{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T04:58:26Z","timestamp":1790398706192,"version":"4.1.0"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T00:00:00Z","timestamp":1782518400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T00:00:00Z","timestamp":1790121600000},"content-version":"vor","delay-in-days":88,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"National Key R&D Program of China","award":["2021YFC2301700"],"award-info":[{"award-number":["2021YFC2301700"]}]},{"name":"Beijing Scholars Program","award":["099"],"award-info":[{"award-number":["099"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-026-58573-0","type":"journal-article","created":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T12:55:50Z","timestamp":1782564950000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["CIST: A clade-informed sequence transformer framework for predicting influenza virus antigenicity"],"prefix":"10.1038","volume":"16","author":[{"given":"Kang","family":"Hu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongshan","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingchuan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,27]]},"reference":[{"key":"58573_CR1","doi-asserted-by":"publisher","first-page":"2336357","DOI":"10.1080\/21645515.2024.2336357","volume":"20","author":"CA Russell","year":"2024","unstructured":"Russell, C. A. Seasonal influenza vaccine performance and the potential benefits of mRNA vaccines. Hum. Vaccines \\& Immunotherapeutics. 20, 2336357 (2024).","journal-title":"Hum. Vaccines \\& Immunotherapeutics"},{"key":"58573_CR2","doi-asserted-by":"publisher","first-page":"126381","DOI":"10.1016\/j.vaccine.2024.126381","volume":"42","author":"YJ Choi","year":"2024","unstructured":"Choi, Y. J. Real-world effectiveness of influenza vaccine over a decade during the 2011\u20132021 seasons\u2014Implications of vaccine mismatch. Vaccine 42, 126381 (2024).","journal-title":"Vaccine"},{"key":"58573_CR3","doi-asserted-by":"publisher","first-page":"976","DOI":"10.1126\/science.1244730","volume":"342","author":"BF Koel","year":"2013","unstructured":"Koel, B. F. et al. Substitutions Near the Receptor Binding Site Determine Major Antigenic Change During Influenza Virus Evolution. Science 342, 976\u2013979. https:\/\/doi.org\/10.1126\/science.1244730 (2013).","journal-title":"Science"},{"key":"58573_CR4","doi-asserted-by":"publisher","first-page":"101128mbio00230","DOI":"10.1128\/mBio.00230-13","volume":"4","author":"H Sun","year":"2013","unstructured":"Sun, H. et al. Using Sequence Data To Infer the Antigenicity of Influenza Virus. mBio 4, 101128mbio00230\u2013101128mbio00213 (2013).","journal-title":"mBio"},{"key":"58573_CR5","doi-asserted-by":"publisher","first-page":"e00689","DOI":"10.1128\/jvi.00689-24","volume":"98","author":"AN Loes","year":"2024","unstructured":"Loes, A. N. High-throughput sequencing-based neutralization assay reveals how repeated vaccinations impact titers to recent human H1N1 influenza strains. J. Virol. 98, e00689\u2013e00624 (2024).","journal-title":"J. Virol."},{"key":"58573_CR6","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1093\/infdis\/jiae122","volume":"230","author":"WW Lim","year":"2024","unstructured":"Lim, W. W., Feng, S., Wong, S. S., Sullivan, S. G. & Cowling, B. J. Hemagglutination Inhibition Antibody Titers as Mediators of Influenza Vaccine Efficacy Against Symptomatic Influenza A(H1N1), A(H3N2), and B\/Victoria Virus Infections. J. Infect. Dis. 230, 152\u2013160 (2024).","journal-title":"J. Infect. Dis."