{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T00:51:52Z","timestamp":1792025512284,"version":"4.4.0"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T00:00:00Z","timestamp":1781049600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T00:00:00Z","timestamp":1790035200000},"content-version":"vor","delay-in-days":104,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100003246","name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","doi-asserted-by":"publisher","award":["KICH1.ST01.20.011"],"award-info":[{"award-number":["KICH1.ST01.20.011"]}],"id":[{"id":"10.13039\/501100003246","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003246","name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","doi-asserted-by":"publisher","award":["KICH1.ST01.20.011"],"award-info":[{"award-number":["KICH1.ST01.20.011"]}],"id":[{"id":"10.13039\/501100003246","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003246","name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","doi-asserted-by":"publisher","award":["KICH1.ST01.20.011"],"award-info":[{"award-number":["KICH1.ST01.20.011"]}],"id":[{"id":"10.13039\/501100003246","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003246","name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","doi-asserted-by":"publisher","award":["KICH1.ST01.20.011"],"award-info":[{"award-number":["KICH1.ST01.20.011"]}],"id":[{"id":"10.13039\/501100003246","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Data"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>In this study, a Knowledge Graph (KG) for Drug-Induced Acute Kidney Injury (DAKI) was developed to provide structured and standardized knowledge about drugs known to cause AKI. The DAKI-KG is integrated from several credible domain sources, which we standardized to international vocabularies. We demonstrate the applicability of the DAKI-KG through competency questions and expert evaluations. The envisioned two application areas are: (1) the KG can be used as input for a decision support tool to get insights into potential side-effects and drug-drug interactions harmful for kidneys, especially in patients with chronic kidney disease and (2) researchers can utilize the KG to derive confounders and variables for (causal) machine learning models or as input into link prediction methods. The evaluation results show the applicability of our KG through varying competency questions and use cases, though further improvements are needed before it is ready for clinical application. We anticipate the DAKI-KG to be relevant for tasks such as confounder identification, variable analysis, and the development of QA systems.<\/jats:p>","DOI":"10.1038\/s41597-026-07579-4","type":"journal-article","created":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T09:46:05Z","timestamp":1781084765000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Computer-Interpretable Domain Knowledge for Drug-Induced Acute Kidney Injury: a Knowledge Graph Approach"],"prefix":"10.1038","volume":"13","author":[{"given":"Romy","family":"Vos","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Iacopo","family":"Vagliano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cornelis","family":"Boersma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Frank","family":"van Harmelen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Annette","family":"ten Teije","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joanna E.","family":"Klopotowska","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"On behalf of the LEAPfROG Consortium","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,10]]},"reference":[{"issue":"1","key":"7579_CR1","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1038\/s41572-021-00284-z","volume":"7","author":"JA Kellum","year":"2021","unstructured":"Kellum, J. A. et al. Acute kidney injury. Nature reviews Disease primers 7(1), 52, https:\/\/doi.org\/10.1038\/s41572-021-00284-z (2021).","journal-title":"Nature