{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T23:31:24Z","timestamp":1772148684834,"version":"3.50.1"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1009655","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2021,12,22]],"date-time":"2021-12-22T00:00:00Z","timestamp":1640131200000}}],"reference-count":53,"publisher":"Public Library of Science (PLoS)","issue":"12","license":[{"start":{"date-parts":[[2021,12,10]],"date-time":"2021-12-10T00:00:00Z","timestamp":1639094400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61873001"],"award-info":[{"award-number":["61873001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61873001"],"award-info":[{"award-number":["61873001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U19A2064"],"award-info":[{"award-number":["U19A2064"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["11701318"],"award-info":[{"award-number":["11701318"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZR2020KC022"],"award-info":[{"award-number":["ZR2020KC022"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZR2020KC022"],"award-info":[{"award-number":["ZR2020KC022"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZR2020KC022"],"award-info":[{"award-number":["ZR2020KC022"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZR2020KC022"],"award-info":[{"award-number":["ZR2020KC022"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Project of Anhui Provincial Key Labortory of Multimodal Cognitive Computation, Anhui University","award":["MMC202006"],"award-info":[{"award-number":["MMC202006"]}]},{"name":"Open Project of Anhui Provincial Key Labortory of Multimodal Cognitive Computation, Anhui University","award":["MMC202006"],"award-info":[{"award-number":["MMC202006"]}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>microRNAs (miRNAs) are small non-coding RNAs related to a number of complicated biological processes. A growing body of studies have suggested that miRNAs are closely associated with many human diseases. It is meaningful to consider disease-related miRNAs as potential biomarkers, which could greatly contribute to understanding the mechanisms of complex diseases and benefit the prevention, detection, diagnosis and treatment of extraordinary diseases. In this study, we presented a novel model named Graph Convolutional Autoencoder for miRNA-Disease Association Prediction (GCAEMDA). In the proposed model, we utilized miRNA-miRNA similarities, disease-disease similarities and verified miRNA-disease associations to construct a heterogeneous network, which is applied to learn the embeddings of miRNAs and diseases. In addition, we separately constructed miRNA-based and disease-based sub-networks. Combining the embeddings of miRNAs and diseases, graph convolutional autoencoder (GCAE) was utilized to calculate association scores of miRNA-disease on two sub-networks, respectively. Furthermore, we obtained final prediction scores between miRNAs and diseases by adopting an average ensemble way to integrate the prediction scores from two types of subnetworks. To indicate the accuracy of GCAEMDA, we applied different cross validation methods to evaluate our model whose performances were better than the state-of-the-art models. Case studies on a common human diseases were also implemented to prove the effectiveness of GCAEMDA. The results demonstrated that GCAEMDA was beneficial to infer potential associations of miRNA-disease.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1009655","type":"journal-article","created":{"date-parts":[[2021,12,10]],"date-time":"2021-12-10T18:35:25Z","timestamp":1639161325000},"page":"e1009655","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":23,"title":["GCAEMDA: Predicting miRNA-disease associations via graph convolutional