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Lu Yin on Muck Rack

Lu Yin

As seen in: Arthritis & Rheumatology, Color Research & Application, Nature, Wiley, Wiley Online Library, American Journal of Clinical Dermatology, arXiv, ScienceDaily, ScienceDirect, BMJ Open and
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Articles

Quantum-sensing-based super-resolution live cell microenvironment imaging

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By Yuxian Lu, Yibo Yang, Ke Xu, Lu Yin, Yang Xu, Xin Wang, Chi Zhang, Wenxin Zhu, Jiandong Feng, Zihan Mao, Zengrong Zhou
| Nature Verified
Abstract Direct monitoring the multifaceted intracellular microenvironment is fundamental for deciphering localized cellular behavior and function. However, performing nanoscale spatiotemporal sensing of the dynamic physiochemical environment within a live cell has remained challenging, mainly limited by the lack of robust, biocompatible method which satisfies the requirements for spatiotemporal resolution, sensitivity, multi-physical sensing capability and long-term viability.
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An mPFC–DMV cortical–autonomic–immune axis governs stress-induced immune dysregulation in sepsis

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By Lu Yin, Fuhong Liu, Mengyun Li, Ye Wang, Lei Liu, Xinxin Zhang, Tingting Gu, Yaru Guo, Dan Wang, Guangchao Zhao, Yongxin Guo, Hongwei Ma, Jing Han, Xijing Zhang, Zhongmin Fan
| Nature Verified
Abstract Chronic psychological stress is a major predisposing factor that worsens sepsis outcomes, yet the neural mechanisms linking stress exposure to immune dysregulation remain poorly understood. Here, using a mouse model of chronic restraint stress (CRS) followed by endotoxemia, we show that prior stress markedly aggravates mortality, systemic inflammation, and immune imbalance during sepsis.
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Drillability-informed ROP prediction and parameter optimization in complex formations

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By Lu Yin, Hualin Liao, Fengtao Qu, Jiafang Xu, Jiansheng Liu
| Nature Verified
Abstract Rate of penetration (ROP) is a key indicator of drilling efficiency in complex formations and directly affects drilling time and cost. Under heterogeneous geological conditions, variations in formation drillability and mismatches between drilling parameters and formation characteristics can reduce rock-breaking efficiency and constrain ROP. This study develops a drillability-informed framework integrating formation characterization, ROP prediction, and drilling parameter optimization.
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