{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T14:20:16Z","timestamp":1791555616254,"version":"4.3.4"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,4,14]],"date-time":"2025-04-14T00:00:00Z","timestamp":1744588800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,4,14]],"date-time":"2025-04-14T00:00:00Z","timestamp":1744588800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100002383","name":"King Saud University","doi-asserted-by":"publisher","award":["RSP2025R506"],"award-info":[{"award-number":["RSP2025R506"]}],"id":[{"id":"10.13039\/501100002383","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-025-97208-8","type":"journal-article","created":{"date-parts":[[2025,4,14]],"date-time":"2025-04-14T04:14:37Z","timestamp":1744604077000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Integrating machine learning driven virtual screening and molecular dynamics simulations to identify potential inhibitors targeting PARP1 against prostate cancer"],"prefix":"10.1038","volume":"15","author":[{"given":"Fahad M.","family":"Aldakheel","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shatha A.","family":"Alduraywish","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Khaled H.","family":"Dabwan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,4,14]]},"reference":[{"key":"97208_CR1","doi-asserted-by":"publisher","first-page":"862","DOI":"10.1016\/j.eururo.2016.05.043","volume":"70","author":"MC Wong","year":"2016","unstructured":"Wong, M. C. et al. Global incidence and mortality for prostate cancer: Analysis of temporal patterns and trends in 36 countries. Eur. Urol. 70, 862\u2013874 (2016).","journal-title":"Eur. Urol."},{"key":"97208_CR2","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1093\/gerona\/gls135","volume":"68","author":"BT Howrey","year":"2013","unstructured":"Howrey, B. T., Kuo, Y.-F., Lin, Y.-L. & Goodwin, J. S. The impact of PSA screening on prostate cancer mortality and overdiagnosis of prostate cancer in the United States. J. Gerontol. Series A Biomed. Sci. Med. Sci. 68, 56\u201361 (2013).","journal-title":"J. Gerontol. Series A Biomed. Sci. Med. Sci."},{"key":"97208_CR3","doi-asserted-by":"publisher","first-page":"5730","DOI":"10.3390\/molecules27175730","volume":"27","author":"M Sekhoacha","year":"2022","unstructured":"Sekhoacha, M. et al. Prostate cancer review: Genetics, diagnosis, treatment options, and alternative approaches. Molecules 27, 5730 (2022).","journal-title":"Molecules"},{"key":"97208_CR4","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1042\/bj3420249","volume":"342","author":"D D\u2019Amours","year":"1999","unstructured":"D\u2019Amours, D., Desnoyers, S., D\u2019Silva, I. & Poirier, G. G. Poly (ADP-ribosyl) ation reactions in the regulation of nuclear functions. Biochem. J. 342, 249\u2013268 (1999).","journal-title":"Biochem. J."},{"key":"97208_CR5","doi-asserted-by":"publisher","first-page":"943","DOI":"10.3390\/cancers5030943","volume":"5","author":"AF Swindall","year":"2013","unstructured":"Swindall, A. F., Stanley, J. A. & Yang, E. S. PARP1: Friend or foe of DNA damage and repair in tumorigenesis?. Cancers 5, 943\u2013958 (2013).","journal-title":"Cancers"},{"key":"97208_CR6","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1016\/j.dnarep.2018.08.022","volume":"71","author":"JM Pascal","year":"2018","unstructured":"Pascal, J. M. The comings and goings of PARP1 in response to DNA damage. DNA Repair 71, 177\u2013182 (2018).","journal-title":"DNA Repair"},{"key":"97208_CR7","doi-asserted-by":"publisher","first-page":"917","DOI":"10.1038\/nature03445","volume":"434","author":"H Farmer","year":"2005","unstructured":"Farmer, H. et al. Targeting the DNA repair defect in BRCA mutant cells as a therapeutic strategy. Nature 434, 917\u2013921 (2005).","journal-title":"Nature"},{"key":"97208_CR8","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1002\/emmm.200900041","volume":"1","author":"AM Mendes-Pereira","year":"2009","unstructured":"Mendes-Pereira, A. M. et al. Synthetic lethal targeting of PTEN mutant cells with PARP inhibitors. EMBO Mol. Med. 1, 315\u2013322 (2009).","journal-title":"EMBO Mol. Med."