Phytochemical Profile, Antioxidant, Antimicrobial, and Antidiabetic Activities of Ajuga iva (L.)
Bibliographic record
Abstract
In Morocco, many applications in ethnomedicine on Ajuga iva (L.) have been recognized as able to treat various pathologies such as diabetes, stress, and microbial infections. The objective of this work is to carry out phytochemical, biological, and pharmacological investigations on the extracts of Ajuga iva leaves in order to confirm its therapeutic effects. The phytochemical screening carried out on the different extracts of Ajuga iva showed its richness in primary (lipids and proteins) and secondary metabolites (flavonoids, tannins, reducing compounds, oses, and holoside. The best contents of polyphenols, flavonoids, and tannins evaluated by spectrophotometric methods were found in the hydroethanolic extract (69.850 ± 2.783 mg EAG/g DE, 17.127 ± 0.474 mg EQ/g DE, 5.566 ± 0.000 mg EQC/g DE), respectively. Analysis of the chemical composition of the aqueous extract by LC/UV/MS revealed 32 polyphenolic compounds including ferulic acid (19.06%), quercetin (10.19%), coumaric acid (9.63%), and apigenin-7-(2-O-apiosylglucoside) (6.8%). The antioxidant activity of Ajuga iva extracts was evaluated by three methods (DPPH*, FRAP, CAT). The hydroethanolic extract recorded the strongest reducing power: DPPH* (IC50 = 59.92 ± 0.7 µg/mL), FRAP (EC50 = 196.85 ± 1.54 (µg/mL), and CAT (199.21 ± 0.37 mg EAG/gE). A strong correlation between phenolic compounds and antioxidant activities was confirmed by the determination of Pearson’s coefficient. The antimicrobial activity of Ajuga iva studied by the microtiter method revealed potent antifungal and antibacterial qualities against Candida parapsilosis and Staphylococcus aureus BLACT. An in vivo oral glucose tolerance test (OGTT) using normal rats revealed that the antihyperglycemic action of the aqueous extract significantly reduced postprandial hyperglycaemia at (30 min, p < 0.01) and area under the curve (AUC glucose), p < 0.01. Similarly, the aqueous extract, tested on pancreatic α-amylase enzyme activity in vitro and in vivo significantly inhibited pancreatic α-amylase activity with IC50 = 1.52 ± 0.03 mg/mL. In conclusion, the extract from Ajuga iva could be a good source of bioactive molecules, which exhibit potent antioxidant and antimicrobial activity, as well as strong antidiabetic activity, for applications in the pharmaceutical industry.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".