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Related Experiment Video

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Induction and Assessment of Exertional Skeletal Muscle Damage in Humans
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Urinary Metabolites Variation After High-Intensity Rowing Training and Potential Biomarker Screening for

Jie Wu1, Junjie Ding2,3, Ziyue Zhao2,3

  • 1Department of Physical Education, Beijing Institute of Technology, Zhuhai 519000, China.

International Journal of Molecular Sciences
|August 28, 2025
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Summary

This study reveals that urine analysis can predict exercise-induced muscle damage (EIMD). Researchers identified specific urinary metabolite changes linked to EIMD, offering a non-invasive prediction method.

Keywords:
biomarker screeningexercise-induced muscle damagemetabolomicsrowing exerciseurinary metabolites

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Area of Science:

  • Sports Medicine
  • Biochemistry
  • Metabolomics

Background:

  • Exercise-induced muscle damage (EIMD) is a common risk in physical activity.
  • Current EIMD prediction methods lack non-invasive and instant capabilities.
  • Urinary analysis presents a potential avenue for EIMD prediction, but metabolite changes remain uncharacterized.

Purpose of the Study:

  • To investigate urinary metabolite variations following high-intensity exercise-induced muscle damage.
  • To identify potential urinary biomarkers for non-invasive EIMD prediction.
  • To explore the relationship between EIMD and metabolic changes.

Main Methods:

  • Recruited eighteen young students without regular exercise habits.
  • Induced EIMD through high-intensity rowing exercise.
  • Analyzed urinary metabolites using quasi-targeted metabolomics and confirmed EIMD with blood tests and pain assessment.

Main Results:

  • High-intensity rowing exercise successfully induced EIMD.
  • Significant alterations in urinary metabolites were observed, with 23 upregulated and 26 downregulated.
  • Identified differential metabolites are associated with energy, antioxidant metabolism, and exercise performance.

Conclusions:

  • Urinary metabolite profiling can detect EIMD.
  • Potential urinary biomarkers for EIMD prediction were identified with high sensitivity and specificity.
  • This research offers a novel, non-invasive approach for monitoring muscle damage.