Bibliographic record
Abstract
Background: The objective of this study was to investigate and compare the effect of omega 3 and zinc supplementation (both simultaneously and separately) on glycemic indices (fasting blood sugar (FBS), fasting insulin, insulin sensitivity, insulin resistance, HbA1C), serum zinc level, blood pressure, and Body composition in the patients with diabetes type 2. Method: This study is a double-blind randomized controlled clinical trial conducted on 100 patients with diabetes.The patients were divided into four intervention groups: omega 3 group (n=25, a daily 1000 mg of omega-3), zinc group (n=25, 30 mg zinc gluconate), zinc and omega-3 group (n=25), and the placebo group (n=25).Results: There was a significant reduction in the individuals' weight after intervention in omega 3 and zinc groups (p=0.000 and p=0.038, respectively).Zinc supplementation (by itself or with omega 3) significantly changed the patients' BMI (p=0.033).Blood pressure has been significantly reduced after intervention in all three groups of intervention with omega 3 and zinc (p<0.001).FBS was reduced in all three groups after intervention; however, this reduction was significant in the zinc group and the zinc and omega 3 group (p<0.001 and p=0.002, respectively).The values of serum insulin were significantly reduced after intervention in all three groups of intervention with omega 3, intervention with zinc, and intervention with omega 3 and zinc (p=0.001,p=0.000, and p=0.002).HBA1C was also significantly reduced after intervention in all three groups of intervention.Conclusion: Omega 3 and zinc supplementation can be useful for improving weight and controlling glycemic as well as blood pressure.The effects of zinc supplementation on glycemic indices are more useful than omega 3.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.892 | 0.899 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".