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Yingxin Lin on Muck Rack

Yingxin Lin

As seen in: Nature, PLOS, MDPI, Taylor & Francis Online, Royal Society of Chemistry, BioRxiv, Genome Research
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Articles

A pilot study of the effect of norepinephrine dose on left ventricular-arterial coupling in patients with septic shock

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By Xueqing Wang, Xuwei Lin, Yingxin Lin, Bin Huang, Qing Feng, Ying Shan, Lei Huang, Yunyin Xu
| Nature Verified
Abstract Left ventricular-arterial (V-A) coupling is a key determinant of cardiovascular performance, which integrates intrinsic myocardial contractility with ventricular afterload. Septic shock frequently disrupts this coupling, and norepinephrine (NE) may worsen it in some scenarios.
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Lineage and organ signals sequentially build organ intrinsic nervous systems

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By I-Uen Hsu, Jia Zhao, Yingxin Lin, Yunshan Guo, qian Xu, Yuancheng Shao, Ruiqi Wang, Kakali Ghoshal, Ambra Pozzi, Carmen M. Halabi, Lawrence H. Young, Hongyu Zhao, Le Fu Zhang, Rui B. Chang, Dominic Yin, Rida Mourad
| Nature Verified
Abstract Organ intrinsic nervous systems (OINSs) are critical components of the body–brain axis and coordinate visceral organ function with systemic physiological control1,2,3,4,5,6,7. Despite their importance, how these distinct neural architectures arise from a common neural crest cell origin has remained unclear.
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Interpretable, flexible and spatially aware integration of multiple spatial transcriptomics datasets from diverse sources

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By Jia Zhao, Xiangyu Zhang, Gefei Wang, Yingxin Lin, Tianyu Liu, Rui B. Chang, Hongyu Zhao
| Nature Verified
Abstract Recent advances in spatial transcriptomics (ST) have generated an expanding collection of heterogeneous datasets, offering unprecedented opportunities to investigate tissue organizations and functions. However, effective interpretation and integration of data originating from diverse sources and conditions remain a major challenge. We present INSPIRE, a deep-learning method for interpretable, integrative analysis of multiple ST datasets.
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