{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T15:38:17Z","timestamp":1787585897933,"version":"build-2736575974"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T00:00:00Z","timestamp":1763596800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T00:00:00Z","timestamp":1763596800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Psychiatry"],"DOI":"10.1186\/s12888-025-07544-2","type":"journal-article","created":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T07:51:35Z","timestamp":1763625095000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Cortical morphometric inverse divergence alterations in first-episode, treatment-na\u00efve COVID-19 secondary depression correlate with transcriptional signatures"],"prefix":"10.1186","volume":"25","author":[{"given":"Chenlu","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingshi","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-7750-6178","authenticated-orcid":false,"given":"Liaoliao","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,11,20]]},"reference":[{"key":"7544_CR1","doi-asserted-by":"publisher","first-page":"113190","DOI":"10.1016\/j.psychres.2020.113190","volume":"291","author":"M Luo","year":"2020","unstructured":"Luo M, Guo L, Yu M, et al. The psychological and mental impact of coronavirus disease 2019 (COVID-19) on medical staff and general public - a systematic review and meta-analysis. Psychiatry Res. 2020;291:113190.","journal-title":"Psychiatry Res"},{"issue":"6","key":"7544_CR2","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1001\/jama.2020.12603","volume":"324","author":"A Carfi","year":"2020","unstructured":"Carfi A, Bernabei R, Landi F, et al. Persistent symptoms in patients after acute COVID-19. Jama. 2020;324(6):603\u201305.","journal-title":"Jama"},{"issue":"3","key":"7544_CR3","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1038\/s41579-022-00846-2","volume":"21","author":"HE Davis","year":"2023","unstructured":"Davis HE, McCorkell L, Vogel JM, et al. Long covid: major findings, mechanisms and recommendations. Nat Rev Microbiol. 2023;21(3):133\u201346.","journal-title":"Nat Rev Microbiol"},{"issue":"7","key":"7544_CR4","doi-asserted-by":"publisher","first-page":"1511","DOI":"10.1038\/s41380-019-0477-2","volume":"25","author":"van Velzen Ls","year":"2020","unstructured":"van Velzen Ls, Kelly S, Isaev D, et al. White matter disturbances in major depressive disorder: a coordinated analysis across 20 international cohorts in the enigma MDD working group. Mol Psychiatry. 2020;25(7):1511\u201325.","journal-title":"Mol Psychiatry"},{"issue":"1","key":"7544_CR5","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1038\/s41398-022-02113-7","volume":"12","author":"H Lemke","year":"2022","unstructured":"Lemke H, Klute H, Skupski J, et al. Brain structural correlates of recurrence following the first episode in patients with major depressive disorder. Transl Psychiatry. 2022;12(1):349.","journal-title":"Transl Psychiatry"},{"issue":"7","key":"7544_CR6","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1016\/j.biopsych.2014.02.018","volume":"76","author":"MS Korgaonkar","year":"2014","unstructured":"Korgaonkar MS, Fornito A, Williams LM, et al. Abnormal structural networks characterize major depressive disorder: a connectome analysis. Biol Psychiatry. 2014;76(7):567\u201374.","journal-title":"Biol Psychiatry"},{"issue":"7","key":"7544_CR7","doi-asserted-by":"publisher","first-page":"1550","DOI":"10.1038\/s41380-019-0603-1","volume":"25","author":"J Repple","year":"2020","unstructured":"Repple J, Mauritz M, Meinert S, et al. Severity of current depression and remission status are associated with structural connectome alterations in major depressive disorder. Mol Psychiatry. 