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Yin Feng Li on Muck Rack

Yin Feng Li

As seen in: Color Research & Application, Nature, Wiley Online Library, arXiv, MDPI, ACS Publications, Science Magazine, Royal Society of Chemistry, BioRxiv, Dove Medical Press and
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Articles

CX3CR1⁺ CD8⁺ cytotoxic T cells drive tumor killing in esophageal squamous cell carcinoma during neoadjuvant therapy

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By Yahui Zhao, Ruixiang Zhang, Songming Liu, Cheng Liu, Yuhao Wang, Tongtong Wang, Meng Xiao, Jinling Huang, Bo Zhang, Zhaoren He, Yin Feng Li, Zhihua Liu
| Nature Verified
Abstract Immune checkpoint inhibitor (ICI) responses in esophageal squamous cell carcinoma (ESCC) are highly variable, and the immune mechanisms underlying therapeutic sensitivity remain unclear. Here we show, using single-cell RNA, T-cell receptor and whole-exome sequencing of 52 ESCC patients from a phase 3 neoadjuvant trial, that treatment response is associated with coordinated tumor microenvironment remodeling.
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A multi-class gastric biopsy artificial intelligence model developed from whole slide histopathological images

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By Jian-ning Chen, Chang Zhao, Hui Chen, Rui Chen, Qian-Qian Chen, Wen-wen Luo, Xiao-Wei Huang, Zhi Li, Yin Feng Li, Ren-Ming Liu, Xiao-Fang Zhang, Hong Du, Xu-Dan Yang, Chun-Kui Shao, Jian-Xiong Gu, Qin-Yue Yao, Da-Yang Hui, Jin-Yue Zheng, Wang-Sheng Zuo, Qing-Ping Jiang, Jie-Xia Guan, Bo-Jin Su, Yi-Shi Wang, Yi-Wang Zhang, Ze-Qin Wu
| Nature Verified
Abstract Pathological diagnosis of biopsies remains the gold standard for gastric diseases such as gastric carcinoma (GC), but it suffers from clinical misdiagnosis and high workload. Accurately distinguishing early-stage GC (EGC) from advanced-stage GC (AGC) and preoperatively predicting lymph node metastasis (LNM) are crucial for precise treatment; however, this remains a challenge in biopsies.
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A Multimodal Machine Learning Model for Framingham Risk Score–Based Cardiovascular Risk Stratification in Patients With Obstructive Sleep Apnea

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By Feng Zhao, Yin Feng Li, Chenyang Li
| Wiley Online Library Verified
1 Introduction Obstructive sleep apnea (OSA) is a highly prevalent sleep disorder characterized by recurrent upper-airway collapse during sleep, leading to intermittent hypoxia, sleep fragmentation, and excessive daytime sleepiness. It affects hundreds of millions of people worldwide (Iannella et al. 2025).
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