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Leying Chen on Muck Rack

Leying Chen

As seen in: Nature, Science Magazine, BioRxiv, eLife
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Articles

JAK inhibitors alleviate EGFR-inhibitor-induced diarrhea by protecting intestinal stem cells from adaptive-immune-exacerbated injury

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By Yuan Daniel Cheng, Chenyue Xu, Dazhao Lv, Meng Tian, Haoyu Wang, Bingxue Yang, Leying Chen, Qing You, Shiyi Zhang
| Nature Verified
Abstract While intestinal stem cells (ISC) are essential for epithelial homeostasis, their dynamic regulation during immune-mediated injury remains undefined. Here we show that suppression of jejunal ISC proliferation contributes to pathology arising from oral EGFR (epidermal growth factor receptor) tyrosine kinase inhibitor (TKI) treatment.
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Topical JAK inhibition ameliorates EGFR inhibitor-induced rash in rodents and humans

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By Qing You, Ashish Patel, Yi Pan, Leying Chen
| Science Magazine Verified
Editor’s summary Epidermal growth factor receptor inhibitors (EGFRis) are used to treat several common cancers, but EGFRi use is frequently complicated by a skin rash that shows limited response to current treatments. Here, You et al. conducted a transcriptomic analysis of the skin of rats exposed to an EGFRi to uncover early changes preceding rash development, finding early activation of keratinocytes that led to activation of the JAK-STAT pathway and recruitment of inflammatory cells.
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Redefining the Game: MVAE-DFDPnet's Low-Dimensional Embeddings for Superior Drug-Protein Interaction Predictions

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By Yu Ye Wu, Longfei Zhao, Leying Chen, Liang-Yong Xia
| BioRxiv
Abstract Precisely predicting drug-protein interactions (DPIs) is pivotal for drug discovery and advancing precision medicine. A significant challenge in this domain is the high-dimensional and heterogeneous data characterizing drug and protein attributes, along with their intricate interactions. In our study, we introduce a novel deep learning architecture: the Multi-view Variational Auto-Encoder embedded within a cascade Deep Forest (MVAE-DFDPnet).
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