Combined high‐fat‐resveratrol diet and RIP140 knockout mice reveal a novel relationship between elevated bone mitochondrial content and compromised bone microarchitecture, bone mineral mass, and bone strength in the tibia
Bibliographic record
Abstract
SCOPE: While resveratrol (RSV) is associated with the prevention of high-fat (HF) diet-induced insulin resistance, the effects on bone health combined with an HF-diet is unknown. Therefore, we determined the effect of RSV on bone microarchitecture in the presence of an HF-diet, while also elucidating molecular adaptations within bone that could contribute to bone health status. METHODS AND RESULTS: Male C57BL6 mice were provided control (10% fat) or HF-diet (60% fat) in the presence or absence of RSV for 12 weeks. While RSV prevented HF diet-induced glucose intolerance, HF-RSV compromised tibial microarchitecture, mineral mass, and strength. The compromised outcomes following HF-RSV corresponded with higher markers of osteoclast-activation and bone-resorption (decreased OPG/RANKL ratio; increased cathepsin K), as well as higher markers of tibial mitochondrial content. A molecular model of elevated mitochondrial content (RIP140 knock out (KO) mice) was utilized to determine proof-of-principle that increasing mitochondrial content coincides with decrements in bone health. RIP140 KO mice displayed higher markers of mitochondrial content, and similar to HF-RSV, had compromised bone microarchitecture, lower BMD/strength, and higher markers of osteoclast-activation/bone-resorption. CONCLUSION: These data show that in the presence of an HF-diet, RSV negatively alters bone health, a process associated with increased mitochondrial content and markers of bone resorption.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".