Notes

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Taken together, our findings suggest that RND3 and FOXD3 may be involved in pathogenesis of RM and may serve as potential therapeutic targets. Copyright © 2020 Ma, Li, Tian, Zeng, Zhang, Mo, Qin, Sun, Zhang, Zhang and Lin.Background Rheumatoid arthritis (RA) is an autoimmune disease that may be associated with gut microbiota via the aryl hydrocarbon receptor (AhR). Human umbilical mesenchymal stem cells (HUMSCs) have therapeutic potential against RA, but the underlying mechanism has not been fully elucidated. The purpose of this study was to explore the mechanism of action of HUMSCs in rats with collagen-induced arthritis (CIA). Method HUMSCs (1 × 106) were transplanted into each rat with CIA. The tissue localization of HUMSCs and the therapeutic effects in the ankles were assessed. The immune status and expression of immune-related genes and proteins in related lymphoid tissues were subsequently tested. Furthermore, the levels of immune-related factors in serum and the changes in gut microbiota in the ileum were detected, and the levels of indole and their derivatives in plasma and the levels of AhR in the ileum were evaluated. Results HUMSCs homed to the popliteal lymph node (PLN), mesenteric lymph node (MLN), ankle cartilagf indole, indoleacetic acid, and indole-3-lactic acid were consistently upregulated, and this upregulation was accompanied by increases in AhR gene and protein expression. Conclusion Our study demonstrates that HUMSCs play a therapeutic role in rats with CIA by regulating the interactions between host immunity and gut microbiota via the AhR. Copyright © 2020 Li, Lu, Fan, Lu, Xia, Zhao, Xu, Zhu, Li, Liu and Xiao.Alzheimer's disease (AD, OMIM 104300) is an age-related disorder that affects millions of people. One of the underlying causes of AD is generation of hydrophobic amyloid-beta 42 (Aβ42) peptides that accumulate to form amyloid plaques. These plaques induce oxidative stress and aberrant signaling, which result in the death of neurons and other pathologies linked to neurodegeneration. selleck kinase inhibitor We have developed a Drosophila eye model of AD by targeted misexpression of human Aβ42 in the differentiating retinal neurons, where an accumulation of Aβ42 triggers a characteristic neurodegenerative phenotype. In a forward deficiency screen to look for genetic modifiers, we identified a molecularly defined deficiency, which suppresses Aβ42-mediated neurodegeneration. This deficiency uncovers hippo (hpo) gene, a member of evolutionarily conserved Hippo signaling pathway that regulates growth. Activation of Hippo signaling causes cell death, whereas downregulation of Hippo signaling triggers cell proliferation. We found that Hippo signaling is activated in Aβ42-mediated neurodegeneration. Downregulation of Hippo signaling rescues the Aβ42-mediated neurodegeneration, whereas upregulation of Hippo signaling enhances the Aβ42-mediated neurodegeneration phenotypes. It is known that c-Jun-amino-terminal kinase (JNK) signaling pathway is upregulated in AD. We found that activation of JNK signaling enhances the Aβ42-mediated neurodegeneration, whereas downregulation of JNK signaling rescues the Aβ42-mediated neurodegeneration. We tested the nature of interactions between Hippo signaling and JNK signaling in Aβ42-mediated neurodegeneration using genetic epistasis approach. Our data suggest that Hippo signaling and JNK signaling, two independent signaling pathways, act synergistically upon accumulation of Aβ42 plaques to trigger cell death. Our studies demonstrate a novel role of Hippo signaling pathway in Aβ42-mediated neurodegeneration. Copyright © 2020 Irwin, Tare, Singh, Puli, Gogia, Riccetti, Deshpande, Kango-Singh and Singh.Neural repair in injury and disease presents a pressing unmet need in regenerative medicine. Due to the intrinsically reduced ability of the brain to replace lost and damaged neurons, reversing long-term cognitive and functional impairments poses a unique problem. Over the years, advancements in cellular and molecular understanding of neurogenesis mechanisms coupled with sophistication of biotechnology tools have transformed neural repair into a cross-disciplinary field that integrates discoveries from developmental neurobiology, transplantation and tissue engineering to design disease- and patient-specific remedies aimed at boosting either native rehabilitation or delivering exogenous hypoimmunogenic interventions. Advances in deciphering the blueprint of neural ontogenesis and annotation of the human genome has led to the development of targeted therapeutic opportunities that have the potential of treating the most vulnerable patient populations and whose findings from benchside suggest looming clinical translation. This review discusses how findings from studies of adult neurogenesis have informed development of interventions that target endogenous neural regenerative machineries and how advances in biotechnology, including the use of new gene-editing tools, have made possible the development of promising, complex neural transplant-based strategies. Adopting a multi-pronged strategy that is tailored to underlying neural pathology and that encompasses facilitation of endogenous regeneration, correction of patient's genomic mutations and delivery of transformed neural precursors and mature disease-relevant neuronal populations to replace injured or lost neural tissue remains no longer a fantasy. Copyright © 2020 Chohan.Background Prediction models for the overall survival of pancreatic cancer remain unsatisfactory. We aimed to explore artificial neural networks (ANNs) modeling to predict the survival of unresectable pancreatic cancer patients. Methods Thirty-two clinical parameters were collected from 221 unresectable pancreatic cancer patients, and their prognostic ability was evaluated using univariate and multivariate logistic regression. ANN and logistic regression (LR) models were developed on a training group (168 patients), and the area under the ROC curve (AUC) was used for comparison of the ANN and LR models. The models were further tested on the testing group (53 patients), and k-statistics were used for accuracy comparison. Results We built three ANN models, based on 3, 7, and 32 basic features, to predict 8 month survival. All 3 ANN models showed better performance, with AUCs significantly higher than those from the respective LR models (0.811 vs. 0.680, 0.844 vs. 0.722, 0.921 vs. 0.849, all p less then 0.05).
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