autoencoder"],"prefix":"10.1371","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0013-2735","authenticated-orcid":true,"given":"Lei","family":"Li","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8033-8727","authenticated-orcid":true,"given":"Yu-Tian","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7004-3351","authenticated-orcid":true,"given":"Cun-Mei","family":"Ji","sequence":"additional","affiliation":[]},{"given":"Chun-Hou","family":"Zheng","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5667-9807","authenticated-orcid":true,"given":"Jian-Cheng","family":"Ni","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3855-7133","authenticated-orcid":true,"given":"Yan-Sen","family":"Su","sequence":"additional","affiliation":[]}],"member":"340","published-online":{"date-parts":[[2021,12,10]]},"reference":[{"key":"pcbi.1009655.ref001","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/S0092-8674(04)00045-5","article-title":"MicroRNAs: Genomics, Biogenesis, Mechanism, and Function.","volume":"116","author":"DP Bartel","year":"2004","journal-title":"Cell"},{"key":"pcbi.1009655.ref002","doi-asserted-by":"crossref","first-page":"823","DOI":"10.1016\/S0092-8674(01)00616-X","article-title":"microRNAs: tiny regulators with great potential","volume":"107","author":"V. Ambros","year":"2001","journal-title":"Cell"},{"key":"pcbi.1009655.ref003","doi-asserted-by":"crossref","first-page":"350","DOI":"10.1038\/nature02871","article-title":"The function of animal microRNAs","volume":"431","author":"V. Ambros","year":"2004","journal-title":"Nature"},{"key":"pcbi.1009655.ref004","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1038\/nature02873","article-title":"Mechanisms of gene silencing by double-stranded RNA","volume":"431","author":"G Meister","year":"2004","journal-title":"Nature"},{"key":"pcbi.1009655.ref005","first-page":"3","article-title":"The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14","volume":"75","author":"RC Lee","year":"1993","journal-title":"Cell"},{"key":"pcbi.1009655.ref006","doi-asserted-by":"crossref","first-page":"855","DOI":"10.1016\/0092-8674(93)90530-4","article-title":"Posttranscriptional regulation of the heterochronic gene lin-14 by lin-4 mediates temporal pattern formation in C. elegans","volume":"75","author":"B Wightman","year":"1993","journal-title":"Cell"},{"key":"pcbi.1009655.ref007","doi-asserted-by":"crossref","first-page":"1290","DOI":"10.1093\/nar\/gki200","article-title":"Antisense inhibition of human miRNAs and indications for an involvement of miRNA in cell growth and apoptosis","volume":"33","author":"AM Cheng","year":"2005","journal-title":"Nucleic Acids Res"},{"key":"pcbi.1009655.ref008","doi-asserted-by":"crossref","first-page":"1288","DOI":"10.1126\/science.1121566","article-title":"Developmental biology. Encountering microRNAs in cell fate signaling","volume":"310","author":"X Karp","year":"2005","journal-title":"Science"},{"key":"pcbi.1009655.ref009","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1016\/j.gde.2005.08.005","article-title":"How microRNAs control cell division, differentiation and death","volume":"15","author":"EA Miska","year":"2005","journal-title":"Curr Opin Genet Dev"},{"key":"pcbi.1009655.ref010","doi-asserted-by":"crossref","first-page":"S1","DOI":"10.1186\/1471-2105-14-S12-S1","article-title":"Using context-specific effect of miRNAs to identify functional associations between miRNAs and gene signatures","volume":"14","author":"M Alshalalfa","year":"2013","journal-title":"BMC Bioinformatics"},{"key":"pcbi.1009655.ref011","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1016\/j.tig.2004.09.010","article-title":"MicroRNAs and the regulation of cell death","volume":"20","author":"P Xu","year":"2004","journal-title":"Trend Genet"},{"key":"pcbi.1009655.ref012","doi-asserted-by":"crossref","first-page":"1112","DOI":"10.1093\/bioinformatics\/btt769","article-title":"SNPdryad: predicting deleterious non-synonymous human SNPs using only orthologous protein sequences","volume":"30","author":"KC Wong","year":"2014","journal-title":"Bioinformatics"},{"key":"pcbi.1009655.ref013","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1007\/s00059-012-3656-3","article-title":"miRNA as activity markers in Parvo B19 associated heart disease","volume":"37","author":"U K\u00fchl","year":"2012","journal-title":"Herz"},{"key":"pcbi.1009655.ref014","doi-asserted-by":"crossref","first-page":"759","DOI":"10.4161\/cc.7.6.5834","article-title":"The let-7 