{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T21:04:03Z","timestamp":1791925443870,"version":"4.3.4"},"reference-count":49,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T00:00:00Z","timestamp":1783555200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100008459","name":"University of Calgary","doi-asserted-by":"crossref","award":["#10543"],"award-info":[{"award-number":["#10543"]}],"id":[{"id":"10.13039\/100008459","id-type":"DOI","asserted-by":"crossref"}]},{"award":["#10543"],"award-info":[{"award-number":["#10543"]}],"id":[{"id":"https:\/\/ror.org\/03yjb2x39","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>Traumatic brain injury (TBI) disrupts brain metabolism, which evolves over time and varies with the severity of the injury. Monitoring these metabolomic changes may reveal biomarkers indicating early damage, mechanisms of injury, and potentially help predict outcomes. This study used untargeted plasma metabolomics to investigate systemic time-dependent metabolic changes in mice exposed to controlled cortical impact (CCI) with or without replacement of a modified skull cap designed to reduce compensatory space for cerebral edema modelling a severe closed skull TBI, compared to sham controls. Male mice were subjected to CCI, CCI + CAP, or sham procedures comprised a scalp incision or a craniotomy. Plasma samples were collected at 4, 8, and 16 h, and 3 and 7 days after injury. Hydrophilic interaction liquid chromatography\u2013mass spectrometry (HILIC-MS) was used to profile metabolites in all groups and time points, while ion-pair liquid chromatography\u2013mass spectrometry (RPIPLC-MS) was used in CCI and sham mice at the early time points. The largest metabolic changes occurred at 8 h post-injury, distinguishing mice with CCI from sham controls. The early changes concerned metabolism of amino acids, energy, and nucleotide pathways, with metabolites such as succinate, phenylalanine, and cytidine showing significant changes. By 7 days, the metabolic patterns of the injured mice, especially CCI mice, had partially converged toward the sham state, although oxidative and mitochondrial disturbances persisted. The CCI + CAP mice had more pronounced and persistent metabolic disturbances compared to the CCI mice, which may reflect the effect of increased intracranial pressure post-injury. Plasma metabolomics can efficiently capture the evolving biochemical effects of TBI. The findings identified circulating metabolites that were associated with progression and severity of brain injury and provide a basis for future translational studies in human TBI.<\/jats:p>","DOI":"10.3390\/ijms27146144","type":"journal-article","created":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T14:17:51Z","timestamp":1783606671000},"page":"6144","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Exploring the Metabolic Impact of Traumatic Brain Injury in CCI Mouse Models: A Focus on Early and Prolonged Injury Responses"],"prefix":"10.3390","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-2635-1574","authenticated-orcid":false,"given":"Mohammad Mehdi","family":"Banoei","sequence":"first","affiliation":[{"name":"Department of Critical Care Medicine, Health Research Innovation Center (HRIC), University of Calgary, Room 4C64, 3280 Hospital Drive N.W, Calgary, AB T2N 4Z6, Canada"},{"name":"Department of Bio-Medical Engineering, University of Calgary, Calgary, AB T2L 0Y2, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brittney N. V.","family":"Scott","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine, Health Research Innovation Center (HRIC), University of Calgary, Room 4C64, 3280 Hospital Drive N.W, Calgary, AB T2N 4Z6, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2993-8871","authenticated-orcid":false,"given":"Brent W.","family":"Winston","sequence":"additional","affiliation":[{"name":"Department of Critical Care Medicine, Health Research Innovation Center (HRIC), University of Calgary, Room 4C64, 3280 Hospital Drive N.W, Calgary, AB T2N 4Z6, Canada"},{"name":"Departments of Medicine, Biochemistry and Molecular Biology, University of Calgary, Calgary, AB T2N 2T9, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Wang, Y. (2025). Global, regional, and national burdens of traumatic brain injury, spinal cord injury, and skull fracture and their attributable risk factors from 1990 to 2021: A systematic analysis of the global burden of disease study 2021. Front. Public Health, 13.","DOI":"10.3389\/fpubh.2025.1622693"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"341","DOI":"10.3233\/NRE-2007-22502","article-title":"The impact of traumatic brain injuries: A global perspective","volume":"22","author":"Hyder","year":"2007","journal-title":"NeuroRehabilitation"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"11903","DOI":"10.3390\/ijms160611903","article-title":"What\u2019s New in Traumatic Brain Injury: Update on Tracking, Monitoring and Treatment","volume":"16","author":"Reis","year":"2015","journal-title":"Int. J. Mol. