisa de caráter exploratório e descritivo, de abordagem qualitativa, utilizando a estratégia de triangulação de dados e Análise de Conteúdo de Bardin. Participaram do estudo 8 Conselhos da Comunidade. A análise dos dados coletados resultou em cinco categorias temáticas para discussão: Políticas Públicas; Controle da tuberculose; Infraestrutura; Ações dos Conselhos da Comunidade; Dificuldades de atuação dos Conselhos da Comunidade. Identificou-se que os Conselhos da Comunidade se configuram como potentes dispositivos de controle social e interlocução para saúde no sistema prisional, contudo a presença de profissionais de saúde como membros efetivos poderiam qualificar as ações voltadas à saúde das Pessoas Privadas de Liberdade e aos profissionais destas instituições.

A Educação Permanente em Saúde e os atores do sistema prisional no cenário pandêmico

Resumo A Educação Permanente em Saúde legitimou a educação na saúde com base na aprendizagem significativa, em vivências no cotidiano de trabalho e na solução de problemas de forma coletiva, além de estar pautada no Quadrilátero Ensino-Gestão-Atenção-Controle Social. A pandemia da Covid-19 exigiu novas formas de fazer saúde e educação, principalmente no sistema prisional, onde a superlotação é um impeditivo ao isolamento social. Este estudo teve como objetivo identificar, por meio de rodas de conversa virtuais, os desafios encontrados no cotidiano de trabalho e discutir propostas de intervenção com os atores do sistema prisional no período pandêmico, na perspectiva da Educação Permanente em Saúde. Foi utilizada abordagem qualitativa de investigação com caráter descritivo, interpretativo e compreensivo de análise do fenômeno social, por meio da análise de conteúdo temático de Minayo. Da análise temática de conteúdo emergiram quatro categorias: desafios da assistência em saúde no sistema prisional no contexto da pandemia da Covid-19; desafios para a gestão da saúde nos estabelecimentos prisionais; interlocução entre instituições de ensino e sistema prisional; e o controle social e a representação familiar. As rodas de conversa virtuais propiciaram discussões aprofundadas e construções coletivas, propondo encaminhamentos pautados no Quadrilátero da Educação Permanente em Saúde

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Using structural MRI to identify bipolar disorders – 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47–67.00, ROC-AUC = 71.49%, 95% CI = 69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa = 0.83, 95% CI = 0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data

Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47–67.00, ROC-AUC = 71.49%, 95% CI = 69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa = 0.83, 95% CI = 0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data

Analyse des gènes EYA1, SIX1 ET SIX5 dans une cohorte de 64 patients atteints d un syndrome branchio-oto-rénal

Le syndrome branchio-oto-rénal (BOR), de transmission autosomique dominante, associe une surdité, des anomalies des arcs branchiaux et une atteinte rénale. Ce syndrome est génétiquement hétérogène et est associé à des mutations homozygotes des gènes EYA1, SIX1, et SIX5. L objectif de cette étude rétrospective multicentrique est d évaluer la fréquence des mutations et délétions du gène EYA1, la fréquence des mutations ponctuelles des gènes SIX1 et SIX5 et d analyser les phénotypes associés à ces mutations. Il nous semble aussi intéressant de préciser la fréquence des mutations chez les BOR atypiques. Nous avons étudié une cohorte de 64 patients atteints d un syndrome BOR, en définissant deux groupes, les syndromes BOR typiques et les BOR atypiques. Nous avons séquencé tous les exons codants d EYA1, SIX1 et SIX5, et pour le gène EYA1, les délétions ont été recherchées par la méthode QMPSF. Chez les 31 familles BOR typiques, nous avons identifié 21 mutations d EYA1 (68%) dont deux délétions, une mutation de SIX1 (3%), mais aucune mutation de SIX5, donc 71% de la population BOR typique porte une mutation sur l un de ces trois gènes. Chez les BOR atypiques, seules deux mutations d EYA1 ont été identifiées. 93% de cette population n a aucune mutation identifiée. Sur le plan clinique, nous avons noté des phénotypes particuliers associés aux mutations d EYA1. Un patient porteur d un variant SIX5 présente un tableau très atypique. Notre étude est la première à préciser la fréquence des mutations dans les BOR atypiques. Elle confirme le faible taux de délétion d EYA1 et de mutations de SIX1 et SIX5, et apporte de nouvelles perspectives dans la stratégie diagnostique du BOR.PARIS6-Bibl.Pitié-Salpêtrie (751132101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Generation of submesoscale frontal eddies in the Agulhas Current

This study addresses the dynamics of the Agulhas inshore front in the submesoscale range upstream of 26°E. Submesoscale frontal eddies are observed in the vicinity of Port Elizabeth (26°E) from satellite images and in observations collected from under‐water gliders. Using a submesoscale‐resolving numerical model (dx ~ 0.75 km) we are able to simulate similar submesoscale eddies. Barotropic instability is confirmed as the generation mechanism by a 1D linear stability analysis and an eddy kinetic energy budget. Kinetic energy is transferred from the mean flow to the eddies through the mean horizontal shear, which is a signature of barotropic instability. When the Agulhas Current is in a non‐meandering state, submesoscale eddy generation is a recurrent process which locally drives the front's variability. Along the front, the spatial variability of barotropic instability is shaped by the background strain. A large strain aligned with the frontal axis intensifies the frontal shear upstream of 28°E while a weakening of the strain allows for barotropic instability to be triggered downstream. Although an intermittent process, the barotropic instability shows a dominant period of variability comparable with the variability of the Agulhas Current and Undercurrent