{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,4]],"date-time":"2026-11-04T19:51:55Z","timestamp":1793821915705,"version":"4.6.1"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T00:00:00Z","timestamp":1779235200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T00:00:00Z","timestamp":1784764800000},"content-version":"vor","delay-in-days":64,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2234910"],"award-info":[{"award-number":["2234910"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2149956"],"award-info":[{"award-number":["2149956"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2149956"],"award-info":[{"award-number":["2149956"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2525493"],"award-info":[{"award-number":["2525493"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2525493"],"award-info":[{"award-number":["2525493"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"US NSF","doi-asserted-by":"crossref","award":["2234910"],"award-info":[{"award-number":["2234910"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000001","name":"US NSF","doi-asserted-by":"crossref","award":["2200138"],"award-info":[{"award-number":["2200138"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000001","name":"US NSF","doi-asserted-by":"crossref","award":["2234910"],"award-info":[{"award-number":["2234910"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-026-53625-x","type":"journal-article","created":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T10:57:29Z","timestamp":1779274649000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Explainable convolutional neural network model provides an alternative genome-wide association perspective on mutations in SARS-CoV-2"],"prefix":"10.1038","volume":"16","author":[{"given":"Parisa","family":"Hatami","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard","family":"Annan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luis","family":"Miranda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jane","family":"Gorman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengjun","family":"Xie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Letu","family":"Qingge","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong","family":"Qin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,20]]},"reference":[{"key":"53625_CR1","doi-asserted-by":"crossref","unstructured":"Yan, D., Qin, H., Wu, H. Y. & Chen, J. Y. Editorial: AI-enabled data science for COVID-19. Front Big Data 4, (2021).","DOI":"10.3389\/fdata.2021.802452"},{"key":"53625_CR2","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1007\/s44163-023-00049-5","volume":"3","author":"N Ghaffar Nia","year":"2023","unstructured":"Ghaffar Nia, N., Kaplanoglu, E. & Nasab, A. Evaluation of artificial intelligence techniques in disease diagnosis and prediction. Discover Artif. Intell. 3, 5 (2023).","journal-title":"Discover Artif. Intell."},{"key":"53625_CR3","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1016\/j.csbj.2024.12.027","volume":"27","author":"A Budhkar","year":"2025","unstructured":"Budhkar, A., Song, Q., Su, J. & Zhang, X. Demystifying the black box: A survey on explainable artificial intelligence (XAI) in bioinformatics. Comput. Struct. Biotechnol. J. 27, 346\u2013359 (2025).","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"53625_CR4","unstructured":"Lundberg, S. M. & Lee, S. I. A unified approach to interpreting model predictions. In Advances in Neural Information Processing Systems (eds Guyon, I. et al.) Vol. 30 (Curran Associates, Inc., 2017)."},{"key":"53625_CR5","doi-asserted-by":"publisher","first-page":"1327","DOI":"10.1126\/science.abm1208","volume":"376","author":"F Obermeyer","year":"2022","unstructured":"Obermeyer, F. et al. Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness. Science 376, 1327\u20131332 (2022).","journal-title":"Science"},{"key":"53625_CR6","doi-asserted-by":"publisher","first-page":"e1012469","DOI":"10.1371\/journal.pcbi.1012469","volume":"20","author":"K Li","year":"2024","unstructured":"Li, K. et al. Genome-wide association study between SARS-CoV-2 single nucleotide polymorphisms and virus copies during infections. PLoS Comput. Biol. 20, e1012469 (2024).","journal-title":"PLoS Comput. Biol."},{"key":"53625_CR7","doi-asserted-by":"crossref","unstructured":"Sigala, R. E. et al. Machine learning to advance human genome-wide association studies. Genes (Basel) 15, (2024).","DOI":"10.3390\/genes15010034"},{"key":"53625_CR8","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1038\/s43586-021-00056-9","volume":"1","author":"E Uffelmann","year":"2021","unstructured":"Uffelmann, E. et al. Genome-wide association studies. Nat. Reviews Methods Primers. 1, 59 (2021).","journal-title":"Nat. Reviews Methods Primers"},{"key":"53625_CR9","unstructured":"World Health Organization (WHO). Updated working definitions and primary actions for SARSCoV2 variants. https:\/\/www.who.int\/publications\/m\/item\/updated-working-definitions-and-primary-actions-for--sars-cov-2-variants."},{"key":"53625_CR10","doi-asserted-by":"publisher","first-page":"409","DOI":"10.1038\/s41579-021-00573-0","volume":"19","author":"WT Harvey","year":"2021","unstructured":"Harvey, W. T. et al. SARS-CoV-2 variants, spike mutations and immune escape. Nat. Rev. Microbiol. 19, 409\u2013424 (2021).","journal-title":"Nat. Rev. Microbiol."},{"key":"53625_CR11","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1038\/s41579-022-00841-7","volume":"21","author":"AM Carabelli","year":"2023","unstructured":"Carabelli, A. M. et al. SARS-CoV-2 variant biology: immune escape, transmission and fitness. Nat. Rev. Microbiol. 21, 162\u2013177 (2023).","journal-title":"Nat. Rev. Microbiol."},{"key":"53625_CR12","doi-asserted-by":"crossref","unstructured":"Yektadoust, E., Janghorbani, A. & Talebi, A. F. XCNN-SC: Explainable CNN for SARS-CoV-2 variants classification and mutation detection. Comput. Biol. Med. 167\u00a0(2023).","DOI":"10.1016\/j.compbiomed.2023.107606"},{"key":"53625_CR13","unstructured":"GISAID. GISAID - gisaid.org. https:\/\/gisaid.org\/."},{"key":"53625_CR14","doi-asserted-by":"crossref","unstructured":"Shu, Y. & McCauley, J. GISAID: Global initiative on sharing all influenza data \u2013 from vision to reality. Eurosurveillance 22, (2017).","DOI":"10.2807\/1560-7917.ES.2017.22.13.30494"},{"key":"53625_CR15","doi-asserted-by":"publisher","first-page":"31","DOI":"10.17849\/insm-47-01-31-39.1","volume":"47","author":"SJ Rigatti","year":"2017","unstructured":"Rigatti, S. J. Random Forest. J. Insur Med. 47, 31\u201339 (2017).","journal-title":"J. Insur Med."},{"key":"53625_CR16","doi-asserted-by":"publisher","unstructured":"Chen, T., & Guestrin, C. XGBoost: A scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 785\u2013794. https:\/\/doi.org\/10.1145\/2939672.2939785 (Association for Computing Machinery, 2016).","DOI":"10.1145\/2939672.2939785"},{"key":"53625_CR17","unstructured":"Prokhorenkova, L., Gusev, G., Vorobev, A., Dorogush, A. V. & Gulin, A. CatBoost: unbiased boosting with categorical features. In Proceedings of the 32nd International Conference on Neural Information Processing Systems 6639\u20136649 (Curran Associates Inc., 2018)."},{"key":"53625_CR18","doi-asserted-by":"publisher","DOI":"10.3390\/v14112375","author":"MK Kurpas","year":"2022","unstructured":"Kurpas, M. K., Jaksik, R., Ku\u015b, P. & Kimmel, M. Genomic analysis of SARS-CoV-2 Alpha, Beta and Delta variants of concern uncovers signatures of neutral and non-neutral evolution. Viruses https:\/\/doi.org\/10.3390\/v14112375 (2022).","journal-title":"Viruses"},{"key":"53625_CR19","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1002\/jmv.27515","volume":"94","author":"M Kandeel","year":"2022","unstructured":"Kandeel, M., Mohamed, M. E. M., El-Lateef, A., Venugopala, H. M., & El-Beltagi, H. S. Omicron variant genome evolution and phylogenetics. J. Med. Virol. 