},{"key":"97208_CR9","doi-asserted-by":"publisher","first-page":"8109","DOI":"10.1158\/0008-5472.CAN-06-0140","volume":"66","author":"N McCabe","year":"2006","unstructured":"McCabe, N. et al. Deficiency in the repair of DNA damage by homologous recombination and sensitivity to poly (ADP-ribose) polymerase inhibition. Can. Res. 66, 8109\u20138115 (2006).","journal-title":"Can. Res."},{"key":"97208_CR10","doi-asserted-by":"publisher","first-page":"1124","DOI":"10.1016\/j.mam.2013.04.001","volume":"34","author":"C Thomas","year":"2013","unstructured":"Thomas, C. & Tulin, A. V. Poly-ADP-ribose polymerase: Machinery for nuclear processes. Mol. Aspects Med. 34, 1124\u20131137 (2013).","journal-title":"Mol. Aspects Med."},{"key":"97208_CR11","doi-asserted-by":"publisher","first-page":"290","DOI":"10.3389\/fonc.2013.00290","volume":"3","author":"AN Weaver","year":"2013","unstructured":"Weaver, A. N. & Yang, E. S. Beyond DNA repair: Additional functions of PARP1 in cancer. Front. Oncol. 3, 290 (2013).","journal-title":"Front. Oncol."},{"key":"97208_CR12","doi-asserted-by":"publisher","first-page":"728","DOI":"10.1126\/science.1216338","volume":"336","author":"M-F Langelier","year":"2012","unstructured":"Langelier, M.-F., Planck, J. L., Roy, S. & Pascal, J. M. Structural basis for DNA damage\u2013dependent poly (ADP-ribosyl) ation by human PARP1. Science 336, 728\u2013732 (2012).","journal-title":"Science"},{"key":"97208_CR13","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1016\/j.tibs.2009.12.003","volume":"35","author":"MO Hottiger","year":"2010","unstructured":"Hottiger, M. O., Hassa, P. O., L\u00fcscher, B., Sch\u00fcler, H. & Koch-Nolte, F. Toward a unified nomenclature for mammalian ADP-ribosyltransferases. Trends Biochem. Sci. 35, 208\u2013219 (2010).","journal-title":"Trends Biochem. Sci."},{"key":"97208_CR14","doi-asserted-by":"publisher","first-page":"1745","DOI":"10.1002\/ijc.33918","volume":"150","author":"C Zong","year":"2022","unstructured":"Zong, C. et al. PARP mediated DNA damage response, genomic stability and immune responses. Int. J. Cancer 150, 1745\u20131759 (2022).","journal-title":"Int. J. Cancer"},{"key":"97208_CR15","doi-asserted-by":"publisher","first-page":"118975","DOI":"10.1016\/j.lfs.2020.118975","volume":"267","author":"K Thapa","year":"2021","unstructured":"Thapa, K., Khan, H., Sharma, U., Grewal, A. K. & Singh, T. G. Poly (ADP-ribose) polymerase-1 as a promising drug target for neurodegenerative diseases. Life Sci. 267, 118975 (2021).","journal-title":"Life Sci."},{"key":"97208_CR16","doi-asserted-by":"publisher","first-page":"1437","DOI":"10.1093\/annonc\/mdz192","volume":"30","author":"J Mateo","year":"2019","unstructured":"Mateo, J. et al. A decade of clinical development of PARP inhibitors in perspective. Ann. Oncol. 30, 1437\u20131447 (2019).","journal-title":"Ann. Oncol."},{"key":"97208_CR17","doi-asserted-by":"publisher","first-page":"117485","DOI":"10.1016\/j.biopha.2024.117485","volume":"180","author":"S-H Zhang","year":"2024","unstructured":"Zhang, S.-H. et al. Design, synthesis and biological evaluation of dual inhibitors targeting AR\/AR-Vs and PARP1 in castration resistant prostate cancer therapy. Biomed. Pharmacother. 180, 117485 (2024).","journal-title":"Biomed. Pharmacother."},{"key":"97208_CR18","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1016\/j.euo.2023.07.013","volume":"7","author":"C Messina","year":"2024","unstructured":"Messina, C. et al. Combining PARP inhibitors and androgen receptor signalling inhibitors in metastatic prostate cancer: A quantitative synthesis and meta-analysis. Eur. Urol. Oncol. 7, 179\u2013188 (2024).","journal-title":"Eur. Urol. Oncol."