Ameliorating effects of antioxidative compounds from four plant extracts in experimental models of diabetes
Bibliographic record
Abstract
Given that oxidative stress plays a major role in pancreatic ?-cell dysfunction and ultimate destruction, as well as in different complications of diabetes, therapy with antioxidants has assumed an important place in diabetes management. The relatively limited effects of established antioxidant compounds have stimulated efforts to develop new therapeutic strategies, e.g. to increase the endogenous antioxidant defenses through pharmacological modulation of key antioxidant enzymes. Plant extracts are gaining popularity in treating diabetes because many substances synthesized by higher plants and fungi possess antioxidant activities and can prevent or protect tissues against the damaging effects of free radicals. This review summarizes experimental models of diabetes and possible mechanisms that lie behind the antioxidative effects of ?-lipoic acid (LA), a powerful antioxidant and compound that stimulates cellular glucose uptake, as well as of plant extracts from sweet chestnut (Castanea sativa), edible mushroom (Lactarius deterrimus) and natural products containing ?-glucans in the treatment of diabetes. Their roles in preventing pancreatic ?-cell death and in ameliorating the effects of severe diabetic complications are discussed.
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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 | 0.001 | 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".