{"id":58,"date":"2019-05-09T13:36:27","date_gmt":"2019-05-09T17:36:27","guid":{"rendered":"https:\/\/health.uconn.edu\/beiyan-zhou-lab\/?page_id=58"},"modified":"2024-09-19T14:46:38","modified_gmt":"2024-09-19T18:46:38","slug":"research","status":"publish","type":"page","link":"https:\/\/health.uconn.edu\/beiyan-zhou-lab\/research\/","title":{"rendered":"Research"},"content":{"rendered":"

Research<\/h1>\n<\/div><\/div><\/div><\/div>

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Immune cells are often presented with diversified origins\/residences and execute multifaceted functions ever-adapting to microenvironmental cues. \u00a0It is the essence of Immunology to capture and harness the actions of immune cells in complex tissue and stress settings is the essence of immunology.<\/p>\n

My research program focuses on understanding the regulatory mechanisms of immune cells in obesity-induced type 2 diabetes (T2DM) and atherosclerotic cardiovascular diseases (ASCVD). We have identified several critical regulators in controlling immune lineage determination, cancerous transformation, and their interaction with host tissue cells under chronic stress conditions. Work from my lab has contributed to the first discovery of miR-150 as a potent regulator for hematopoietic stem cell-derived B-cell formation and function under normal, obese, and cancerous transformation conditions (PNAS, 2007; Mol Cancer Res, 2013;\u00a0 Sci Report, 2016<\/em>); and miR-223 as a potent regulator of macrophage polarization (Circulation, 2012; J.C.I. 2015<\/em>).<\/p>\n

Our group recently developed new bioinformatics programs that incorporated single-cell transcriptome technology to allow in-depth fine-mapping monocyte\/macrophage function under various diseases conditions (J.C.I. Insight, 2019; Mol Cell, 2019, Cell Metabolism, 2022<\/em>) and immune cell-function guided predictive tools for immunotherapy (J.E.M., 2021<\/em>). Notedly, the application of these novel algorithms revealed a hitherto unknown pathogenic foaming program directly associated with the incidence of ASCVD, which enabled the development of a high-performance, proof-of-concept CVD risk prediction model (Circulation, 2022<\/em>). To address the unique challenges in large bio-data analyses, we developed additional computational tools empowered by machine learning algorithms and tailored to biological big data mining (invention,\u00a0patent pending<\/em>).<\/p>\n

While compelling evidence has indicated the crucial roles played by epigenetic regulators in both normal developmental control and pathogenesis of diseases, our understanding of the full picture is still in its infancy.<\/p>\n

Keep tuned......<\/strong><\/p>\n

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<\/a>Macrophage Polarization\u00a0 -MacSpectrum, and AtheroSpectrum<\/a>,<\/h3>\n

We have developed a set of transcriptome analysis tools, MacSpectrum, and AtheroSpectrum<\/a>, which integrate original algorithms based on macrophage single-cell RNA sequencing data. MacSpectrum and AtheroSpectrum provide high-resolution annotation of macrophage subsets by precisely detailing maturation,\u00a0 activation, and lipid metabolism status and is adaptable across mice, humans, and several disease states.<\/p>\n

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