{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T04:51:17Z","timestamp":1782967877033,"version":"3.54.5"},"reference-count":17,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2024,6,19]],"date-time":"2024-06-19T00:00:00Z","timestamp":1718755200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,6,19]],"date-time":"2024-06-19T00:00:00Z","timestamp":1718755200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Youth PhD Advancement Project of Air Force Medical Center, PLA","award":["21ZT07"],"award-info":[{"award-number":["21ZT07"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neuroradiology"],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1007\/s00234-024-03396-x","type":"journal-article","created":{"date-parts":[[2024,6,19]],"date-time":"2024-06-19T09:01:50Z","timestamp":1718787710000},"page":"1291-1299","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Characterizing the relationship between MRI radiomics and AHR expression and deriving a predictive model for prognostic assessment in glioblastoma"],"prefix":"10.1007","volume":"66","author":[{"given":"Chen","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dingkang","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Limin","family":"Meng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongqi","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiguang","family":"Fu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maohui","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaolong","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-6287-0052","authenticated-orcid":false,"given":"Yingjie","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,6,19]]},"reference":[{"issue":"suppl 2","key":"3396_CR1","doi-asserted-by":"publisher","first-page":"ii1","DOI":"10.1093\/neuonc\/not151","volume":"15","author":"QT Ostrom","year":"2013","unstructured":"Ostrom QT, Gittleman H, Farah P et al (2013) CBTRUS Statistical Report: primary brain and central nervous system tumors diagnosed in the United States in 2006\u20132010. Neurooncology 15(suppl 2):ii1\u2013ii56. https:\/\/doi.org\/10.1093\/neuonc\/not151","journal-title":"Neurooncology"},{"key":"3396_CR2","doi-asserted-by":"publisher","unstructured":"Grech N, Dalli T, Mizzi S, Meilak L, Calleja N, Zrinzo A (2020) Rising incidence of Glioblastoma Multiforme in a well-defined Population. Cureus Published Online May 19. https:\/\/doi.org\/10.7759\/cureus.8195","DOI":"10.7759\/cureus.8195"},{"issue":"1","key":"3396_CR3","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1038\/s41392-022-01274-7","volume":"8","author":"L Jing","year":"2023","unstructured":"Jing L, Qian Z, Gao Q et al (2023) Diffuse midline glioma treated with epigenetic agent-based immunotherapy. Sig Transduct Target Ther 8(1):23. https:\/\/doi.org\/10.1038\/s41392-022-01274-7","journal-title":"Sig Transduct Target Ther"},{"issue":"8","key":"3396_CR4","doi-asserted-by":"publisher","first-page":"1231","DOI":"10.1093\/neuonc\/noab106","volume":"23","author":"DN Louis","year":"2021","unstructured":"Louis DN, Perry A, Wesseling P et al (2021) The 2021 WHO classification of tumors of the Central Nervous System: a summary. Neurooncology 23(8):1231\u20131251. https:\/\/doi.org\/10.1093\/neuonc\/noab106","journal-title":"Neurooncology"},{"key":"3396_CR5","doi-asserted-by":"publisher","unstructured":"Mulero-Navarro S, Fernandez-Salguero PM (2016) New trends in Aryl Hydrocarbon receptor Biology. Front Cell Dev Biol 4. https:\/\/doi.org\/10.3389\/fcell.2016.00045","DOI":"10.3389\/fcell.2016.00045"},{"issue":"2","key":"3396_CR6","doi-asserted-by":"publisher","first-page":"422","DOI":"10.1016\/j.drudis.2021.09.021","volume":"27","author":"TX Lim","year":"2022","unstructured":"Lim TX, Ahamed M, Reutens DC (2022) The aryl hydrocarbon receptor: a diagnostic and therapeutic target in glioma. Drug Discovery Today 27(2):422\u2013435. https:\/\/doi.org\/10.1016\/j.drudis.2021.09.021","journal-title":"Drug Discovery Today"},{"issue":"2","key":"3396_CR7","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1007\/s11060-018-2869-6","volume":"139","author":"AR Guastella","year":"2018","unstructured":"Guastella AR, Michelhaugh SK, Klinger NV et al (2018) Investigation of the aryl hydrocarbon receptor and the intrinsic tumoral component of the kynurenine pathway of tryptophan metabolism in primary brain tumors. J Neurooncol 139(2):239\u2013249. https:\/\/doi.org\/10.1007\/s11060-018-2869-6","journal-title":"J Neurooncol"},{"key":"3396_CR8","doi-asserted-by":"publisher","first-page":"691288","DOI":"10.3389\/fonc.2021.691288","volume":"11","author":"D Xu","year":"2021","unstructured":"Xu D, Wei Q, Li Z et al (2021) Development and Validation of Predicting Nomograms for Craniopharyngioma: a retrospective, Multiple-Center, Cohort Study. Front Oncol 11:691288. https:\/\/doi.org\/10.3389\/fonc.2021.691288","journal-title":"Front Oncol"},{"issue":"1","key":"3396_CR9","doi-asserted-by":"publisher","first-page":"198","DOI":"10.1186\/s12916-023-02898-4","volume":"21","author":"C Ma","year":"2023","unstructured":"Ma C, Wang L, Song D et al (2023) Multimodal-based machine learning strategy