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Background: Metabolic syndrome (MetS), characterized by elevated blood pressure, high blood glucose, excess abdominal fat, and abnormal cholesterol or triglyceride levels, significantly increases the risk of various non-communicable diseases. This study focuses on understanding the sex-specific association between Apolipoprotein E (APOE) polymorphism and MetS among middle-aged and older adults in rural southern India. Methods: This cross-sectional study utilized data from the Centre for Brain Research-Srinivaspura Aging, Neuro Senescence, and COGnition (CBR-SANSCOG) study. Participants (n = 3741) underwent comprehensive clinical assessments and blood investigations, including APOE genotyping. MetS was defined using the National Cholesterol Education Program - Adult Treatment Panel III (NCEP ATP III) and the Consensus criteria. Statistical analyses, including chi-square tests, ANCOVA, and logistic regression, were conducted to explore the association of APOE genotype with MetS and its components, stratified by sex. Results: Females carrying the APOE E4 allele had 1.31-fold increased odds of MetS (95 % CI: 1.02,1.69, p = 0.035) according to the NCEP ATP III criteria but not when the Consensus criteria were applied. The study also noted sex-specific differences in the association of APOE with various MetS components, including lipid levels and waist circumference. Discussion: Our findings reveal a sex-specific association between the APOE E4 allele and MetS, with only females having an increased risk. This study contributes to the understanding of the genetic underpinnings of MetS and highlights the importance of considering sex-specific differences in MetS research and its prevention strategies. This study underscores the complexity of MetS etiology and emphasizes the need for further research to elucidate the role of genetic, environmental, and lifestyle factors in its progression, particularly in sex-specific contexts.
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Post-stroke recrudescence (PSR) is a clinical entity characterized by the acute transient recurrence of previously recovered focal stroke deficits. Various names have been used to describe PSR, which further complicates its diagnosis. Increased awareness of this condition is crucial for preventing inappropriate management and unnecessary testing. Mechanisms proposed for PSR include altered drug response in diseased brain areas and immune activation due to a compromised blood-brain barrier (BBB). Patients with PSR have a distinct vascular risk profile and fewer cardiovascular complications than those with transient ischemic attacks (TIAs). Accurate differentiation of PSR from other conditions that mimic stroke is essential for its appropriate management. Misdiagnosis may lead to unnecessary procedures and prolonged hospitalization. This article presents the case of a 56-year-old female with multiple episodes of PSR that were initially misdiagnosed in the emergency department. The patient had a history of hypertension and ischemic stroke, and her episodes of PSR were often triggered by elevated blood pressure. Future studies should focus on developing validated prediction scores to guide recurrent stroke workup. Enhancing awareness and understanding of PSR can optimize resource allocation and improve patient outcomes.
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Background: The study of brain networks, particularly the spread of disease, is made easier thanks to the network theory. The aberrant accumulation of beta-amyloid plaques and tau protein tangles in Alzheimer's disease causes disruption in brain networks. The evaluation scores, such as the mini-mental state examination (MMSE) and neuropsychiatric inventory questionnaire, which provide a clinical diagnosis, are affected by this build-up. Purpose: The percolation of beta-amyloid/tau tangles and their impact on cognitive tests are still unspecified. Methods: Percolation centrality could be used to investigate beta-amyloid migration as a characteristic of positron emission tomography (PET)-image-based networks. The PET-image-based network was built utilizing a public database containing 551 scans published by the Alzheimer's Disease Neuroimaging Initiative. Each image in the Julich atlas has 121 zones of interest, which are network nodes. Furthermore, the influential nodes for each scan are computed using the collective influence algorithm. Results: For five nodal metrics, analysis of variance (ANOVA; P < .05) reveals the region of interest (ROI) in gray matter (GM) Broca's area for Pittsburgh compound B (PiB) tracer type. The GM hippocampus area is significant for three nodal metrics in the case of florbetapir (AV45). Pairwise variance analysis of the clinical groups reveals five to twelve statistically significant ROIs for AV45 and PiB, respectively, that can distinguish between pairs of clinical situations. Based on multivariate linear regression, the MMSE is a trustworthy evaluation tool. Conclusion: Percolation values suggest that around 50 of the memory, visual-spatial skills, and language ROIs are critical to the percolation of beta-amyloids within the brain network when compared to the other extensively used nodal metrics. The anatomical areas rank higher with the advancement of the disease, according to the collective influence algorithm.
