Effect of a Low Glycemic Index Diet on Markers of Oxidative Damage in Type 2 Diabetes
Bibliographic record
Abstract
Aims Larger glycemic excursions are linked to greater oxidative stress and low GI diets have been shown to improve glycemic control. We therefore assessed the effect of a low glycemic index (GI) diet on oxidative damage to LDL in type 2 diabetes. Methods In 151 type 2 diabetic subjects who completed either 6 months of low GI or high cereal fiber diets thiobarbituric acid reactive substances (TBARS) and conjugated dienes (CDs), as markers of LDL oxidation, were measured. Results The low GI diet reduced HbA1c but did not significantly change markers of oxidative damage. Pooled data from the two treatments showed change in oxidized LDL measured as TBARS and CDs related to low GI carbohydrate intake (r=‐0.17, N=150, P=0.042 and r=‐0.22, n=151, P=0.008, respectively). Moreover, those with reductions in glycemic excursions over the day (individuals with a reduction in HbA1c but no reduction in fasting blood glucose) showed greater reduction in oxidized LDL compared to a group with a predicted rise in glycemic excursions (P=0.040). Conclusion Low GI carbohydrates are associated with reduction in oxidized LDL. Funding Barilla
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".