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Hspb1 and Lgals3 in spinal neurons are closely associated with autophagy following excitotoxicity based on machine learning algorithms
Excitotoxicity represents the primary cause of neuronal death following spinal cord injury (SCI). While autophagy plays a critical and intricate role in SCI, the specific mechanism underlying the relationship between excitotoxicity and autophagy in SCI has been largely overlooked. In this study, we...
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Published in: | PloS one 2024-05, Vol.19 (5), p.e0303235-e0303235 |
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description | Excitotoxicity represents the primary cause of neuronal death following spinal cord injury (SCI). While autophagy plays a critical and intricate role in SCI, the specific mechanism underlying the relationship between excitotoxicity and autophagy in SCI has been largely overlooked. In this study, we isolated primary spinal cord neurons from neonatal rats and induced excitotoxic neuronal injury by high concentrations of glutamic acid, mimicking an excitotoxic injury model. Subsequently, we performed transcriptome sequencing. Leveraging machine learning algorithms, including weighted correlation network analysis (WGCNA), random forest analysis (RF), and least absolute shrinkage and selection operator analysis (LASSO), we conducted a comprehensive investigation into key genes associated with spinal cord neuron injury. We also utilized protein-protein interaction network (PPI) analysis to identify pivotal proteins regulating key gene expression and analyzed key genes from public datasets (GSE2599, GSE20907, GSE45006, and GSE174549). Our findings revealed that six genes-Anxa2, S100a10, Ccng1, Timp1, Hspb1, and Lgals3-were significantly upregulated not only in vitro in neurons subjected to excitotoxic injury but also in rats with subacute SCI. Furthermore, Hspb1 and Lgals3 were closely linked to neuronal autophagy induced by excitotoxicity. Our findings contribute to a better understanding of excitotoxicity and autophagy, offering potential targets and a theoretical foundation for SCI diagnosis and treatment. |
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While autophagy plays a critical and intricate role in SCI, the specific mechanism underlying the relationship between excitotoxicity and autophagy in SCI has been largely overlooked. In this study, we isolated primary spinal cord neurons from neonatal rats and induced excitotoxic neuronal injury by high concentrations of glutamic acid, mimicking an excitotoxic injury model. Subsequently, we performed transcriptome sequencing. Leveraging machine learning algorithms, including weighted correlation network analysis (WGCNA), random forest analysis (RF), and least absolute shrinkage and selection operator analysis (LASSO), we conducted a comprehensive investigation into key genes associated with spinal cord neuron injury. We also utilized protein-protein interaction network (PPI) analysis to identify pivotal proteins regulating key gene expression and analyzed key genes from public datasets (GSE2599, GSE20907, GSE45006, and GSE174549). Our findings revealed that six genes-Anxa2, S100a10, Ccng1, Timp1, Hspb1, and Lgals3-were significantly upregulated not only in vitro in neurons subjected to excitotoxic injury but also in rats with subacute SCI. Furthermore, Hspb1 and Lgals3 were closely linked to neuronal autophagy induced by excitotoxicity. Our findings contribute to a better understanding of excitotoxicity and autophagy, offering potential targets and a theoretical foundation for SCI diagnosis and treatment.