Oophorectomy Reduces Estradiol Levels and Long-Term Spontaneous Neurovascular Recovery in a Female Rat Model of Focal Ischemic Stroke

Although epidemiological evidence suggests significant sex and gender-based differences in stroke risk and recovery, females have been widely under-represented in preclinical stroke research. The neurovascular sequelae of brain ischemia in females, in particular, are largely uncertain. We set out to address this gap by a multimodal in vivo study of neurovascular recovery from endothelin-1 model of cortical focal-stroke in sham vs. ovariectomized female rats. Three weeks post ischemic insult, sham operated females recapitulated the phenotype previously reported in male rats in this model, of normalized resting perfusion but sustained peri-lesional cerebrovascular hyperreactivity. In contrast, ovariectomized (Ovx) females showed reduced peri-lesional resting blood flow, and elevated cerebrovascular responsivity to hypercapnia in the peri-lesional and contra-lateral cortices. Electrophysiological recordings showed an attenuation of theta to low-gamma phase-amplitude coupling in the peri-lesional tissue of Ovx animals, despite relative preservation of neuronal power. Further, this chronic stage neuronal network dysfunction was inversely correlated with serum estradiol concentration. Our pioneering data demonstrate dramatic differences in spontaneous recovery in the neurovascular unit between Ovx and Sham females in the chronic stage of stroke, underscoring the importance of considering hormonal-dependent aspects of the ischemic sequelae in the development of novel therapeutic approaches and patient recruitment in clinical trials

THE SEXUALITY OF SEX WORKERS: SEXUAL AROUSABILITY AND THE SEXUAL PROFILE OF WOMEN ENGAGED IN PROSTITUTION IN SERBIA

Background: In a view of sex work being a sexual behavioural activity, the main objective of our research was to explore the sexuality of sex workers in Serbia regarding to intensity of their sexual arousability. Subjects and methods: The research was conducted on 30 sex workers and 30 controls of randomly selected social and demographic characteristics, without any signs of psychiatric morbidity. For the evaluation of the intensity of sexual arousability, SAI (Sexual Arousability Index) questionnaire was used. Results: The analysis of the main total scores of the SAI for the sex workers and control participants showed no statistically significant difference in the overall intensity of arousability (p>0.05). However, item by item analysis of the questionnaire showed qualitative difference in sexuality between sex workers and controls, related to certain aspects of sexuality. Conclusions: These findings allow the space for further research in the way of identifying origins of qualitative issues in the sexual profile of sex workers, in correlation to women who are not sex workers, i.e. whether they had been result of potential biological, specific psychodynamic factors, or have been formed as a result of the direct influence of the sex work

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

Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states

Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer’s disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, ‘shape connections’ between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus

Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer’s Disease using structural MR and FDG-PET images

Alzheimer’s Disease (AD) is a progressive neurodegenerative disease where biomarkers for disease based on pathophysiology may be able to provide objective measures for disease diagnosis and staging. Neuroimaging scans acquired from MRI and metabolism images obtained by FDG-PET provide in-vivo measurements of structure and function (glucose metabolism) in a living brain. It is hypothesized that combining multiple different image modalities providing complementary information could help improve early diagnosis of AD. In this paper, we propose a novel deep-learning-based framework to discriminate individuals with AD utilizing a multimodal and multiscale deep neural network. Our method delivers 82.4% accuracy in identifying the individuals with mild cognitive impairment (MCI) who will convert to AD at 3 years prior to conversion (86.4% combined accuracy for conversion within 1–3 years), a 94.23% sensitivity in classifying individuals with clinical diagnosis of probable AD, and a 86.3% specificity in classifying non-demented controls improving upon results in published literature

The impact of PICALM genetic variations on reserve capacity of posterior cingulate in AD continuum

Phosphatidylinositolbinding clathrin assembly protein (PICALM) gene is one novel genetic player associated with late-onset Alzheimer’s disease (LOAD), based on recent genome wide association studies (GWAS). However, how it affects AD occurrence is still unknown. Brain reserve hypothesis highlights the tolerant capacities of brain as a passive means to fight against neurodegenerations. Here, we took the baseline volume and/or thickness of LOAD-associated brain regions as proxies of brain reserve capacities and investigated whether PICALM genetic variations can influence the baseline reserve capacities and the longitudinal atrophy rate of these specific regions using data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. In mixed population, we found that brain region significantly affected by PICALM genetic variations was majorly restricted to posterior cingulate. In sub-population analysis, we found that one PICALM variation (C allele of rs642949) was associated with larger baseline thickness of posterior cingulate in health. We found seven variations in health and two variations (rs543293 and rs592297) in individuals with mild cognitive impairment were associated with slower atrophy rate of posterior cingulate. Our study provided preliminary evidences supporting that PICALM variations render protections by facilitating reserve capacities of posterior cingulate in non-demented elderly

Early role of vascular dysregulation on late-onset Alzheimer's disease based on multifactorial data-driven analysis

Multifactorial mechanisms underlying late-onset Alzheimer's disease (LOAD) are poorly characterized from an integrative perspective. Here spatiotemporal alterations in brain amyloid-β deposition, metabolism, vascular, functional activity at rest, structural properties, cognitive integrity and peripheral proteins levels are characterized in relation to LOAD progression. We analyse over 7,700 brain images and tens of plasma and cerebrospinal fluid biomarkers from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Through a multifactorial data-driven analysis, we obtain dynamic LOAD–abnormality indices for all biomarkers, and a tentative temporal ordering of disease progression. Imaging results suggest that intra-brain vascular dysregulation is an early pathological event during disease development. Cognitive decline is noticeable from initial LOAD stages, suggesting early memory deficit associated with the primary disease factors. High abnormality levels are also observed for specific proteins associated with the vascular system's integrity. Although still subjected to the sensitivity of the algorithms and biomarkers employed, our results might contribute to the development of preventive therapeutic interventions