D-25 Free Communication/Poster - Physical Activity Correlates
Bibliographic record
Abstract
High impact physical training is beneficial for bone structure and mineralization and typically results in increased levels of bone turnover markers. However, the acute effects of a single exercise session on bone markers are unclear. In adults, inconsistent results have been demonstrated following high impact exercise. In children, there is a paucity of data in this area. PURPOSE: To investigate the acute response of bone turnover markers to an exercise session consisting of high mechanical loading in boys and men. METHODS: Participants underwent a protocol of plyometric jumping exercises (total 144 jumps). Venous blood samples were collected pre, 5 minutes post-, 1 hour post- and 24 hours post-exercise session to measure bone-specific alkaline phosphatase (BAP), amino-terminal cross-linking telopeptide (NTx), osteoprotegrin (OPG) and receptor activator of nuclear factor kb ligand (RANKL). RESULTS: Boys had higher BAP levels, with an increase 24 hours post-exercise (111.9±29.2 vs. 137.6±36.3 μg/L, respectively), which was not observed in the men (31.4±11.1 vs. 33.3±10.5 μg/L, respectively). NTx levels were higher in boys, with a greater increase over time in boys than in men (boys: 48.7±13.7 vs. 58.8±16.7 nM BCE pre- and 24 hours post-exercise, respectively; men: 21.7±5.4 vs. 19.4±5.0 NM BCE pre- and 24 hours post-exercise, respectively). OPG and RANKL levels were similar in boys and men before and after exercise, with no change over 24 hours. CONCLUSIONS: These results indicate that even one session of exercise stimulates bone turnover, as reflected in the increase in both BAP and NTx values, in boys (but not men) within 24 hours.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.864 | 0.718 |
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".