Bone resorption is suppressed immediately after the third and fourth days of multiday cycling but persistently increased following overnight recovery
Bibliographic record
Abstract
Previous studies suggest that seasoned cyclists may incur a low bone mineral density. This study investigated the effect of multiday cycling on bone turnover. Ten male cyclists completed 4 consecutive days of cycling for 3 h·day(-1). Sweat calcium excretion during exercise and serum calcium, cortisol, bone formation marker (bone alkaline phosphotase (bone-ALP)), bone resorptive marker (C-terminal telopeptide of type I collagen (β-CTX)), and parathyroid hormone concentration were measured before and immediately postexercise each day. Serum β-CTX concentration increased from pre- to postcycling on days 1 and 2 (p = 0.01) (day 1: 0.31 ± 0.14 to 0.60 ± 0.4 ng·mL(-1); day 2: 0.58 ± 0.26 to 0.87 ± 0.42 ng·mL(-1)), while serum bone-ALP concentration remained unchanged. Conversely, on days 3 and 4 both serum β-CTX (day 3: 0.60 ± 0.26 to 0.43 ± 0.26 ng·mL(-1), p < 0.05; day 4: 0.63 ± 0.21 to 0.43 ± 0.22 ng·mL(-1), p < 0.001) and bone-ALP (p < 0.01) response to exercise was suppressed. Interestingly, calcium lost to sweat and postexercise serum cortisol concentration were also significantly lower on days 3 and 4 than on day 1 (p < 0.05). However, both serum β-CTX (102%-124%) and bone-ALP (25%-29%) remained persistently elevated after 21 h of overnight recovery on all successive days compared with day 1 pre-exercise, where the percentage increase was greater for β-CTX (p < 0.05). Bone resorption, immediately following prolonged cycling, is acutely reduced by the third and fourth consecutive days and is coincident to reduced sweat calcium excretion and cortisol concentration. However, multiday cycling imposes a persistent increase in bone resorption following overnight recovery.
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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) | 0.001 | 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) | 0.002 | 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".