PDC Awards 11 ENABLE Research Grants to Enhance Faculty Research
The PDC is pleased to announce that 11 PDC Members from six clinical departments have received grants to expand their involvement in basic science research. An additional 23 PDC Members were awarded a second year of funding to continue their research. [CLICK TO SEE LAST YEAR’S RECIPIENTS]
The ENhanced Academics in a Basic Laboratory Environment (ENABLE) program provides up to two years of salary support to PDC members to dedicate a portion of their effort working closely with a primary research team.
“The clinical department chairs and the PDC are committed to supporting the professional development of our faculty and to conducting research that leads to real world answers,” said Mark F. Newman, MD, president of the Private Diagnostic Clinic. “ENABLE provides our clinical faculty with the time to engage with faculty from across the School of Medicine and the School of Engineering to make discoveries that are translated into practice.”
2016 ENABLE RESEARCH GRANT RECIPIENTS
Ali, Hakim (Medicine): Profiling complement mediators of donor-specific antibody related tissue injury to diagnose and predict antibody-mediated rejection in lung transplant recipients
Berger, Miles (Anesthesiology): Understanding mechanisms of postoperative cognitive dysfunction and delirium and determining if these disorders are associated with increased long term risk of developing Alzheimer's disease.
Clark, Jeffrey (Medicine): Institutional collaboration to develop novel therapeutic strategies targeting TGFb in human malignancies
Francis, Samuel (Surgery): A novel platelet biomarker for detection of acute arterial and venous thrombosis in emergency department patients
Garrigues, Grant (Orthopaedic Surgery): Shoulder kinematics and cartilage contact in vivo, in states of health, disease, and after treatment
Ghadimi, Kamrouz (Anesthesiology): Role of sirtuins in platelet aging and perioperative thrombocytopenia after mechanical circulatory support
Hartsell, Fletcher (Neurology): Using machine learning analytics, we hope to gain insights that will help optimize symptom management, inform selection of disease modifiers, and even predict relapses.
Kimmick, Gretchen (Medicine): Harnessing the power of light to see and treat breast cancer
Lad, Shivanand (Neurosurgery): Validation of a novel therapeutic approach for crytococcal meningitis
Mettu, Niharika (Medicine): Test the hypothesis that the intratumoral delivery of oncolytic poliovirus immunotherapy will be a safe and feasible approach that may improve the clinical outcomes for patients with pancreatic cancer
Quinones, Quintin (Anesthesiology): Organ protective mechanisms invoked in Mammalian Hibernation: The role of innate immunity