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Directed by Debraj “Raj” Mukherjee, MD, MPH, the laboratory focuses on improving access to care, reducing disparities, maximizing surgical outcomes, and optimizing quality of life for patients with brain and skull base tumors.
The laboratory achieves these aims by creating and analyzing institutional and national databases, developing and validating novel patient-centered quality of life instruments, leveraging machine learning and artificial intelligence platforms to risk-stratify vulnerable patient populations, and designing novel surgical trials to push the boundaries of neurosurgical innovation.
Our research also investigates novel approaches to improve neurosurgical medical education including studying the utility of video-based surgical coaching and the design of new operative instrumentation.
Richard Chaisson Lab
Research in the Richard Chaisson Lab primarily examines tuberculosis and HIV infection, with specific focus on global epidemiology, clinical trials, diagnostics and public health interventions. Our recent research has involved evaluating a molecular diagnostic test for tuberculosis in HIV patients; observing TB responses during treatment of pulmonary tuberculosis; and examining antiretroviral therapy adherence, virologic and immunologic outcomes in adolescents compared with adults in Southern Africa.
Robert Bollinger Lab
The key research interests in the Robert Bollinger Lab include identifying biological and behavioral risk factors for HIV transmission as well as characterizing the clinical progression and treatment of HIV and related infectious diseases. We also have a long-standing interest in optimizing health care capacity and delivery in settings with limited resources. Our work includes implementing science research projects to explore the effectiveness of initiatives such as task-shifting, clinical education, distance learning and mobile health programs as a way to improve health care in these locations.
The Ramanathan Lab
Chronic rhinosinusitis (CRS) is a leading cause of morbidity globally and is the single most common self-reported chronic health condition and accounts for billions of dollars in health care costs and lost work days annually. Exposure to air pollutants is thought to be a critical modifier of CRS susceptibility. Despite marked reductions in air pollution levels in the United States, the fine particulate component of air pollution (PM2.5) and ultrafine pollutants secondary to traffic continue to remain a recalcitrant issue globally and in the United States. The Ramanathan Lab focuses on studying the role of air pollution (PM2.5) in CRS. In collaboration with scientists at the Bloomberg School of Public Health, we have utilized a state of the art air pollution exposure system to develop a novel mouse model of air pollution induced rhinosinusitis that mimics many of the features of CRS in humans. Our lab uses transgenic mouse models and novel immunologic/genomic techniques to study the mec...hanisms by which PM2.5 causes eosinophilic inflammation and sinonasal epithelial barrier dysfunction. We are also interested in the role of the antioxidant transcription factor, Nrf2, which has shown to stabilize the epithelial barrier and reduce eosinophilia in PM induced rhinosinusitis as a potential therapeutic target. view more
The mission the Translational Informatics Research and Innovation (TIRI) Lab is to understand and create advanced technology and digital device solutions that address challenges to the translation of biomedical data science-informed guidance into clinical use to improve the health of individuals, especially for people that are often underrepresented in research.
Dr. Wu leads a multi-disciplinary team with collaborators from the Bloomberg School of Public Health, JHU Whiting School of Engineering, and JHU Krieger School of Arts and Sciences. She conducts ongoing investigations with the Multicenter AIDS Cohort Study and Women’s Inter-agency Health Study. Her lab’s goals are to develop, implement, and validate novel imaging-based metrics of cardiac structure and function to improve risk prediction and stratification at the individual patient-level.
Predictors of Sudden Cardiac Death by Magnetic Resonance Imaging
Subclinical myocardial disease in people living with HIV
Individualized risk prediction
Cardiac structural and mechanical modeling