Cowansnider1094

It was shown that microglial exosomes could transport to and be uptake by neurons, which may either be beneficial or instead, detrimental to CNS diseases. The focus of this review is to summarize the involvement of microglial exosomes in critical pathologies associated with neurodegenerative disease and how they contribute to these disorders, including PD, AD, and ALS. We also review the application of microglia exosomes as potential biomarkers in monitoring disease progression, as well as focusing on their roles as drug delivery vehicles in treating neurodegenerative disorders.Background Identifying patients with intractable epilepsy who would benefit from therapeutic chronic vagal nerve stimulation (VNS) preoperatively remains a major clinical challenge. We have developed a statistical model for predicting VNS efficacy using only routine preimplantation electroencephalogram (EEG) recorded with the TruScan EEG device (Brazdil et al., 2019). It remains to be seen, however, if this model can be applied in different clinical settings. Objective To validate our model using EEG data acquired with a different recording system. Methods We identified a validation cohort of eight patients implanted with VNS, whose preimplantation EEG was recorded on the BrainScope device and who underwent the EEG recording according to the protocol. The classifier developed in our earlier work, named Pre-X-Stim, was then employed to classify these patients as predicted responders or non-responders based on the dynamics in EEG power spectra. Predicted and real-world outcomes were compared to establish the applicability of this classifier. In total, two validation experiments were performed using two different validation approaches (single classifier or classifier voting). Results The classifier achieved 75% accuracy, 67% sensitivity, and 100% specificity. Only two patients, both real-life responders, were classified incorrectly in both validation experiments. Conclusion We have validated the Pre-X-Stim model on EEGs from a different recording system, which indicates its application under different technical conditions. Our approach, based on preoperative EEG, is easily applied and financially undemanding and presents great potential for real-world clinical use.In the regulation of emotional and social behaviors, both oxytocin (OT) and vasopressin (AVP) are sex specific. Although significant sex differences have been reported in the context of behavioral and hormonal responses to social stress, such differences in response to chronic social defeat stress (CSDS) and the underlying neural mechanisms remain largely unknown. By investigating monogamous mandarin voles (Microtus mandarinus), CSDS was found to decrease the percentages of time spent in the central area of the open field, in the open arms of the elevated plus maze, as well as in the light area of the light and dark boxes in both male and female voles. CSDS also increased the observed level of social withdrawal in both sex groups. However, CSDS exposure increased the percentages of immobile time in both the tail suspension test and the forced swim test and reduced the locomotor activity in the open field (in females only). Along with these behavioral changes, the oxytocin receptor (OTR) levels in the nucleus accumbens (NAc) were significantly lower in CSDS-exposed voles of both sexes; however, in males, the levels of OTR in the paraventricular nucleus (PVN) were reduced. CSDS-exposed males showed lower levels of V1aR in the NAc than CSDS-exposed females. Furthermore, induced by a single social defeat event, CSDS reduced c-Fos and OT double labeling in the PVN of females but increased c-Fos and AVP double-labeled neurons in the PVN of males exposed to a single social defeat event. https://www.selleckchem.com/products/ZLN005.html Collectively, the present study indicates that OT and AVP systems may play important regulatory roles in the sex differences of behavioral performances in response to CSDS. These findings suggest mandarin voles as a useful animal model for studying sex-specific behavioral performance and the underlying neurobiological mechanisms of stress-related mental disorders in preclinical studies.Multiple sclerosis (MS) is an autoimmune disorder influenced by genetic and environmental factors. Many studies have provided insights into genetic factors' contribution to MS via large-scale genome-wide association study (GWAS) datasets. However, genetic variants identified to date do not adequately explain genetic risks for MS. This study hypothesized that novel MS risk genes could be identified by analyzing the MS-GWAS dataset using gene-based tests. We analyzed a GWAS dataset consisting of 9,772 MS cases and 17,376 healthy controls of European descent. We performed gene-based tests of 464,357 autosomal single nucleotide polymorphisms (SNPs) using two methods (PLINK and VEGAS2) and identified 28 shared genes satisfied p-value less then 4.56 × 10-6. In further gene expression analysis, ten of the 28 genes were significantly differentially expressed in the MS case-control gene expression omnibus (GEO) database. GALC and HLA-DOB showed the most prominent differences in gene expression (two- and three-fold, respectively) between MS patients and healthy controls. In conclusion, our results reveal more information about MS hereditary characteristics and provide a basis for further studies.Wearable devices are a fast-growing technology with impact on personal healthcare for both society and economy. Due to the widespread of sensors in pervasive and distributed networks, power consumption, processing speed, and system adaptation are vital in future smart wearable devices. The visioning and forecasting of how to bring computation to the edge in smart sensors have already begun, with an aspiration to provide adaptive extreme edge computing. Here, we provide a holistic view of hardware and theoretical solutions toward smart wearable devices that can provide guidance to research in this pervasive computing era. We propose various solutions for biologically plausible models for continual learning in neuromorphic computing technologies for wearable sensors. To envision this concept, we provide a systematic outline in which prospective low power and low latency scenarios of wearable sensors in neuromorphic platforms are expected. We successively describe vital potential landscapes of neuromorphic processors exploiting complementary metal-oxide semiconductors (CMOS) and emerging memory technologies (e.g., memristive devices). Furthermore, we evaluate the requirements for edge computing within wearable devices in terms of footprint, power consumption, latency, and data size. We additionally investigate the challenges beyond neuromorphic computing hardware, algorithms and devices that could impede enhancement of adaptive edge computing in smart wearable devices.Pain and depression are leading causes of disability and of profound social and economic burden. Their impact is aggravated by their chronicity and comorbidity and the insufficient efficacy of current treatments. Morphological and functional metabolism studies link chronic pain and depressive disorders to dysfunctional neuroplastic changes in fronto-limbic brain regions that control emotional responses to painful injuries and stressful events. Glutamate modulators are emerging new therapies targeting dysfunctional brain areas implicated in the generation and maintenance of chronic pain and depression. Here, we report the effects of two clinically approved glutamate modulators acetyl-L-carnitine (ALCAR) and S, R(±)ketamine (KET). ALCAR is a natural neurotrophic compound currently marketed for the treatment of neuropathies. KET is the prototypical non-competitive antagonist at N-methyl-D-aspartate glutamate receptors and a clinically approved anesthetic. Although they differ in pharmacological profiles, ALCAR ay, a single, low dose of KET (0.5 mg/kg) at induction of anesthesia determined a very fast (hours) amelioration of post-operative depression and pain and an opioid-sparing effect. These findings indicate that ALCAR and KET, two non-selective glutamate modulators, still offer viable therapeutic options in comorbid pain and depression.Complex natural tasks likely recruit many different functional brain networks, but it is difficult to predict how such tasks will be represented across cortical areas and networks. Previous electrophysiology studies suggest that task variables are represented in a low-dimensional subspace within the activity space of neural populations. Here we develop a voxel-based state space modeling method for recovering task-related state spaces from human fMRI data. link2 We apply this method to data acquired in a controlled visual attention task and a video game task. We find that each task induces distinct brain states that can be embedded in a low-dimensional state space that reflects task parameters, and that attention increases state separation in the task-related subspace. Our results demonstrate that the state space framework offers a powerful approach for modeling human brain activity elicited by complex natural tasks.

