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Thus, HDX-MS is instrumental for resolving the structure-dynamic landscapes of membrane proteins in their apo (ligand-free) and ligand-bound forms, shedding light on the molecular mechanism underlying the transport process and drug binding. Copyright © 2020 Giladi and Khananshvili.Tumor-induced immunosuppressive microenvironment in which myeloid-derived suppressor cells (MDSCs) plays an important role, remains an obstacle for effective oncotherapy currently. Inducing MDSCs into maturation was confirmed as an effective method to reduce the tumor-bearing host's immunosuppression. Traditional Chinese medicines (TCM) possess characteristics of alleviating immunosuppression of cancer patients and low toxicity. Jianpi Huayu Decoction (JHD) was an experienced formula of TCM for oncotherapy based on TCM theory and clinical practice. We previously observed that JHD attenuated the expression of interleukin-10 (IL-10) and transforming growth factor beta (TGF-β) in tumor. Spautin-1 IL-10 and TGF-β were found to be cytokines positively related to immunosuppression induced by MDSCs. Here, our study was designed to further investigate the regulation of JHD on the immune system in the H22 liver-cancer mouse model. Mainly, flow cytometry was used to detect the proportion of immune cells, to analyze the apoptosiss and promote it mature to replenish dendritic cell, at the same time. Generally, JHD may be a complementary and alternative drug for attenuating the immunosuppressive status induced by hepatocellular carcinoma, possibly by promoting differentiation and inhibiting the immunosuppressive activity of MDSCs. Copyright © 2020 Xie, Zhang, Wei, Zhou, Huang, Zhu, Chen, Wen, Huang, Lin, Wang, Ren, Fan, Deng, Tan and Wang.Mitochondrial autophagy is involved in myocardial protection of sevoflurane postconditioning (SPostC) and in diabetic state this protective effect is weakened due to impaired HIF-1 signaling pathway. Previous studies have proved that deferoxamine (DFO) could activate impaired HIF-1α in diabetic state to restore the cardioprotective of sevoflurane, while the specific mechanism is unclear. This study aims to investigate whether HIF-1/BNIP3-mediated mitochondrial autophagy is involved in the restoration of sevoflurane postconditioning cardioprotection in diabetic state. Ischemia/reperfusion (I/R) model was established by ligating the anterior descending coronary artery and sevoflurane was administered at the first 15 min of reperfusion. Myocardial infarct size, mitochondrial ultrastructure and autophagosome, ATP content, mitochondrial membrane potential, ROS production, HIF-1α, BNIP3, LC3B-II, Beclin-1, P62, LAMP2 protein expression were detected 2 h after reperfusion, and cardiac function was evaluated by ultrasound at 24 h after reperfusion. Our results showed that with DFO treatment, SPostC up-regulated the expression of HIF-1α and BNIP3, thus reduced the expression of key autophagy proteins LC3B-II, Beclin-1, p62, and increased the expression of LAMP2. link2 Furthermore, it reduced the accumulation of autophagosomes and ROS production, increased the content of ATP, and stabilized the membrane potential. Finally, the myocardial infarction size was reduced and cardiac function was improved. Taken together, DFO treatment combined with SPostC could alleviate myocardial ischemia reperfusion injury in diabetic rats by restoring and promoting HIF-1/BNIP3-mediated mitochondrial autophagy. Copyright © 2020 Yang, Xie, Wu, Yu, Li, Ma, Yu, Wang, Ye, Wang and Zheng.Ultrafast Shape Recognition (USR), along with its derivatives, are Ligand-Based Virtual Screening (LBVS) methods that condense 3-dimensional information about molecular shape, as well as other properties, into a small set of numeric descriptors. These can be used to efficiently compute a measure of similarity between pairs of molecules using a simple inverse Manhattan Distance metric. In this study we explore the use of suitable Machine Learning techniques that can be trained using USR descriptors, so as to improve the similarity detection of potential new leads. We use molecules from the Directory for Useful Decoys-Enhanced to construct machine learning models based on three different algorithms Gaussian Mixture Models (GMMs), Isolation Forests and Artificial Neural Networks (ANNs). We train models based on full molecule conformer models, as well as the Lowest Energy Conformations (LECs) only. We also investigate the performance of our models when trained on smaller datasets so as to model virtual screening scenarios when only a small number of actives are known a priori. Our results indicate significant performance gains over a state of the art USR-derived method, ElectroShape 5D, with GMMs obtaining a mean performance up to 430% better than that of ElectroShape 5D in terms of Enrichment Factor with a maximum improvement of up to 940%. Additionally, we demonstrate that our models are capable of maintaining their performance, in terms of enrichment factor, within 10% of the mean as the size of the training dataset is successively reduced. Furthermore, we also demonstrate that running times for retrospective screening using the machine learning models we selected are faster than standard USR, on average by a factor of 10, including the time required for training. Our results show that machine learning techniques can significantly improve the virtual screening performance and efficiency of the USR family of methods. Copyright © 2020 Bonanno and Ebejer.Mild cognitive impairment (MCI) is often considered a critical time window for predicting early conversion to Alzheimer's disease (AD). Brain functional connectome data (i.e., functional connections, global and nodal graph metrics) based on resting-state functional magnetic resonance imaging (rs-fMRI) provides numerous information about brain networks and has been used to discriminate normal controls (NCs) from subjects with MCI. In this paper, Student's t-tests and group-least absolute shrinkage and selection operator (group-LASSO) were used to extract functional connections with significant differences