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0303235</identifier><identifier>PMID: 38728287</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Animals ; Apoptosis ; Autophagy ; Bioinformatics ; Calcium-binding protein ; Cell culture ; Cell death ; Data mining ; Excitotoxicity ; Galectin 3 - genetics ; Galectin 3 - metabolism ; Gene expression ; Genes ; Glutamate ; Glutamic acid ; Glutamic Acid - metabolism ; Heat-Shock Proteins - genetics ; Heat-Shock Proteins - metabolism ; Injury analysis ; Interdisciplinary subjects ; Learning algorithms ; Machine Learning ; Medical diagnosis ; Molecular biology ; Molecular Chaperones - genetics ; Molecular Chaperones - metabolism ; Neonates ; Nervous system ; Network analysis ; Neurons ; Neurons - metabolism ; Penicillin ; Protein interaction ; Protein Interaction Maps ; Protein-protein interactions ; Proteins ; Rats ; Rats, Sprague-Dawley ; Research methodology ; S100 protein ; Spinal cord ; Spinal Cord - metabolism ; Spinal Cord - pathology ; Spinal cord injuries ; Spinal Cord Injuries - genetics ; Spinal Cord Injuries - metabolism ; Spinal Cord Injuries - pathology ; Tissue inhibitor of metalloproteinase 1 ; Transcriptomes</subject><ispartof>PloS one, 2024-05, Vol.19 (5), p.e0303235-e0303235</ispartof><rights>Copyright: © 2024 Yan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2024 Public Library of Science</rights><rights>2024 Yan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 Yan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c586t-6cf5ae22ef9bcd373c3c6914de321d10a0bbb7ab1e4152caa372f595c7f1d24f3</cites><orcidid>0000-0003-2715-8337</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/3069286107/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/3069286107?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,37013,44590,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38728287$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Tian, Suyan</contributor><creatorcontrib>Yan, Lei</creatorcontrib><creatorcontrib>Li, Zihao</creatorcontrib><creatorcontrib>Li, Chuanbo</creatorcontrib><creatorcontrib>Chen, Jingyu</creatorcontrib><creatorcontrib>Zhou, Xun</creatorcontrib><creatorcontrib>Cui, Jiaming</creatorcontrib><creatorcontrib>Liu, Peng</creatorcontrib><creatorcontrib>Shen, Chong</creatorcontrib><creatorcontrib>Chen, Chu</creatorcontrib><creatorcontrib>Hong, Hongxiang</creatorcontrib><creatorcontrib>Xu, Guanhua</creatorcontrib><creatorcontrib>Cui, Zhiming</creatorcontrib><title>Hspb1 and Lgals3 in spinal neurons are closely associated with autophagy following excitotoxicity based on machine learning algorithms</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Excitotoxicity represents the primary cause of neuronal death following spinal cord injury (SCI). While autophagy plays a critical and intricate role in SCI, the specific mechanism underlying the relationship between excitotoxicity and autophagy in SCI has been largely overlooked. In this study, we isolated primary spinal cord neurons from neonatal rats and induced excitotoxic neuronal injury by high concentrations of glutamic acid, mimicking an excitotoxic injury model. Subsequently, we performed transcriptome sequencing. Leveraging machine learning algorithms, including weighted correlation network analysis (WGCNA), random forest analysis (RF), and least absolute shrinkage and selection operator analysis (LASSO), we conducted a comprehensive investigation into key genes associated with spinal cord neuron injury. We also utilized protein-protein interaction network (PPI) analysis to identify pivotal proteins regulating key gene expression and analyzed key genes from public datasets (GSE2599, GSE20907, GSE45006, and GSE174549). Our findings revealed that six genes-Anxa2, S100a10, Ccng1, Timp1, Hspb1, and Lgals3-were significantly upregulated not only in vitro in neurons subjected to excitotoxic injury but also in rats with subacute SCI. Furthermore, Hspb1 and Lgals3 were closely linked to neuronal autophagy induced by excitotoxicity. Our findings contribute to a better understanding of excitotoxicity and autophagy, offering potential targets and a theoretical foundation for SCI diagnosis and treatment.