reviews Disease primers"},{"issue":"1","key":"7579_CR2","doi-asserted-by":"publisher","DOI":"10.1186\/s13054-023-04720-2","volume":"27","author":"I Karimzadeh","year":"2023","unstructured":"Karimzadeh, I. et al. Moving toward a contemporary classification of drug-induced kidney disease. Critical Care 27(1), 435, https:\/\/doi.org\/10.1186\/s13054-023-04720-2 (2023).","journal-title":"Critical Care"},{"issue":"2","key":"7579_CR3","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1016\/j.ccc.2020.11.002","volume":"37","author":"SL Kane-Gill","year":"2021","unstructured":"Kane-Gill, S. L. Nephrotoxin stewardship. Critical care clinics 37(2), 303\u2013320, https:\/\/doi.org\/10.1016\/j.ccc.2020.11.002 (2021).","journal-title":"Critical care clinics"},{"key":"7579_CR4","doi-asserted-by":"publisher","unstructured":"Hsu, R.K. & Hsu, C. Y The role of acute kidney injury in chronic kidney disease. In: Seminars in nephrology. vol. 36, pp. 283\u2013292, https:\/\/doi.org\/10.1016\/j.semnephrol.2016.05.005 (Elsevier, 2016).","DOI":"10.1016\/j.semnephrol.2016.05.005"},{"issue":"9","key":"7579_CR5","doi-asserted-by":"publisher","first-page":"1700","DOI":"10.1093\/ndt\/gfab249","volume":"37","author":"A Hamroun","year":"2022","unstructured":"Hamroun, A. et al. New insights into acute-on-chronic kidney disease in nephrology patients: the ckd-rein study. Nephrology Dialysis Transplantation 37(9), 1700\u20131709, https:\/\/doi.org\/10.1093\/ndt\/gfab249 (2022).","journal-title":"Nephrology Dialysis Transplantation"},{"issue":"1","key":"7579_CR6","doi-asserted-by":"publisher","first-page":"sfae357","DOI":"10.1093\/ckj\/sfae357","volume":"18","author":"SM Laville","year":"2025","unstructured":"Laville, S. M. et al. Quantifying the potential contribution of drugs to the occurrence of acute kidney injury in patients with chronic kidney disease. Clinical Kidney Journal 18(1), sfae357, https:\/\/doi.org\/10.1093\/ckj\/sfae357 (2025).","journal-title":"Clinical Kidney Journal"},{"issue":"12","key":"7579_CR7","doi-asserted-by":"publisher","first-page":"2497","DOI":"10.1093\/ckj\/sfab120","volume":"14","author":"MJ van Oosten","year":"2021","unstructured":"van Oosten, M. J. et al. Polypharmacy and medication use in patients with chronic kidney disease with and without kidney replacement therapy compared to matched controls. Clinical Kidney Journal 14(12), 2497\u20132523, https:\/\/doi.org\/10.1093\/ckj\/sfab120 (2021).","journal-title":"Clinical Kidney Journal"},{"issue":"4","key":"7579_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3447772","volume":"54","author":"A Hogan","year":"2021","unstructured":"Hogan, A. et al. Knowledge graphs. ACM Computing Surveys (Csur) 54(4), 1\u201337, https:\/\/doi.org\/10.1145\/3447772 (2021).","journal-title":"ACM Computing Surveys (Csur)"},{"issue":"6","key":"7579_CR9","doi-asserted-by":"publisher","first-page":"bbae461","DOI":"10.1093\/bib\/bbae461","volume":"25","author":"P Perdomo-Quinteiro","year":"2024","unstructured":"Perdomo-Quinteiro, P. & Belmonte-Hern\u00e1ndez, A. Knowledge graphs for drug repurposing: a review of databases and methods. Briefings in Bioinformatics 25(6), bbae461, https:\/\/doi.org\/10.1093\/bib\/bbae461 (2024).","journal-title":"Briefings in Bioinformatics"},{"issue":"6","key":"7579_CR10","doi-asserted-by":"publisher","first-page":"bbac404","DOI":"10.1093\/bib\/bbac404","volume":"23","author":"S Bonner","year":"2022","unstructured":"Bonner, S. et al. A review of biomedical datasets relating to drug discovery: a knowledge graph perspective. Briefings in Bioinformatics 23(6), bbac404, https:\/\/doi.org\/10.1093\/bib\/bbac404 (2022).","journal-title":"Briefings in Bioinformatics"},{"key":"7579_CR11","doi-asserted-by":"publisher","unstructured":"Wang, L. et al. Construction of a knowledge graph for diabetes complications from expert-reviewed clinical evidences 25(1), 