Chemical composition, cholinesterase, and α-glucosidase inhibitory activity of the essential oils of some Iranian native Salvia species
Bibliographic record
Abstract
BACKGROUND: The plants from Salvia genus contain widely distributed species which have been used in folk medicine as well as pharmaceutical and food industries. METHODS: The chemical composition of 12 native Iranian Salvia species (14 plants) was identified using gas chromatography-mass spectrometry (GC-MS). Also, the inhibitory activity of all essential oils (EOs) was evaluated toward α-glucosidase and two types of cholinesterase (ChE) using spectrophotometric methods. The in vitro α-glucosidase inhibition assay was performed by the determination of p-nitrophenol (pNP) obtained from the enzymatic dissociation of p-nitrophenol-α-D-glucopyranoside (pNPG) as the substrate. In vitro ChE inhibitory assay was conducted based on the modified Ellman's procedure using the measurement of 5-thio-2-nitrobenzoic acid produced from the hydrolysis of thiocholine derivatives as the substrate, in the presence of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). RESULTS: Totally, 139 compounds were detected and caryophyllene oxide and trans-β-caryophyllene were the most abundant compounds in all EOs. The yield of EOs extracted from the plants were also calculated in the range of 0.06 to 0.96% w/w. Herein, α-glucosidase inhibitory activity of 8 EOs was reported for the first time and among all, S. spinosa L. was found to be the most potent inhibitor (90.5 inhibition at 500 μg/mL). Also, the ChE inhibitory activity of 8 species was reported for the first time and our results showed that the BChE inhibitory effect of all EOs was more potent than that of AChE. The ChE inhibition assay indicated that S. mirzayanii Rech.f. & Esfand. collected from Shiraz was the most potent inhibitor (72.68% and 40.6% at the concentration of 500 μg/mL, toward AChE and BChE, respectively). CONCLUSIONS: It seems that native Salvia species of Iran could be considered in the development of anti-diabetic and anti-Alzheimer's disease supplements.
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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 | 0.001 | 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 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".