2020;25(7):1550\u201358.","journal-title":"Mol Psychiatry"},{"issue":"1","key":"7544_CR8","doi-asserted-by":"publisher","first-page":"196","DOI":"10.1038\/s41398-023-02499-y","volume":"13","author":"A Tura","year":"2023","unstructured":"Tura A, Goya-Maldonado R. Brain connectivity in major depressive disorder: a precision component of treatment modalities? Transl Psychiatry. 2023;13(1):196.","journal-title":"Transl Psychiatry"},{"issue":"1","key":"7544_CR9","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1016\/j.neuron.2017.11.039","volume":"97","author":"J Seidlitz","year":"2018","unstructured":"Seidlitz J, Vasa F, Shinn M, et al. Morphometric similarity networks detect microscale cortical organization and predict inter-individual cognitive variation. Neuron. 2018;97(1):231\u201347 e237.","journal-title":"Neuron"},{"issue":"12","key":"7544_CR10","doi-asserted-by":"publisher","first-page":"3713","DOI":"10.1111\/cns.14384","volume":"29","author":"M Cai","year":"2023","unstructured":"Cai M, Ma J, Wang Z, et al. Individual-level brain morphological similarity networks: current methodologies and applications. CNS Neurosci Ther. 2023;29(12):3713\u201324.","journal-title":"CNS Neurosci Ther"},{"issue":"3","key":"7544_CR11","doi-asserted-by":"publisher","first-page":"1146","DOI":"10.1038\/s41380-022-01896-x","volume":"28","author":"X Wu","year":"2023","unstructured":"Wu X, Palaniyappan L, Yu G, et al. Morphometric dis-similarity between cortical and subcortical areas underlies cognitive function and psychiatric symptomatology: a preadolescence study from ABCD. Mol Psychiatry. 2023;28(3):1146\u201358.","journal-title":"Mol Psychiatry"},{"issue":"1","key":"7544_CR12","doi-asserted-by":"publisher","first-page":"1647","DOI":"10.1038\/s41467-021-21943-5","volume":"12","author":"J Li","year":"2021","unstructured":"Li J, Seidlitz J, Suckling J, et al. Cortical structural differences in major depressive disorder correlate with cell type-specific transcriptional signatures. Nat Commun. 2021;12(1):1647.","journal-title":"Nat Commun"},{"key":"7544_CR13","doi-asserted-by":"crossref","unstructured":"Wang T, Xue L, Dai Z, et al. Genetically informed disassortative brain morphometric similarities revealing suicide risk in bipolar disorder. Biol Psychiatry Cogn Neurosci Neuroimaging. 2025.","DOI":"10.1016\/j.bpsc.2025.04.011"},{"issue":"19","key":"7544_CR14","doi-asserted-by":"publisher","first-page":"9604","DOI":"10.1073\/pnas.1820754116","volume":"116","author":"SE Morgan","year":"2019","unstructured":"Morgan SE, Seidlitz J, Whitaker KJ, et al. Cortical patterning of abnormal morphometric similarity in psychosis is associated with brain expression of schizophrenia-related genes. Proc Natl Acad Sci U S A. 2019;116(19):9604\u201309.","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"8","key":"7544_CR15","doi-asserted-by":"publisher","first-page":"1461","DOI":"10.1038\/s41593-023-01376-7","volume":"26","author":"I Sebenius","year":"2023","unstructured":"Sebenius I, Seidlitz J, Warrier V, et al. Robust estimation of cortical similarity networks from brain mri. Nat Neurosci. 2023;26(8):1461\u201371.","journal-title":"Nat Neurosci"},{"issue":"1","key":"7544_CR16","doi-asserted-by":"publisher","first-page":"4237","DOI":"10.1038\/s41467-021-24306-2","volume":"12","author":"A Arnatkeviciute","year":"2021","unstructured":"Arnatkeviciute A, Fulcher BD, Oldham S, et al. Genetic influences on hub connectivity of the human connectome. Nat Commun. 