Jonathan F. Wenk, Gill Associate Professor

Department of Mechanical Engineering

Lab Introduction:

The primary focus of our research is using computational methods to better understand the progression and treatment of various types of heart disease. These methods are also validated with experimental measurements at multiple scales.

Multiscale modeling of inherited cardiomyopathies and therapeutic interventions

The goal of this research is to develop a predictive multiscale model that will improve understanding of familial cardiomyopathies and that can be used to help test potential new therapies for cardiac disease. The research plan integrates state-of-the-art hierarchically-coupled mathematical models with validation experiments that range from stopped-flow molecular kinetic assays to magnetic resonance imaging of myocardial strain patterns. The model will be tested using molecular to organ-level experimental data obtained from wild-type mice and from transgenic animals that develop cardiac hypertrophy because of a mutation in myosin regulatory light chain. Additional tests will be performed using drugs that enhance and inhibit myosin-level contractile function.

Personnel:

Jonathan F. Wenk (PI)

Students:

Hossein Sharifi (PhD student), Added on MCC 2/14/2022, Added to LCC 3/23/2022

Mohammad Mehri (PhD student), Added on MCC 2/14/2022

Charles Kurtis Mann (Postdoc), Added on MCC 02/14/2022, Added on LCC 06/03/2022

Mohammad Mehri (Graduate), Added on LCC 09/20/2022

Gokul Anugrah Gopakumar, (Graduate), Added on MCC 04/04/2023

Methods:

We use multiscale finite element (FE) modeling techniques in the FEniCS framework, which is an open-source FE solver. This includes a modular structure that couples ODE systems, which represent calcium and binding kinetics, to the PDE system that represents global structural mechanics.

Software:

FEniCS, Singularity

Collaborators:

Kenneth S. Campbell (UK Physiology, co-PI), Lik Chuan (Lee Michigan State Engineering, co-PI)

Grant:

U01 HL133359 (NIH)

Publications:

There are several papers associated with this grant, but none that have used UK HPC resources since we just started using the system. This will be updated later.