The goals of the Columbia University Medical Center Skin Disease Research Center are to understand the developmental biology of the skin, and to understand the pathogenic interactions between immune cells and target cells in the skin in humans. These goals require sophisticated processing and analysis of primary human tissues and blood. Since these materials are precious and cell yields are small, it is essential to bring the greatest analytic capacity to bear on each human tissue sample. The Immunophenotype Core (IPC) takes advantage of the ongoing experience of the Clynes and Sykes labs, in applying basic immunological research to translational questions in human diseases to now focus this expertise on inflammatory diseases of the skin. Flow cytometry has become the primary tool for the identification of cell populations according to specific parameters, and is therefore employed by an ever-growing number of biomedical scientists. The ability to design, perform and analyze data from multi-parametric flow cytometric experiments requires technical expertise but also immunological expertise to appropriately design the experiment. The method is technologically complex and the equipment is expensive, necessitating shared instrumentation amongst groups of users to facilitate expert use and availability of these vital and versatile instruments. In the next five years, together with our colleagues in the SDRCCUMC, flow cytometric analysis and sorting strategies will 1) define the inflammatory response in alopecia, specifically the NKG2D positive CDS T cell population in the human and mouse;2) isolate relevant cutaneous rare cellular populations for functional studies (Merkel, epithelial stem cell, myeloid suppressor cells, and 3) analyse phenotypic consequences of skin perturbations on cellular function.

National Institute of Health (NIH)
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Center Core Grants (P30)
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Special Emphasis Panel (ZAR1-HL)
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Columbia University (N.Y.)
New York
United States
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