What is it about?

Much of what we know about the effects of various disease conditions involving skeletal muscle dysfunction and of the effects of putative therapeutic procedures and agents is gathered from analyses of muscle tissue samples. However the quantitative information gathered from such material is subject to some distortion and bias arising from the methods used for analysis and with their interaction with the polarized structure of muscle tissue. This article addresses some of the major concerns and suggests ways of removing or minimizing their ill-effects on interpretation of such data.

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Why is it important?

The aim of using information from data gathered in experimental animal models to improve our understanding of human disease requires some common reference points. For histological and cell biological analyses of tissues, such common reference points are only rarely established. The complex and highly polarized structure skeletal of muscle makes it an especially blatant example, where information must be interpreted with due caution when applied between species where differences in size, metabolism and lifestyle can have major influences. In this article it is proposed that data should be gathered in such a way as sy minimize minimize technical bias and to standardize, where possible, to reference denominators that common to the experimental system and to the system of basic interest, commonly Homo sapiens.

Perspectives

The scandal of irreproducibility of much preclinical data arises from many causes of which one is the use of measures of effectiveness that are special to each individual study and to interpret in other work aimed at the same issues but using different sets of criteria. Ideally one would aim to at least use criteria that relate as directly as possible to the biological issue of interest and have common points of reference between investigations and the ultimate target condition, e.g. the human disease of interest.

Terence Partridge

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This page is a summary of: Enhancing Interrogation of Skeletal Muscle Samples for Informative Quantitative Data, Journal of Neuromuscular Diseases, November 2021, IOS Press,
DOI: 10.3233/jnd-210736.
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