Healing effects of monomer and dimer resveratrol in a mouse periodontitis model
Bibliographic record
Abstract
BACKGROUND: The antioxidant and anti-inflammatory effects of resveratrol have been reported previously. Particularly, monomeric trans-resveratrol has been demonstrated to produce positive effects in various pathological processes. We reported previously that resveratrol dimer-rich melinjo extract, among others, caused bone healing, decreased local oxidative damage, and activated antioxidants nuclear factor erythroid 2-related factor 2 (Nrf2) pathways in a mouse model of experimentally induced periodontitis (EP). This study aimed to compare the bone-healing effects of the resveratrol monomer to the resveratrol dimer (gnetin C found in melinjo seed extract) in a model of EP and investigate the involvement of Nrf2 for effects of either form of resveratrol. METHODS: EP was induced experimentally in mice by placement of a 9 - 0 silk ligature around the left second molar. Mice received 10 mg/kg of either resveratrol monomer or dimer intraperitoneally on day 15 after induction of EP. The bone level around the ligated teeth was measured over time, and levels of proinflammatory cytokines and oxidative stress were measured in the periodontal tissues around the ligated teeth. RESULTS: Resveratrol dimer induced greater periodontal bone healing as compared to that related to use of the resveratrol monomer. It appears that healing of periodontal bone in either group was likely related to master regulation of antioxidant nuclear factor erythroid 2-related factor 2 (Nrf2) significantly. Downregulation of IL-1β, a proinflammatory cytokine was also demonstrated in the resveratrol dimer group. CONCLUSION: Our results showed that administration of resveratrol in either dimer form or the monomeric form reduced periodontal bone loss with greater inhibition of bone loss being demonstrated in the dimer group as compared to the monomer group and that these effects were related in all likelihood to decreased oxidative stress and hence reduction in local inflammation.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".