microrna reduces tumor growth in mouse models of lung cancer","volume":"7","author":"A Esquela-Kerscher","year":"2008","journal-title":"Cell Cycle"},{"key":"pcbi.1009655.ref015","doi-asserted-by":"crossref","first-page":"7065","DOI":"10.1158\/0008-5472.CAN-05-1783","article-title":"MicroRNA Gene Expression Deregulation in Human Breast Cancer","volume":"65","author":"MV Iorio","year":"2005","journal-title":"Cancer Res"},{"key":"pcbi.1009655.ref016","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1186\/1471-2164-10-407","article-title":"Reproducibility of quantitative RT-PCR array in miRNA expression profiling and comparison with microarray analysis","volume":"10","author":"Y Chen","year":"2009","journal-title":"BMC Genomics"},{"key":"pcbi.1009655.ref017","doi-asserted-by":"crossref","first-page":"e1006931","DOI":"10.1371\/journal.pcbi.1006931","article-title":"Adaptive multi-view multi-label learning for identifying disease-associated candidate miRNAs.","volume":"15","author":"C Liang","year":"2019","journal-title":"PLoS Comput Biol"},{"key":"pcbi.1009655.ref018","doi-asserted-by":"crossref","first-page":"e3420","DOI":"10.1371\/journal.pone.0003420","article-title":"An analysis of human microRNA and disease associations.","volume":"3","author":"M Lu","year":"2008","journal-title":"PLoS One"},{"key":"pcbi.1009655.ref019","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1186\/1758-907X-1-6","article-title":"Development of the human cancer microRNA network","volume":"1","author":"S Bandyopadhyay","year":"2010","journal-title":"Silence"},{"key":"pcbi.1009655.ref020","doi-asserted-by":"crossref","first-page":"S2","DOI":"10.1186\/1752-0509-4-S1-S2","article-title":"Prioritization of disease microRNAs through a human phenome-microRNAome network","volume":"4","author":"Q Jiang","year":"2010","journal-title":"BMC Syst Biol"},{"key":"pcbi.1009655.ref021","article-title":"Predicting microRNA-disease associations by integrating multiple biological information","author":"W Lan","year":"2015","journal-title":"IEEE International Conference on Bioinformatics & Biomedicine IEEE"},{"key":"pcbi.1009655.ref022","doi-asserted-by":"crossref","first-page":"65257","DOI":"10.18632\/oncotarget.11251","article-title":"HGIMDA: Heterogeneous graph inference for miRNA-disease association prediction.","volume":"7","author":"X Chen","year":"2016","journal-title":"Oncotarget"},{"key":"pcbi.1009655.ref023","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1186\/s12967-018-1722-1","article-title":"A heterogeneous label propagation approach to explore the potential associations between miRNA and disease.","volume":"16","author":"X Chen","year":"2018","journal-title":"J Transl Med"},{"key":"pcbi.1009655.ref024","doi-asserted-by":"crossref","first-page":"17901","DOI":"10.1038\/s41598-020-75005-9","article-title":"Seq-SymRF: a random forest model predicts potential miRNA-disease associations based on information of sequences and clinical symptoms.","volume":"10","author":"J Li","year":"2020","journal-title":"Sci Rep"},{"key":"pcbi.1009655.ref025","doi-asserted-by":"crossref","first-page":"21106","DOI":"10.1038\/srep21106","article-title":"WBSMDA: Within and Between Score for MiRNA-Disease Association prediction.","volume":"6","author":"X Chen","year":"2016","journal-title":"Sci Rep"},{"key":"pcbi.1009655.ref026","doi-asserted-by":"crossref","first-page":"e1005455","DOI":"10.1371\/journal.pcbi.1005455","article-title":"PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction.","volume":"13","author":"Z You","year":"2017","journal-title":"PLoS Comput Biol"},{"key":"pcbi.1009655.ref027","doi-asserted-by":"crossref","first-page":"104963","DOI":"10.1016\/j.knosys.2019.104963","article-title":"Prediction of potential miRNA-disease associations using matrix decomposition and label propagation","volume":"186","author":"J Qu","year":"2019","journal-title":"Knowledge-Based Systems"},{"key":"pcbi.1009655.ref028","doi-asserted-by":"crossref","first-page":"617569","DOI":"10.3389\/fcell.2021.617569","article-title":"SNFIMCMDA: Similarity Network Fusion and Inductive Matrix Completion for miRNA-Disease Association