29\u201335. https:\/\/doi.org\/10.1080\/24699322.2020.1850866.","DOI":"10.1080\/24699322.2020.1850866"},{"key":"7579_CR12","doi-asserted-by":"publisher","unstructured":"Huang, Z., Yang, J., van Harmelen, F. & Hu, Q. Constructing knowledge graphs of depression. In: International conference on health information science. pp. 149\u2013161. Springer https:\/\/doi.org\/10.1007\/978-3-319-69182-4_16 (2017).","DOI":"10.1007\/978-3-319-69182-4_16"},{"issue":"D1","key":"7579_CR13","doi-asserted-by":"publisher","first-page":"D1074","DOI":"10.1093\/nar\/gkx1037","volume":"46","author":"DS Wishart","year":"2018","unstructured":"Wishart, D. S. et al. Drugbank 5.0: a major update to the drugbank database for 2018. Nucleic acids research 46(D1), D1074\u2013D1082, https:\/\/doi.org\/10.1093\/nar\/gkx1037 (2018).","journal-title":"Nucleic acids research"},{"key":"7579_CR14","doi-asserted-by":"publisher","unstructured":"Bodenreider, O. The unified medical language system (umls): integrating biomedical terminology. Nucleic acids research 32(suppl_1), D267\u2013D270, https:\/\/doi.org\/10.1093\/nar\/gkh061 (2004).","DOI":"10.1093\/nar\/gkh061"},{"key":"7579_CR15","doi-asserted-by":"publisher","first-page":"100760","DOI":"10.1016\/j.websem.2022.100760","volume":"75","author":"A Sakor","year":"2023","unstructured":"Sakor, A. et al. Knowledge4covid-19: A semantic-based approach for constructing a COVID-19 related knowledge graph from various sources and analyzing treatments\u2019 toxicities. Journal of Web Semantics 75, 100760, https:\/\/doi.org\/10.1016\/j.websem.2022.100760 (2023).","journal-title":"Journal of Web Semantics"},{"issue":"D1","key":"7579_CR16","doi-asserted-by":"publisher","first-page":"D1075","DOI":"10.1093\/nar\/gkv1075","volume":"44","author":"M Kuhn","year":"2016","unstructured":"Kuhn, M., Letunic, I., Jensen, L. J. & Bork, P. The sider database of drugs and side effects. Nucleic acids research 44(D1), D1075\u2013D1079, https:\/\/doi.org\/10.1093\/nar\/gkv1075 (2016).","journal-title":"Nucleic acids research"},{"key":"7579_CR17","doi-asserted-by":"publisher","unstructured":"Zhao, X. et al. The construction of a TCM knowledge graph and application of potential knowledge discovery in diabetic kidney disease by integrating diagnosis and treatment guidelines and real-world clinical data 14, 1147677, https:\/\/doi.org\/10.3389\/fphar.2023.1147677","DOI":"10.3389\/fphar.2023.1147677"},{"key":"7579_CR18","doi-asserted-by":"publisher","unstructured":"Xie, J. et al. Knowledge graph construction of chronic kidney disease diagnosis and treatment with traditional chinese medicine 2023 (1), 3169031. https:\/\/doi.org\/10.1155\/2023\/3169031","DOI":"10.1155\/2023\/3169031"},{"issue":"12","key":"7579_CR19","doi-asserted-by":"publisher","first-page":"2523","DOI":"10.1007\/S11548-025-03495-X","volume":"20","author":"A Kumar","year":"2025","unstructured":"Kumar, A., Singh, D., Cypko, M. A. & Amft, O. A multi-view validation framework for llm-generated knowledge graphs of chronic kidney disease. Int. J. Comput. Assist. Radiol. Surg. 20(12), 2523\u20132528, https:\/\/doi.org\/10.1007\/S11548-025-03495-X (2025).","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"issue":"1","key":"7579_CR20","doi-asserted-by":"publisher","DOI":"10.1007\/s13755-024-00309-3","volume":"12","author":"J Man","year":"2024","unstructured":"Man, J. et al. Ksdkg: construction and application of knowledge graph for kidney stone disease based on biomedical literature and public databases. Health information science and systems 12(1), 54, https:\/\/doi.org\/10.1007\/s13755-024-00309-3 (2024).","journal-title":"Health information science and systems"},{"key":"7579_CR21","first-page":"279","volume":"121","author":"K Donnelly","year":"2006","unstructured":"Donnelly, K. et al. Snomed-ct: The advanced terminology and coding system for ehealth. Studies in health technology and informatics 121, 279 (2006).","journal-title":"Studies in health technology and informatics"},{"key":"7579_CR22","doi-asserted-by":"publisher","first-page":"e26726","DOI":"10.7554\/eLife.26726","volume":"6","author":"DS