School of Medicine
Showing 1-10 of 18 Results
Clinical Professor, Medicine - Primary Care and Population Health
Current Research and Scholarly InterestsIn the Philippines where hypertension and prehypertension are prevalent and medication not affordable, we are looking into prevention of hypertension through education and lifestyle modification as a practical alternatives.
Stephen J. Galli, MD
Mary Hewitt Loveless, MD, Professor in the School of Medicine and Professor of Pathology and of Microbiology and Immunology
Current Research and Scholarly InterestsThe goals of Dr. Galli's laboratory are to understand the regulation of mast cell and basophil development and function, and to develop and use genetic approaches to elucidate the roles of these cells in health and disease. We study both the roles of mast cells, basophils, and IgE in normal physiology and host defense, e.g., in responses to parasites and in enhancing resistance to venoms, and also their roles in pathology, e.g., anaphylaxis, food allergy, and asthma, both in mice and humans.
Manuel Garcia-Toca MD, MS
Clinical Professor, Surgery - Vascular Surgery
Current Research and Scholarly InterestsOpen and endovascular management of vascular trauma, aortic dissection, complex thoracic and abdominal aortic aneurysm disease, critical limb ischemia, extracranial cerebrovascular disease and dialysis access.
Rehnborg Farquhar Professor
Current Research and Scholarly InterestsThe role of nutrition in individual and societal health, with particular interests in: plant-based diets, differential response to low-carb vs. low-fat weight loss diets by insulin resistance status, chronic disease prevention, randomized controlled trials, human nutrition, community based studies, Community Based Participatory Research, sustainable food movement (animal rights and welfare, global warming, human labor practices), stealth health, nutrition policy, nutrition guidelines
Assistant Professor (Research) of Pathology, of Medicine (BMIR) and, by courtesy, of Biomedical Data Science
Current Research and Scholarly InterestsComputational systems biology of human disease. Particular focus on integration of high-throughput datasets with each other, and with phenotypic information and clinical outcomes.
Paul George, MD, PhD
Assistant Professor of Neurology and, by courtesy, of Neurosurgery
Current Research and Scholarly InterestsCONDUCTIVE POLYMER SCAFFOLDS FOR STEM CELL-ENHANCED STROKE RECOVERY:
We focus on developing conductive polymers for stem cell applications. We have created a microfabricated, polymeric system that can continuously interact with its biological environment. This interactive polymer platform allows modifications of the recovery environment to determine essential repair mechanisms. Recent work studies the effect of electrical stimulation on neural stem cells seeded on the conductive scaffold and the pathways by which it enhances stroke recovery Further understanding the combined effect of electrical stimulation and stem cells in augmenting neural repair for clinical translational is a major focus of this research going forward.
BIOPOLYMER SYSTEMS FOR NEURAL RECOVERY AND STEM CELL MODULATION:
The George lab develops biomaterials to improve neural recovery in the peripheral and central nervous systems. By controlled release of drugs and molecules through biomaterials we can study the temporal effect of these neurotrophic factors on neural recovery and engineer drug delivery systems to enhance regenerative effects. By identifying the critical mechanisms for stroke and neural recovery, we are able to develop polymeric technologies for clinical translation in nerve regeneration and stroke recovery. Recent work utilizing these novel conductive polymers to differentiate stem cells for therapeutic and drug discovery applications.
APPLYING ENGINEERING TECHNIQUES TO DETERMINE BIOMARKERS FOR STROKE DIAGNOSTICS:
The ability to create diagnostic assays and techniques enables us to understand biological systems more completely and improve clinical management. Previous work utilized mass spectroscopy proteomics to find a simple serum biomarker for TIAs (a warning sign of stroke). Our study discovered a novel candidate marker, platelet basic protein. Current studies are underway to identify further candidate biomarkers using transcriptome analysis. More accurate diagnosis will allow for aggressive therapies to prevent subsequent strokes.
Daniel Aaron Gerber, MD
Clinical Assistant Professor, Medicine - Cardiovascular Medicine
BioDr. Gerber is a critical care cardiologist with dual subspecialty training in cardiovascular and critical care medicine. He is a Clinical Assistant Professor at Stanford University Medical Center in the Department of Medicine’s Division of Cardiovascular Medicine. He completed his residency in internal medicine, fellowship in cardiovascular medicine, and an additional fellowship in critical care medicine at Stanford University and joined as faculty in 2021.
Dr. Gerber manages the full spectrum of heart and vascular conditions with a focus on critically ill patients with life-threatening cardiovascular disease. He is active in medical education, teaching introductory echocardiography to Stanford medical students and residents, critical care echocardiography and point-of-care ultrasonography to Stanford’s Critical Care Medicine fellows and was invited faculty at the Society of Critical Care Medicine’s 2021 Advanced Critical Care Ultrasound Course. Finally, Dr. Gerber’s research interests focus on optimizing cardiac intensive care, including working with the Critical Care Cardiology Trials Network (CCCTN), a national network of tertiary cardiac ICUs coordinated by the TIMI Study Group, and studying temporary mechanical circulatory support techniques, including extracorporeal membrane oxygenation (ECMO), to improve patient outcomes.
Associate Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science
Current Research and Scholarly InterestsMy lab focuses on biomedical data fusion: the development of machine learning methods for biomedical decision support using multi-scale biomedical data. We primarily use methods based on regularized linear regression to accomplish this. We primarily focus on applications in oncology and neuroscience.