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"4323","DOI":"10.1007\/s10787-025-01870-3","article-title":"Traumatic Brian Injury (TBI) unraveled: Molecular disruptions and therapeutic avenues","volume":"33","author":"Kumari","year":"2025","journal-title":"Inflammopharmacology"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"134347","DOI":"10.1016\/j.neulet.2019.134347","article-title":"Mitochondrial dysfunctioning and neuroinflammation: Recent highlights on the possible mechanisms involved in Traumatic Brain Injury","volume":"710","author":"Kaira","year":"2019","journal-title":"Neurosci. Lett."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Lin, C., Tian, Q., Guo, S., Xie, D., Cai, Y., Wang, Z., Chu, H., Qiu, S., Tang, S., and Zhang, A. (2024). Metabolomics for Clinical Biomarker Discovery and Therapeutic Target Identification. Molecules, 29.","DOI":"10.3390\/molecules29102198"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1831","DOI":"10.1089\/neu.2017.5326","article-title":"Metabolomics and Biomarker Discovery in Traumatic Brain Injury","volume":"35","author":"Banoei","year":"2018","journal-title":"J. Neurotrauma"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1186\/s13054-023-04573-9","article-title":"Using metabolomics to predict severe traumatic brain injury outcome (GOSE) at 3 and 12 months","volume":"27","author":"Banoei","year":"2023","journal-title":"Crit. Care"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1602\/neurorx.2.3.410","article-title":"Animal models of head trauma","volume":"2","author":"Cernak","year":"2005","journal-title":"NeuroRx"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.pharmthera.2011.01.001","article-title":"Animal models of traumatic brain injury: A critical evaluation","volume":"130","author":"Smyth","year":"2011","journal-title":"Pharmacol. Ther."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Chen, Z.X.J., Xu, X.-M., and Zhang, J. (2009). Controlled Cortical Impact Injury Model. Animal Models of Acute Neurological Injuries, Humana Press.","DOI":"10.1007\/978-1-60327-185-1"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1007\/978-1-4939-3816-2_11","article-title":"The Controlled Cortical Impact Model of Experimental Brain Trauma: Overview, Research Applications, and Protocol","volume":"1462","author":"Osier","year":"2016","journal-title":"Methods Mol. Biol."},{"key":"ref_13","first-page":"e51781","article-title":"Controlled cortical impact model for traumatic brain injury","volume":"90","author":"Romine","year":"2014","journal-title":"J. Vis. Exp."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.expneurol.2018.07.004","article-title":"Criteria to define mild, moderate, and severe traumatic brain injury in the mouse controlled cortical impact model","volume":"310","author":"Siebold","year":"2018","journal-title":"Exp. Neurol."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Fesharaki-Zadeh, A., and Datta, D. (2024). An overview of preclinical models of traumatic brain injury (TBI): Relevance to pathophysiological mechanisms. Front. Cell. Neurosci., 18.","DOI":"10.3389\/fncel.2024.1371213"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"492","DOI":"10.1007\/s12975-011-0125-x","article-title":"Blood-brain barrier pathophysiology in traumatic brain injury","volume":"2","author":"Chodobski","year":"2011","journal-title":"Transl. Stroke Res."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Fedoruk, R.P., Lee, C.H., Banoei, M.M., and Winston, B.W. (2023). Metabolomics in severe traumatic brain injury: A scoping review. BMC Neurosci., 24.","DOI":"10.1186\/s12868-023-00824-1"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1186\/s13054-025-05258-1","article-title":"Metabolomic in severe traumatic brain injury: Exploring primary, secondary injuries, diagnosis, and severity","volume":"29","author":"Banoei","year":"2025","journal-title":"Crit. Care"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Zheng, F., Xia, Z.-A., Zeng, Y.-F., Luo, J.-K., Sun, P., Cui, H.-J., Wang, Y., Tang, T., and Zhou, Y.-T. (2017). Plasma metabolomics profiles in rats with acute traumatic brain injury. