{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T15:26:03Z","timestamp":1787585163907,"version":"build-2736575974"},"reference-count":43,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T00:00:00Z","timestamp":1787529600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T00:00:00Z","timestamp":1787529600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82301889"],"award-info":[{"award-number":["82301889"]}],"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":["12288101 8206100646 T2321001"],"award-info":[{"award-number":["12288101 8206100646 T2321001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["advanced.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Advanced Science"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Non\u2010invasive preimplantation genetic testing (niPGT) using cell\u2010free DNA (cfDNA) extracted from spent embryo culture medium (SECM) has shown great potential, providing economic and practical advantages for embryo ploidy testing and quality assessment, while minimizing the risk of embryo damage. However, maternal DNA contamination, which can result in sex discordance and false\u2010negative findings, remains a critical barrier to its clinical application in embryo prioritization. In this study, we present the NICE (Non\u2010Invasive CfDNA\u2010based Embryo assessment) framework, designed to enable contamination\u2010resistant evaluation and support\u00a0accurate embryo selection. The workflow integrates a two\u2010step strategy: first, embryonic cfDNA is effectively purified using DECENT\u2010plus\u2014an enhanced version of our previously established deep CNV reconstruction algorithm (DECENT)\u2014that minimizes interference from polar body\u2010derived maternal DNA and improves signal resolution between maternal and embryonic origins. Subsequently, machine learning models based on biometric features extracted from the purified cfDNA are constructed to classify embryo quality, providing intelligent decision support for\u00a0clinical embryo prioritization. By addressing the challenge of maternal contamination, NICE establishes a more automated, standardized and non\u2010invasive paradigm for embryo quality assessment and underscores the critical role of cfDNA\u2010based analysis in facilitating\u00a0non\u2010invasive selection of high\u2010quality embryos\u00a0to improve outcomes in assisted reproductive technology.<\/jats:p>","DOI":"10.1002\/advs.77327","type":"journal-article","created":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T14:39:58Z","timestamp":1787582398000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["NICE: A Two\u2010Step Non\u2010Invasive Framework for Embryo cfDNA Read Enrichment and Quality Assessment"],"prefix":"10.1002","author":[{"given":"Xueya","family":"Zhou","sequence":"first","affiliation":[{"name":"Center for Machine Learning Research Center for Quantitative Biology State Key Laboratory of Female Fertility Promotion Center for Reproductive Medicine Department of Obstetrics and Gynecology Third Hospital Peking University  Beijing China"},{"name":"AI for Science Institute  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shu","family":"Ding","sequence":"additional","affiliation":[{"name":"Center for Machine Learning Research Center for Quantitative Biology State Key Laboratory of Female Fertility Promotion Center for Reproductive Medicine Department of Obstetrics and Gynecology Third Hospital Peking University  Beijing China"},{"name":"National Clinical Research Center for Obstetrics and Gynecology  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-5351-7154","authenticated-orcid":false,"given":"Zhenyi","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences Peking University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiaoling","family":"Shangguan","sequence":"additional","affiliation":[{"name":"Center for Machine Learning Research Center for Quantitative Biology State Key Laboratory of Female Fertility Promotion Center for Reproductive Medicine Department of Obstetrics and Gynecology Third Hospital Peking University  Beijing China"},{"name":"National Clinical Research Center for Obstetrics and Gynecology  Beijing China"},{"name":"Peking\u2010Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies Peking University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2126-1376","authenticated-orcid":false,"given":"Jie","family":"Qiao","sequence":"additional","affiliation":[{"name":"Center for Machine Learning Research Center for Quantitative Biology State Key Laboratory of Female Fertility Promotion Center for Reproductive Medicine Department of Obstetrics and Gynecology Third Hospital Peking University  Beijing China"},{"name":"National Clinical Research Center for Obstetrics and Gynecology  Beijing China"},{"name":"Peking\u2010Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies Peking University  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4585-2923","authenticated-orcid":false,"given":"Peijie","family":"Zhou","sequence":"additional","affiliation":[{"name":"Center for Machine Learning Research Center for Quantitative Biology State Key Laboratory of Female Fertility Promotion Center for Reproductive Medicine Department of Obstetrics and Gynecology Third Hospital Peking University  Beijing China"},{"name":"AI for Science Institute  Beijing China"},{"name":"National Engineering Laboratory for Big Data Analysis and Applications  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3154-6511","authenticated-orcid":false,"given":"Yidong","family":"Chen","sequence":"additional","affiliation":[{"name":"Center for Machine Learning Research Center for Quantitative Biology State Key Laboratory of Female Fertility Promotion Center for Reproductive Medicine Department of Obstetrics and Gynecology Third Hospital Peking University  Beijing China"},{"name":"National Clinical Research Center for Obstetrics and Gynecology  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,8,24]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"crossref","first-page":"1270","DOI":"10.1093\/humrep\/der037","article-title":"Alpha Scientists in Reproductive Medicine and ESHRE Special Interest Group of Embryology. 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