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Automated Analysis of Skeletal Muscle Fiber Cross-sectional Area and Metabolic Ty

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 2R42AR055604-02A1
Agency Tracking Number: R42AR055604
Amount: $1,188,087.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: NIAMS
Solicitation Number: PA10-051
Solicitation Year: 2011
Award Year: 2011
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
11575 Sorrento Valley Rd.
United States
DUNS: 612181532
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 (858) 461-6863
Business Contact
Phone: (858) 461-6861
Research Institution
980 Indiana Avenue Lockfield Village, RM 2232
United States

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 Nonprofit College or University

DESCRIPTION (provided by applicant): The accurate quantification of skeletal muscle morphology is desired in a wide variety of medical areas such as muscle regeneration, muscular dystrophy, exercise physiology, and nutrition. For such studies, skeletal muscle is often fixed, sectioned, and labeled to visualize the borders of the muscle fibers, and digitally photographed. Investigators then use laborious time- consuming techniques to trace the outline of muscle fibers to calculate the cross-sectional area (CSA). Investigators also label muscle tissues to identify the expression of certain myosin subtypes, but current reagents do not work well in the mouse, the most widely utilized experimental animal. In Phase I of this STTR project, an algorithm was developed and incorporated into Vala's CyteSeer(R) cell image analysis program, to enable rapid calculation of CSA, and quantification of a single myosin isoform within the muscle. For Phase II, we propose: 1) to develop monoclonal antibodies (MAbs) for identification of myosin subtypes (slow, IIa, IIb, and IIx), laminin, and OXPAT in the mouse, and to label the MAbs with organic fluorophores or nanocrystals (aka quantum dots) for use in direct immunocytofluorescence procedures, 2) to enable CyteSeer(R) to performmultichannel analysis for the analysis of multiple myosin isoforms, the analyze of distribution of nuclei within the fibers (important to detect regenerating fibers or inflammation), or analysis of intramyocellular lipids and proteins associated with obesity, and 3) to improve the ability of CyteSeer(R) to characterize fibers in healthy and damaged muscle, especially with regard to muscular dystrophy. The research will develop reagents and software which will greatly increase the accuracy and speed with which skeletal muscle can be analyzed a subject of great importance in a variety of health contexts. PUBLIC HEALTH RELEVANCE: The research will develop novel reagents and a PC-compatible image analysis program which will be useful to researchers working on muscle health. Reagents will selectively label certain muscle fiber types, depending upon the type of muscle that is found (slow vs. fast contracting). The program will provide for very fast analysis of the structure and metabolic character of musclefibers, from images obtained from the muscle by microscopes linked to digital cameras. This will be of interest to medical researchers studying exercise, nutrition, obesity, space-flight, and muscular dystrophies. The methods developed by this project willimprove the way muscle is characterized in the most common animal used in biomedical research (the mouse), and greatly increase the speed and quality of the analysis of muscle fiber types.

* Information listed above is at the time of submission. *

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