Resveratrol fails to improve marginal mass engraftment of transplanted islets of Langerhans in mice
Bibliographic record
Abstract
One limitation of current islet transplantation protocols is the loss of up to 70% of the transplanted islet mass. Inflammatory events play a major role in islet loss including the cytokines TNFα and IL-1. Resveratrol, a compound with anti-inflammatory and anti-oxidant properties, has the potential to mitigate islet loss. Using a syngeneic marginal after mouse islet transplantation model we tested the ability of resveratrol to enhance islet engraftment. We failed to show a difference in diabetes reversal between mice treated with vehicle and those treated with either 10 mg/kg (47.1% for resveratrol vs. 35.3% for control) or 50 mg/kg (20% for resveratrol vs. 22.2% for control) of resveratrol daily for three weeks. In addition, at one month there was no difference in glucose tolerance or graft survival (10 mg/kg: 552.6 ng/ml resveratrol group vs. 576.6 ng/ml control group; 50 mg/kg: 463 ng/ml resveratrol group vs. 444.1 ng/ml control group). In summary, over a wide range of doses, resveratrol did not exert a benefit on mouse islet engraftment. Further studies should be conducted with human islets before deeming resveratrol ineffective in islet engraftment and survival.
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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 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".