{"id":"https://openalex.org/W4394580459","doi":"https://doi.org/10.1021/acs.jcim.3c02011","title":"ESPDHot: An Effective Machine Learning-Based Approach for Predicting Protein\u2013DNA Interaction Hotspots","display_name":"ESPDHot: An Effective Machine Learning-Based Approach for Predicting Protein\u2013DNA Interaction Hotspots","publication_year":2024,"publication_date":"2024-04-08","ids":{"openalex":"https://openalex.org/W4394580459","doi":"https://doi.org/10.1021/acs.jcim.3c02011","pmid":"https://pubmed.ncbi.nlm.nih.gov/38587997"},"language":"en","primary_location":{"id":"doi:10.1021/acs.jcim.3c02011","doi":"https://doi.org/10.1021/acs.jcim.3c02011","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1021/acs.jcim.3c02011","pdf_url":null,"source":{"id":"https://openalex.org/S167262187","display_name":"Journal of Chemical Information and Modeling","issn_l":"1549-9596","issn":["1549-9596","1549-960X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-b","jufo-1","ki-jl-1","medline","norway-2","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320006","host_organization_name":"American Chemical Society","host_organization_lineage":["https://openalex.org/P4310320006"],"host_organization_lineage_names":["American Chemical Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Chemical Information and Modeling","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101333199","display_name":"Lianci Tao","orcid":"https://orcid.org/0009-0009-0435-2701","observed_orcids":["https://orcid.org/0009-0009-0435-2701"]},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianci Tao","raw_affiliation_strings":["College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053412015","display_name":"Tong Zhou","orcid":"https://orcid.org/0000-0003-4911-073X","observed_orcids":["https://orcid.org/0000-0003-4911-073X"]},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Zhou","raw_affiliation_strings":["College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China"],"raw_orcid":"https://orcid.org/0000-0003-4911-073X","affiliations":[{"raw_affiliation_string":"College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086915875","display_name":"Zhixiang Wu","orcid":"https://orcid.org/0000-0003-1166-8914","observed_orcids":["https://orcid.org/0000-0003-1166-8914"]},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixiang Wu","raw_affiliation_strings":["College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113312284","display_name":"Fangrui Hu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fangrui Hu","raw_affiliation_strings":["College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034361693","display_name":"Shuang Yang","orcid":"https://orcid.org/0009-0003-0834-1889","observed_orcids":["https://orcid.org/0009-0003-0834-1889"]},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Yang","raw_affiliation_strings":["College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043704406","display_name":"Xiaotian Kong","orcid":"https://orcid.org/0000-0001-7557-1674","observed_orcids":["https://orcid.org/0000-0001-7557-1674"]},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaotian Kong","raw_affiliation_strings":["College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100781352","display_name":"Chunhua Li","orcid":"https://orcid.org/0000-0002-0895-3506","observed_orcids":["https://orcid.org/0000-0002-0895-3506"]},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chunhua Li","raw_affiliation_strings":["College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China"],"raw_orcid":"https://orcid.org/0000-0002-0895-3506","affiliations":[{"raw_affiliation_string":"College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5043704406","https://openalex.org/A5100781352"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":{"value":4500,"currency":"USD","value_usd":4500},"apc_paid":null,"fwci":0.542,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.54468397,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":97},"biblio":{"volume":"64","issue":"8","first_page":"3548","last_page":"3557"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.98580002784729,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.98580002784729,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.010599999688565731,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.00139999995008111,"subfield":{"id":"https://openalex.org/subfields/3002","display_name":"Drug Discovery"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/protein-dna-interactions","display_name":"protein-DNA interactions","score":0.5799999833106995},{"id":"https://openalex.org/keywords/binding-free-energy-prediction","display_name":"binding