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0182025"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1007\/s11306-016-0957-1","article-title":"Identification of candidate biomarkers of brain damage in a mouse model of closed head injury: A metabolomic pilot study","volume":"12","author":"Graham","year":"2016","journal-title":"Metabolomics"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1007\/s11306-016-1044-3","article-title":"Serum metabolomic markers for traumatic brain injury: A mouse model","volume":"12","author":"Graham","year":"2016","journal-title":"Metabolomics"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1186\/s12974-024-03280-8","article-title":"Metabolic-driven analytics of traumatic brain injury and neuroprotection by ethyl pyruvate","volume":"21","author":"Golovachev","year":"2024","journal-title":"J. Neuroinflamm."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"e2431115","DOI":"10.1001\/jamanetworkopen.2024.31115","article-title":"Diagnostic Performance of GFAP, UCH-L1, and MAP-2 Within 30 and 60 Minutes of Traumatic Brain Injury","volume":"7","author":"Papa","year":"2024","journal-title":"JAMA Netw. Open"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1089\/neu.2007.0481","article-title":"Early and sustained alterations in cerebral metabolism after traumatic brain injury in immature rats","volume":"25","author":"Casey","year":"2008","journal-title":"J. Neurotrauma"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Song, K., Li, Y., Zhang, H., An, N., Wei, Y., Wang, L., Tian, C., Yuan, M., Sun, Y., and Xing, Y. (2020). Oxidative Stress-Mediated Blood-Brain Barrier (BBB) Disruption in Neurological Diseases. Oxid. Med. Cell. Longev., 2020.","DOI":"10.1155\/2020\/4356386"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Zheng, F., Zhou, Y.-T., Li, P.-F., Hu, E., Li, T., Tang, T., Luo, J.-K., Zhang, W., Ding, C.-S., and Wang, Y. (2020). Metabolomics Analysis of Hippocampus and Cortex in a Rat Model of Traumatic Brain Injury in the Subacute Phase. Front. Neurosci., 14.","DOI":"10.3389\/fnins.2020.00876"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"22260","DOI":"10.1038\/s41598-023-48539-x","article-title":"The longitudinal biochemical profiling of TBI in a drop weight model of TBI","volume":"13","author":"Yilmaz","year":"2023","journal-title":"Sci. Rep."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1097\/WNR.0000000000001982","article-title":"Acute and sub-acute metabolic change in different brain regions induced by moderate blunt traumatic brain injury","volume":"35","author":"Kumari","year":"2024","journal-title":"Neuroreport"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Leontyev, D., Pulliam, A.N., Ma, X., Gaul, D.A., LaPlaca, M.C., and Fern\u00e1ndez, F.M. (2024). Spatial Lipidomics Maps Brain Alterations Associated with Mild Traumatic Brain Injury. bioRxiv.","DOI":"10.1101\/2024.01.25.577203"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Pulliam, A.N., Pybus, A.F., Gaul, D.A., Moore, S.G., Wood, L.B., Fern\u00e1ndez, F.M., and LaPlaca, M.C. (2024). Integrative Analysis of Cytokine and Lipidomics Datasets Following Mild Traumatic Brain Injury in Rats. Metabolites, 14.","DOI":"10.3390\/metabo14030133"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Xu, S., Zhuo, J., Racz, J., Roys, S., Shi, D., Fiskum, G., and Gullapalli, R. (2010). Early Metabolic and Structural Changes in the Rat Brain Following Trauma in vivo Using MRI. 26th Southern Biomedical Engineering Conference SBEC 2010, 30 April\u20132 May 2010, College Park, Maryland, USA, Springer Berlin Heidelberg.","DOI":"10.1007\/978-3-642-14998-6_2"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Li, T., Hu, E., Li, P., Yang, Z., Wu, Y., Ding, R., Zhu, X., Tang, T., and Wang, Y. (2020). Metabolomics Deciphers Potential Targets of Xuefu Zhuyu Decoction Against Traumatic Brain Injury in Rat. Front. Pharmacol., 11.","DOI":"10.3389\/fphar.2020.559618"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1097\/WNR.0000000000001576","article-title":"UPLC-Q-TOF\/MS-based plasma metabolome to identify biomarkers and time of injury in traumatic brain injured rats","volume":"32","author":"Zhang","year":"2021","journal-title":"Neuroreport"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"e01520","DOI":"10.1002\/brb3.1520","article-title":"Metabolomics analysis of the hippocampus in a rat model of traumatic brain injury during the acute phase","volume":"10","author":"Zheng","year":"2020","journal-title":"Brain Behav."