},{"key":"97208_CR19","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1186\/s13073-024-01370-z","volume":"16","author":"A Herencia-Ropero","year":"2024","unstructured":"Herencia-Ropero, A. et al. The PARP1 selective inhibitor saruparib (AZD5305) elicits potent and durable antitumor activity in patient-derived BRCA1\/2-associated cancer models. Genome Medicine 16, 107 (2024).","journal-title":"Genome Medicine"},{"key":"97208_CR20","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1007\/s40268-020-00301-8","volume":"20","author":"S Boussios","year":"2020","unstructured":"Boussios, S. et al. Poly (ADP-Ribose) polymerase inhibitors: Talazoparib in ovarian cancer and beyond. Drugs in R 20, 55\u201373 (2020).","journal-title":"Drugs in R"},{"key":"97208_CR21","first-page":"1","volume":"3","author":"D Deshmukh","year":"2015","unstructured":"Deshmukh, D. & Qiu, Y. Role of PARP1 in prostate cancer. Am. J. Clin. Exp. Urol. 3, 1 (2015).","journal-title":"Am. J. Clin. Exp. Urol."},{"key":"97208_CR22","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13045-021-01061-x","volume":"14","author":"D Teyssonneau","year":"2021","unstructured":"Teyssonneau, D. et al. Prostate cancer and PARP inhibitors: progress and challenges. J. Hematol. Oncol. 14, 1\u201319 (2021).","journal-title":"J. Hematol. Oncol."},{"key":"97208_CR23","doi-asserted-by":"publisher","first-page":"1947","DOI":"10.1007\/s10462-021-10058-4","volume":"55","author":"S Dara","year":"2022","unstructured":"Dara, S., Dhamercherla, S., Jadav, S. S., Babu, C. M. & Ahsan, M. J. Machine learning in drug discovery: A review. Artif. Intell. Rev. 55, 1947\u20131999 (2022).","journal-title":"Artif. Intell. Rev."},{"key":"97208_CR24","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1016\/j.csbj.2014.11.005","volume":"13","author":"K Kourou","year":"2015","unstructured":"Kourou, K., Exarchos, T. P., Exarchos, K. P., Karamouzis, M. V. & Fotiadis, D. I. Machine learning applications in cancer prognosis and prediction. Comput. Struct. Biotechnol. J. 13, 8\u201317 (2015).","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"97208_CR25","doi-asserted-by":"publisher","first-page":"772296","DOI":"10.3389\/fphar.2021.772296","volume":"12","author":"H Zhang","year":"2021","unstructured":"Zhang, H. et al. An integrated deep learning and molecular dynamics simulation-based screening pipeline identifies inhibitors of a new cancer drug target TIPE2. Front. Pharmacol. 12, 772296 (2021).","journal-title":"Front. Pharmacol."},{"key":"97208_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12964-024-01954-7","volume":"22","author":"R Zhou","year":"2024","unstructured":"Zhou, R. et al. Machine learning-aided discovery of T790M-mutant EGFR inhibitor CDDO-Me effectively suppresses non-small cell lung cancer growth. Cell Commun. Signal. 22, 1\u201325 (2024).","journal-title":"Cell Commun. Signal."},{"key":"97208_CR27","doi-asserted-by":"publisher","first-page":"D198","DOI":"10.1093\/nar\/gkl999","volume":"35","author":"T Liu","year":"2007","unstructured":"Liu, T., Lin, Y., Wen, X., Jorissen, R. N. & Gilson, M. K. BindingDB: A web-accessible database of experimentally determined protein\u2013ligand binding affinities. Nucleic Acids Res. 35, D198\u2013D201 (2007).","journal-title":"Nucleic Acids Res."},{"key":"97208_CR28","doi-asserted-by":"publisher","first-page":"6582","DOI":"10.1021\/jm300687e","volume":"55","author":"MM Mysinger","year":"2012","unstructured":"Mysinger, M. M., Carchia, M., Irwin, J. J. & Shoichet, B. K. Directory of useful decoys, enhanced (DUD-E): Better ligands and decoys for better benchmarking. J. Med. Chem. 55, 6582\u20136594 (2012).","journal-title":"J. Med. Chem."},{"key":"97208_CR29","first-page":"173","volume":"4","author":"S Karamizadeh","year":"2020","unstructured":"Karamizadeh, S. et al. An overview of principal component analysis. J. Signal Inf. Process. 4, 173\u2013175 (2020).","journal-title":"J. Signal Inf. Process."