Himmelstein","year":"2017","unstructured":"Himmelstein, D. S. et al. Systematic integration of biomedical knowledge prioritizes drugs for repurposing. elife 6, e26726, https:\/\/doi.org\/10.7554\/eLife.26726 (2017).","journal-title":"elife"},{"key":"7579_CR23","doi-asserted-by":"publisher","unstructured":"Walsh, B., Mohamed, S. K. & Nov\u00e1\u010dek, V. Biokg: A knowledge graph for relational learning on biological data. In: Proceedings of the 29th ACM International Conference on Information & Knowledge Management. pp. 3173\u20133180, https:\/\/doi.org\/10.1145\/3340531.3412776 (2020).","DOI":"10.1145\/3340531.3412776"},{"key":"7579_CR24","doi-asserted-by":"publisher","unstructured":"Boudin, M., Diallo, G., Dranc\u00e9, M. & Mougin, F. The oregano knowledge graph for computational drug repurposing. Scientific data 10(1), 871, https:\/\/doi.org\/10.1038\/s41597-023-02757-0 (2023).","DOI":"10.1038\/s41597-023-02757-0"},{"issue":"1","key":"7579_CR25","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-023-01960-3","volume":"10","author":"P Chandak","year":"2023","unstructured":"Chandak, P., Huang, K. & Zitnik, M. Building a knowledge graph to enable precision medicine. Scientific Data 10(1), 67, https:\/\/doi.org\/10.1038\/s41597-023-01960-3 (2023).","journal-title":"Scientific Data"},{"issue":"5","key":"7579_CR26","doi-asserted-by":"publisher","first-page":"599","DOI":"10.1080\/17460441.2025.2490253","volume":"20","author":"A Serra","year":"2025","unstructured":"Serra, A., Fratello, M., Federico, A. & Greco, D. An update on knowledge graphs and their current and potential applications in drug discovery. Expert opinion on drug discovery 20(5), 599\u2013619, https:\/\/doi.org\/10.1080\/17460441.2025.2490253 (2025).","journal-title":"Expert opinion on drug discovery"},{"key":"7579_CR27","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1016\/j.sbi.2021.09.003","volume":"72","author":"X Zeng","year":"2022","unstructured":"Zeng, X., Tu, X., Liu, Y., Fu, X. & Su, Y. Toward better drug discovery with knowledge graph. Current opinion in structural biology 72, 114\u2013126, https:\/\/doi.org\/10.1016\/j.sbi.2021.09.003 (2022).","journal-title":"Current opinion in structural biology"},{"key":"7579_CR28","unstructured":"Farmacotherapeutisch Kompas \u2014 farmacotherapeutischkompas.nl. https:\/\/www.farmacotherapeutischkompas.nl\/, [Accessed 29-11-2024]."},{"key":"7579_CR29","unstructured":"Farmacotherapie in de G-Standaard; Z-Index \u2014 z-index.nl. https:\/\/www.z-index.nl\/g-standaard-over-de-g-standaard\/farmacotherapie-de-g-standaard, [Accessed 29-11-2024]."},{"key":"7579_CR30","unstructured":"for Drug Statistics Methodology, W. C. C. The atc\/ddd methodology. https:\/\/www.who.int\/tools\/atc-ddd-toolkit\/methodology, accessed: 2025."},{"issue":"2","key":"7579_CR31","doi-asserted-by":"publisher","first-page":"109","DOI":"10.2165\/00002018-199920020-00002","volume":"20","author":"EG Brown","year":"1999","unstructured":"Brown, E. G., Wood, L. & Wood, S. The medical dictionary for regulatory activities (meddra). Drug safety 20(2), 109\u2013117, https:\/\/doi.org\/10.2165\/00002018-199920020-00002 (1999).","journal-title":"Drug safety"},{"issue":"W1","key":"7579_CR32","doi-asserted-by":"publisher","first-page":"W84","DOI":"10.1093\/nar\/gkaf402","volume":"53","author":"J Vendetti","year":"2025","unstructured":"Vendetti, J. et al. Bioportal: an open community resource for sharing, searching, and utilizing biomedical ontologies. Nucleic acids research 53(W1), W84\u2013W94, https:\/\/doi.org\/10.1093\/nar\/gkaf402 (2025).","journal-title":"Nucleic acids research"},{"issue":"1","key":"7579_CR33","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1007\/s40264-024-01474-w","volume":"48","author":"D Fern\u00e1ndez-Llaneza","year":"2025","unstructured":"Fern\u00e1ndez-Llaneza, D. et al. the LEAPfROG Consortium: An integrated approach for representing knowledge on the potential of drugs to cause acute kidney injury. Drug Safety 48(1), 43\u201358, https:\/\/doi.org\/10.1007\/s40264-024-01474-w (2025).","journal-title":"Drug Safety"},{"key":"7579_CR34","unstructured":"Richardson, L. Beautiful soup documentation (2007)."