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1007\/s11306-007-0082-2","article-title":"Proposed minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI)","volume":"3","author":"Sumner","year":"2007","journal-title":"Metabolomics"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1007\/s12028-013-9950-y","article-title":"The ketamine effect on ICP in traumatic brain injury","volume":"21","author":"Zeiler","year":"2014","journal-title":"Neurocrit. Care"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1186\/s13054-020-03452-x","article-title":"Ketamine in acute phase of severe traumatic brain injury \u201can old drug for new uses?\u201d","volume":"25","author":"Godoy","year":"2021","journal-title":"Crit. Care"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"e2414316122","DOI":"10.1073\/pnas.2414316122","article-title":"Imaging a concussion and the ensuing immune response at the blood-brain barrier","volume":"122","author":"Nguyen","year":"2025","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Banoei, M.M., Iupe, I., Bazaz, R.D., Campos, M., Vogel, H.J., Winston, B.W., and Mirsaeidi, M. (2019). Metabolomic and metallomic profile differences between Veterans and Civilians with Pulmonary Sarcoidosis. Sci. Rep., 9.","DOI":"10.1038\/s41598-019-56174-8"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1684","DOI":"10.1074\/mcp.M114.046508","article-title":"Optimized Analytical Procedures for the Untargeted Metabolomic Profiling of Human Urine and Plasma by Combining Hydrophilic Interaction (HILIC) and Reverse-Phase Liquid Chromatography (RPLC)-Mass Spectrometry","volume":"14","author":"Contrepois","year":"2015","journal-title":"Mol. Cell. Proteom."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1021\/ac102523q","article-title":"HILIC-UPLC-MS for Exploratory Urinary Metabolic Profiling in Toxicological Studies","volume":"83","author":"Spagou","year":"2011","journal-title":"Anal. Chem."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"3212","DOI":"10.1021\/ac902837x","article-title":"Metabolomic Analysis via Reversed-Phase Ion-Pairing Liquid Chromatography Coupled to a Stand Alone Orbitrap Mass Spectrometer","volume":"82","author":"Lu","year":"2010","journal-title":"Anal. Chem."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"6876","DOI":"10.1021\/ac401140h","article-title":"Toward \u2018omic scale metabolite profiling: A dual separation-mass spectrometry approach for coverage of lipid and central carbon metabolism","volume":"85","author":"Ivanisevic","year":"2013","journal-title":"Anal. Chem."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.jchromb.2013.07.027","article-title":"A novel ion pairing LC\/MS metabolomics protocol for study of a variety of biologically relevant polar metabolites","volume":"936","author":"Knee","year":"2013","journal-title":"J. Chromatogr. B"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"14.11.1","DOI":"10.1002\/0471250953.bi1411s37","article-title":"LC-MS Data Processing with MAVEN: A Metabolomic Analysis and Visualization Engine","volume":"37","author":"Clasquin","year":"2012","journal-title":"Curr. Protoc. Bioinform."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"e86","DOI":"10.1002\/cpbi.86","article-title":"Using MetaboAnalyst 4.0 for Comprehensive and Integrative Metabolomics Data Analysis","volume":"68","author":"Chong","year":"2019","journal-title":"Curr. Protoc. Bioinform."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"43969","DOI":"10.1038\/srep43969","article-title":"Volatile metabolomic signature of human breast cancer cell lines","volume":"7","author":"Silva","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"9818","DOI":"10.1021\/ac1021166","article-title":"Metabolomic analysis and visualization engine for LC-MS data","volume":"82","author":"Melamud","year":"2010","journal-title":"Anal. Chem."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1007\/978-1-4939-9236-2_19","article-title":"El-MAVEN: A Fast, Robust, and User-Friendly Mass Spectrometry Data Processing Engine for Metabolomics","volume":"1978","author":"Agrawal","year":"2019","journal-title":"Methods Mol. Biol."}],"container-title":["International Journal of Molecular Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1422-0067\/27\/14\/6144\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T04:12:20Z","timestamp":1784002340000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1422-0067\/27\/14\/6144"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,9]]},"references-count":49,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2026,7]]}},"alternative-id":["ijms27146144"],"URL":"https:\/\/doi.org\/10.3390\/ijms27146144","relation":{},"ISSN":["1422-0067"],"issn-type":[{"value":"1422-0067","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,9]]}}}