for accurate and non-invasive prediction of intramedullary glioma grade and mutation status of molecular markers: a retrospective study. BMC Med 21(1):198. https:\/\/doi.org\/10.1186\/s12916-023-02898-4","journal-title":"BMC Med"},{"issue":"1","key":"3396_CR10","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1038\/s41698-021-00205-z","volume":"5","author":"J Yan","year":"2021","unstructured":"Yan J, Zhang B, Zhang S et al (2021) Quantitative MRI-based radiomics for noninvasively predicting molecular subtypes and survival in glioma patients. npj Precis Onc 5(1):72. https:\/\/doi.org\/10.1038\/s41698-021-00205-z","journal-title":"npj Precis Onc"},{"key":"3396_CR11","doi-asserted-by":"publisher","first-page":"949509","DOI":"10.3389\/fimmu.2022.949509","volume":"13","author":"Q Gao","year":"2022","unstructured":"Gao Q, Luo J, Pan J et al (2022) Integrative analyses identify HIF-1\u03b1 as a potential protective role with immune cell infiltration in adamantinomatous craniopharyngioma. Front Immunol 13:949509. https:\/\/doi.org\/10.3389\/fimmu.2022.949509","journal-title":"Front Immunol"},{"key":"3396_CR12","doi-asserted-by":"publisher","first-page":"847624","DOI":"10.3389\/fimmu.2022.847624","volume":"13","author":"J Xie","year":"2022","unstructured":"Xie J, Chen L, Tang Q et al (2022) A necroptosis-related Prognostic Model of Uveal Melanoma was constructed by Single-Cell Sequencing Analysis and Weighted Co-expression Network Analysis Based on Public Databases. Front Immunol 13:847624. https:\/\/doi.org\/10.3389\/fimmu.2022.847624","journal-title":"Front Immunol"},{"issue":"2","key":"3396_CR13","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1093\/toxsci\/kfs158","volume":"128","author":"A Gu","year":"2012","unstructured":"Gu A, Ji G, Jiang T et al (2012) Contributions of Aryl Hydrocarbon Receptor Genetic Variants to the risk of glioma and PAH-DNA adducts. Toxicol Sci 128(2):357\u2013364. https:\/\/doi.org\/10.1093\/toxsci\/kfs158","journal-title":"Toxicol Sci"},{"issue":"12","key":"3396_CR14","doi-asserted-by":"publisher","first-page":"9705","DOI":"10.1007\/s00432-023-04894-w","volume":"149","author":"N Tan","year":"2023","unstructured":"Tan N, Zhao W, Wang Y et al (2023) AHR, a novel inhibitory immune checkpoint receptor, is a potential therapeutic target for chemoresistant glioblastoma. J Cancer Res Clin Oncol 149(12):9705\u20139720. https:\/\/doi.org\/10.1007\/s00432-023-04894-w","journal-title":"J Cancer Res Clin Oncol"},{"issue":"1","key":"3396_CR15","doi-asserted-by":"publisher","first-page":"848","DOI":"10.1186\/s12885-023-11338-8","volume":"23","author":"Z Liu","year":"2023","unstructured":"Liu Z, Hong X, Wang L et al (2023) Radiomic features from multiparametric magnetic resonance imaging predict molecular subgroups of pediatric low-grade gliomas. BMC Cancer 23(1):848. https:\/\/doi.org\/10.1186\/s12885-023-11338-8","journal-title":"BMC Cancer"},{"issue":"4","key":"3396_CR16","doi-asserted-by":"publisher","first-page":"629","DOI":"10.1002\/1878-0261.13380","volume":"17","author":"J Duan","year":"2023","unstructured":"Duan J, Zhang Z, Chen Y et al (2023) Imaging phenotypes from MRI for the prediction of glioma immune subtypes from RNA sequencing: a multicenter study. Mol Oncol 17(4):629\u2013646. https:\/\/doi.org\/10.1002\/1878-0261.13380","journal-title":"Mol Oncol"},{"issue":"28","key":"3396_CR17","doi-asserted-by":"publisher","first-page":"2593","DOI":"10.1038\/onc.2009.104","volume":"28","author":"D Gramatzki","year":"2009","unstructured":"Gramatzki D, Pantazis G, Schittenhelm J et al (2009) Aryl hydrocarbon receptor inhibition downregulates the TGF-\u03b2\/Smad pathway in human glioblastoma cells. Oncogene 28(28):2593\u20132605. https:\/\/doi.org\/10.1038\/onc.2009.104","journal-title":"Oncogene"}],"container-title":["Neuroradiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00234-024-03396-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00234-024-03396-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00234-024-03396-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,13]],"date-time":"2024-07-13T06:04:14Z","timestamp":1720850654000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00234-024-03396-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,19]]},"references-count":17,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2024,8]]}},"alternative-id":["3396"],"URL":"https:\/\/doi.org\/10.1007\/s00234-024-03396-x","relation":{},"ISSN":["0028-3940","1432-1920"],"issn-type":[{"value":"0028-3940","type":"print"},{"value":"1432-1920","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,6,19]]},"assertion":[{"value":"7 February 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 June 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 June 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"No ethics approval was required for this work. All subjects from TCGA had obtained informed consent and ethical approval in the original study.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"The authors declare that they have no conflicts of interest.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}