High-impact exercise and growing bone: relation between high strain rates and enhanced bone formation
Bibliographic record
Abstract
We investigated whether high-impact drop jumps could increase bone formation in the middiaphyseal tarsometatarsus of growing rooster. Roosters were designated as sedentary controls (n = 10) or jumpers (n = 10). Jumpers performed 200 drop jumps per day for 3 wk. The mechanical milieu of the tarsometatarsus was quantified via in vivo strain gauges. Indexes of bone formation and mechanical parameters were determined in each of twelve 30 degrees sectors subdividing the middiaphyseal cortex. Compared with baseline walking, drop jumping produced large peak strain rates (+740%) in the presence of moderately increased peak strain magnitudes (+30%) and unaltered strain distributions. Bone formation rates were significantly increased by jump training at periosteal (+40%) and endocortical surfaces (+370%). Strain rate was significantly correlated with the specific sites of increased formation rates at endocortical but not at periosteal surfaces. Previously, treadmill running did not enhance bone growth in this model. Comparing the mechanical milieus produced by running and drop jumps revealed that jumping significantly elevated only peak strain rates. This further emphasized the sensitivity of immature bone to high strain rates.
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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".