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Xiaodong Huang

As seen in: British Journal of Cancer, Nature, Wiley Online Library, Memory Studies, PLOS, Elsevier, Frontiers, MDPI, Royal Society of Chemistry, BioRxiv and
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Articles

Emerging role of ETV4 in colorectal cancer: from molecular mechanisms to clinical implications

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By Yuanbin Liu, Yiyun Wang, Min Huang, Xia Tian, Xiaodong Huang
| Frontiers
Abstract ETV4 (ETS-transformation-specific variant 4) is a member of the ETS transcription factor family that has been extensively studied for its oncogenic functions in cancers. Here, we summarize the role and mechanisms of ETV4 in cancer biology, with a particular focus on colorectal cancer (CRC), as well as its biomarkers and therapeutic potential. As a transcription factor, ETV4 regulates the expression of target genes by recognizing the GGA(A/T) core conserved sequence.
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Kirigami-Cut Pattern Designs for the Enhancement of Sensing Performance Induced by Programmable Out-of-Plane Deformation

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By Xiaodong Huang, Yuhao Wu, Shan Lu
| Wiley Online Library Verified
1 Introduction Recently, mechanical meta-structures based on kirigami have aroused extensive research interest [1-3]. Due to the special structural design, kirigami meta-structure exhibits excellent mechanical properties such as super-stretchablity [4-6], programmable deformation [7-11], multi-stability [12], etc.
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A unified multi-modal foundation model for end-to-end emergency care

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By Zhenwei Huang, Yunfeng Xu, Zixuan Nie, Huiyu Wang, Xiaodong Huang, Ling Huang, Jianhuang Lai, Xiaotu Xi, Changdong Wang, Peiyuan Lai, Cai Wen, Tao Yu
| Nature Verified
Abstract Against the backdrop of population aging and the rising burden of chronic diseases in China, emergency departments (EDs) in tertiary hospitals remain persistently overcrowded. ED overcrowding is a multifactorial phenomenon arising from the interplay of input, throughput, and output factors along the emergency care workflow. Existing artificial intelligence approaches for emergency care are predominantly task-specific.
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