Voluntary running of defined distances alters bone microstructure in C57BL/6 mice fed a high-fat diet
Bibliographic record
Abstract
Obesity increases the risk for pathological conditions such as bone loss. On the other hand, physical exercise reduces body adiposity. To test the hypothesis that physical activity improves bone quality, we evaluated voluntary running of defined distances on trabecular and cortical microstructure in mice fed a high-fat diet (HFD). Sedentary mice were fed the standard AIN93G diet or the HFD. Mice fed the HFD remained sedentary or were assigned to unrestricted running or 75%, 50%, and 25% of unrestricted running with an average running activity at 8.3, 6.3, 4.2, and 2.1 km per day, respectively. The bone structural differences found in sedentary mice were that HFD, compared with the AIN93G diet, resulted in a lower bone volume fraction (BV/TV) and a higher structure model index (SMI) in vertebrae. Running had a greater effect on trabecular microstructure in femurs than in vertebrae; the decrease in SMI and an increase in trabecular thickness (Tb.Th) were in dose-dependent manners. Running was positively correlated with BV/TV and Tb.Th and inversely correlated with SMI in femurs. The HFD increased plasma concentrations of tartrate-resistant acid phosphatase 5b, a marker of bone resorption, in sedentary mice, while running decreased it in a dose-dependent manner. The findings show that voluntary running improves bone quality in young adult mice fed an HFD. Novelty: The high-fat diet alters bone microstructure by increasing bone resorption. Quantitative voluntary running improves bone microstructure through its attenuation of bone resorption in mice fed a high-fat diet.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".