Wnt Signaling–Related Osteokines and Transforming Growth Factors Before and After a Single Bout of Plyometric Exercise in Child and Adolescent Females
Bibliographic record
Abstract
This study examined resting levels of catabolic and anabolic osteokines related to Wnt signaling and their responses to a single bout of plyometric exercise in child and adolescent females. Fourteen premenarcheal girls [10.5 (1.8) y old] and 12 postmenarcheal adolescent girls [15.0 (1.0) y old] performed a plyometric exercise trial. One resting and 3 postexercise blood samples (5 min, 1 h, and 24 h postexercise) were analyzed for sclerostin, dickkopf-1 (DKK-1), osteoprotegerin (OPG), receptor activator of nuclear factor kappa-β ligand (RANKL), and transforming growth factors (TGF-β1, TGF-β2, and TGF-β3). Premenarcheal girls had significantly higher resting sclerostin, TGF-β1, TGF-β2, and TGF-β3 than the postmenarcheal girls, with no significant time effect or group-by-time interaction. DKK-1 was higher in premenarcheal compared with postmenarcheal girls. There was an overall significant DKK-1 decrease from baseline to 1 h postexercise, which remained lower than baseline 24 h postexercise in both groups. There was neither a significant group effect nor group-by-time interaction in OPG, RANKL, and their ratio. RANKL decreased 5 min postexercise compared with baseline and remained significantly lower from baseline 24 h following the exercise. No changes were observed in OPG. OPG/RANKL ratio was significantly elevated compared with resting values 1 h postexercise. In young females, high-impact exercise induces an overall osteogenic effect through a transitory suppression of catabolic osteokines up to 24 h following exercise.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".