2021;12(1):4237.","journal-title":"Nat Commun"},{"issue":"1","key":"7544_CR17","doi-asserted-by":"publisher","first-page":"1056","DOI":"10.1038\/s42003-022-04028-x","volume":"5","author":"Z Xu","year":"2022","unstructured":"Xu Z, Xia M, Wang X, et al. Meta-connectomic analysis maps consistent, reproducible, and transcriptionally relevant functional connectome hubs in the human brain. Commun Biol. 2022;5(1):1056.","journal-title":"Commun Biol"},{"issue":"12","key":"7544_CR18","doi-asserted-by":"publisher","first-page":"711","DOI":"10.1016\/j.tins.2012.09.005","volume":"35","author":"EH Shen","year":"2012","unstructured":"Shen EH, Overly CC, Jones AR. The allen human brain atlas: comprehensive gene expression mapping of the human brain. Trends Neurosci. 2012;35(12):711\u201314.","journal-title":"Trends Neurosci"},{"key":"7544_CR19","unstructured":"First MB, Gibbon M. The structured clinical interview for DSM-IV axis I disorders (SCID-I) and the structured clinical interview for DSM-IV axis II disorders (SCID-II). 2004."},{"key":"7544_CR20","doi-asserted-by":"publisher","first-page":"473","DOI":"10.1016\/j.jad.2020.09.131","volume":"279","author":"L Costantini","year":"2021","unstructured":"Costantini L, Pasquarella C, Odone A, et al. Screening for depression in primary care with patient health questionnaire-9 (PHQ-9): a systematic review. J Affect Disord. 2021;279:473\u201383.","journal-title":"J Affect Disord"},{"issue":"4","key":"7544_CR21","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1177\/104012371702900404","volume":"29","author":"SA Mossman","year":"2017","unstructured":"Mossman SA, Luft MJ, Schroeder HK, et al. The generalized anxiety disorder 7-item scale in adolescents with generalized anxiety disorder: signal detection and validation. Ann Clin Psychiatry. 2017;29(4):227\u201334A.","journal-title":"Ann Clin Psychiatry"},{"issue":"1","key":"7544_CR22","doi-asserted-by":"publisher","first-page":"e 3285","DOI":"10.1002\/smi.3285","volume":"40","author":"E Yilmaz Kogar","year":"2024","unstructured":"Yilmaz Kogar E, Kogar H. A systematic review and meta-analytic confirmatory factor analysis of the perceived stress scale (PSS-10 and PSS-14). Stress Health. 2024;40(1):e 3285.","journal-title":"Stress Health"},{"issue":"3","key":"7544_CR23","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1016\/S0022-3999(02)00604-9","volume":"55","author":"CR Soldatos","year":"2003","unstructured":"Soldatos CR, Dikeos DG, Paparrigopoulos TJ. The diagnostic validity of the athens insomnia scale. J Psychosom Res. 2003;55(3):263\u201367.","journal-title":"J Psychosom Res"},{"issue":"2","key":"7544_CR24","doi-asserted-by":"publisher","first-page":"774","DOI":"10.1016\/j.neuroimage.2012.01.021","volume":"62","author":"B Fischl","year":"2012","unstructured":"Fischl B. FreeSurfer. Neuroimage. 2012;62(2):774\u201381.","journal-title":"Neuroimage"},{"issue":"4","key":"7544_CR25","doi-asserted-by":"publisher","first-page":"3522","DOI":"10.1016\/j.neuroimage.2011.10.086","volume":"59","author":"R Romero-Garcia","year":"2012","unstructured":"Romero-Garcia R, Atienza M, Clemmensen LH, et al. Effects of network resolution on topological properties of human neocortex. Neuroimage. 2012;59(4):3522\u201332.","journal-title":"Neuroimage"},{"key":"7544_CR26","doi-asserted-by":"publisher","first-page":"118751","DOI":"10.1016\/j.neuroimage.2021.118751","volume":"246","author":"EP Hedges","year":"2022","unstructured":"Hedges EP, Dimitrov M, Zahid U, et al. Reliability of structural mri measurements: the effects of scan session, head tilt, inter-scan interval, acquisition sequence, FreeSurfer version and processing stream. Neuroimage. 2022;246:118751.","journal-title":"Neuroimage"},{"issue":"3","key":"7544_CR27","doi-asserted-by":"publisher","first-page":"1125","DOI":"10.1152\/jn.00338.2011","volume":"106","author":"BT Yeo","year":"2011","unstructured":"Yeo BT, Krienen FM, Sepulcre J, et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J Neurophysiol. 