Resveratrol Consumption and RIP140 Knockout Mice Demonstrate a Novel Relationship between Increased Mitochondrial Content and Compromised Bone Mineral Mass, Microarchitecture, and Strength
Bibliographic record
Abstract
The polyphenol resveratrol (RSV) is associated with many health benefits, including the prevention of high fat (HF) diet induced glucose‐intolerance. However, the off‐target effects of resveratrol on bone health, specifically within the context of diet induced glucose‐intolerance, is unknown. The purpose of this study was to evaluate, in tibias, the effect of RSV on bone microarchitecture, mineral mass, and strength. Moreover, we aimed to elucidate molecular adaptations within bone that could provide insight regarding the impact of RSV on bone health. Male C57BL6 mice (8 weeks old) were randomized to 1 of 3 diets: control, CON (10% fat), HF (60% fat), or HF‐RSV (100mg/kg/day) for 12 weeks. Glucose‐tolerance tests verified that the HF diet induced glucose‐intolerance and that RSV prevented this effect. Combined HF‐RSV consumption led to compromised trabecular microarchitecture, lower bone mineral mass, and lower bone strength. This corresponded with elevated markers of osteoclast activation (decreased ratio of osteoprotegerin to receptor activator of nuclear factor kappa‐B ligand), bone resorption (cathepsin K), and increased mitochondrial content (electron transport chain complex subunits I–V). Further, we demonstrated proof‐of‐principle that elevated bone mitochondrial content is inversely related to bone health. Specifically, we utilized RIP140 knockout (KO) mice, a molecular model of elevated mitochondrial content. Similar to HF‐RSV mice, RIP140 KO mice displayed elevated mitochondrial content and compromised bone microarchitecture, bone mineral, and bone strength. This corresponded with higher markers of osteoclast activation and bone resorption, similar to HF‐RSV mice. Together, these findings suggest that although RSV successfully mitigates HF diet induced glucose‐intolerance, there can be negative consequences on bone health. Further, insulin sensitizing agents that are known to increase mitochondrial biogenesis should be considered for off‐target effects on bone health, as these data demonstrate that elevations in bone mitochondrial content are associated with decrements in bone health. Support or Funding Information Supported by NSERC, OMAFRA, and CFI, Canada.
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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) | 0.004 | 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".