},{"key":"58573_CR7","doi-asserted-by":"publisher","first-page":"e13286","DOI":"10.1111\/irv.13286","volume":"18","author":"J Youhanna","year":"2024","unstructured":"Youhanna, J., Tran, V., Hyer, R. & Domnich, A. Immunogenicity of Enhanced Influenza Vaccines Against Mismatched Influenza Strains in Older Adults: A Review of Randomized Controlled Trials. Influenza Other Respir. Viruses. 18, e13286 (2024).","journal-title":"Influenza Other Respir. Viruses"},{"key":"58573_CR8","doi-asserted-by":"crossref","unstructured":"Bibby, D. C. et al. & Interlaboratory Reproducibility of Standardized Hemagglutination Inhibition Assays. mSphere 7, (2022).","DOI":"10.1128\/msphere.00953-21"},{"key":"58573_CR9","doi-asserted-by":"publisher","first-page":"21364","DOI":"10.1038\/s41598-025-03275-2","volume":"15","author":"F Durazzi","year":"2025","unstructured":"Durazzi, F., Koopmans, M. P. G., Fouchier, R. A. M. & Remondini, D. Language models learn to represent antigenic properties of human influenza A(H3) virus. Sci. Rep. 15, 21364. https:\/\/doi.org\/10.1038\/s41598-025-03275-2 (2025).","journal-title":"Sci. Rep."},{"key":"58573_CR10","doi-asserted-by":"publisher","first-page":"2690","DOI":"10.1080\/21645515.2020.1734397","volume":"16","author":"EK Lee","year":"2020","unstructured":"Lee, E. K., Tian, H. & Nakaya, H. I. Antigenicity prediction and vaccine recommendation of human influenza virus A (H3N2) using convolutional neural networks. Hum. Vaccines \\& Immunotherapeutics. 16, 2690\u20132708 (2020).","journal-title":"Hum. Vaccines \\& Immunotherapeutics"},{"key":"58573_CR11","doi-asserted-by":"publisher","first-page":"68","DOI":"10.3390\/antib14030068","volume":"14","author":"J Prechl","year":"2025","unstructured":"Prechl, J., Kov\u00e1cs, \u00c1., Papp, K., H\u00e9rincs, Z. & Pfeil, T. A 3D Surface Plot for the Effective Visualization of Specific Serum Antibody Binding Properties. Antibodies 14, 68. (2025). https:\/\/doi.org\/10.3390\/antib14030068","journal-title":"Antibodies"},{"key":"58573_CR12","doi-asserted-by":"publisher","first-page":"973","DOI":"10.46234\/ccdcw2025.164","volume":"7","author":"J Feng","year":"2025","unstructured":"Feng, J. Mapping the Global Antigenic Evolution of Human Influenza A\/H3N2 Neuraminidase Based on a Machine Learning Model\u2009\u2013\u20091968\u20132024. China CDC Wkly. 7, 973\u2013978 (2025).","journal-title":"China CDC Wkly."},{"key":"58573_CR13","doi-asserted-by":"publisher","first-page":"1345794","DOI":"10.3389\/fmicb.2024.1345794","volume":"15","author":"X Li","year":"2024","unstructured":"Li, X., Li, Y., Shang, X. & Kong, H. A sequence-based machine learning model for predicting antigenic distance for H3N2 influenza virus. Front. Microbiol. 15, 1345794 (2024). https:\/\/doi.org\/10.3389\/fmicb.2024.1345794","journal-title":"Front. Microbiol."},{"key":"58573_CR14","doi-asserted-by":"publisher","first-page":"3833","DOI":"10.1038\/s41467-024-47862-9","volume":"15","author":"SAW Shah","year":"2024","unstructured":"Shah, S. A. W. et al. Seasonal antigenic prediction of influenza A H3N2 using machine learning. Nat. Commun. 15, 3833 (2024).","journal-title":"Nat. Commun."},{"key":"58573_CR15","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1016\/j.virol.2022.02.004","volume":"569","author":"X Chen","year":"2022","unstructured":"Chen, X. Functional antibody-dependent cell mediated cytotoxicity (ADCC) responses to vaccine and circulating influenza strains following vaccination. Virology 569, 44\u201355 (2022).","journal-title":"Virology"},{"key":"58573_CR16","doi-asserted-by":"publisher","first-page":"bbae033","DOI":"10.1093\/bib\/bbae033","volume":"25","author":"J Meng","year":"2024","unstructured":"Meng, J. PREDAC-CNN: predicting antigenic clusters of seasonal influenza A viruses with convolutional neural network. Brief. Bioinform. 