High-fat, sucrose diet impairs geometrical and mechanical properties of cortical bone in mice
Bibliographic record
Abstract
Exposure to diets high in fat and sucrose can induce hyperinsulinaemia, affect Ca and Mg metabolism, and alter bone mineralisation and mechanical properties. The present study assessed morphological and mechanical changes in a murine model exposed to a high-fat/sucrose (HFS) diet, as well as corresponding molecular and endocrine markers of bone turnover. Female C57BL/6 mice (aged 9 weeks) consumed either a low-fat, complex carbohydrate diet or an HFS diet for 10 weeks. At the end of the 10 weeks, serum was collected for biochemical analysis. Tibiae from half the mice (n 15) were randomly selected to be micro-computed tomography scanned and tested to failure in cantilever bending, while the remaining half were prepared for real-time PCR analysis. Serum tartrate-resistant acid phosphatase was significantly elevated in HFS mice, while osteocalcin remained unchanged. Both body mass and percentage body fat were greater in mice fed HFS diet. After adjusting for body mass, tibial structural and morphological properties were adversely affected in the HFS cohort. Cortical thickness, cross-sectional area, and load at maximum were all significantly lower in mice fed HFS diet. Receptor activator of nuclear factor kappabeta ligand (RANKL) mRNA was significantly upregulated in HFS mice, but osteoprotegerin/RANKL mRNA ratio remained unchanged between cohorts. Moreover, cyclo-oxygenase-2 mRNA tended to be increased in HFS. Thus, ingestion of an HFS diet had a significant adverse effect on mouse bone morphology and mechanics, and these effects were likely due to elevated osteoclast activity associated with the inflammatory state of obesity, and not necessarily osteoclast recruitment/proliferation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".