U.S. Department of Health and Human Services
 

 Contact Info

 
Tel: +1 301 496 0895
Email: vipulp@mail.nih.gov
 

 Training and Experience

 
Ph.D., Princeton University, 1988

M.A., Princeton University, 1984

B.S., California Institute of Technology, 1983

Assistant Professor, Physics Department, Princeton University, 1993-2001

Member, The Institute for Advanced Study, 1991-1993

Research Physicist, Institute for Theoretical Physics, University of California, 1988-1991
 

 Related Links

 
Specialties: Biomedical Engineering/ Biophysics/ Physics, Computational Biology/ Bioinformatics/ Biostatistics/ Mathematics, Systems Biology

Research Summary

Research Goal

The ultimate goal of our research is to predict the response of human metabolism to dietary changes, and to predict the whole body effects of new therapies.

Current Research

Quantitative Estimation of Sensitivity of Lipolysis to Insulin

Insulin resistance is a primary risk factor for several common diseases, including diabetes, cardiovascular disease, hypertension, and some forms of cancer.  The mechanisms underlying insulin resistance are not completely understood.  One important gap in our understanding relates to defects in insulin’s ability to regulate lipolysis, leading to relative elevations of free fatty acids (FFA) in plasma.  Elevated FFAs have been implicated in the modification of insulin action of various tissues, as well as in altering intermediates of the insulin signaling pathway and mitochondrial enzymes.  Therefore, methods to quantify insulin’s effects on lipolysis and plasma FFA levels in various conditions of insulin resistance would be useful.  As insulin is a critical modulator of FFA levels in vivo, our goal is to find a simple mathematical model that could reproduce the time course of serum FFA levels in response to insulin and to use this model as the basis of an index of FFA sensitivity to insulin that describes insulin’s acute effect (minutes to hours) on plasma FFA levels.

Model of Reactive Oxygen Species in Mitochondria

Reactive oxygen species (ROS) have been shown to have tissue-damaging effects that underlie many disease complications, including those associated with diabetes, Parkinson's, Alzheimer's, and atherosclerosis (Brownlee, 2005).  This oxidative stress is thought to result from an organism's inability to detoxify and repair damage at the same rate that ROS are produced.  On the other hand, it should be noted that ROS signaling is important in cellular functioning.  In mitochondria, where ROS (e.g., superoxide) are produced through a process that is very sensitive to the proton motive force, oxidative stress is prevented by scavenging enzymes (e.g., MnSOD) and uncoupling proteins (e.g., UCP2).  Details of this regulation in mitochondria are still being established.  The interplay between nutrient sensing and ROS signaling is complex, and the goal of our research is to mathematically model the relevant pathways to understand the deleterious aspects of this interplay as it relates to the metabolic syndrome and obesity.

Adipocyte Development and Insulin Resistance

Our overall goal is to understand how adipose tissue dynamics are related to insulin resistance and diabetes.  Adipose tissue grows by two mechanisms: hyperplasia (cell number increase) and hypertrophy (cell size increase).  How do genetics and diet affect the relative contributions of these two mechanisms to the growth of adipose tissue in obesity?  We are particularly interested in investigating the role played by insulin-sensitizing agents such as thiazoledinediones in altering the development of adipocytes.  We chose to investigate this dynamic behavior by mathematically modeling the changes in cell size distributions in adipose tissue over time under several conditions, since this will provide a global view of cell size dynamics as adipocytes accumulate lipids and move from small sizes to maturity.​

How will this research help the public?

Obesity and diabetes are critical public health issues. We have only the beginnings of an understanding of how human metabolism works and what therapies will be effective over the long-term in controlling the complications of these diseases. Our purpose is to make quantitative predictive models that allow researchers to develop therapies and diets more effectively.

Need for further study

The systems level understanding of the various organs that are involved in metabolism needs further study.​