},{"key":"97208_CR30","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1016\/j.artmed.2015.02.002","volume":"63","author":"MA Khamis","year":"2015","unstructured":"Khamis, M. A., Gomaa, W. & Ahmed, W. F. Machine learning in computational docking. Artif. Intell. Med. 63, 135\u2013152 (2015).","journal-title":"Artif. Intell. Med."},{"key":"97208_CR31","doi-asserted-by":"publisher","first-page":"1169","DOI":"10.1093\/bioinformatics\/btq112","volume":"26","author":"PJ Ballester","year":"2010","unstructured":"Ballester, P. J. & Mitchell, J. B. A machine learning approach to predicting protein\u2013ligand binding affinity with applications to molecular docking. Bioinformatics 26, 1169\u20131175 (2010).","journal-title":"Bioinformatics"},{"key":"97208_CR32","doi-asserted-by":"crossref","unstructured":"Karthikeyan, M., Vyas, R., Karthikeyan, M. & Vyas, R. Machine learning methods in chemoinformatics for drug discovery. Pract. Chemoinf. 133\u2013194 (2014).","DOI":"10.1007\/978-81-322-1780-0_3"},{"key":"97208_CR33","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1002\/jcc.21334","volume":"31","author":"O Trott","year":"2010","unstructured":"Trott, O. & Olson, A. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem. 31, 455\u2013461 (2010).","journal-title":"J. Comput. Chem."},{"key":"97208_CR34","unstructured":"Bekker, H. et al. in 4th International Conference on Computational Physics (PC 92). 252\u2013256 (World Scientific Publishing)."},{"key":"97208_CR35","doi-asserted-by":"publisher","first-page":"3257","DOI":"10.1021\/ct300400x","volume":"8","author":"RB Best","year":"2012","unstructured":"Best, R. B. et al. Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone \u03d5, \u03c8 and side-chain \u03c71 and \u03c72 dihedral angles. J. Chem. Theory Comput. 8, 3257\u20133273 (2012).","journal-title":"J. Chem. Theory Comput."},{"key":"97208_CR36","doi-asserted-by":"publisher","first-page":"9478","DOI":"10.1021\/acs.chemrev.9b00055","volume":"119","author":"E Wang","year":"2019","unstructured":"Wang, E. et al. End-point binding free energy calculation with MM\/PBSA and MM\/GBSA: Strategies and applications in drug design. Chem. Rev. 119, 9478\u20139508 (2019).","journal-title":"Chem. Rev."},{"key":"97208_CR37","volume-title":"Amber 2021","author":"DA Case","year":"2021","unstructured":"Case, D. A. et al. Amber 2021 (University of California, 2021)."},{"key":"97208_CR38","doi-asserted-by":"publisher","first-page":"W257","DOI":"10.1093\/nar\/gky318","volume":"46","author":"P Banerjee","year":"2018","unstructured":"Banerjee, P., Eckert, A. O., Schrey, A. K. & Preissner, R. J. ProTox-II: A webserver for the prediction of toxicity of chemicals. Nucleic Acids Res. 46, W257\u2013W263 (2018).","journal-title":"Nucleic Acids Res."},{"key":"97208_CR39","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1002\/0471141755.ph0912s49","volume":"49","author":"MP Pollastri","year":"2010","unstructured":"Pollastri, M. P. Overview on the rule of five. Curr. Protoc. Pharmacol. 49, 9\u201312 (2010).","journal-title":"Curr. Protoc. Pharmacol."},{"key":"97208_CR40","doi-asserted-by":"crossref","unstructured":"Plinski, E. F. & Plinska, S. Veber\u2019s rules in terahertz light. (2020).","DOI":"10.21203\/rs.2.22281\/v1"},{"key":"97208_CR41","first-page":"268","volume":"10","author":"N Priya","year":"2019","unstructured":"Priya, N. & Shobana, G. Application of machine learning models in drug discovery: A review. Int. J. Emerg. Technol. 10, 268\u2013275 (2019).","journal-title":"Int. J. Emerg. Technol."},{"key":"97208_CR42","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/j.eswa.2016.12.008","volume":"72","author":"G Cano","year":"2017","unstructured":"Cano, G. et al. Automatic selection of molecular descriptors using random forest: Application to drug discovery. Expert Syst. Appl. 72, 151\u2013159 (2017).","journal-title":"Expert Syst. Appl."