Bibliographic record
Abstract
Diabetes mellitus is a multi-faceted metabolic disorder where there is increased oxidative stress that contributes to the pathogenesis of this debilitating disease. This has prompted several investigations into the use of antioxidants as a complementary therapeutic approach. Alpha lipoic acid, a naturally occurring dithiol compound which plays an essential role in mitochondrial bioenergetic reactions, has gained considerable attention as an antioxidant for use in managing diabetic complications. Lipoic acid quenches reactive oxygen species, chelates metal ions, and reduces the oxidized forms of other antioxidants such as vitamin C, vitamin E, and glutathione. It also boosts antioxidant defense system through Nrf-2-mediated antioxidant gene expression and by modulation of peroxisome proliferator activated receptors-regulated genes. ALA inhibits nuclear factor kappa B and activates AMPK in skeletal muscles, which in turn have a plethora of metabolic consequences. These diverse actions suggest that lipoic acid acts by multiple mechanisms, many of which have only been uncovered recently. In this review we briefly summarize the known biochemical properties of lipoic acid and then discussed the oxidative mechanisms implicated in diabetic complications and the mechanisms by which lipoic acid may ameliorate these reactions. The findings of some of the clinical trials in which lipoic acid administration has been tested in diabetic patients during the last 10 years are summarized. It appears that the clearest benefit of lipoic acid supplementation is in patients with diabetic neuropathy.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".