Association of Dietary Vitamin C and E Intake and Antioxidant Enzymes in Type 2 Diabetes Mellitus Patients
Bibliographic record
Abstract
BACKGROUND: Diabetes mellitus consist of a various metabolic diseases such as hyperglycemia, increase glycosylated hemoglobin (HbA1c) and disorder in antioxidant enzymes activity, hence supplementing with antioxidant nutrients, mainly vitamin C and E seems to reduce oxidative injure in patients with type 2 diabetes mellitus (T2DM). AIM: To evaluate outcome of vitamin C and E supplementation on type 2 DM patients. SETTING AND DESIGN: The study was completed in 170 T2DM on consumption of vitamin C, E, combination of C & E and placebo. MATERIALS AND METHODS: The cases groups of this study consist of two major groups, which were named supplementation and placebo group. The group of supplementation consisted of 3 sub-groups, which received three capsules per day for a phase of three months. The parameters such as HbA1c, glucose, superoxide dismutase (SOD) and glutathione peroxides (GSH) were evaluated in baseline and after three months with supplementation. STATISTICAL ANALYSES: The statistical analyses were evaluated with the use of mean ± SD, ANOVA-test and paired-sample t-test. RESULTS: Mean age of 170 patients, 84 male and 86 female were 53.82±5.26 in the range of 30-60 years. The blood pressure results showed significant differences between the all supplement groups in baseline as compared to after receiving supplements (p<0.05). Use of vitamin C, E, and E & C showed significant differences in concentration of plasma FBS and HbA1c (p<0.05 & <0.001), but there was no significant differences in placebo groups. SOD and GSH enzymes levels showed a significant increased after consumption of vitamins in supplementation groups (p<0.001). CONCLUSION: This research confirmed that subjects with T2DM after three months supplementation of vitamins demonstrated significantly low level of hypertension, decrease levels of blood glucose, and increase SOD and GSH enzyme activity that can probably reduce insulin resistance by enhanced lowering oxidative stress parameters.
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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 | 0.001 |
| 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 | 0.000 | 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".