An emerging body of research has developed around tobacco retailer density and its contribution to smoking behavior. This cross-sectional study aimed to determine the association between tobacco retailer density and smoking behavior in a rural Australian jurisdiction without a tobacco retailer licensing system in place.

A local government database (updated 2018) of listed tobacco retailers (n=93) was accessed and potential unlisted tobacco retailers (n=230) were added using online searches. All retailers (n=323) were visited in 2019 and GPS coordinates of retailers that sold tobacco (n=125) were assigned to suburbs in ArcMap. A community survey conducted in the Local Government Area provided smoking and sociodemographic data amongst adult respondents (n=8981). Associations between tobacco retailer density (calculated as the number of retailers per km

based on respondents' suburb of residence) and daily, occasional and experimental smoking were assessed using multilevel logistic regression analysis. Sepaive association between tobacco retailer density and the likelihood of occasional smoking in a rural Australian jurisdiction without a tobacco retailer licensing system in place. link3 The findings strengthen calls for the introduction of a comprehensive, positive tobacco retailer licensing system to provide a framework for improving compliance with legislation and to reduce the overall availability of tobacco products in the community.

Primary care nurses are well-suited to provide care management for common mental disorders, but their practices depend on context. Various strategies can be considered to improve the adoption of nursing care manager activities, but data from implementation studies rarely address strategy formulation.

To analyze the influence of contextual factors on strategy formulation to improve the adoption of care manager activities by primary care nurses.

A qualitative multiple case study in three primary care clinics was carried out. Data were collected through individual interviews (n = 32) and observations (n = 7), working group meetings, and relevant documents. Thematic analysis was conducted.

Contextual factors influenced strategy formulation through organizational readiness for change, which resulted from tension for change and perceived organizational ability to implement change. Tension for change was generated through the perceived gap between patient needs and service availability, perceived compatibility with the nurses work environment, and their assessment of their capacity to perform care manager activities or acquire the necessary skills.