},{"key":"7579_CR35","doi-asserted-by":"publisher","unstructured":"Turner, N. N. et al. Oxford Textbook of Clinical Nephrology: Three-Volume Pack. https:\/\/doi.org\/10.1093\/med\/9780199592548.001.0001 (Oxford University Press, 2015).","DOI":"10.1093\/med\/9780199592548.001.0001"},{"key":"7579_CR36","unstructured":"Nederlandse Internisten Vereniging: Acute nierinsuffici\u00ebntie. https:\/\/www.hetacuteboekje.nl\/hoofdstuk\/nefrologie\/acute_nierinsufficientie.html (2023)."},{"key":"7579_CR37","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.imu.2025.101673","volume":"58","author":"M Mohammadi","year":"2025","unstructured":"Mohammadi, M., Teije, A., Christen, T., de Groot, J. & Verhoeff, M. Cross-linking clinical practice guidelines for multimorbidity. Informatics in Medicine Unlocked (IMU) 58, 1\u201310, https:\/\/doi.org\/10.1016\/j.imu.2025.101673 (2025).","journal-title":"Informatics in Medicine Unlocked (IMU)"},{"issue":"1","key":"7579_CR38","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1111\/bcp.15882","volume":"90","author":"JE Klopotowska","year":"2024","unstructured":"Klopotowska, J. E. et al. Adverse drug events caused by three high-risk drug\u2013drug interactions in patients admitted to intensive care units: A multicentre retrospective observational study. British journal of clinical pharmacology 90(1), 164\u2013175, https:\/\/doi.org\/10.1111\/bcp.15882 (2024).","journal-title":"British journal of clinical pharmacology"},{"key":"7579_CR39","unstructured":"Beckett, D., Berners-Lee, T., Prud\u2019hommeaux, E. & Carothers, G. Rdf 1.1 turtle. https:\/\/www.w3.org\/TR\/turtle\/ (2014)."},{"key":"7579_CR40","unstructured":"Dublin Core Metadata Initiative: Dublin core metadata terms. https:\/\/www.dublincore.org\/specifications\/dublin-core\/dcmi-terms\/, accessed: 2025-12-18."},{"key":"7579_CR41","doi-asserted-by":"publisher","unstructured":"Miles, A., Matthews, B., Wilson, M. & Brickley, D. Skos core: simple knowledge organisation for the web. In: Proceedings of the International Conference on Dublin Core and Metadata Applications. Dublin Core Metadata Initiative. https:\/\/doi.org\/10.23106\/dcmi.952107985 (2005).","DOI":"10.23106\/dcmi.952107985"},{"key":"7579_CR42","doi-asserted-by":"publisher","unstructured":"Vos, R. et al. Computer-Interpretable Domain Knowledge for Drug-Induced Acute Kidney Injury: a Knowledge Graph Approach (1.0.0) [Data set]. Zenodo. https:\/\/doi.org\/10.5281\/zenodo.19661646 (2026).","DOI":"10.5281\/zenodo.19661646"},{"key":"7579_CR43","doi-asserted-by":"publisher","unstructured":"Landis, J. R. & Koch, G. G.The measurement of observer agreement for categorical data. biometrics pp. 159\u2013174, https:\/\/doi.org\/10.2307\/2529310 (1977).","DOI":"10.2307\/2529310"}],"container-title":["Scientific Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41597-026-07579-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41597-026-07579-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41597-026-07579-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T03:46:32Z","timestamp":1790307992000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41597-026-07579-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,10]]},"references-count":43,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["7579"],"URL":"https:\/\/doi.org\/10.1038\/s41597-026-07579-4","relation":{},"ISSN":["2052-4463"],"issn-type":[{"value":"2052-4463","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,10]]},"assertion":[{"value":"19 December 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 May 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 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":"Ethics"}}],"article-number":"1335"}}