2011;106(3):1125\u201365.","journal-title":"J Neurophysiol"},{"issue":"1","key":"7544_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s00429-012-0382-9","volume":"218","author":"F Cauda","year":"2013","unstructured":"Cauda F, Torta DM, Sacco K, et al. Functional anatomy of cortical areas characterized by Von economo neurons. Brain Struct Funct. 2013;218(1):1\u201320.","journal-title":"Brain Struct Funct"},{"issue":"8","key":"7544_CR29","doi-asserted-by":"publisher","first-page":"665","DOI":"10.1038\/nmeth.1635","volume":"8","author":"T Yarkoni","year":"2011","unstructured":"Yarkoni T, Poldrack RA, Nichols TE, et al. Large-scale automated synthesis of human functional neuroimaging data. Nat Methods. 2011;8(8):665\u201370.","journal-title":"Nat Methods"},{"key":"7544_CR30","doi-asserted-by":"crossref","unstructured":"Markello RD, Arnatkeviciute A, Poline JB, et al. Standardizing workflows in imaging transcriptomics with the abagen toolbox. Elife. 2021;10.","DOI":"10.7554\/eLife.72129"},{"key":"7544_CR31","doi-asserted-by":"publisher","first-page":"549","DOI":"10.1007\/978-1-62703-059-5_23","volume":"930","author":"H Abdi","year":"2013","unstructured":"Abdi H, Williams LJ. Partial least squares methods: partial least squares correlation and partial least square regression. Methods Mol Biol. 2013;930:549\u201379.","journal-title":"Methods Mol Biol"},{"key":"7544_CR32","doi-asserted-by":"publisher","first-page":"120493","DOI":"10.1016\/j.neuroimage.2023.120493","volume":"285","author":"G Yao","year":"2024","unstructured":"Yao G, Luo J, Zou T, et al. Transcriptional patterns of the cortical morphometric inverse divergence in first-episode, treatment-naive early-onset schizophrenia. Neuroimage. 2024;285:120493.","journal-title":"Neuroimage"},{"issue":"1","key":"7544_CR33","doi-asserted-by":"publisher","first-page":"1523","DOI":"10.1038\/s41467-019-09234-6","volume":"10","author":"Y Zhou","year":"2019","unstructured":"Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019;10(1):1523.","journal-title":"Nat Commun"},{"issue":"1","key":"7544_CR34","first-page":"66","volume":"17","author":"MJ Gandal","year":"2019","unstructured":"Gandal MJ, Haney JR, Parikshak NN, et al. Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap. Focus (am Psychiatr Publ). 2019;17(1):66\u201372.","journal-title":"Focus (am Psychiatr Publ)"},{"issue":"3","key":"7544_CR35","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1093\/bib\/bbr049","volume":"13","author":"JH Hung","year":"2012","unstructured":"Hung JH, Yang TH, Hu Z, et al. Gene set enrichment analysis: performance evaluation and usage guidelines. Brief Bioinform. 2012;13(3):281\u201391.","journal-title":"Brief Bioinform"},{"issue":"13","key":"7544_CR36","doi-asserted-by":"publisher","first-page":"4218","DOI":"10.1093\/nar\/gkq130","volume":"38","author":"JD Dougherty","year":"2010","unstructured":"Dougherty JD, Schmidt EF, Nakajima M, et al. Analytical approaches to rna profiling data for the identification of genes enriched in specific cells. Nucleic Acids Res. 2010;38(13):4218\u201330.","journal-title":"Nucleic Acids Res"},{"key":"7544_CR37","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1186\/1471-2105-14-7","volume":"14","author":"S Hanzelmann","year":"2013","unstructured":"Hanzelmann S, Castelo R, Guinney J. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinf. 2013;14:7.","journal-title":"BMC Bioinf"},{"issue":"1","key":"7544_CR38","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1093\/cercor\/bhx249","volume":"28","author":"F Vasa","year":"2018","unstructured":"Vasa F, Seidlitz J, Romero-Garcia R, et al. Adolescent tuning of association cortex in human structural brain networks. Cereb Cortex. 