Scavenging Activity, Anti-Inflammatory and Diabetes Related Enzyme Inhibition Properties of Leaves Extract from some Varieties of <i>Phoenyx dactylifera l.</i>
Bibliographic record
Abstract
In this study we investigate the antioxidant, anti-inflammatory, and antidiabetic activities of ethanolic leaves extracts of three selected varieties of Phoenyx dactylifera L. namely: “Ghars”, “Deglet Nour” and “Hamraya”. The assessment of the antioxidant potential of crude leaves extracts, using superoxide anions inhibition, DPPH and total antioxidant activity essays, was carried out. Furthermore, the anti-inflammatory properties of the extracts were determined by measuring the inhibition of nitric oxide (NO) production. Moreover, the antidiabetic effect was evaluated by inhibition of α-amylase enzymes. The total phenolic content measured by Folin-Ciocalteu method was as well conducted. The raw leaves extracts of the selected varieties was found to contain a high content of total phenolic content (342.45 mg GAE/gDW for GE) and therefore exhibited a higher antioxidant activity and inhibitory effect of radicals scavenging activity against DPPH and superoxide anion (IC 50 = 7.44 μg/mL and 39.11 μg/mL respectively). The three varieties exhibited significant inhibition nitric oxide using In Vitro assay (IC50 = 240.28 μg/mL for GE). The extracts also displayed high inhibition actions against α-amylase enzymes. The results suggest that the leaves of the three selected varieties of Phoenyx dactylifera can be considered as a good source of natural antioxidant and anti-inflammation drugs as well as potent antidiabetic medicine.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 teacher head, 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".