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      Severe Spinal Cord Injury in Rats Induces Chronic Changes in the Spinal Cord and Cerebral Cortex Metabolism, Adjusted by Thiamine That Improves Locomotor Performance

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          Abstract

          Our study aims at developing knowledge-based strategies minimizing chronic changes in the brain after severe spinal cord injury (SCI). The SCI-induced long-term metabolic alterations and their reactivity to treatments shortly after the injury are characterized in rats. Eight weeks after severe SCI, significant mitochondrial lesions outside the injured area are demonstrated in the spinal cord and cerebral cortex. Among the six tested enzymes essential for the TCA cycle and amino acid metabolism, mitochondrial 2-oxoglutarate dehydrogenase complex (OGDHC) is the most affected one. SCI downregulates this complex by 90% in the spinal cord and 30% in the cerebral cortex. This is associated with the tissue-specific changes in other enzymes of the OGDHC network. Single administrations of a pro-activator (thiamine, or vitamin B1, 1.2 mmol/kg) or a synthetic pro-inhibitor (triethyl glutaryl phosphonate, TEGP, 0.02 mmol/kg) of OGDHC within 15–20 h after SCI are tested as protective strategies. The biochemical and physiological assessments 8 weeks after SCI reveal that thiamine, but not TEGP, alleviates the SCI-induced perturbations in the rat brain metabolism, accompanied by the decreased expression of (acetyl)p53, increased expression of sirtuin 5 and an 18% improvement in the locomotor recovery. Treatment of the non-operated rats with the OGDHC pro-inhibitor TEGP increases the p53 acetylation in the brain, approaching the brain metabolic profiles to those after SCI. Our data testify to an important contribution of the OGDHC regulation to the chronic consequences of SCI and their control by p53 and sirtuin 5.

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          Inflammation as a central mechanism in Alzheimer's disease

          Alzheimer's disease (AD) is a progressive neurodegenerative disorder that is characterized by cognitive decline and the presence of two core pathologies, amyloid β plaques and neurofibrillary tangles. Over the last decade, the presence of a sustained immune response in the brain has emerged as a third core pathology in AD. The sustained activation of the brain's resident macrophages (microglia) and other immune cells has been demonstrated to exacerbate both amyloid and tau pathology and may serve as a link in the pathogenesis of the disorder. In the following review, we provide an overview of inflammation in AD and a detailed coverage of a number of microglia-related signaling mechanisms that have been implicated in AD. Additional information on microglia signaling and a number of cytokines in AD are also reviewed. We also review the potential connection of risk factors for AD and how they may be related to inflammatory mechanisms.
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            A sensitive and reliable locomotor rating scale for open field testing in rats.

            Behavioral assessment after spinal cord contusion has long focused on open field locomotion using modifications of a rating scale developed by Tarlov and Klinger (1954). However, on-going modifications by several groups have made interlaboratory comparison of locomotor outcome measures difficult. The purpose of the present study was to develop an efficient, expanded, and unambiguous locomotor rating scale to standardize locomotor outcome measures across laboratories. Adult rats (n = 85) were contused at T7-9 cord level with an electromagnetic or weight drop device. Locomotor behavior was evaluated before injury, on the first or second postoperative day, and then for up to 10 weeks. Scoring categories and attributes were identified, operationally defined, and ranked based on the observed sequence of locomotor recovery patterns. These categories formed the Basso, Beattie, Bresnahan (BBB) Locomotor Rating Scale. The data indicate that the BBB scale is a valid and predictive measure of locomotor recovery able to distinguish behavioral outcomes due to different injuries and to predict anatomical alterations at the lesion center. Interrater reliability tests indicate that examiners with widely varying behavioral testing experience can apply the scale consistently and obtain similar scores. The BBB Locomotor Rating Scale offers investigators a more discriminating measure of behavioral outcome to evaluate treatments after spinal cord injury.
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              Detecting outliers when fitting data with nonlinear regression – a new method based on robust nonlinear regression and the false discovery rate

              Background Nonlinear regression, like linear regression, assumes that the scatter of data around the ideal curve follows a Gaussian or normal distribution. This assumption leads to the familiar goal of regression: to minimize the sum of the squares of the vertical or Y-value distances between the points and the curve. Outliers can dominate the sum-of-the-squares calculation, and lead to misleading results. However, we know of no practical method for routinely identifying outliers when fitting curves with nonlinear regression. Results We describe a new method for identifying outliers when fitting data with nonlinear regression. We first fit the data using a robust form of nonlinear regression, based on the assumption that scatter follows a Lorentzian distribution. We devised a new adaptive method that gradually becomes more robust as the method proceeds. To define outliers, we adapted the false discovery rate approach to handling multiple comparisons. We then remove the outliers, and analyze the data using ordinary least-squares regression. Because the method combines robust regression and outlier removal, we call it the ROUT method. When analyzing simulated data, where all scatter is Gaussian, our method detects (falsely) one or more outlier in only about 1–3% of experiments. When analyzing data contaminated with one or several outliers, the ROUT method performs well at outlier identification, with an average False Discovery Rate less than 1%. Conclusion Our method, which combines a new method of robust nonlinear regression with a new method of outlier identification, identifies outliers from nonlinear curve fits with reasonable power and few false positives.
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                Author and article information

                Contributors
                Journal
                Front Mol Neurosci
                Front Mol Neurosci
                Front. Mol. Neurosci.
                Frontiers in Molecular Neuroscience
                Frontiers Media S.A.
                1662-5099
                29 March 2021
                2021
                : 14
                : 620593
                Affiliations
                [1] 1Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University , Moscow, Russia
                [2] 2Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University , Moscow, Russia
                [3] 3Russian Cardiology Research-and-Production Complex, Ministry of Health of the Russian Federation , Moscow, Russia
                [4] 4Faculty of Biology, Lomonosov Moscow State University , Moscow, Russia
                [5] 5Faculty of Nano-, Bio-, Informational and Cognitive Technologies, Moscow Institute of Physics and Technology , Moscow, Russia
                [6] 6Department of Biological Chemistry, Sechenov University , Moscow, Russia
                Author notes

                Edited by: Arnau Hervera Abad, Institute for Bioengineering of Catalonia (IBEC), Spain

                Reviewed by: Stanislava Jergova, University of Miami, United States; Carlos A. Toro, Icahn School of Medicine at Mount Sinai, United States

                *Correspondence: Victoria Bunik, bunik@ 123456belozersky.msu.ru

                Present Address: Alexandra Boyko, Unit of Structural Microbiology, Institut Pasteur, CNRS, University of Paris, Paris, France; Garik Mkrtchyan, Department of Cellular and Molecular Medicine, Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark

                Article
                10.3389/fnmol.2021.620593
                8044794
                33867932
                cffd1ae7-1c18-4990-83d7-4cea33c30305
                Copyright © 2021 Boyko, Tsepkova, Aleshin, Artiukhov, Mkrtchyan, Ksenofontov, Baratova, Ryabov, Graf and Bunik.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 23 October 2020
                : 05 March 2021
                Page count
                Figures: 9, Tables: 2, Equations: 0, References: 106, Pages: 22, Words: 0
                Funding
                Funded by: Russian Science Foundation 10.13039/501100006769
                Categories
                Neuroscience
                Original Research

                Neurosciences
                amino acids metabolism,cerebral cortex,2-oxoglutarate dehydrogenase,p53,phosphonate analog of 2-oxo acid,spinal cord injury,sirtuin 5,thiamine

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