Prediction","volume":"9","author":"L Li","year":"2021","journal-title":"Front Cell Dev Biol"},{"key":"pcbi.1009655.ref029","doi-asserted-by":"crossref","first-page":"106718","DOI":"10.1016\/j.knosys.2020.106718","article-title":"MLPMDA: Multi-layer linear projection for predicting miRNA-disease association.","volume":"214","author":"L Guo","year":"2021","journal-title":"Knowledge-Based Systems"},{"key":"pcbi.1009655.ref030","doi-asserted-by":"crossref","first-page":"977","DOI":"10.3390\/cells8090977","article-title":"A Novel Computational Model for Predicting microRNA\u2013Disease Associations Based on Heterogeneous Graph Convolutional Networks.","volume":"8","author":"C Li","year":"2019","journal-title":"Cells"},{"key":"pcbi.1009655.ref031","first-page":"855","article-title":"node2vec: Scalable Feature Learning for Networks.","volume":"2016","author":"A Grover","year":"2016","journal-title":"the 22nd ACM SIGKDD International Conference"},{"key":"pcbi.1009655.ref032","doi-asserted-by":"crossref","first-page":"2538","DOI":"10.1093\/bioinformatics\/btz965","article-title":"Neural Inductive Matrix Completion with Graph Convolutional Networks for miRNA-disease Association Prediction","volume":"36","author":"J Li","year":"2020","journal-title":"Bioinformatics"},{"key":"pcbi.1009655.ref033","doi-asserted-by":"crossref","first-page":"1197","DOI":"10.1007\/s00438-020-01693-7","article-title":"FCGCNMDA: predicting miRNA-disease associations by applying fully connected graph convolutional networks","volume":"295","author":"J Li","year":"2020","journal-title":"Mol Genet Genomics"},{"key":"pcbi.1009655.ref034","doi-asserted-by":"crossref","first-page":"bbab174","DOI":"10.1093\/bib\/bbab174","article-title":"Multi-view Multichannel Attention Graph Convolutional Network for miRNA\u2013disease association prediction.","author":"X Tang","year":"2021","journal-title":"Brief Bioinform"},{"key":"pcbi.1009655.ref035","doi-asserted-by":"crossref","first-page":"bbaa240","DOI":"10.1093\/bib\/bbaa240","article-title":"A graph auto-encoder model for miRNA-disease associations prediction","volume":"22","author":"Z Li","year":"2020","journal-title":"Brief Bioinform"},{"key":"pcbi.1009655.ref036","doi-asserted-by":"crossref","first-page":"1040","DOI":"10.3390\/cells8091040","article-title":"Prediction of Potential miRNA-Disease Associations Through a Novel Unsupervised Deep Learning Framework with Variational Autoencoder.","volume":"8","author":"L Zhang","year":"2019","journal-title":"Cells"},{"key":"pcbi.1009655.ref037","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1093\/bioinformatics\/btaa670","article-title":"AEMDA: inferring miRNA-disease associations based on deep autoencoder","volume":"37","author":"C Ji","year":"2021","journal-title":"Bioinformatics"},{"key":"pcbi.1009655.ref038","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1186\/s12859-021-04135-2","article-title":"SMALF: miRNA-disease associations prediction based on stacked autoencoder and XGBoost","volume":"22","author":"D Liu","year":"2021","journal-title":"BMC Bioinformatics"},{"key":"pcbi.1009655.ref039","doi-asserted-by":"crossref","first-page":"D98","DOI":"10.1093\/nar\/gkn714","article-title":"miR2Disease: a manually curated database for microRNA deregulation in human disease","volume":"37","author":"Q Jiang","year":"2009","journal-title":"Nucleic Acids Res"},{"key":"pcbi.1009655.ref040","doi-asserted-by":"crossref","first-page":"D812","DOI":"10.1093\/nar\/gkw1079","article-title":"dbDEMC 2.0: updated database of differentially expressed miRNAs in human cancers","volume":"45","author":"Z Yang","year":"2017","journal-title":"Nucleic Acids Res"},{"key":"pcbi.1009655.ref041","doi-asserted-by":"crossref","first-page":"D1013","DOI":"10.1093\/nar\/gky1010","article-title":"HMDD v3.0: a database for experimentally supported human microRNA-disease associations","volume":"47","author":"Z Huang","year":"2019","journal-title":"Nucleic Acids Res"},{"key":"pcbi.1009655.ref042","doi-asserted-by":"crossref","first-page":"D68","DOI":"10.1093\/nar\/gkt1181","article-title":"miRBase: annotating high confidence microRNAs using deep