Neuroscience
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This study explored surface brain morphometry in type 1 diabetes including focus on painful diabetic peripheral neuropathy (DPN). Brain MRI was obtained from 56 individuals with diabetes (18 without DPN, 19 with painless DPN, 19 with painful DPN) and 20 healthy controls. Cortical thickness, sulcus depth, and gyrification were analysed globally and regionally in each group and in the combined diabetes group. ⋯ Cortical thinning manifested across the brain cortex in diabetes, especially for painful DPN. Altered postcentral gyrus morphometry may be associated with neuropathic pain. Assessing cortical morphometry may be critical for comprehending central neuropathy and the manifestation of painful DPN in diabetes.
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The diagnosis and analysis of major depressive disorder (MDD) faces some intractable challenges such as dataset limitations and clinical variability. Resting-state functional magnetic resonance imaging (Rs-fMRI) can reflect the fluctuation data of brain activity in a resting state, which can find the interrelationships, functional connections, and network characteristics among brain regions of the patients. In this paper, a brain functional connectivity matrix is constructed using Pearson correlation based on the characteristics of multi-site Rs-fMRI data and brain atlas, and an adaptive propagation operator graph convolutional network (APO-GCN) model is designed. ⋯ The experimental results on Rs-fMRI data from 1601 participants (830 MDD and 771 HC) and 16 sites of REST-meta-MDD project show that the APO-GCN achieved a classification accuracy of 91.8%, outperforming those of the state-of-the-art classifier methods. The classification process is driven by multiple significant brain regions, and our method further reveals functional connectivity abnormalities between these brain regions, which are important biomarkers of classification. It is worth noting that the brain regions identified by the classifier and the networks involved are consistent with existing research results, which suggest that the pathogenesis of depression may be related to dysfunction of multiple brain networks.
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The aim of this study was to assess the potential causal relationship between lifestyle factors and intracranial aneurysms (IAs) using a two-sample Mendelian randomization (MR) approach. The study used a pooled dataset from a genome-wide association study that covered information on 24 lifestyle factors, intracranial aneurysm cases, subarachnoid hemorrhage, and unruptured aneurysms. Five MR methods were applied for analysis by selecting single nucleotide polymorphisms as instrumental variables, with the inverse variance weighting method as the main method. ⋯ Sensitivity analyses and inverse MR verified the robustness of these results. After adjusting for exposure factors, multivariate MR confirmed daily smoking and smoking initiation as risk factors for intracranial aneurysms, unruptured aneurysms, and subarachnoid hemorrhage, whereas red wine intake was a genetically protective factor against intracranial aneurysms and subarachnoid hemorrhage. This MR analysis revealed a genetic causal link between specific lifestyle factors and intracranial aneurysms, emphasizing the need for further studies to confirm these findings and explore their mechanisms.
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Focal Cortical Dysplasia (FCD) & Mesial Temporal Lobe Epilepsy-Hippocampal Sclerosis (MTLE-HS) are two common pathologies of drug-resistant focal epilepsy (DRE). Inappropriate localization of the epileptogenic zones (EZs) in FCD is a significant contributing factor to the unsatisfactory surgical results observed in FCD cases. Currently, no molecular or cellular indicators are available which can aid in identifying the epileptogenic zones (EZs) in FCD. ⋯ These findings suggest that employing distinct lipid mass spectra could be an effective method for identifying the EZs in FCD. The unique lipid mass spectra of cortical tissues from patients with FCD can be utilized for real-time surgical guidance. Additionally, the plasma triglyceride (TAG) level has the potential to act as a biomarker once validated on a larger cohort.
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Alzheimer's disease (AD) is a growing health problem worldwide, particularly in the developed world due to an ageing population. Glutamate excitotoxicity plays a major role in the pathophysiology of AD, and glutamate re-uptake is controlled by excitatory amino acid transporters (EAATs). The EAAT2 isoform is the predominant transporter involved in glutamate reuptake, therefore EAAT1 has not been the focus of AD research. ⋯ Labeling of EAAT1 appeared astrocytic in nature, showing close association with astrocytic processes in AD cases. We also report that a higher EAAT1 density was positively correlated with the age of AD cases, but this relationship was not observed in control cases. Overall, our results indicate an upregulation of EAAT1 across several hippocampal subregions and layers in AD cases, indicating a potential physiological role for this transporter that needs further investigation.