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      Melatonin Alleviates Neuroinflammation and Metabolic Disorder in DSS-Induced Depression Rats

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          Abstract

          There is a bidirectional relationship between inflammatory bowel disease (IBD) and depression/anxiety. Emerging evidences indicate that the liver may be involved in microbiota-gut-brain axis. This experiment focused on the role of melatonin in regulating the gut microbiota and explores its mechanism on dextran sulphate sodium- (DSS-) induced neuroinflammation and liver injury. Long-term DSS-treatment increased lipopolysaccharide (LPS), proinflammation cytokines IL-1 β and TNF- α, and gut leak in rats, breaking blood-brain barrier and overactivated astrocytes and microglia. Ultimately, the rats showed depression-like behavior, including reduction of sucrose preference and central time in open field test and elevation of immobility time in a forced swimming test. Oral administration with melatonin alleviated neuroinflammation and depression-like behaviors. However, melatonin supplementation did not decrease the level of LPS but increase short-chain fatty acid (SCFA) production to protect DSS-induced neuroinflammation. Additionally, western blotting analysis suggested that signaling pathways farnesoid X receptor-fibroblast growth factor 15 (FXR-FGF 15) in gut and apoptosis signal-regulating kinase 1 (ASK1) in the liver overactivated in DSS-treated rats, indicating liver metabolic disorder. Supplementation with melatonin markedly inhibited the activation of these two signaling pathways and its downstream p38. As for the gut microbiota, we found that immune response- and SCFA production-related microbiota, like Lactobacillus and Clostridium significantly increased, while bile salt hydrolase activity-related microbiota, like Streptococcus and Enterococcus, significantly decreased after melatonin supplementation. These altered microbiota were consistent with the alleviation of neuroinflammation and metabolic disorder. Taken together, our findings suggest melatonin contributes to reshape gut microbiota and improves inflammatory processes in the hippocampus (HPC) and metabolic disorders in the liver of DSS rats.

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          FLASH: fast length adjustment of short reads to improve genome assemblies.

          Next-generation sequencing technologies generate very large numbers of short reads. Even with very deep genome coverage, short read lengths cause problems in de novo assemblies. The use of paired-end libraries with a fragment size shorter than twice the read length provides an opportunity to generate much longer reads by overlapping and merging read pairs before assembling a genome. We present FLASH, a fast computational tool to extend the length of short reads by overlapping paired-end reads from fragment libraries that are sufficiently short. We tested the correctness of the tool on one million simulated read pairs, and we then applied it as a pre-processor for genome assemblies of Illumina reads from the bacterium Staphylococcus aureus and human chromosome 14. FLASH correctly extended and merged reads >99% of the time on simulated reads with an error rate of <1%. With adequately set parameters, FLASH correctly merged reads over 90% of the time even when the reads contained up to 5% errors. When FLASH was used to extend reads prior to assembly, the resulting assemblies had substantially greater N50 lengths for both contigs and scaffolds. The FLASH system is implemented in C and is freely available as open-source code at http://www.cbcb.umd.edu/software/flash. t.magoc@gmail.com.
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            Random forest: a classification and regression tool for compound classification and QSAR modeling.

            A new classification and regression tool, Random Forest, is introduced and investigated for predicting a compound's quantitative or categorical biological activity based on a quantitative description of the compound's molecular structure. Random Forest is an ensemble of unpruned classification or regression trees created by using bootstrap samples of the training data and random feature selection in tree induction. Prediction is made by aggregating (majority vote or averaging) the predictions of the ensemble. We built predictive models for six cheminformatics data sets. Our analysis demonstrates that Random Forest is a powerful tool capable of delivering performance that is among the most accurate methods to date. We also present three additional features of Random Forest: built-in performance assessment, a measure of relative importance of descriptors, and a measure of compound similarity that is weighted by the relative importance of descriptors. It is the combination of relatively high prediction accuracy and its collection of desired features that makes Random Forest uniquely suited for modeling in cheminformatics.
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              Stress and Health: Psychological, Behavioral, and Biological Determinants

              Stressors have a major influence upon mood, our sense of well-being, behavior, and health. Acute stress responses in young, healthy individuals may be adaptive and typically do not impose a health burden. However, if the threat is unremitting, particularly in older or unhealthy individuals, the long-term effects of stressors can damage health. The relationship between psychosocial stressors and disease is affected by the nature, number, and persistence of the stressors as well as by the individual's biological vulnerability (i.e., genetics, constitutional factors), psychosocial resources, and learned patterns of coping. Psychosocial interventions have proven useful for treating stress-related disorders and may influence the course of chronic diseases.
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                Author and article information

                Contributors
                Journal
                Oxid Med Cell Longev
                Oxid Med Cell Longev
                OMCL
                Oxidative Medicine and Cellular Longevity
                Hindawi
                1942-0900
                1942-0994
                2020
                30 July 2020
                : 2020
                : 1241894
                Affiliations
                1Guangdong Laboratory for Lingnan Modern Agriculture/College of Veterinary Medicine, South China Agricultural University/Guangdong Technology Research for Traditional Chinese Veterinary Medicine and Natural Medicine, Guangzhou 510642, China
                2Institute of Animal Health, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China
                3College of Animal Medicine, South China Agricultural University, Guangzhou 510642, China
                4Key Laboratory of Agro-Ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, Changsha, China
                Author notes

                Guest Editor: Anderson J. Teodoro

                Author information
                https://orcid.org/0000-0002-1176-6664
                https://orcid.org/0000-0002-0609-0073
                https://orcid.org/0000-0002-7311-2519
                https://orcid.org/0000-0002-6194-6065
                https://orcid.org/0000-0001-5109-1449
                https://orcid.org/0000-0002-7914-8344
                https://orcid.org/0000-0002-8968-0932
                https://orcid.org/0000-0001-6112-6975
                https://orcid.org/0000-0003-3066-6906
                Article
                10.1155/2020/1241894
                7415091
                32802257
                6fdda201-2b24-451a-915b-9180ea89f852
                Copyright © 2020 Wei-jie Lv et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 20 March 2020
                : 31 May 2020
                : 17 June 2020
                Funding
                Funded by: R&D Projects
                Award ID: 2019B020218003
                Funded by: National Natural Science Foundation of China
                Award ID: 31472232
                Categories
                Research Article

                Molecular medicine
                Molecular medicine

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