94, 1627\u20131632 (2022).","journal-title":"J. Med. Virol."},{"key":"53625_CR20","doi-asserted-by":"publisher","first-page":"1063","DOI":"10.1038\/s41564-022-01155-3","volume":"7","author":"X Sun","year":"2022","unstructured":"Sun, X. et al. Neutralization mechanism of a human antibody with pan-coronavirus reactivity including SARS-CoV-2. Nat. Microbiol. 7, 1063\u20131074 (2022).","journal-title":"Nat. Microbiol."},{"key":"53625_CR21","doi-asserted-by":"publisher","first-page":"1230","DOI":"10.1038\/s41591-021-01378-7","volume":"27","author":"FG Naveca","year":"2021","unstructured":"Naveca, F. G. et al. COVID-19 in Amazonas, Brazil, was driven by the persistence of endemic lineages and P.1 emergence. Nat. Med. 27, 1230\u20131238 (2021).","journal-title":"Nat. Med."},{"key":"53625_CR22","first-page":"e01511","volume":"10","author":"WP Lamb","year":"2022","unstructured":"Lamb, W. P. et al. Genomic surveillance of SARS-CoV-2 lineages indicates early circulation of P.1 (gamma) variant of concern in southern Brazil. Microbiol. Spectr. 10, e01511\u2013e01521 (2022).","journal-title":"Microbiol. Spectr."},{"key":"53625_CR23","doi-asserted-by":"publisher","first-page":"980","DOI":"10.1016\/j.ijbiomac.2022.07.254","volume":"219","author":"C Chakraborty","year":"2022","unstructured":"Chakraborty, C., Bhattacharya, M., Sharma, A. R. & Mallik, B. Omicron (B.1.1.529) - A new heavily mutated variant: Mapped location and probable properties of its mutations with an emphasis on S-glycoprotein. Int. J. Biol. Macromol. 219, 980\u2013997 (2022).","journal-title":"Int. J. Biol. Macromol."},{"key":"53625_CR24","doi-asserted-by":"publisher","unstructured":"Yurkovetskiy, L. et al. S:D614G and S:H655Y are gateway mutations that act epistatically to promote SARS-CoV-2 variant fitness. bioRxiv 03.30.535005 https:\/\/doi.org\/10.1101\/2023.03.30.535005 (2023).","DOI":"10.1101\/2023.03.30.535005"},{"key":"53625_CR25","doi-asserted-by":"publisher","first-page":"5189","DOI":"10.1002\/jmv.27964","volume":"94","author":"CAK Cruz","year":"2022","unstructured":"Cruz, C. A. K. & Medina, P. M. B. Temporal changes in the accessory protein mutations of SARS-CoV-2 variants and their predicted structural and functional effects. J. Med. Virol. 94, 5189\u20135200 (2022).","journal-title":"J. Med. Virol."},{"key":"53625_CR26","doi-asserted-by":"publisher","first-page":"18644","DOI":"10.1038\/s41598-023-45517-1","volume":"13","author":"MA Islam","year":"2023","unstructured":"Islam, M. A. et al. Some common deleterious mutations are shared in SARS-CoV-2 genomes from deceased COVID-19 patients across continents. Sci. Rep. 13, 18644 (2023).","journal-title":"Sci. Rep."},{"key":"53625_CR27","doi-asserted-by":"publisher","first-page":"666","DOI":"10.1038\/s42003-022-03565-9","volume":"5","author":"MD Parker","year":"2022","unstructured":"Parker, M. D. et al. Altered subgenomic RNA abundance provides unique insight into SARS-CoV-2 B.1.1.7\/Alpha variant infections. Commun. Biol. 5, 666 (2022).","journal-title":"Commun. Biol."},{"key":"53625_CR28","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/j.chom.2021.11.013","volume":"30","author":"C Liu","year":"2022","unstructured":"Liu, C. et al. The antibody response to SARS-CoV-2 Beta underscores the antigenic distance to other variants. Cell. Host Microbe. 30, 53\u201368 (2022).","journal-title":"Cell. Host Microbe"},{"key":"53625_CR29","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1007\/s00705-022-05365-2","volume":"167","author":"M Salehi-Vaziri","year":"2022","unstructured":"Salehi-Vaziri, M. et al. The ins and outs of SARS-CoV-2 variants of concern (VOCs). Arch. Virol. 167, 327\u2013344 (2022).","journal-title":"Arch. Virol."