},{"key":"97208_CR43","doi-asserted-by":"publisher","first-page":"755","DOI":"10.1016\/j.molcel.2015.10.013","volume":"60","author":"JM Dawicki-McKenna","year":"2015","unstructured":"Dawicki-McKenna, J. M. et al. PARP1 activation requires local unfolding of an autoinhibitory domain. Mol. Cell 60, 755\u2013768 (2015).","journal-title":"Mol. Cell"},{"key":"97208_CR44","doi-asserted-by":"publisher","first-page":"844","DOI":"10.1038\/s41467-018-03234-8","volume":"9","author":"M-F Langelier","year":"2018","unstructured":"Langelier, M.-F., Zandarashvili, L., Aguiar, P. M., Black, B. E. & Pascal, J. M. NAD+ analog reveals PARP1 substrate-blocking mechanism and allosteric communication from catalytic center to DNA-binding domains. Nat. Commun. 9, 844 (2018).","journal-title":"Nat. Commun."},{"key":"97208_CR45","doi-asserted-by":"publisher","first-page":"3060","DOI":"10.1080\/07391102.2020.1844803","volume":"40","author":"N Adelakun","year":"2022","unstructured":"Adelakun, N. et al. Discovery of new promising USP14 inhibitors: Computational evaluation of the thumb-palm pocket. J. Biomol. Struct. Dyn. 40, 3060\u20133070 (2022).","journal-title":"J. Biomol. Struct. Dyn."},{"key":"97208_CR46","doi-asserted-by":"publisher","first-page":"425","DOI":"10.2217\/fon-2021-0811","volume":"18","author":"N Agarwal","year":"2022","unstructured":"Agarwal, N. et al. Talazoparib plus enzalutamide in metastatic castration-resistant prostate cancer: TALAPRO-2 phase III study design. Future Oncol. 18, 425\u2013436 (2022).","journal-title":"Future Oncol."},{"key":"97208_CR47","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1016\/S1470-2045(21)00757-9","volume":"23","author":"MR Smith","year":"2022","unstructured":"Smith, M. R. et al. Niraparib in patients with metastatic castration-resistant prostate cancer and DNA repair gene defects (GALAHAD): A multicentre, open-label, phase 2 trial. Lancet Oncol. 23, 362\u2013373 (2022).","journal-title":"Lancet Oncol."},{"key":"97208_CR48","doi-asserted-by":"publisher","first-page":"2091","DOI":"10.1056\/NEJMoa1911440","volume":"382","author":"J de Bono","year":"2020","unstructured":"de Bono, J. et al. Olaparib for metastatic castration-resistant prostate cancer. N. Engl. J. Med. 382, 2091\u20132102 (2020).","journal-title":"N. Engl. J. Med."},{"key":"97208_CR49","doi-asserted-by":"publisher","first-page":"3763","DOI":"10.1200\/JCO.20.01035","volume":"38","author":"W Abida","year":"2020","unstructured":"Abida, W. et al. Rucaparib in men with metastatic castration-resistant prostate cancer harboring a BRCA1 or BRCA2 gene alteration. J. Clin. Oncol. 38, 3763\u20133772 (2020).","journal-title":"J. Clin. Oncol."},{"key":"97208_CR50","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1002\/onco.13585","volume":"26","author":"MS Anscher","year":"2021","unstructured":"Anscher, M. S. et al. FDA approval summary: Rucaparib for the treatment of patients with deleterious BRCA-mutated metastatic castrate-resistant prostate cancer. Oncologist 26, 139\u2013146 (2021).","journal-title":"Oncologist"}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-97208-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-97208-8","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-97208-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,14]],"date-time":"2025-04-14T05:02:01Z","timestamp":1744606921000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-97208-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,14]]},"references-count":50,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["97208"],"URL":"https:\/\/doi.org\/10.1038\/s41598-025-97208-8","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,14]]},"assertion":[{"value":"10 December 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 April 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 April 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 authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"12764"}}