Protection of hippocampal CA1 neurons against ischemia/Reperfusion injury by exercise preconditioning via modulation of Bax/Bcl-2 ratio and prevention of Caspase-3 Activation

Introduction: Ischemia leads to loss of neurons by apoptosis in specific brain regions, especially in the hippocampus. The purpose of this study was investigating the effects of exercise preconditioning on expression of Bax, Bcl-2, and caspase-3 proteins in hippocampal CA1 neurons after induction of cerebral ischemia. Methods: Male rats weighing 260-300 g were randomly allocated into three groups (sham, exercise, and ischemia). The rats in exercise group were trained to run on atreadmill 5 days a week for 4 weeks. Ischemia was induced by the occlusion of both common carotid arteries (CCAs) for 20 min. Levels of expression of Bax, Bcl-2, and caspase-3 proteins in CA1 area of hippocampus were determined by immunohistochemical staining . Results: The number of active caspase-3-positive neurons in CA1 area were significantly increased in ischemia group, compared to sham-operated group (P<0.001), and exercise preconditioning significantly reduced the ischemia/reperfusion-induced caspase-3 activation, compared to the ischemia group (P<0.05). Also, results indicated a significant increase in Bax/Bcl-2 ratio in ischemia group, compared to sham-operated group (P<0.001). Discussion: This study indicated that exercise has a neuroprotective effects against cerebral ischemia when used as preconditioning stimuli

Dual EZH2 and EHMT2 histone methyltransferase inhibition increases biological efficacy in breast cancer cells

Background: Many cancers show aberrant silencing of gene expression and overexpression of histone methyltransferases. The histone methyltransferases (HKMT) EZH2 and EHMT2 maintain the repressive chromatin histone methylation marks H3K27me and H3K9me, respectively, which are associated with transcriptional silencing. Although selective HKMT inhibitors reduce levels of individual repressive marks, removal of H3K27me3 by specific EZH2 inhibitors, for instance, may not be sufficient for inducing the expression of genes with multiple repressive marks. Results: We report that gene expression and inhibition of triple negative breast cancer cell growth (MDA-MB-231) are markedly increased when targeting both EZH2 and EHMT2, either by siRNA knockdown or pharmacological inhibition, rather than either enzyme independently. Indeed, expression of certain genes is only induced upon dual inhibition. We sought to identify compounds which showed evidence of dual EZH2 and EHMT2 inhibition. Using a cell-based assay, based on the substrate competitive EHMT2 inhibitor BIX01294, we have identified proof-of-concept compounds that induce re-expression of a subset of genes consistent with dual HKMT inhibition. Chromatin immunoprecipitation verified a decrease in silencing marks and an increase in permissive marks at the promoter and transcription start site of re-expressed genes, while Western analysis showed reduction in global levels of H3K27me3 and H3K9me3. The compounds inhibit growth in a panel of breast cancer and lymphoma cell lines with low to sub-micromolar IC50s. Biochemically, the compounds are substrate competitive inhibitors against both EZH2 and EHMT1/2. Conclusions: We have demonstrated that dual inhibition of EZH2 and EHMT2 is more effective at eliciting biological responses of gene transcription and cancer cell growth inhibition compared to inhibition of single HKMTs, and we report the first dual EZH2-EHMT1/2 substrate competitive inhibitors that are functional in cells

Barriers to Family Caregivers’ Coping With Patients With Severe Mental Illness in Iran

The broad spectrum of problems caused by caring for a patient with mental illness imposes a high burden on family caregivers. This can affect how they cope with their mentally ill family members. Identifying caregivers’ experiences of barriers to coping is necessary to develop a program to help them overcome these challenges. This qualitative content analysis study explored barriers impeding family caregivers’ ability to cope with their relatives diagnosed with severe mental illness (defined here as schizophrenia, schizoaffective disorders, and bipolar affective disorders). Sixteen family caregivers were recruited using purposive sampling and interviewed using a semi-structured in-depth interview method. Data were analyzed by a conventional content analytic approach. Findings consisted of four major categories: the patient’s isolation from everyday life, incomplete recovery, lack of support by the mental health care system, and stigmatization. Findings highlight the necessity of providing support for caregivers by the mental health care delivery service system.The study was supported by Grant TBZMED·REC.5825 from the deputy of research in Tabriz University of Medical Sciences

The Effects of Cognitive Therapy versus ‘No Intervention’ for Major Depressive Disorder

BACKGROUND: Major depressive disorder afflicts an estimated 17% of individuals during their lifetimes at tremendous suffering and costs. Cognitive therapy may be an effective treatment option for major depressive disorder, but the effects have only had limited assessment in systematic reviews. METHODS/PRINCIPAL FINDINGS: We used The Cochrane systematic review methodology with meta-analyses and trial sequential analyses of randomized trials comparing the effects of cognitive therapy versus 'no intervention' for major depressive disorder. Participants had to be older than 17 years with a primary diagnosis of major depressive disorder to be eligible. Altogether, we included 12 trials randomizing a total of 669 participants. All 12 trials had high risk of bias. Meta-analysis on the Hamilton Rating Scale for Depression showed that cognitive therapy significantly reduced depressive symptoms (four trials; mean difference -3.05 (95% confidence interval (Cl), -5.23 to -0.87; P<0.006)) compared with 'no intervention'. Trial sequential analysis could not confirm this result. Meta-analysis on the Beck Depression Inventory showed that cognitive therapy significantly reduced depressive symptoms (eight trials; mean difference on -4.86 (95% CI -6.44 to -3.28; P = 0.00001)). Trial sequential analysis on these data confirmed the result. Only a few trials reported on 'no remission', suicide inclination, suicide attempts, suicides, and adverse events without significant differences between the compared intervention groups. DISCUSSION: Cognitive therapy might be an effective treatment for depression measured on Hamilton Rating Scale for Depression and Beck Depression Inventory, but these outcomes may be overestimated due to risks of systematic errors (bias) and random errors (play of chance). Furthermore, the effects of cognitive therapy on no remission, suicidality, adverse events, and quality of life are unclear. There is a need for randomized trials with low risk of bias, low risk of random errors, and longer follow-up assessing both benefits and harms with clinically relevant outcome measures

