A SHORTENED TREATMENT WITH ROSEMARY TEA (ROSMARINUS OFFICINALIS) INSTEAD OF POWDER DECREASES INSULIN RESISTANCE AND SERUM GLUCOSE IN PATIENTS WITH DIABETES MELLITUS TYPE 2 (T2D)
Bibliographic record
Abstract
BACKGROUND: Rosemary leaves powder has been reported to reduce in a dose-dependent manner, glucose levels, lipid profile and lipid peroxidation in humans. However, patients should ingest high doses of powder contained in capsules. This formulation constitutes the intake of 10 capsules per day, so the active metabolite must first, be released and then absorbed (for which, rosemary leaf powder must be mixed with gastric juice). AIM: Evaluate whether a shortened dose and time of treatment as well as the pharmaceutical presentation in rosemary tea (Rosmarinus officinalis) instead of powder have a therapeutic effect in the treatment of T2D. METHOD: The complementary therapy with Rosemary tea (2g/1 litre of water per day) were evaluate on resistance to insulin, oxidative stress, biochemical parameters and anthropometric measurements in forty patients T2D under treatment with metformin and/or glibenclamide afther giving your authorization through informed consent. RESULTS: The data indicated that Rosemary tea intake after 90 days, statistically decreased (p < 0.05) anthropometric parameters like the body mass index and waist-hip ratio. Remarkably, this treatment decreased the percentages of glycated hemoglobin, insulin resistance, and the pancreatic β-cell function and lastly, a significant difference in lipid peroxide levels was found. CONCLUSION: These data show that shortening time and dose, as well as changing the formulation of the Rosemary plant constitutes a promising treatment for drug-resistant T2D patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.002 | 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".