25, bbae033 (2024).","journal-title":"Brief. Bioinform."},{"key":"58573_CR17","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1111\/imcb.12312","volume":"98","author":"HA Vanderven","year":"2020","unstructured":"Vanderven, H. A. & Kent, S. J. The protective potential of Fc-mediated antibody functions against influenza virus and other viral pathogens. Immunol. Cell Biol. 98, 253\u2013263 (2020).","journal-title":"Immunol. Cell Biol."},{"key":"58573_CR18","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1111\/imr.13393","volume":"328","author":"JE Edgar","year":"2024","unstructured":"Edgar, J. E. & Bournazos, S. Fc-Fc \\ensuremath \\gamma R interactions during infections: From neutralizing antibodies to antibody-dependent enhancement. Immunol. Rev. 328, 221\u2013242 (2024).","journal-title":"Immunol. Rev."},{"key":"58573_CR19","doi-asserted-by":"publisher","first-page":"104350","DOI":"10.1016\/j.ebiom.2022.104350","volume":"86","author":"M Zhang","year":"2022","unstructured":"Zhang, M. et al. Retrospective immunogenicity analysis of seasonal flu H3N2 vaccines recommended in the past ten years using immunized animal sera. EBioMedicine 86, 104350. https:\/\/doi.org\/10.1016\/j.ebiom.2022.104350 (2022).","journal-title":"EBioMedicine"},{"key":"58573_CR20","doi-asserted-by":"publisher","first-page":"30494","DOI":"10.2807\/1560-7917.es.2017.22.13.30494","volume":"22","author":"Y Shu","year":"2017","unstructured":"Shu, Y. & McCauley, J. G. I. S. A. I. D. Global initiative on sharing all influenza data - from vision to reality. Euro. Surveill. 22, 30494. https:\/\/doi.org\/10.2807\/1560-7917.es.2017.22.13.30494 (2017).","journal-title":"Euro. Surveill"},{"key":"58573_CR21","doi-asserted-by":"publisher","first-page":"1155880","DOI":"10.3389\/fimmu.2023.1155880","volume":"14","author":"S Sawant","year":"2023","unstructured":"Sawant, S. et al. H3N2 influenza hemagglutination inhibition method qualification with data driven statistical methods for human clinical trials. Front. Immunol. 14, 1155880 (2023). https:\/\/doi.org\/10.3389\/fimmu.2023.1155880","journal-title":"Front. Immunol."},{"key":"58573_CR22","doi-asserted-by":"publisher","first-page":"1545","DOI":"10.1038\/s41598-017-01699-z","volume":"7","author":"Y Yao","year":"2017","unstructured":"Yao, Y. Predicting influenza antigenicity from Hemagglutintin sequence data based on a joint random forest method. Sci. Rep. 7, 1545 (2017).","journal-title":"Sci. Rep."},{"key":"58573_CR23","doi-asserted-by":"publisher","first-page":"936","DOI":"10.1186\/s12864-018-5282-9","volume":"19","author":"X Zhou","year":"2018","unstructured":"Zhou, X., Yin, R., Kwoh, C. K. & Zheng, J. A context-free encoding scheme of protein sequences for predicting antigenicity of diverse influenza A viruses. BMC Genom. 19, 936 (2018).","journal-title":"BMC Genom."},{"key":"58573_CR24","doi-asserted-by":"publisher","first-page":"1286","DOI":"10.1016\/j.csbj.2025.03.038","volume":"27","author":"E Barkan","year":"2025","unstructured":"Barkan, E. Leveraging large language models to predict antibody biological activity against influenza A hemagglutinin. Comput. Struct. Biotechnol. J. 27, 1286\u20131295 (2025).","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"58573_CR25","doi-asserted-by":"publisher","first-page":"e1009566","DOI":"10.1371\/journal.ppat.1009566","volume":"17","author":"J West","year":"2021","unstructured":"West, J. et al. Characterization of changes in the hemagglutinin that accompanied the emergence of H3N2\/1968 pandemic influenza viruses. PLoS Pathog. 