The effects of cognitive therapy versus 'treatment as usual' in patients with major depressive disorder

BACKGROUND: Major depressive disorder afflicts an estimated 17% of individuals during their lifetimes at tremendous suffering and costs. Cognitive therapy may be an effective treatment option for major depressive disorder, but the effects have only had limited assessment in systematic reviews. METHODS/PRINCIPAL FINDINGS: Cochrane systematic review methodology, with meta-analyses and trial sequential analyses of randomized trials, are comparing the effects of cognitive therapy versus 'treatment as usual' for major depressive disorder. To be included the participants had to be older than 17 years with a primary diagnosis of major depressive disorder. Altogether, we included eight trials randomizing a total of 719 participants. All eight trials had high risk of bias. Four trials reported data on the 17-item Hamilton Rating Scale for Depression and four trials reported data on the Beck Depression Inventory. Meta-analysis on the data from the Hamilton Rating Scale for Depression showed that cognitive therapy compared with 'treatment as usual' significantly reduced depressive symptoms (mean difference -2.15 (95% confidence interval -3.70 to -0.60; P<0.007, no heterogeneity)). However, meta-analysis with both fixed-effect and random-effects model on the data from the Beck Depression Inventory (mean difference with both models -1.57 (95% CL -4.30 to 1.16; P = 0.26, I(2) = 0) could not confirm the Hamilton Rating Scale for Depression results. Furthermore, trial sequential analysis on both the data from Hamilton Rating Scale for Depression and Becks Depression Inventory showed that insufficient data have been obtained. DISCUSSION: Cognitive therapy might not be an effective treatment for major depressive disorder compared with 'treatment as usual'. The possible treatment effect measured on the Hamilton Rating Scale for Depression is relatively small. More randomized trials with low risk of bias, increased sample sizes, and broader more clinically relevant outcomes are needed

Crowdsourced mapping of unexplored target space of kinase inhibitors

Despite decades of intensive search for compounds that modulate the activity of particular protein targets, a large proportion of the human kinome remains as yet undrugged. Effective approaches are therefore required to map the massive space of unexplored compound-kinase interactions for novel and potent activities. Here, we carry out a crowdsourced benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data. We find the top-performing predictions are based on various models, including kernel learning, gradient boosting and deep learning, and their ensemble leads to a predictive accuracy exceeding that of single-dose kinase activity assays. We design experiments based on the model predictions and identify unexpected activities even for under-studied kinases, thereby accelerating experimental mapping efforts. The open-source prediction algorithms together with the bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking prediction algorithms and for extending the druggable kinome. The IDG-DREAM Challenge carried out crowdsourced benchmarking of predictive algorithms for kinase inhibitor activities on unpublished data. This study provides a resource to compare emerging algorithms and prioritize new kinase activities to accelerate drug discovery and repurposing efforts

High cycle fatigue behavior and life prediction for additively manufactured 17-4 PH stainless steel: Effect of sub-surface porosity and surface roughness

The high potential of additive manufacturing (AM) techniques offers novel opportunities and unexplored design freedom. However, typical internal defects and poor surface quality inherent to AM process not only cause a lower fatigue resistance, but also more scatter in fatigue data; thus, hindering adoption of AM to fatigue critical applications. This study investigates the effect of surface quality and sub-surface porosity on high cycle fatigue behavior of 17-4 precipitation hardening (PH) stainless steel (SS) fabricated using laser beam powder bed fusion (LB-PBF) process. Parts were fabricated in three conditions: net-shape (NS) specimens, oversized specimens, and cylindrical rods. The oversized specimens and cylindrical rods were, respectively, further shallow machined (SM) and deep machined (DM) to the dimensions and geometry of net-shape specimens. The population of defects was investigated via optical microscopy of polished sections, X-ray micro-CT scan analysis, and fractography of fracture surfaces after fatigue tests. The fatigue crack growth (FCG) properties were generated at three stress ratios of R=-1,0.1,0.7 to determine the Kitagawa-Takahashi diagram and propagation curve. The polished sections showed the presence of large sub-surface, close-to-surface pores in the NS specimens, while SM and DM conditions had smaller and more uniformly distributed porosity. Critical defects detected on the fracture surfaces were small pores in machined specimens, and relatively large surface irregularities in NS specimens. Machining process, both in SM and DM conditions, enhanced the fatigue performance of the material as compared to that of NS condition. However, in terms of level of machining allowance, no further enhancement in fatigue performance was observed for DM specimens as compared to that of SM ones. Fatigue assessment for both net-shape and machined conditions was obtained performing FCG simulations based on the typical surface features and volumetric defects. Simulation results yielded correct estimates for both net-shape and machined specimens