2018;28(1):281\u201394.","journal-title":"Cereb Cortex"},{"issue":"7886","key":"7544_CR39","doi-asserted-by":"publisher","first-page":"628","DOI":"10.1038\/s41586-021-04103-z","volume":"599","author":"JD Backman","year":"2021","unstructured":"Backman JD, Li AH. Marcketta a et al: exome sequencing and analysis of 454, 787 Uk biobank participants. Nature. 2021;599(7886):628\u201334.","journal-title":"Nature"},{"key":"7544_CR40","doi-asserted-by":"crossref","unstructured":"Stoyanov D, Khorev V, Paunova R, et al. Resting-state functional connectivity impairment in patients with major depressive episode. Int J Environ Res Public Health. 2022;19(21).","DOI":"10.3390\/ijerph192114045"},{"issue":"10","key":"7544_CR41","doi-asserted-by":"publisher","first-page":"857","DOI":"10.1631\/jzus.B2300401","volume":"25","author":"W Zheng","year":"2024","unstructured":"Zheng W, Zhang Q, Zhao Z, et al. Aberrant dynamic functional connectivity of thalamocortical circuitry in major depressive disorder. J Zhejiang Univ Sci B. 2024;25(10):857\u201377.","journal-title":"J Zhejiang Univ Sci B"},{"issue":"2","key":"7544_CR42","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1111\/acps.13385","volume":"145","author":"S Varghese","year":"2022","unstructured":"Varghese S, Frey BN, Schneider MA, et al. Functional and cognitive impairment in the first episode of depression: a systematic review. Acta Psychiatr Scand. 2022;145(2):156\u201385.","journal-title":"Acta Psychiatr Scand"},{"issue":"10","key":"7544_CR43","doi-asserted-by":"publisher","first-page":"1032","DOI":"10.1001\/jamapsychiatry.2022.2594","volume":"79","author":"AL Richards","year":"2022","unstructured":"Richards AL, Cardno A, Harold G, et al. Genetic liabilities differentiating bipolar disorder, schizophrenia, and major depressive disorder, and phenotypic heterogeneity in bipolar disorder. JAMA Psychiarty. 2022;79(10):1032\u201339.","journal-title":"JAMA Psychiarty"},{"issue":"6","key":"7544_CR44","first-page":"630","volume":"8","author":"DJ Ardesch","year":"2023","unstructured":"Ardesch DJ, Libedinsky I, Scholtens LH, et al. Convergence of brain transcriptomic and neuroimaging patterns in schizophrenia, bipolar disorder, autism spectrum disorder, and major depressive disorder. Biol Psychiatry Cogn Neurosci Neuroimaging. 2023;8(6):630\u201339.","journal-title":"Biol Psychiatry Cogn Neurosci Neuroimaging"},{"issue":"4","key":"7544_CR45","doi-asserted-by":"publisher","first-page":"534","DOI":"10.1097\/MIB.0000000000001059","volume":"23","author":"BJ Macer","year":"2017","unstructured":"Macer BJ, Prady SL. Mikocka-walus a: antidepressants in inflammatory bowel disease: a systematic review. Inflamm Bowel Dis. 2017;23(4):534\u201350.","journal-title":"Inflamm Bowel Dis"},{"issue":"1","key":"7544_CR46","doi-asserted-by":"publisher","first-page":"997","DOI":"10.1186\/s12967-024-05758-8","volume":"22","author":"C Hu","year":"2024","unstructured":"Hu C, Ge M, Liu Y, et al. From inflammation to depression: key biomarkers for IBD-related major depressive disorder. J Transl Med. 2024;22(1):997.","journal-title":"J Transl Med"},{"issue":"5","key":"7544_CR47","doi-asserted-by":"publisher","first-page":"564","DOI":"10.1176\/appi.ajp.2013.13070920","volume":"171","author":"S Whittle","year":"2014","unstructured":"Whittle S, Lichter R, Dennison M, et al. Structural brain development and depression onset during adolescence: a prospective longitudinal study. Am J Psychiatry. 2014;171(5):564\u201371.","journal-title":"Am J Psychiatry"},{"issue":"1","key":"7544_CR48","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1002\/hup.182","volume":"16","author":"DF Horrobin","year":"2001","unstructured":"Horrobin DF. Phospholipid metabolism and depression: the possible roles of phospholipase A2 and coenzyme A-independent transacylase. Hum Psychopharmacol. 