free energy prediction","score":0.6269999742507935},{"id":"https://openalex.org/keywords/interface-residues","display_name":"interface residues","score":0.5730000138282776},{"id":"https://openalex.org/keywords/adasyn-oversampling","display_name":"ADASYN oversampling","score":0.7390000224113464},{"id":"https://openalex.org/keywords/class-imbalance","display_name":"class imbalance","score":0.7739999890327454},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.7799999713897705},{"id":"https://openalex.org/keywords/boruta","display_name":"Boruta","score":0.7749999761581421},{"id":"https://openalex.org/keywords/stacking-ensemble","display_name":"stacking ensemble","score":0.6919999718666077}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6499269604682922},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5889161229133606},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5769866108894348},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5709362626075745},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.5344855785369873},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5235357284545898},{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.5182366371154785},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5181789994239807},{"id":"https://openalex.org/C146481406","wikidata":"https://www.wikidata.org/wiki/Q105131","display_name":"Hotspot (geology)","level":2,"score":0.43949127197265625},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4373193681240082},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4140934348106384},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.4109698235988617},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35760828852653503},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C8058405","wikidata":"https://www.wikidata.org/wiki/Q46255","display_name":"Geophysics","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004247","descriptor_name":"DNA","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":true},{"descriptor_ui":"D004247","descriptor_name":"DNA","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":true},{"descriptor_ui":"D004268","descriptor_name":"DNA-Binding Proteins","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":false},{"descriptor_ui":"D004268","descriptor_name":"DNA-Binding Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D011485","descriptor_name":"Protein Binding","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":false},{"descriptor_ui":"D011506","descriptor_name":"Proteins","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D013816","descriptor_name":"Thermodynamics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1021/acs.jcim.3c02011","doi":"https://doi.org/10.1021/acs.jcim.3c02011","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1021/acs.jcim.3c02011","pdf_url":null,"source":{"id":"https://openalex.org/S167262187","display_name":"Journal of Chemical Information and Modeling","issn_l":"1549-9596","issn":["1549-9596","1549-960X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-b","jufo-1","ki-jl-1","medline","norway-2","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320006","host_organization_name":"American Chemical Society","host_organization_lineage":["https://openalex.org/P4310320006"],"host_organization_lineage_names":["American Chemical Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Chemical Information and Modeling","raw_type":"journal-article"},{"id":"pmid:38587997","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38587997","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of chemical information and modeling","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G4777356863","display_name":null,"funder_award_id":"32271294","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5657665892","display_name":null,"funder_award_id":"31971180","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W1903623309","https://openalex.org/W1964940342","https://openalex.org/W1966960114","https://openalex.org/W1990155556","https://openalex.org/W1995341919","https://openalex.org/W2008545402","https://openalex.org/W2008708467","https://openalex.org/W2017337590","https://openalex.org/W2029118067","https://openalex.org/W2038670706","https://openalex.org/W2042655455","https://openalex.org/W2073229442","https://openalex.org/W2087518504","https://openalex.org/W2089716128","https://openalex.org/W2094148990","https://openalex.org/W2099672241","https://openalex.org/W2100530251","https://openalex.org/W2101017457","https://openalex.org/W2119571185","https://openalex.org/W2139262886","https://openalex.org/W2139460080","https://openalex.org/W2143766664","https://openalex