</description><subject>Algorithms</subject><subject>Animals</subject><subject>Apoptosis</subject><subject>Autophagy</subject><subject>Bioinformatics</subject><subject>Calcium-binding protein</subject><subject>Cell culture</subject><subject>Cell death</subject><subject>Data mining</subject><subject>Excitotoxicity</subject><subject>Galectin 3 - genetics</subject><subject>Galectin 3 - metabolism</subject><subject>Gene expression</subject><subject>Genes</subject><subject>Glutamate</subject><subject>Glutamic acid</subject><subject>Glutamic Acid - metabolism</subject><subject>Heat-Shock Proteins - genetics</subject><subject>Heat-Shock Proteins - metabolism</subject><subject>Injury analysis</subject><subject>Interdisciplinary subjects</subject><subject>Learning algorithms</subject><subject>Machine Learning</subject><subject>Medical diagnosis</subject><subject>Molecular biology</subject><subject>Molecular Chaperones - genetics</subject><subject>Molecular Chaperones - metabolism</subject><subject>Neonates</subject><subject>Nervous system</subject><subject>Network analysis</subject><subject>Neurons</subject><subject>Neurons - metabolism</subject><subject>Penicillin</subject><subject>Protein interaction</subject><subject>Protein Interaction Maps</subject><subject>Protein-protein interactions</subject><subject>Proteins</subject><subject>Rats</subject><subject>Rats, Sprague-Dawley</subject><subject>Research methodology</subject><subject>S100 protein</subject><subject>Spinal cord</subject><subject>Spinal Cord - metabolism</subject><subject>Spinal Cord - pathology</subject><subject>Spinal cord injuries</subject><subject>Spinal Cord Injuries - genetics</subject><subject>Spinal Cord Injuries - metabolism</subject><subject>Spinal Cord Injuries - pathology</subject><subject>Tissue inhibitor of metalloproteinase 1</subject><subject>Transcriptomes</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqNkt1q3DAQhU1padK0b1BaQaC0F7uVLP_IlyG0zcJCoH-3YiyPvVpky5Vkkn2BPne1XSdkSy6KLiTEN2dGRydJXjO6ZLxkH7d2cgOY5WgHXFJOecrzJ8kpq3i6KFLKnz44nyQvvN9SmnNRFM-TEy7KVKSiPE1-X_mxZgSGhqw7MJ4TPRA_6qhMBpycHTwBh0QZ69HsCHhvlYaADbnRYUNgCnbcQLcjrTXG3uihI3irdLDB3uq470gNPtJ2ID2ojR6QGAQ37EEwnXVRpfcvk2dt7I6v5v0s-fH50_fLq8X6-svq8mK9ULkowqJQbQ6YpthWtWp4yRVXRcWyBnnKGkaB1nVdQs0wY3mqAHiZtnmVq7JlTZq1_Cx5e9Ad43vkbKGXnBZVKgpGy0isDkRjYStHp3twO2lBy78X1nUSXNDKoBQFChA1V1VdZJlAIRohalHROE0jyixqvZ-7OftrQh9kr71CY2BAO-3b5rwqqeBFRM__QR8fbqbiV6HUQ2uDA7UXlRdlxaMhjPNILR-h4mqw1yrGpdXx_qjgw1FBZALehg4m7-Xq29f_Z69_HrPvHrAbBBM23pop6BirYzA7gMpZ7x2298YzKvdpv3ND7tMu57THsjezaVPdY3NfdBdv_ge3evsO</recordid><startdate>20240510</startdate><enddate>20240510</enddate><creator>Yan, Lei</creator><creator>Li, Zihao</creator><creator>Li, Chuanbo</creator><creator>Chen, Jingyu</creator><creator>Zhou, Xun</creator><creator>Cui, Jiaming</creator><creator>Liu, Peng</creator><creator>Shen, Chong</creator><creator>Chen, Chu</creator><creator>Hong, Hongxiang</creator><creator>Xu, Guanhua</creator><creator>Cui, Zhiming</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-2715-8337</orcidid></search><sort><creationdate>20240510</creationdate><title>Hspb1 and Lgals3 in spinal neurons are closely associated with autophagy following excitotoxicity based on machine learning algorithms</title><author>Yan, Lei ; Li, Zihao ; Li, Chuanbo ; Chen, Jingyu ; Zhou, Xun ; Cui, Jiaming ; Liu, Peng ; Shen, Chong ; Chen, Chu ; Hong, Hongxiang ; Xu, Guanhua ; Cui, Zhiming</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c586t-6cf5ae22ef9bcd373c3c6914de321d10a0bbb7ab1e4152caa372f595c7f1d24f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Algorithms</topic><topic>Animals</topic><topic>Apoptosis</topic><topic>Autophagy</topic><topic>Bioinformatics</topic><topic>Calcium-binding