{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T11:58:23Z","timestamp":1789214303088,"version":"build-2803163510"},"reference-count":30,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2024,9,16]],"date-time":"2024-09-16T00:00:00Z","timestamp":1726444800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2024,9,16]],"date-time":"2024-09-16T00:00:00Z","timestamp":1726444800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100014717","name":"National Outstanding Youth Science Fund Project of National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82160888"],"award-info":[{"award-number":["82160888"]}],"id":[{"id":"10.13039\/100014717","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Gastro and Hepatol"],"published-print":{"date-parts":[[2024,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background and Aim<\/jats:title>\n                    <jats:p>Currently, hepatitis B virus\u2010related acute liver failure (HBV\u2010ALF) has limited treatment options. Studies have shown that histone lactylation plays a role in the progression of liver\u2010related diseases. Therefore, it is essential to explore lactylation\u2010related gene (LRGs) biomarkers in HBV\u2010ALF to provide new information for the treatment of HBV\u2010ALF.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Two HBV\u2010ALF\u2010related datasets (GSE38941 and GSE14668) and 65 LRGs were used. First, the differentially expressed genes (DEGs) were derived from differential expression analysis, the key module genes from weighted gene co\u2010expression network analysis; and LRGs were used to intersect to obtain the candidate genes. Subsequently, the feature genes obtained from least absolute shrinkage and selection operator regression analysis and support vector machine analysis were intersected to obtain the candidate key genes. Among them, genes with consistent and significant expression trends in both GSE38941 and GSE14668 were used as biomarkers. Subsequently, biomarkers were analyzed for functional enrichment, immune infiltration, and sensitive drug prediction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In this study, five candidate genes (\n                      <jats:italic>PIGM<\/jats:italic>\n                      ,\n                      <jats:italic>PIGA<\/jats:italic>\n                      ,\n                      <jats:italic>EGR1<\/jats:italic>\n                      ,\n                      <jats:italic>PIGK<\/jats:italic>\n                      , and\n                      <jats:italic>PIGL<\/jats:italic>\n                      ) were identified by intersecting 6461 DEGs and 2496 key module genes with 65 LRGs. We then screened four candidate key genes from the machine learning algorithm, among which\n                      <jats:italic>PIGM<\/jats:italic>\n                      and\n                      <jats:italic>PIGA<\/jats:italic>\n                      were considered biomarkers in HBV\u2010ALF. Moreover, the results of enrichment analysis showed that the significant enrichment signaling pathways for biomarkers included allograft rejection and valine, leucine, and isoleucine degradation. Thereafter, 11 immune cells differed significantly between groups, with resting memory CD4+ T cells having the strongest positive correlation with biomarkers. Methylphenidate hydrochloride is a potential therapeutic drug for\n                      <jats:italic>PIGM<\/jats:italic>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      Two genes,\n                      <jats:italic>PIGM<\/jats:italic>\n                      and\n                      <jats:italic>PIGA<\/jats:italic>\n                      , were identified as biomarkers related to LRGs in HBV\u2010ALF, providing a basis for understanding HBV\u2010ALF pathogenesis.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/jgh.16739","type":"journal-article","created":{"date-parts":[[2024,9,17]],"date-time":"2024-09-17T15:29:55Z","timestamp":1726586995000},"page":"2903-2915","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Bioinformatics and experimental validation were combined to explore lactylation\u2010related biomarkers in HBV\u2010associated acute liver failure"],"prefix":"10.1111","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-9482-4248","authenticated-orcid":false,"given":"Hao","family":"Pei","sequence":"first","affiliation":[{"name":"Graduate School Guangxi University of Traditional Chinese Medicine  Nanning China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue\u2010qiao","family":"Chen","sequence":"additional","affiliation":[{"name":"First Clinical Medical College Guangxi University of Traditional Chinese Medicine  Nanning China"},{"name":"Guangxi Key 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