17, e1009566. https:\/\/doi.org\/10.1371\/journal.ppat.1009566 (2021).","journal-title":"PLoS Pathog"},{"key":"58573_CR26","doi-asserted-by":"publisher","DOI":"10.64898\/2026.02.10.704996","author":"B Koel","year":"2026","unstructured":"Koel, B. et al. Emergence and antigenic characterisation of influenza A(H3N2) viruses with hemagglutinin substitutions N158K and K189R during the 2024\/25 influenza season. bioRxiv https:\/\/doi.org\/10.64898\/2026.02.10.704996 (2026).","journal-title":"bioRxiv"},{"key":"58573_CR27","doi-asserted-by":"publisher","first-page":"27190","DOI":"10.1038\/s41598-024-72716-1","volume":"14","author":"S Urdy","year":"2024","unstructured":"Urdy, S. et al. Multi-strain modeling of influenza vaccine effectiveness in older adults and its dependence on antigenic distance. Sci. Rep. 14, 27190. https:\/\/doi.org\/10.1038\/s41598-024-72716-1 (2024).","journal-title":"Sci. Rep."},{"key":"58573_CR28","doi-asserted-by":"publisher","first-page":"859","DOI":"10.3390\/vaccines13080859","volume":"13","author":"AM Martins","year":"2025","unstructured":"Martins, A. M., Juan, V., Santos, L. F., Martins, J. P. & M. & Immunogenicity as a Predictor of Influenza Vaccine Efficacy: A Systematic Review. Vaccines 13, 859 (2025). https:\/\/doi.org\/10.3390\/vaccines13080859","journal-title":"Vaccines"},{"key":"58573_CR29","doi-asserted-by":"publisher","first-page":"eabp9185","DOI":"10.1126\/sciadv.abp9185","volume":"9","author":"M Hayati","year":"2023","unstructured":"Hayati, M., Sobkowiak, B., Stockdale, J. E. & Colijn, C. Phylogenetic identification of influenza virus candidates for seasonal vaccines. Sci. Adv. 9, eabp9185 (2023).","journal-title":"Sci. Adv."},{"key":"58573_CR30","doi-asserted-by":"publisher","first-page":"1254","DOI":"10.1109\/TCBB.2024.3378468","volume":"21","author":"C Cai","year":"2024","unstructured":"Cai, C., Li, J., Xia, Y. & Li, W. F. P. M. T. Prediction of Predominant Strains of Influenza A Viruses via Multi-Task Learning. IEEE\/ACM Trans. Comput. Biol. Bioinf. 21, 1254\u20131263. https:\/\/doi.org\/10.1109\/TCBB.2024.3378468 (2024).","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinf."},{"key":"58573_CR31","doi-asserted-by":"publisher","first-page":"e70044","DOI":"10.1111\/irv.70044","volume":"18","author":"LK Borkenhagen","year":"2024","unstructured":"Borkenhagen, L. K. & Runstadler, J. A. Examining the Influenza A Virus Sialic Acid Binding Preference Predictions of a Sequence-Based Convolutional Neural Network. Influenza Other Respir. Viruses. 18, e70044. https:\/\/doi.org\/10.1111\/irv.70044 (2024).","journal-title":"Influenza Other Respir. Viruses"}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-58573-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-58573-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-58573-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T04:02:12Z","timestamp":1790395332000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-58573-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,27]]},"references-count":31,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["58573"],"URL":"https:\/\/doi.org\/10.1038\/s41598-026-58573-0","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,27]]},"assertion":[{"value":"6 February 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 June 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 June 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"29586"}}