ArticleJournal of animal science2023
Semi-automated technique for bovine skeletal muscle fiber cross-sectional area and myosin heavy chain determination.
Article in Journal of animal science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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Who cites it
5 citing papers in PubMed.
- Article
- Machine Learning-Based Analysis of Differentially Expressed Genes in the Muscle Transcriptome Between Beef Cattle and Dairy Cattle.International journal of molecular sciences · 2025Article
- Effects of implant status and breed type on feedlot performance, carcass characteristics, sera metabolites, and immunohistochemical responses in finishing steers.Journal of animal science · 2025Article
- A pre- and postnatal immune challenge influences muscle growth and metabolism in weaned pigs.Journal of animal science · 2024Article
- Body, carcass, and steak dimensions of straightbred Holstein calves and Angus-sired calves from Holstein, Jersey, and crossbred beef dams.Journal of animal science · 2023Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Myosin heavy chain (MyHC) type and muscle fiber size are informative but time-consuming variables of interest for livestock growth, muscle biology, and meat science. The objective of this study was to validate a semi-automated protocol for determining MyHC type and size of muscle fibers. Muscle fibers obtained from the longissimus and semitendinosus of fed beef carcasses were embedded and frozen within 45 min of harvest. Immunohistochemistry was used to distinguish MyHC type I, IIA, and IIX proteins, dystrophin, and nuclei in transverse sections of frozen muscle samples. Stained muscle cross sections were imaged and analyzed using two workflows: 1) Nikon workflow which used Nikon Eclipse inverted microscope and NIS Elements software and 2) Cytation5 workflow consisting of Agilent BioTek Cytation5 imaging reader and Gen5 software. With the Cytation5 workflow, approximately six times more muscle fibers were evaluated compared to the Nikon workflow within both the longissimus (P < 0.01; 768 vs. 129 fibers evaluated) and semitendinosus (P < 0.01; 593 vs. 96 fibers evaluated). Combined imaging and analysis took approximately 1 h per sample with the Nikon workflow and 10 min with the Cytation5 workflow. When muscle fibers were evaluated by the objective thresholds of the Cytation5 workflow, a greater proportion of fibers were classified as glycolytic MyHC types, regardless of muscle (P < 0.01). Overall mean myofiber cross-sectional area was 14% smaller (P < 0.01; 3,248 vs. 3,780) when determined by Cytation5 workflow than when determined by Nikon workflow. Regardless, Pearson correlation of mean muscle fiber cross-sectional areas determined by Nikon and Cytation5 workflows was 0.73 (P < 0.01). In both workflows cross-sectional area of MyHC type I fibers was the smallest and area of MyHC type IIX fibers was the largest. These results validated the Cytation5 workflow as an efficient and biologically relevant tool to expedite data capture of muscle fiber characteristics while using objective thresholds for muscle fiber classification.
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