Predicting problems in one of the body’s most complex organs soon may become easier because of work being done by Wayne State University researchers.
Howard Matthew, Ph.D. and Yinlun Huang, Ph.D., professors of chemical engineering and materials science, recently received a $550,000 grant from the National Science Foundation (NSF) to develop a mathematical model of liver metabolism that can be used to analyze and more effectively predict responses to possible treatments for hepatic steatosis, more commonly known as fatty liver.
The condition affects between 15 and 20 percent of the U.S. population and often is a precursor to more serious problems. Accumulation of fat droplets, or lipids, inside liver cells is a key characteristic in many of the organ’s failure modes. Increased lipid accumulation is usually the first symptom to appear before a measurable dysfunction occurs.
Identifying the causes of fat accumulation, however, is difficult because of the complex nature of the liver, which is involved in making and redistributing metabolites for most tissues in the body. Additionally, a variety of mechanisms trigger liver dysfunctions.
Matthew and Huang’s goal is to develop a mathematical model to analyze and optimally compute possible interventions for treating fatty livers. Their main approach assumes that cellular control of fat metabolism acts as an optimal feedback-control system, and that the liver is trying to maintain certain levels of metabolites to satisfy the needs of other tissues.
Predicting problems in one of the body’s most complex organs soon may become easier because of work being done by Wayne State University researchers.
Howard Matthew and Yinlun Huang, professors of chemical engineering and materials science, recently received a $550,000 grant from the National Science Foundation to develop a mathematical model of liver metabolism that can be used to analyze and more effectively predict responses to possible treatments for hepatic steatosis, more commonly known as fatty liver.