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Chen Lin

Verified
Asia–Pacific (APAC)
As seen in: Reuters, Folha de S.Paulo, Line Today (Hong Kong), MSN, MSN Brasil, MSN Canada, MSN India, MSN Ireland, MSN Malaysia, MSN Money Canada, MSN Philippines and
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Chen Lin’s Journalist Portfolio

As U.S. targets China tech, TikTok rival Bigo shifts servers from Hong Kong

As U.S. targets China tech, TikTok rival Bigo shifts servers from Hong Kong

BIGO Technology, a smaller rival of embattled Chinese appmaker ByteDance, is shifting servers from Hong Kong …

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Singapore crushes ivory from around 300 elephants to deter illegal trade

Singapore crushes ivory from around 300 elephants to deter illegal trade

SINGAPORE (Reuters) - Singapore started crushing nine tonnes worth of elephant ivory on Tuesday, in what auth…

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Exclusive: Photoshopping Obama - the company that wants to buy Newcastle United

Exclusive: Photoshopping Obama - the company that wants to buy Newcastle United

SINGAPORE (Reuters) - The Singapore-registered company that says it is close to buying English soccer club Ne…

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Articles

植物乳植杆菌XT016发酵驼奶对葡聚糖硫酸钠诱导结肠炎的保护作用

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By Chen Lin Verified, Huang Lu, Li Shuang
| spgykj.com
Abstract: The aim of this study was to investigate the protective effects of camel milk (CM) fermented by Lactiplantibacillus plantarum ( L. plantarum ) XT016 on DSS-induced colitis, which provided new theoretical basis for the fermented CM application in Xinjiang. The DSS-induced ulcerative colitis mouse model was established. ICR male mice were randomly divided into five groups over a 14-day experimental period: The control group, the model group, the camel milk group, L.
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Quantitative and interface-aware prediction of peptide–protein interactions by VITAL

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By Wei-Hao Chen, Qi-Wen Wang, Zhi-Yi Li, Song-Yang Li, Chen Lin Verified, Zhi-Liang Ji
| Nature Verified
Abstract The quantitative characterization of peptide–protein interactions remains a persistent challenge in computational biology, limiting mechanistic insight and therapeutic development. Here we introduce VITAL (Versatile InTerface-Aware global-local co-Learning), a deep learning framework built on a dual-channel co-learning architecture that fuses protein language model embeddings with a geometry-aware encoder capturing spatial proximity at the interface.
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MedGuard: an LLM-based gatekeeper for detecting clinical risks in Chinese telemedicine consultations

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By Yuntao Shi, Qiwen Wang, Shang Gao, Jing Zhou, Xiangxiang Zeng, Chen Lin Verified, Jinzhen Lin, Zhenzhe Ying
| Nature Verified
Abstract Telemedicine embodies both promise and peril, offering unprecedented convenience while exposing patients and practitioners to potential safety risks. To address these concerns, we present MedGuard, the first LLM-based agent to monitor telemedicine consultations and proactively flag risks in diagnoses, prescriptions, and other clinical dialogs.
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