{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T06:22:55Z","timestamp":1787638975281,"version":"build-2736575974"},"reference-count":84,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T00:00:00Z","timestamp":1787616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Mol. Neurosci."],"abstract":"<jats:p>\n                    Human studies have demonstrated that repetitive head acceleration events (HAEs) disrupt metabolic homeostasis, raising the question of whether similar biochemical cascades scale across diverse platforms, from human to rodent to cell, for other traumatic brain injuries (TBIs). This study analyzed molecular disruptions in (i) humans with repetitive HAEs, (ii) mice with singular blast-elicited HAE with loss of consciousness, and (iii) a human 3D\n                    <jats:italic>in vitro<\/jats:italic>\n                    model of blunt injury. Humans exhibited metabolic, protein glycation, and epigenetic regulation abnormalities, with 30 pre-season metabolites predicting post-season levels with 89% accuracy.\n                    <jats:italic>In vivo<\/jats:italic>\n                    and\n                    <jats:italic>in vitro<\/jats:italic>\n                    RNA sequencing studies revealed convergence in 211 genes, with 123 metabolic genes mirroring human results. Regression analysis reflected an unprecedented 86% information scaling between platforms, namely, cell culture data predicted 86% of the information in the murine data. Athlete data linked these pathways to HAEs and motor behavior, highlighting convergent molecular disruptions across TBI models in metabolic homeostasis required for neural information processing. This approach across three platforms has not been shown before for brain-related disorders.\n                  <\/jats:p>","DOI":"10.3389\/fnmol.2026.1844343","type":"journal-article","created":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T05:36:16Z","timestamp":1787636176000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Molecular abnormalities scale across three models of cerebral injury"],"prefix":"10.3389","volume":"19","author":[{"given":"Volha","family":"Liaudanskaya","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, University of Cincinnati","place":["Cincinnati, OH, United States"]},{"name":"Department of Biomedical Engineering, Tufts University","place":["Medford, MA, United States"]},{"name":"Neuroscience Graduate Program, University of Cincinnati College of Medicine","place":["Cincinnati, OH, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew J.","family":"Robson","sequence":"additional","affiliation":[{"name":"Neuroscience Graduate Program, University of Cincinnati College of Medicine","place":["Cincinnati, OH, United States"]},{"name":"Division of Pharmaceutical Sciences, James L. 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