protein</topic><topic>Cell culture</topic><topic>Cell death</topic><topic>Data mining</topic><topic>Excitotoxicity</topic><topic>Galectin 3 - 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Academic</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yan, Lei</au><au>Li, Zihao</au><au>Li, Chuanbo</au><au>Chen, Jingyu</au><au>Zhou, Xun</au><au>Cui, Jiaming</au><au>Liu, Peng</au><au>Shen, Chong</au><au>Chen, Chu</au><au>Hong, Hongxiang</au><au>Xu, Guanhua</au><au>Cui, Zhiming</au><au>Tian, Suyan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Hspb1 and Lgals3 in spinal neurons are closely associated with autophagy following excitotoxicity based on machine learning algorithms</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2024-05-10</date><risdate>2024</risdate><volume>19</volume><issue>5</issue><spage>e0303235</spage><epage>e0303235</epage><pages>e0303235-e0303235</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Excitotoxicity represents the primary cause of neuronal death following spinal cord injury (SCI). While autophagy plays a critical and intricate role in SCI, the specific mechanism underlying the relationship between excitotoxicity and autophagy in SCI has been largely overlooked. In this study, we isolated primary spinal cord neurons from neonatal rats and induced excitotoxic neuronal injury by high concentrations of glutamic acid, mimicking an excitotoxic injury model. Subsequently, we performed transcriptome sequencing. Leveraging machine learning algorithms, including weighted correlation network analysis (WGCNA), random forest analysis (RF), and least absolute shrinkage and selection operator analysis (LASSO), we conducted a comprehensive investigation into key genes associated with spinal cord neuron injury. We also utilized protein-protein interaction network (PPI) analysis to identify pivotal proteins regulating key gene expression and analyzed key genes from public datasets (GSE2599, GSE20907, GSE45006, and GSE174549). Our findings revealed that six genes-Anxa2, S100a10, Ccng1, Timp1, Hspb1, and Lgals3-were significantly upregulated not only in vitro in neurons subjected to excitotoxic injury but also in rats with subacute SCI. Furthermore, Hspb1 and Lgals3 were closely linked to neuronal autophagy induced by excitotoxicity. Our findings contribute to a better understanding of excitotoxicity and autophagy, offering potential targets and a theoretical foundation for SCI diagnosis and treatment.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>38728287</pmid><doi>10.1371/journal.pone.0303235</doi><tpages>e0303235</tpages><orcidid>https://orcid.org/0000-0003-2715-8337</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Animals Apoptosis Autophagy Bioinformatics Calcium-binding protein Cell culture Cell death Data mining Excitotoxicity Galectin 3 - genetics Galectin 3 - metabolism Gene expression Genes Glutamate Glutamic acid Glutamic Acid - metabolism Heat-Shock Proteins - genetics Heat-Shock Proteins - metabolism Injury analysis Interdisciplinary subjects Learning algorithms Machine Learning Medical diagnosis Molecular biology Molecular Chaperones - genetics Molecular Chaperones - metabolism Neonates Nervous system Network analysis Neurons Neurons - metabolism Penicillin Protein interaction Protein Interaction Maps Protein-protein interactions Proteins Rats Rats, Sprague-Dawley Research methodology S100 protein Spinal cord Spinal Cord - metabolism Spinal Cord - pathology Spinal cord injuries Spinal Cord Injuries - genetics Spinal Cord Injuries - metabolism Spinal Cord Injuries - pathology Tissue inhibitor of metalloproteinase 1 Transcriptomes |
title | Hspb1 and Lgals3 in spinal neurons are closely associated with autophagy following excitotoxicity based on machine learning algorithms |
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