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Fen Wang

As seen in: Nature, Wiley, Wiley Online Library, BMJ Open Diabetes Research & Care, Frontiers, Future Internet, MDPI, Taylor & Francis Online, Women & Health, ACS Publications and
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Articles

Targeting the Ip6k2–Runx2 axis disrupts osteoblast–osteoclast coupling to treat osteoporosis

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By Guixing Ma, Yong Chen, Siyuan Cheng, Fen Wang, Yingying Han, Litong Chen, Zhen Ding, Yiran Li, Huiling Cao
| Nature Verified
Abstract Excessive osteoclast activation disrupts bone homeostasis, contributing to osteoporosis (OP). While Runx2 is known to regulate osteoblast differentiation, its role in osteoclasts is less clear. Using conditional knockout models, we demonstrate that Runx2 directly drives osteoclast differentiation by regulating Ctsk transcription. However, its dual function in both osteoblasts and osteoclasts limits therapeutic potential.
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YTHDC1 drives senescence evasion in ovarian cancer through m6A-mediated TERT stabilization

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By Fen Wang, Zhengyang Zhao, Xiaolei Chen, Weihong Lu, Yanshuo Sun, Qingyuan Feng, Piao Xu, Lingjia Shen, Wenqing Zhang, Yan-yan Zhan, Tianhui Hu, Xiaoting Hong, Zhuanghua Li, Shuying Yao, Jiameng Xi, Huirou Luo, Shuguang Lv, Liangxi Xie
| Nature Verified
Abstract N6-methyladenosine (m6A) represents the most abundant internal RNA modification, and a key regulator of gene expression, yet its role in determining cell fate decisions such as senescence remains largely unexplored. Here, we identify the nuclear m6A reader YTHDC1 as a critical regulator of telomere homeostasis and senescence evasion in ovarian cancer. YTHDC1 expression was markedly elevated in advanced-stage tumors and correlated with poor patient survival.
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Global, regional, and national ectopic pregnancy burden: A trend analysis of global disease burden from 1990 to 2021

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By Zhang-Zhou Shen, Fen Wang, Xiang-Yang Ma
| Taylor & Francis Online
ABSTRACT Ectopic pregnancy is a serious gynecological emergency that imposes a significant global burden. This research aims to provide an effective reference for future strategic planning in various countries. Ectopic pregnancy data from 1990 to 2021 were analyzed, the autoregressive integrated moving average (ARIMA) and exponential smoothing (ES) models were used to predict future disease burden.
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