Level D· Scientific groundwork from lab and animal studiesLaboratory StudyEurope PMCOpen access

Protein Array-Based Approach to Evaluate Biomarkers of Beef Tenderness and Marbling in Cows: Understanding of the Underlying Mechanisms and Prediction

Gagaoua M., Bonnet M., Picard B.

Laboratory Study, published in Foods (2020) — summary generated from the PubMed abstract.

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Level D· Scientific groundwork from lab and animal studiesEvidence level of this study

Evidence from laboratory and animal studies provides groundwork for understanding mechanisms and potential before human studies continue.

  • Level A · Stronger Clinical Evidence
  • Level B · Emerging clinical evidence with positive signals
  • Level C · Early human research exploring benefits
  • Level D · Scientific groundwork from lab and animal studies
  • Emerging · Emerging topic under active research
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This page is generated from the PubMed record. The Thai description is an automated summary of bibliographic fields and the abstract, not a full translation, and is not medical advice.

Study type
Laboratory Study
Journal
Foods (2020)
Reported sample size
—
Source database
Europe PMC
PMID
32858893
PMCID
PMC7554754
DOI
10.3390/foods9091180
Citations
32

Abstract (original English)

This study evaluated the potential of a panel of 20 protein biomarkers, quantified by Reverse Phase Protein Array (RPPA), to explain and predict two important meat quality traits, these being beef tenderness assessed by Warner-Bratzler shear force (WBSF) and the intramuscular fat (IMF) content (also termed marbling), in a large database of 188 Protected Designation of Origin (PDO) Maine-Anjou cows. Thus, the main objective was to move forward in the progression of biomarker-discovery for beef qualities by evaluating, at the same time for the two quality traits, a list of candidate proteins so far identified by proteomics and belonging to five interconnected biological pathways: (i) energy metabolic enzymes, (ii) heat shock proteins (HSPs), (iii) oxidative stress, (iv) structural proteins and (v) cell death and protein binding. Therefore, three statistical approaches were applied, these being Pearson correlations, unsupervised learning for the clustering of WBSF and IMF into quality classes, and Partial Least Squares regressions (PLS-R) to relate the phenotypes with the 20 biomarkers. Irrespective of the statistical method and quality trait, seven biomarkers were related with both WBSF and IMF, including three small HSPs (CRYAB, HSP20 and HSP27), two metabolic enzymes from the oxidative pathway (MDH1: Malate dehydrogenase and ALDH1A1: Retinal dehydrogenase 1), the structural pro

What this study does not prove

  • • This study does not prove SVF is an approved treatment or a replacement for standard care.
  • • This is preclinical work; animal or laboratory results cannot be applied to humans.

Evidence level

Evidence from laboratory and animal studies provides groundwork for understanding mechanisms and potential before human studies continue.

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