Quantificação de parâmetros respiratórios em pacientes com epilepsia do lobo temporal

Dysfunction affecting cardiac or pulmonary systems has been postulated as a major factor in sudden death in epilepsy (SUDEP). Whilst the majority of studies of cardiorespiratory function have focused on changes during seizures, here we investigate whether epilepsy influences basal respiratory parameters in patients with temporal lobe epilepsy (TLE) during the interictal period. Spirometry was performed in 10 females and 10 males. Measurements of Vital Capacity (VC), Forced Vital Capacity (FVC), Forced Expiratory Volume in the first second (FEV1) and ratios of FEV1 to FVC (FEV1/FVC) were obtained, and these values were analyzed as percentages of predicted values. None of the patients had chronic obstructive pulmonary disease and no significant alterations in respiratory function tests were found among these patients. No association between seizure frequency, antiepileptic drugs and SUDEP could be found in this study. Although the study did not identify any specific respiratory abnormality in TLE patients during the interictal period, re-evaluation of clinical data on pulmonary disorders in people with epilepsy should be better investigated.Alterações cardíacas e pulmonares têm sido propostas como principais fatores de risco no fenômeno da morte súbita em epilepsia (SUDEP). Enquanto a maioria dos estudos tem verificado as alterações da função cardiorrespiratória durante as crises epilépticas, nosso estudo avaliou a função pulmonar de indivíduos com epilepsia do lobo temporal (ELT) no período interictal. Vinte pacientes com ELT (10 homens e 10 mulheres) participaram de nosso estudo. Nos testes de função pulmonar foram mensurados os seguintes parâmetros: Capacidade Vital Forçada (CVF), Capacidade Vital Lenta (CVL), Volume Expiratório Forçado no primeiro segundo (VEF1) e o Índice VEF1/CVF. Os resultados foram comparados aos valores de normalidade preditos na literatura. Nenhum dos pacientes apresentou doença pulmonar obstrutiva ou restritiva e alterações significativas nos testes de função pulmonar. Não foram encontradas associações entre a freqüência de crises, drogas antiepilépticas e SUDEP. Embora nosso estudo não tenha identificado qualquer anormalidade respiratória específica em indivíduos com ELT durante o período interictal, os dados clínicos sobre transtornos pulmonares em indivíduos com epilepsia devem ser melhor avaliados.Universidade Federal de São Paulo (UNIFESP) Escola Paulista de Medicina Laboratório de Neurologia ExperimentalUniversidade de Mogi das Cruzes Núcleo de Pesquisas Tecnológicas Laboratório de NeurociênciasUniversidade Federal de São Paulo (UNIFESP) Escola Paulista de Medicina Departamento de FisiologiaUniversity College of London Institute of Neurology Department of Clinical and Experimental EpilepsyUNIFESP, EPM, Laboratório de Neurologia ExperimentalUNIFESP, EPM, Depto. de FisiologiaSciEL

Co-expression network of neural-differentiation genes shows specific pattern in schizophrenia

Background: Schizophrenia is a neurodevelopmental disorder with genetic and environmental factors contributing to its pathogenesis, although the mechanism is unknown due to the difficulties in accessing diseased tissue during human neurodevelopment. The aim of this study was to find neuronal differentiation genes disrupted in schizophrenia and to evaluate those genes in post-mortem brain tissues from schizophrenia cases and controls. Methods: We analyzed differentially expressed genes (DEG), copy number variation (CNV) and differential methylation in human induced pluripotent stem cells (hiPSC) derived from fibroblasts from one control and one schizophrenia patient and further differentiated into neuron (NPC). Expression of the DEG were analyzed with microarrays of post-mortem brain tissue (frontal cortex) cohort of 29 schizophrenia cases and 30 controls. A Weighted Gene Co-expression Network Analysis (WGCNA) using the DEG was used to detect clusters of co-expressed genes that werenon-conserved between adult cases and controls brain samples. Results: We identified methylation alterations potentially involved with neuronal differentiation in schizophrenia, which displayed an over-representation of genes related to chromatin remodeling complex (adjP = 0.04). We found 228 DEG associated with neuronal differentiation. These genes were involved with metabolic processes, signal transduction, nervous system development, regulation of neurogenesis and neuronal differentiation. Between adult brain samples from cases and controls there were 233 DEG, with only four genes overlapping with the 228 DEG, probably because we compared single cell to tissue bulks and more importantly, the cells were at different stages of development. The comparison of the co-expressed network of the 228 genes in adult brain samples between cases and controls revealed a less conserved module enriched for genes associated with oxidative stress and negative regulation of cell differentiation. Conclusion: This study supports the relevance of using cellular approaches to dissect molecular aspects of neurogenesis with impact in the schizophrenic brain. We showed that, although generated by different approaches, both sets of DEG associated to schizophrenia were involved with neocortical development. The results add to the hypothesis that critical metabolic changes may be occurring during early neurodevelopment influencing faulty development of the brain and potentially contributing to further vulnerability to the illness.We thank the patients, doctors and nurses involved with sample collection and the Stanley Medical Research Institute. This research was supported by either Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq #17/2008) and Fundação Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro (FAPERJ). MM (CNPq 304429/2014-7), ACT (FAPESP 2014/00041-1), LL (CAPES 10682/13-9) HV (CAPES) and BP (PPSUS 137270) were supported by their fellowshipsinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio