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Ying Guan on Muck Rack

Ying Guan

Changhongjie
As seen in: Nature, Wiley Online Library, Frontiers in Public Health, MDPI, Taylor & Francis Online, ACS Publications, Royal Society of Chemistry, BioRxiv, Dove Medical Press, EIN News and
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Articles

Development and validation of dual-time-window readmission prediction models under China’s medical insurance multi-payment reform

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By Ying Guan, Xianhao Chen, Ting Zhang, Liyu Zhao, Ru Meng, Zaixiang Tan, Xinru Huang, Fengqi Tang
| Frontiers in Public Health Verified
Abstract Background: Readmission is an important indicator of healthcare quality, reflecting continuity of care, treatment outcomes, and the quality of discharge management. However, existing readmission prediction studies have primarily focused on 30-day readmission as the primary outcome, with limited attention to differences in the underlying risk mechanisms, predictive performance, and clinical applicability across different readmission time windows.
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Linear RAG scanning mediates editing of Igκ variable region repertoires

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By Xiang Li, Hongli Hu, Yiwen Zhang, Tammie Zhu, Ying Guan, Kai Xu, Xin Lin, Camille Hebert, Himanshu Batra, Jenny Zhou, Zhaoqing Ba, Duane R. Wesemann, Adam Yongxin Ye, Frederick W. Alt
| Nature Verified
Abstract V(D)J recombination-mediated Igκ light chain variable region exon assembly in precursor (pre)-B cells involves recombination activating gene (RAG) endonuclease-orchestrated cleavage between and joining of paired Vκ and Jκ gene segments and flanking RAG-targeting recombination signal sequences (RSSs)1,2,3. The 3.1-megabase Igk contains 4 Jκs (Jκ1, 2, 4, 5) and 100-plus Vκs in clusters oriented for deletional or inversional joining2.
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Quantitative evaluation of China's smart aging healthcare policy under the background of silver economy development: based on PMC model

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By Ying Guan, Yu Xiang, Shiyu Su, Xinru Huang, Leyao Huang, Zaixiang Tan
| Frontiers in Public Health Verified
Abstract Background: Against the backdrop of deep integration between population aging and digital technologies, smart aging care has emerged as a pivotal approach to alleviating caregiving pressures, optimizing resource allocation for senior care, and driving high-quality development of the silver economy.
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