sequencing data","volume":"42","author":"A Kozomara","year":"2014","journal-title":"Nucleic Acids Res"},{"key":"pcbi.1009655.ref043","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1016\/0022-2836(70)90057-4","article-title":"A general method applicable to the search for similarities in the amino acid sequence of two proteins","volume":"48","author":"SB Needleman","year":"1970","journal-title":"J Mol Biol"},{"key":"pcbi.1009655.ref044","doi-asserted-by":"crossref","first-page":"1103","DOI":"10.1001\/jama.1994.03510380059038","article-title":"Understanding and using the medical subject headings (MeSH) vocabulary to perform literature searches.","volume":"271","author":"HJ Lowe","year":"1994","journal-title":"Jama"},{"key":"pcbi.1009655.ref045","first-page":"26","article-title":"Inferring the human microRNA functional similarity and functional network based on microRNA-associated diseases","volume":"2010","author":"D Wang","year":"1644","journal-title":"Bioinformatics"},{"key":"pcbi.1009655.ref046","doi-asserted-by":"crossref","first-page":"2617","DOI":"10.1093\/bioinformatics\/btt426","article-title":"Novel human lncRNA-disease association inference based on lncRNA expression profiles","volume":"29","author":"X Chen","year":"2013","journal-title":"Bioinformatics"},{"key":"pcbi.1009655.ref047","article-title":"Semi-Supervised Classification with Graph Convolutional Networks.","author":"TN Kipf","year":"2016","journal-title":"arXiv preprint arXiv"},{"key":"pcbi.1009655.ref048","doi-asserted-by":"crossref","first-page":"3178","DOI":"10.1093\/bioinformatics\/bty333","article-title":"BNPMDA: Bipartite network projection for MiRNA-Disease association prediction","volume":"34","author":"X Chen","year":"2018","journal-title":"Bioinformatics"},{"key":"pcbi.1009655.ref049","doi-asserted-by":"crossref","first-page":"354","DOI":"10.3389\/fgene.2020.00354","article-title":"MSCHLMDA: Multi-Similarity Based Combinative Hypergraph Learning for Predicting MiRNA-Disease Association.","volume":"11","author":"Q Wu","year":"2020","journal-title":"Front Genet"},{"key":"pcbi.1009655.ref050","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1186\/s12911-020-01320-w","article-title":"MiRNA-disease association prediction via hypergraph learning based on high-dimensionality features.","volume":"21","author":"Y Wang","year":"2021","journal-title":"BMC Med Inform Decis Mak"},{"key":"pcbi.1009655.ref051","first-page":"bbaa243","article-title":"Predicting drug-disease associations through layer attention convolutional network","author":"Z Yu","year":"2020","journal-title":"Brief Bioinform"},{"key":"pcbi.1009655.ref052","doi-asserted-by":"crossref","first-page":"1018","DOI":"10.1056\/NEJMe0905763","article-title":"Personalized medicine and inhibition of EGFR signaling in lung cancer","volume":"361","author":"AF Gazdar","year":"2009","journal-title":"N Engl J Med"},{"key":"pcbi.1009655.ref053","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1111\/brv.12176","article-title":"microRNAs in breast cancer: regulatory roles governing the hallmarks of cancer","volume":"91","author":"JN Goh","year":"2016","journal-title":"Biol Rev Camb Philos Soc"}],"updated-by":[{"DOI":"10.1371\/journal.pcbi.1009655","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2021,12,22]],"date-time":"2021-12-22T00:00:00Z","timestamp":1640131200000}}],"container-title":["PLOS Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1009655","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,22]],"date-time":"2021-12-22T18:39:39Z","timestamp":1640198379000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1009655"}},"subtitle":[],"editor":[{"given":"Quan","family":"Zou","sequence":"first","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2021,12,10]]},"references-count":53,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2021,12,10]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pcbi.1009655","relation":{"new_version":[{"id-type":"doi","id":"10.1371\/journal.pcbi.1009655","asserted-by":"object"}]},"ISSN":["1553-7358"],"issn-type":[{"value":"1553-7358","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,10]]}}}