A preliminary study on the effect of loaded and unloaded exercise on <i>N</i>-propeptide of type II collagen and serum cartilage oligomeric matrix protein activity of articular cartilage in healthy young adults
Bibliographic record
Abstract
The serum concentration of cartilage oligomeric matrix protein (sCOMP) is considered a mechanosensitive biomarker of articular cartilage turnover, and N-propeptide of type II collagen (PIIANP), a proposed biomarker of type II collagen synthesis. Few studies have investigated the anabolic and turnover response of articular cartilage in response to acute changes in body mass during exercise. Using a repeated measure cross-over design, 15 healthy adults (age 18–30 years) performed three 30 min bouts of treadmill walking exercise under three loading conditions: (1) control (no alteration to body mass); (2) loaded (12% increase in body mass using a weighted vest); and (3) unloaded (12% decrease in body mass using lower body positive pressure). Venous blood was collected before, immediately after, and 15 and 30 min after exercise to investigate cartilage turnover (sCOMP) and anabolism (PIIANP). A main time effect ( p ≤ 0.05) revealed that sCOMP levels were significantly greater post-exercise (for all three body loading conditions) as compared to before exercise, 15 and 30 min post-exercise. There was a significant condition × time interaction ( p ≤ 0.05) for PIIANP, indicating that in the loaded condition, PIIANP concentrations at 15 min post-exercise were 13.8% greater than immediately following exercise, and 12.9% greater than before exercise. In summary, sCOMP concentration was acutely increased with all three loading conditions. However, PIIANP increased only after exercise in the loaded condition, suggesting an acute anabolic effect on articular cartilage. NCT05925244.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".