2001;16(1):45\u201352.","journal-title":"Hum Psychopharmacol"},{"key":"7544_CR49","doi-asserted-by":"publisher","first-page":"109840","DOI":"10.1016\/j.intimp.2023.109840","volume":"117","author":"W Lai","year":"2023","unstructured":"Lai W, Huang Z, Li S, et al. Kynurenine pathway metabolites modulated the comorbidity of ibd and depressive symptoms through the immune response. Int Immunopharmacol. 2023;117:109840.","journal-title":"Int Immunopharmacol"},{"key":"7544_CR50","unstructured":"!!! INVALID CITATION !."},{"issue":"1","key":"7544_CR51","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1186\/s12974-022-02492-0","volume":"19","author":"H Wang","year":"2022","unstructured":"Wang H, He Y, Sun Z, et al. Microglia in depression: an overview of microglia in the pathogenesis and treatment of depression. J Neuroinflammation. 2022;19(1):132.","journal-title":"J Neuroinflammation"},{"key":"7544_CR52","doi-asserted-by":"publisher","first-page":"109252","DOI":"10.1016\/j.neuropharm.2022.109252","volume":"220","author":"YF Zhao","year":"2022","unstructured":"Zhao YF, Verkhratsky A, Tang Y, et al. Astrocytes and major depression: the purinergic avenue. Neuropharmacology. 2022;220:109252.","journal-title":"Neuropharmacology"},{"issue":"1","key":"7544_CR53","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1038\/s41398-022-02128-0","volume":"12","author":"NY Larsen","year":"2022","unstructured":"Larsen NY, Vihrs N, Moller J, et al. Layer III pyramidal cells in the prefrontal cortex reveal morphological changes in subjects with depression, schizophrenia, and suicide. Transl Psychiatry. 2022;12(1):363.","journal-title":"Transl Psychiatry"},{"issue":"3","key":"7544_CR54","doi-asserted-by":"publisher","first-page":"518","DOI":"10.1038\/s41386-022-01474-3","volume":"48","author":"K Xue","year":"2023","unstructured":"Xue K, Guo L, Zhu W, et al. Transcriptional signatures of the cortical morphometric similarity network gradient in first-episode, treatment-naive major depressive disorder. Neuropsychopharmacology. 2023;48(3):518\u201328.","journal-title":"Neuropsychopharmacology"}],"container-title":["BMC Psychiatry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12888-025-07544-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12888-025-07544-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12888-025-07544-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T09:04:05Z","timestamp":1763629445000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcpsychiatry.biomedcentral.com\/articles\/10.1186\/s12888-025-07544-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,20]]},"references-count":54,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["7544"],"URL":"https:\/\/doi.org\/10.1186\/s12888-025-07544-2","relation":{},"ISSN":["1471-244X"],"issn-type":[{"value":"1471-244X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,20]]},"assertion":[{"value":"13 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 October 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 November 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The protocol of this study was approved by the Ethics Committee of The Affiliated Yueqing Hospital of Wenzhou Medical University (ID: YQYY202500055), and was carried out in compliance with the Declaration of Helsinki. All written informed consents were acquired from all participants prior to the extensive screening procedure.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that there are no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"1110"}}