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Yingxin Li on Muck Rack

Yingxin Li

As seen in: Nature, Wiley Online Library, Frontiers in Public Health, MDPI, Taylor & Francis Online, ACS Publications, Royal Society of Chemistry, Cell Reports, Canadian Journal of Infectious Diseases & Medical Microbiology
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Articles

Multiscale symbolic morpho-barcoding reveals region-specific and scale-dependent neuronal organization

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By Sujun Zhao, Yingxin Li, Hanchuan Peng, Yufeng Liu
| Cell Reports Verified
Results We assembled and standardized a light microscopy dataset of whole mouse brains, comprising imaging data from over 200 specimens and approximately 3.7 petavoxels in uncompressed form.24 Neurons were sparsely labeled across multiple regions, including cortex (CTX), thalamus (TH), cerebral nuclei (CNU), and striatum (STR).
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A culturally integrated framework for infant nutrition beyond health education: lessons and a model from the Tibetan population

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By Xi Huang, Yingxin Li, YUE LI, Yanling Hu, Qiong Chen, Wenqian Su
| Frontiers in Public Health Verified
Abstract Background: Improving infant and young child nutrition among marginalized ethnic groups urgently requires a paradigm shift from traditional health education to culturally integrated systemic interventions. Nutrition in the first 1,000 days is critical for long-term health and human capital development. Amid global efforts to eliminate health disparities, Tibetan infants face severe nutritional challenges, with stunting and anemia rates far exceeding national averages.
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A framework for comparative analysis of human and mouse cortical neuron dendrites in corresponding brain regions

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By Zhixi Yun, Nan Ji, Yujin Wang, Jing Rong, Tian Li, Yingxin Li, Qi Shen, Ruilong Wang, Hairuo Zhang, Hao Xu, Nan Mo, Binghua Song, Xin McRae Chen, Yi Wang, Yiying Mai, Ming Ding, Song-Lin Ding, Lijuan Liu, Liwei Zhang, Hanchuan Peng
| Nature Verified
Abstract Cross-species comparisons of neuronal morphology can reveal evolutionary diversification of cortical organization, but they remain limited by scarce human reconstructions, uncertain regional correspondence and scale-dependent morphometrics. Here we introduce a region correspondence framework to compare single-neuron dendritic morphology between mouse and human cortex.
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