McCarthy Lab

PI: John McCarthy
Postdoc:  Christopher Mobley, added 04/28/2021
PhD Students: Yuan Wen

Removed from group 04/28/2021:

Postdoc: Ivan Vechetti, Vandre Casagrande-Figueiredo, PhD Student: Laura Peterson

Lab Research Activities

The primary research interest is to better understand the cellular and molecular mechanisms underlying the regulation of skeletal muscle mass. We investigate the necessity of satellite cells (resident muscle stem cells) in muscle hypertrophy, re-growth following muscle atrophy, and muscle maintenance with aging. We developed a unique mouse model to specifically ablate satellite cells in adult skeletal muscle which, contrary to dogma, revealed that satellite cells do not appear to be necessary for muscle hypertrophy, regrowth or maintenance but, unexpectedly, for the proper remodeling of the extracellular matrix. In addition to these studies, the laboratory is also interested in understanding the role of β-catenin, proto-oncogene c-myc, and microRNAs in skeletal muscle hypertrophy through the regulation of ribosome biogenesis. Finally, we have recently begun to explore the role of ribosome specialization in skeletal muscle plasticity.

Skeletal Muscle Cell Image Segmentation and Measurement

Description:
Currently, image analysis for skeletal muscle cell morphology is extremely time consuming and error prone. Rudimentary image analysis and segmentation methods cannot delineate muscle cells and nuclei from other tissue with sufficient precision and accuracy. As such, we are working on developing an algorithm to address these issues in order to provide better tools for muscle research.

Personnel:

John McCarthy, PI
Yuan Wen

Taylor R Valentino, Grad 08/28/2020

Christopher Mobley, Added 04/28/2021

Jensen Z Goh, Added 08/20/2021

Software:

MATLAB

Computational Methods

(All available from MATLAB toolboxes or under development):
Image processing and morphological operations, gradient vector based active contour model, 2D anisotropic diffusion, 2D fast continuous max-flow, k-means segmentation