Junguo Chen
17 Papers
2 Citations
Junguo Chen is an academic researcher. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 2, co-authored 12 publications.
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Papers
Mitolysosome exocytosis, a mitophagy-independent mitochondrial quality control in flunarizine-induced parkinsonism-like symptoms
Feixiang Bao,Lingyan Zhou,Rui Zhou,Qiaoying Huang,Junguo Chen,Sheng Zeng,Yi Wu,Liang Yang,Shufang Qian,Meng Wang,Xueying He,Shangyou Liang,Juntao Qi,Ge Xiang,Qi Long,Jingyi Guo,Zhongfu Ying,Yanshuang Zhou,Qiuge Zhao,Jiwei Zhang,Di Zhang,Wei Sun,Minghui Gao,Hao Wu,Yifan Zhao,Jinfu Nie,Min Li,Quan Chen,Jiekai Chen,Xiao Zhang,Guangjin Pan,Long Zhang,Mingtao Li,Mei Tian,Xingguo Liu +34 more
TL;DR: Results reveal not only a previously unidentified lysosome-associated exocytosis process of mitochondrial quality control that may participate in the FNZ-induced parkinsonism but also a drug-based method for generating mitochondria-depleted mammal cells.
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Predicting pathologic complete response in locally advanced rectal cancer patients after neoadjuvant therapy: a machine learning model using XGBoost
TL;DR: In this article , a machine learning model was used to predict pathological complete response (pCR) after neoadjuvant therapy (NAT) in patients with locally advanced rectal cancer.
Nomogram for predicting overall survival time of patients with stage IV colorectal cancer
Min Lv,Xijie Chen,Junguo Chen,Bin Zhang,Yanmei Lin,Tian-Ze Huang,De-Gao He,Kai Wang,Zeng-Jie Chi,Jiancong Hu,Xiaosheng He +10 more
TL;DR: Wang et al. as discussed by the authors proposed a robust prognostic nomogram for predicting overall survival (OS) of patients with stage IV colorectal cancer in order to provide evidence for individualized treatment.
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Senescence‐based colorectal cancer subtyping reveals distinct molecular characteristics and therapeutic strategies
Min Lv,Du Cai,Cheng-Hang Li,Junguo Chen,Guanman Li,Chuling Hu,Baowen Gai,Jiaxin Lei,Ping Lan,Xiaojian Wu,Xiaosheng He,Feng Gao +11 more
TL;DR: Lower senescence scores were highly predictive of longer disease‐free survival, and patients with low senescenced scores may benefit from immunotherapy, and the findings provide potential treatment interventions for each CRCsenescence subtype to promote precision treatment.
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Endoscopy-Based Deep Convolutional Neural Network Predicts Response to Neoadjuvant Treatment for Locally Advanced Rectal Cancer
Xijie Chen,Junguo Chen,Xiaosheng He,Liang-yu Xu,Wei Liu,Dezheng Lin,Yuxuan Luo,Yue Feng,Lei Lian,Jiancong Hu,Ping Lan +10 more
TL;DR: The proposed DCNN model achieved high specificity and NPV in detecting TRG0 LARC tumors after NT, with a better performance than experienced endoscopists, and may serve as a useful tool for identifying surgery candidates in LARC patients after NT.
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