Further, a shRNA mediated downregulation of p35-expression in hippocampal neurons correlated with a decrease in gephyrin phosphorylation and in a reduced density of synaptic γ2-GABAA-receptor clusters. These findings, together with the detection of gephyrin colocalization with CDK5 and p35 by immunostaining and proximity ligation experiments in vivo and in vitro, are supporting our hypothesis that Aβ has a profound impact on inhibitory network properties, likely mediated at least in part by p35/CDK5 signaling. This further underscores the impact of altered inhibitory synaptic transmission in AD.BACKGROUND Subclinical cardiac dysfunction is associated with decreased cerebral blood flow, placing the aging brain at risk for Alzheimer's disease (AD) pathology and neurodegeneration. OBJECTIVE This study investigates the association between subclinical cardiac dysfunction, measured by left ventricular ejection fraction (LVEF), and cerebrospinal fluid (CSF) biomarkers of AD and neurodegeneration. METHODS Vanderbilt Memory & Aging Project participants free of dementia, stroke, and heart failure (n = 152, 72±6 years, 68% male) underwent echocardiogram to quantify LVEF and lumbar puncture to measure CSF levels of amyloid-β42 (Aβ42), phosphorylated tau (p-tau), and total tau (t-tau). Linear regressions related LVEF to CSF biomarkers, adjusting for age, sex, race/ethnicity, education, Framingham Stroke Risk Profile, cognitive diagnosis, and apolipoprotein E ɛ4 status. Secondary models tested an LVEF x cognitive diagnosis interaction and then stratified by diagnosis (normal cognitive (NC), mild cognitive impairment (MCI)). RESULTS Higher LVEF related to decreased CSF Aβ42 levels (β= -6.50, p = 0.04) reflecting greater cerebral amyloid accumulation, but this counterintuitive result was attenuated after excluding participants with cardiovascular disease and atrial fibrillation (p = 0.07). We observed an interaction between LVEF and cognitive diagnosis on CSF t-tau (p = 0.004) and p-tau levels (p = 0.002), whereas lower LVEF was associated with increased CSF t-tau (β= -9.74, p = 0.01) and p-tau in the NC (β= -1.41, p = 0.003) but not MCI participants (p-values>0.13). CONCLUSIONS Among cognitively normal older adults, subclinically lower LVEF relates to greater molecular evidence of tau phosphorylation and neurodegeneration. Modest age-related changes in cardiovascular function may have implications for pathophysiological changes in the brain later in life.Recent studies have revealed the possible role of choroid plexus (ChP) in Alzheimer's disease (AD). T1-weighted MRI is the modality of choice for the segmentation of ChP in humans. Manual segmentation is considered the gold-standard technique, but given its time-consuming nature, large-scale neuroimaging studies of ChP would be impossible. In this study, we introduce a lightweight segmentation algorithm based on the Gaussian Mixture Model (GMM). We compared its performance against manual segmentation as well as automated segmentation by Freesurfer in three separate datasets 1) patients with structural MRIs enhanced with contrast (n = 19), 2) young healthy subjects (n = 20), and 3) patients with AD (n = 20). GMM outperformed Freesurfer and showed high similarity with manual segmentation. To further assess the algorithm's performance in large scale studies, we performed GMM segmentations in young healthy subjects from the Human Connectome Project (n = 1,067), as well as healthy controls, mild cognitive impairment (MCI), and AD patients from the Alzheimer's Disease Neuroimaging Initiative (n = 509). In both datasets, GMM segmented ChP more accurately than Freesurfer. To show the clinical importance of accurate ChP segmentation, total AV1451 (tau) PET binding to ChP was measured in 108 MCI and 32 AD patients. GMM was able to reveal the higher AV1451 binding to ChP in AD compared with MCI. Our results provide evidence for the utility of the GMM in accurately segmenting ChP and show its clinical relevance in AD. Future structural and functional studies of ChP will benefit from GMM's accurate segmentation.BACKGROUND Automated volumetry software (AVS) has recently become widely available to neuroradiologists. MRI volumetry with AVS may support the diagnosis of dementias by identifying regional atrophy. Moreover, automatic classifiers using machine learning techniques have recently emerged as promising approaches to assist diagnosis. However, the performance of both AVS and automatic classifiers has been evaluated mostly in the artificial setting of research datasets. OBJECTIVE Our aim was to evaluate the performance of two AVS and an automatic classifier in the clinical routine condition of a memory clinic. METHODS We studied 239 patients with cognitive troubles from a single memory center cohort. Using clinical routine T1-weighted MRI, we evaluated the classification performance of 1) univariate volumetry using two AVS (volBrain and Neuroreader™); 2) Support Vector Machine (SVM) automatic classifier, using either the AVS volumes (SVM-AVS), or whole gray matter (SVM-WGM); 3) reading by two neuroradiologists. The performance measure was the balanced diagnostic accuracy. The reference standard was consensus diagnosis by three neurologists using clinical, biological (cerebrospinal fluid) and imaging data and following international criteria.  https://www.selleckchem.com/products/MLN8237.html  RESULTS Univariate AVS volumetry provided only moderate accuracies (46% to 71% with hippocampal volume). The accuracy improved when using SVM-AVS classifier (52% to 85%), becoming close to that of SVM-WGM (52 to 90%). Visual classification by neuroradiologists ranged between SVM-AVS and SVM-WGM. CONCLUSION In the routine practice of a memory clinic, the use of volumetric measures provided by AVS yields only moderate accuracy. Automatic classifiers can improve accuracy and could be a useful tool to assist diagnosis.BACKGROUND The curl-up exercise is widely used in clinical practice for strengthening abdominal muscles, but has been applied without a systematic method. OBJECTIVE The purpose of this study was to determine the most effective method considering the angle and muscle contraction direction during the curl-up exercise. METHODS Fourteen healthy males performed the curl-up exercise according to contraction direction (concentric and eccentric) and angle (30∘, 60∘, and 90∘). The muscle activity of the rectus abdominis (RA), external oblique (EO), internal oblique (IO), and iliopsoas (IP) was measured using electromyography (EMG), and the muscle thickness of transversus abdominis (TrA) was measured using ultrasonography. RESULTS The activities of the abdominal muscles (RA, EO, and IO) decreased with increasing angles (30∘, 60∘, and 90∘) (p less then 0.05). There was no significant difference between eccentric and concentric contractions. The thickness ratio of TrA was the largest at an eccentric curl-up at 30∘, and the smallest at a concentric curl-up at 30∘ (p less then 0.