Saffron (Crocus sativus L.): A Source of Nutrients for Health and for the Treatment of Neuropsychiatric and Age-Related Diseases
Bibliographic record
Abstract
L.) is a medicinal plant, originally cultivated in the East and Middle East, and later in some Mediterranean countries. Saffron is obtained from the stigmas of the plant. Currently, the use of saffron is undergoing a revival. The medicinal virtues of saffron, its culinary use and its high added value have led to the clarification of its phytochemical profile and its biological and therapeutic characteristics. Saffron is rich in carotenoids and terpenes. The major products of saffron are crocins and crocetin (carotenoids) deriving from zeaxanthin, pirocrocin and safranal, which give it its taste and aroma, respectively. Saffron and its major compounds have powerful antioxidant and anti-inflammatory properties in vitro and in vivo. Anti-tumor properties have also been described. The goal of this review is to present the beneficial effects of saffron and its main constituent molecules on neuropsychiatric diseases (depression, anxiety and schizophrenia) as well as on the most frequent age-related diseases (cardiovascular, ocular and neurodegenerative diseases, as well as sarcopenia). Overall, the phytochemical profile of saffron confers many beneficial virtues on human health and, in particular, on the prevention of age-related diseases, which is a major asset reinforcing the interest for this medicinal plant.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".