Na Li
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Associate Professor of English
Faculty Researcher
Upstream record may be merged OpenAlex, the source of these figures, lists 111 institutions in 5 countries for this author record — a pattern that usually means it combines several researchers with similar names. The totals above may include work by other people.
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Na Li's research primarily focuses on molecular mechanisms of disease and treatment, with a recent emphasis on COVID-19 and related inflammatory conditions. Li has investigated the effects of various compounds and pathways on disease progression and potential therapeutic interventions. This includes studying the alleviation of ferroptosis in doxorubicin-induced myocardial injury via the Nrf2/SLC7A11/GPX4 signaling pathway and the role of the mTOR/HIF-1α pathway in macrophage polarization for acute liver failure. Additionally, Li's work has explored the diagnostic potential of metabolic reprogramming-related genes for diabetic nephropathy and the immunoprotective effects of inactivated SARS-CoV-2 vaccines in pre-vaccinated mice.
Further research has examined the clinical outcomes of COVID-19 pneumonia through chest CT findings and investigated HIV/AIDS knowledge, depression, and stigma among elderly men in rural China. Li's scholarly contributions are reflected in an h-index of 19 and over 2,800 citations across 108 publications. Collaborations include shared publications with Yuyang Zhang, Derya Cansever, and Xinhe Zhang at Harding University.
Metrics
- h-index: 19
- Publications: 108
- Citations: 2,899
Selected Publications
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Error-In-Variables Methods for Efficient System Identification with Finite-Sample Guarantees (2025)
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Learning High-dimensional Dynamical Systems with Limited Sensing (2025)
Collaboration Network
Top Collaborators
- Learning High-dimensional Dynamical Systems with Limited Sensing
- Learning High-dimensional Dynamical Systems with Limited Sensing
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