A Review on Antidiabetic Activity of Centaurea spp.: A New Approach for Developing Herbal Remedies
Bibliographic record
Abstract
Objective. Diabetes mellitus (DM) is a long-life metabolic disorder, characterized by high blood glucose levels. The hyperglycemic condition generally leads to irreversible nerve injury and vascular damage. Among different types of diabetes, type 2 is more common and has spread all over the world. Although various therapeutic approaches have been developed to control type 2 DM, regulating blood glucose levels has still remained a controversial challenge for patients. Also, most prescription drugs cause different side effects, such as gastrointestinal disorders. Thus, developing novel and efficient antidiabetic agents possessing fewer adverse effects is in high demand. Method. The literature was comprehensively surveyed via search engines such as Google Scholar, PubMed, and Scopus using appropriate keywords. Results. Medicinal plants, both extracts and isolated active components, have played a significant role in controlling the blood glucose levels. Good-to-excellent results documented in the literature have made them a precious origin for developing and designing drugs and supplements against DM. Centaurea spp. have been traditionally used for controlling high blood glucose levels. Also, the antidiabetic properties of different species of Centaurea have been confirmed in recent studies through in vitro assays as well as in vivo experiments. Conclusion. Potent results encouraged us to review their efficacy to open a new horizon for development of herbal antidiabetic agents.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".