.org/W2148143831","https://openalex.org/W2148633389","https://openalex.org/W2154053567","https://openalex.org/W2156125289","https://openalex.org/W2156665896","https://openalex.org/W2158714788","https://openalex.org/W2161671472","https://openalex.org/W2295598076","https://openalex.org/W2329170059","https://openalex.org/W2582543740","https://openalex.org/W2605361745","https://openalex.org/W2607268717","https://openalex.org/W2748022024","https://openalex.org/W2752956856","https://openalex.org/W2766808155","https://openalex.org/W2789926271","https://openalex.org/W2798552692","https://openalex.org/W2887519731","https://openalex.org/W2904602199","https://openalex.org/W2908012161","https://openalex.org/W2911964244","https://openalex.org/W2935793619","https://openalex.org/W2968582788","https://openalex.org/W2991039860","https://openalex.org/W3007342757","https://openalex.org/W3081249922","https://openalex.org/W3082498841","https://openalex.org/W3084524758","https://openalex.org/W3123999613","https://openalex.org/W3163965514","https://openalex.org/W3191108515","https://openalex.org/W4200066430","https://openalex.org/W4213345021","https://openalex.org/W4214910487","https://openalex.org/W4247993926","https://openalex.org/W4256049924","https://openalex.org/W4294992697","https://openalex.org/W4376635982","https://openalex.org/W4381662000"],"related_works":["https://openalex.org/W3084524758","https://openalex.org/W3093006823","https://openalex.org/W2935793619","https://openalex.org/W4387497319","https://openalex.org/W7221772317","https://openalex.org/W4398251299","https://openalex.org/W3160335751","https://openalex.org/W2895146543","https://openalex.org/W3085584475","https://openalex.org/W2113767070"],"abstract_inverted_index":{"Protein\u2013DNA":[0],"interactions":[1,16],"are":[2],"pivotal":[3],"to":[4,64,98,159],"various":[5],"cellular":[6],"processes.":[7],"Precise":[8],"identification":[9],"of":[10,151],"the":[11,22,58,83,88,136,179,188,194,202],"hotspot":[12],"residues":[13],"for":[14,20,29,33,109],"protein\u2013DNA":[15,26,38],"holds":[17],"great":[18],"significance":[19],"revealing":[21],"intricate":[23],"mechanisms":[24],"in":[25],"recognition":[27],"and":[28,132,173,182,210,215],"providing":[30],"essential":[31],"guidance":[32],"protein":[34],"engineering.":[35],"Aiming":[36],"at":[37],"interaction":[39],"hotspots,":[40],"this":[41],"work":[42],"introduces":[43],"an":[44,93,148],"effective":[45],"prediction":[46,161],"method,":[47],"ESPDHot":[48,192],"based":[49],"on":[50,201],"a":[51,65,79,154],"stacked":[52],"ensemble":[53],"machine":[54],"learning":[55],"framework.":[56],"Here,":[57],"interface":[59,123],"residue":[60,122,128],"whose":[61],"mutation":[62],"leads":[63],"binding":[66],"free":[67],"energy":[68],"change":[69],"(\u0394\u0394":[70],"G":[71],")":[72],"exceeding":[73],"2":[74],"kcal/mol":[75],"is":[76,96,157],"defined":[77],"as":[78,178,187],"hotspot.":[80],"To":[81],"tackle":[82],"imbalanced":[84],"data":[85,106,205],"set":[86,150],"issue,":[87],"adaptive":[89],"synthetic":[90],"sampling":[91],"(ADASYN),":[92],"oversampling":[94],"technique,":[95],"adopted":[97],"synthetically":[99],"generate":[100],"new":[101,118],"minority":[102],"samples,":[103],"thereby":[104],"rectifying":[105],"imbalance.":[107],"As":[108],"molecular":[110],"characteristics,":[111,131],"besides":[112],"traditional":[113],"features,":[114],"we":[115,146],"introduce":[116],"three":[117,165],"characteristic":[119],"types":[120],"including":[121],"preference":[124],"proposed":[125],"by":[126],"us,":[127],"fluctuation":[129],"dynamics":[130],"coevolutionary":[133],"features.":[134,152],"Combining":[135],"Boruta":[137],"method":[138],"with":[139,207],"our":[140],"previously":[141],"developed":[142],"Random":[143],"Grouping":[144],"strategy,":[145],"obtained":[147],"optimal":[149],"Finally,":[153],"stacking":[155],"classifier":[156],"constructed":[158],"output":[160],"results,":[162],"which":[163],"integrates":[164],"classical":[166],"predictors,":[167,197],"Support":[168],"Vector":[169],"Machine":[170],"(SVM),":[171],"XGBoost,":[172],"Artificial":[174],"Neural":[175],"Network":[176],"(ANN)":[177],"first":[180],"layer,":[181],"Logistic":[183],"Regression":[184],"(LR)":[185],"algorithm":[186],"second":[189],"one.":[190],"Notably,":[191],"outperforms":[193],"current":[195],"state-of-the-art":[196],"achieving":[198],"superior":[199],"performance":[200],"independent":[203],"test":[204],"set,":[206],"F1,":[208],"MCC,":[209],"AUC":[211],"reaching":[212],"0.571,":[213],"0.516,":[214],"0.870,":[216],"respectively.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2026-10-31T12:09:11.096373","created_date":"2024-04-09T00:00:00"}