},{"key":"53625_CR30","doi-asserted-by":"publisher","first-page":"871","DOI":"10.3390\/v15040871","volume":"15","author":"A Arduini","year":"2023","unstructured":"Arduini, A., Laprise, F. & Liang, C. SARS-CoV-2 ORF8: A rapidly evolving immune and viral modulator in COVID-19. Viruses 15, 871 (2023).","journal-title":"Viruses"},{"key":"53625_CR31","doi-asserted-by":"publisher","DOI":"10.1016\/j.bjid.2021.101606","volume":"25","author":"M Mohammadi","year":"2021","unstructured":"Mohammadi, M., Shayestehpour, M. & Mirzaei, H. The impact of spike mutated variants of SARS-CoV2 [Alpha, Beta, Gamma, Delta, and Lambda] on the efficacy of subunit recombinant vaccines. Braz. J. Infect. Dis. 25, 101606 (2021).","journal-title":"Braz. J. Infect. Dis."},{"key":"53625_CR32","unstructured":"World Health Organization (WHO). Weekly epidemiological update on COVID-19\u201325. May 2021. https:\/\/www.who.int\/publications\/m\/item\/weekly-epidemiological-update-on-covid-19---25-may-2021 (2021)."},{"key":"53625_CR33","doi-asserted-by":"publisher","first-page":"2554","DOI":"10.1038\/s41423-021-00767-9","volume":"18","author":"SC Jordan","year":"2021","unstructured":"Jordan, S. C. et al. T cell immune responses to SARS-CoV-2 and variants of concern (Alpha and Delta) in infected and vaccinated individuals. Cell. Mol. Immunol. 18, 2554\u20132556 (2021).","journal-title":"Cell. Mol. Immunol."},{"key":"53625_CR34","doi-asserted-by":"publisher","first-page":"1288","DOI":"10.3390\/microorganisms11051288","volume":"11","author":"FA Alsuwairi","year":"2023","unstructured":"Alsuwairi, F. A. et al. Association of SARS-CoV-2 nucleocapsid protein mutations with patient demographic and clinical characteristics during the Delta and Omicron waves. Microorganisms 11, 1288 (2023).","journal-title":"Microorganisms"},{"key":"53625_CR35","unstructured":"SARS-CoV-2 Variants. - Omicron BA.1 - Stanford Coronavirus Antiviral & Resistance Database (CoVDB). https:\/\/covdb.stanford.edu\/variants\/omicron_ba_1_3\/."},{"key":"53625_CR36","doi-asserted-by":"publisher","first-page":"1150","DOI":"10.3390\/v16071150","volume":"16","author":"V Mahase","year":"2024","unstructured":"Mahase, V. et al. Impact of missense mutations on spike protein stability and binding affinity in the Omicron variant. Viruses 16, 1150 (2024).","journal-title":"Viruses"},{"key":"53625_CR37","doi-asserted-by":"publisher","first-page":"812","DOI":"10.1016\/j.cell.2020.06.043","volume":"182","author":"B Korber","year":"2020","unstructured":"Korber, B. et al. Tracking changes in SARS-CoV-2 spike: Evidence that D614G increases infectivity of the COVID-19 virus. Cell 182, 812\u2013827 (2020).","journal-title":"Cell"},{"key":"53625_CR38","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1038\/s41586-020-2895-3","volume":"592","author":"JA Plante","year":"2021","unstructured":"Plante, J. A. et al. Spike mutation D614G alters SARS-CoV-2 fitness. Nature 592, 116\u2013121 (2021).","journal-title":"Nature"},{"key":"53625_CR39","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1038\/s41590-020-00808-x","volume":"22","author":"A Nelde","year":"2021","unstructured":"Nelde, A. et al. SARS-CoV-2-derived peptides define heterologous and COVID-19-induced T cell recognition. Nat. Immunol. 22, 74\u201385 (2021).","journal-title":"Nat. Immunol."},{"key":"53625_CR40","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2021.708264","volume":"12","author":"N Redondo","year":"2021","unstructured":"Redondo, N., Zald\u00edvar-L\u00f3pez, S., Garrido, J. J. & Montoya, M. SARS-CoV-2 accessory proteins in viral pathogenesis: Knowns and unknowns. Front. Immunol. 12, 708264 (2021).","journal-title":"Front. Immunol."},{"key":"53625_CR41","unstructured":"Li, W. H. Molecular Evolution (Sinauer Associates, 1997)."