and the most discriminative network nodes, respectively. Based on group-LASSO, the middle temporal, inferior temporal, lingual, posterior cingulate, and middle frontal gyri were the most predominant brain regions for nodal observation in MCI patients. Nodal graph metrics (within-module degree, participation coefficient, and degree centrality) showed the maximum discriminative ability. To effectively combine tWang.Exposure to severe stress has immediate and prolonged neuropsychiatric consequences and increases the risk of developing Posttraumatic Stress Disorder (PTSD). Importantly, PTSD develops in only a subset of individuals after exposure to a traumatic event, with the understanding of this selective vulnerability being very limited. Individuals who go on to develop PTSD after a traumatic experience typically demonstrate sleep disturbances including persistent insomnia and recurrent trauma-related nightmares. We previously established a repeated social defeat paradigm in which rats segregate into either passively or actively coping subpopulations, and we found that this distinction correlates with measures of vulnerability or resilience to stress. In this study, we examined differences between these two behavioral phenotypes in sleep changes resulting from repeated social defeat stress. Our data indicate that, compared to control and actively coping rats, passively coping rats have less slow-wave sleep (SWS) for at least 2 weeks after the end of a series of exposures to social defeat. Furthermore, resilient rats show less exaggerated motor activation at awakenings from rapid eye movement (REM) sleep and less fragmentation of REM sleep compared to control and passively coping rats. Together, these data associate a passive coping strategy in response to repeated social defeat stress with persisting sleep disturbances. Conversely, an active coping strategy may be associated with resilience to sleep disturbances. These findings may have both prognostic and therapeutic applications to stress-associated neuropsychiatric disorders, including PTSD. Copyright © 2020 Grafe, O’Mara, Branch, Dobkin, Luz, Vigderman, Shingala, Kubin, Ross and Bhatnagar.The consistency, efficacy, and safety of cannabis-based medicines have been demonstrated in humans, leading to the approval of the first cannabis-based therapy to alleviate spasticity and pain associated with multiple sclerosis (MS). Indeed, the evidence supporting the therapeutic potential of cannabinoids for the management of pathological events related to this disease is ever increasing. Different mechanisms of action have been proposed for cannabis-based treatments in mouse models of demyelination, such as Experimental Autoimmune Encephalomyelitis (EAE) and Theiler's Murine Encephalomyelitis Virus-Induced Demyelinating Disease (TMEV-IDD). Cells in the immune and nervous system express the machinery to synthesize and degrade endocannabinoids, as well as their CB1 and CB2 receptors, each mediating different intracellular pathways upon activation. Hence, the effects of cannabinoids on cells of the immune system, on the blood-brain barrier (BBB), microglia, astrocytes, oligodendrocytes and neurons, potentially open the way for a plethora of therapeutic actions on different targets that could aid the management of MS. As such, cannabinoids could have an important impact on the outcome of MS in terms of the resolution of inflammation or the potentiation of endogenous repair in the central nervous system (CNS), as witnessed in the EAE, TMEV-IDD and toxic demyelination models, and through other in vitro approaches. In this mini review article, we summarize what is currently known about the peripheral and central effects of cannabinoids in relation to the neuroinflammation coupled to MS. We pay special attention to their effects on remyelination and axon preservation within the CNS, considering the major questions raised in the field and future research directions. Copyright © 2020 Mecha, Carrillo-Salinas, Feliú, Mestre and Guaza.The cerebral cortical tissue of murine embryo and pluripotent stem cell-derived neurons can survive in the adult brain and extend axons to the spinal cord. These features suggest that cell transplantation can be a strategy to reconstruct the corticospinal tract (CST). It is unknown, however, which cell population makes for safe and effective donor cells. To address this issue, we grafted the cerebral cortex of E14.5 mouse to the brain of adult mice and found that the cells in the graft extending axons along the CST expressed CTIP2. By using CTIP2GFP knock-in mouse embryonic stem cells (mESCs), we identified L1CAM as a cell surface marker to enrich CTIP2+ cells. We sorted L1CAM+ cells from E14.5 mouse brain and confirmed that they extended a larger number of axons along the CST compared to L1CAM- cells. Our results suggest that sorting L1CAM+ cells from the embryonic cerebral cortex enriches subcortical projection neurons to reconstruct the CST. Copyright © 2020 Samata, Takaichi, Ishii, Fukushima, Nakagawa, Ono and Takahashi.Alzheimer's disease (AD) is the most common neurodegenerative disorder and the main cause of dementia among the elderly worldwide. link3 Unfortunately, the mechanism of AD remains unclear, and no effective therapies are available yet. An increasing amount of studies have demonstrated that long non-coding RNAs (LncRNAs) play a notable role in the pathogenesis of plenty of human diseases, and they have served as biomarkers and potential therapeutic targets. However, the function of LncRNAs in AD remains unclear. This study aimed to explore the potential role of LncRNA nuclear enriched abundant transcript 1 (NEAT1) in AD. We found that LncRNA NEAT1 was upregulated in the AD animal models. Furthermore, we demonstrated that NEAT1 could interact with NEDD4L and promote PTEN-induced putative kinase 1 (PINK1)'s ubiquitination and degradation and then impaired PINK1-dependent autophagy. Collectively, the lncRNA NEAT1 promotes the pathogenesis of AD and serves as a promising novel target for pharmacological intervention. Copyright © 2020 Huang, Zhao, Wang, Zhou and Zhang.