},{"key":"53625_CR42","doi-asserted-by":"publisher","unstructured":"Hwang, H. et al. SHAP-based explanations are sensitive to feature representation. In Proceedings of the ACM Conference on Fairness, Accountability, and Transparency 1588\u20131601 https:\/\/doi.org\/10.1145\/3715275.3732105 (Association for Computing Machinery, 2025).","DOI":"10.1145\/3715275.3732105"},{"key":"53625_CR43","doi-asserted-by":"publisher","DOI":"10.1002\/gepi.22326","author":"C Quick","year":"2020","unstructured":"Quick, C. et al. Sequencing and imputation in GWAS: Cost-effective strategies to increase power and genomic coverage across diverse populations. Genet. Epidemiol. https:\/\/doi.org\/10.1002\/gepi.22326 (2020).","journal-title":"Genet. Epidemiol."},{"key":"53625_CR44","doi-asserted-by":"publisher","first-page":"17","DOI":"10.3390\/vaccines13010017","volume":"13","author":"F Angius","year":"2025","unstructured":"Angius, F. et al. SARS-CoV-2 evolution: Implications for diagnosis, treatment, vaccine effectiveness and development. Vaccines (Basel) 13, 17 (2025).","journal-title":"Vaccines (Basel)"},{"key":"53625_CR45","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-55973-y","volume":"14","author":"S Dash","year":"2024","unstructured":"Dash, S. et al. Predictive healthcare modeling for early pandemic assessment leveraging deep auto regressor neural prophet. Sci. Rep. 14, 5287 (2024).","journal-title":"Sci. Rep."},{"key":"53625_CR46","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-72005-x","volume":"14","author":"W Chen","year":"2024","unstructured":"Chen, W., Luo, H., Li, J. & Chi, J. Long-term trend prediction of pandemic combining the compartmental and deep learning models. Sci. Rep. 14, 21068 (2024).","journal-title":"Sci. Rep."},{"key":"53625_CR47","doi-asserted-by":"crossref","unstructured":"Annan, R., Qin, H. & Qingge, L. Generalized deep learning models for COVID-19 detection with transfer and continual learning. In\u00a0Proceedings of the 16th International Conference on Bioinformatics and Computational Biology (BICOB-2024)\u00a0Vol.\u00a0101, 58\u201372 (2024).","DOI":"10.29007\/952w"},{"key":"53625_CR48","doi-asserted-by":"publisher","unstructured":"Annan, R. et al. Efficient federated learning with multi-teacher knowledge distillation for COVID-19 detection. in Proceedings of the 15th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. https:\/\/doi.org\/10.1145\/3698587.3701396 (Association for Computing Machinery, 2024).","DOI":"10.1145\/3698587.3701396"},{"key":"53625_CR49","doi-asserted-by":"publisher","DOI":"10.3389\/fpubh.2023.1140353","author":"L Sarmiento Var\u00f3n","year":"2023","unstructured":"Sarmiento Var\u00f3n, L. et al. The role of machine learning in health policies during the COVID-19 pandemic and in long COVID management. Front. Public Health https:\/\/doi.org\/10.3389\/fpubh.2023.1140353 (2023).","journal-title":"Front. Public Health"},{"issue":"1","key":"53625_CR50","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2021.42725","volume":"5","author":"TN Vilches","year":"2022","unstructured":"Vilches, T. N. et al. Estimating COVID-19 infections, hospitalizations, and deaths following the US vaccination campaigns during the pandemic. JAMA Netw. Open 5(1), e2142725 (2022).","journal-title":"JAMA Netw. Open"}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-53625-x","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-53625-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-53625-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,26]],"date-time":"2026-07-26T03:27:00Z","timestamp":1785036420000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-53625-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,20]]},"references-count":50,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["53625"],"URL":"https:\/\/doi.org\/10.1038\/s41598-026-53625-x","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,20]]},"assertion":[{"value":"9 January 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 May 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 May 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":"22989"}}