Antioxidant, Antimicrobial, and Insecticidal Properties of Chemically Characterized Essential Oils Extracted from Mentha longifolia: In Vitro and In Silico Analysis
Bibliographic record
Abstract
The present study aimed to explore the phytochemical profile, and evaluate the antioxidant, antimicrobial, and insecticidal properties, of Moroccan Mentha longifolia L. essential oil (ML-EO) using in vitro and in silico assays. Noteworthily, as chromatography (GC-MS/MS) revealed that ML-EO is majorly composed of piperitenone oxide (53.43%), caryophyllene (20.02%), and (−) germacrene D (16.53%). It possesses excellent antioxidant activity with an IC50 of 1.49 ± 0.00 for DPPH and 0.051 ± 0.06 μg/mL for ABTS. Moreover, the RP and TAC activities were 0.80 ± 0.01 μg/mL and 315.532 ± 0.00 mg EAA/g, respectively. ML-EO exhibited a potent antimicrobial effect, specifically against Pseudomonas aeruginosa. It also exhibited strong antifungal ability, especially against Candida albicans. Regarding insecticidal activity, for ML-EO, a dose of 20 µL/mL produced a complete reduction in fecundity, fertility, and emergence of adult C. maculatus with mortality rates reaching 100%. In silico results showed that the antioxidant activity is mostly attributed to α-Cadinol, the antibacterial efficiency is attributed to piperitenone oxide, and antifungal capacity is related to cis-Muurola-4(15),5-diene and piperitenone oxide. Accordingly, ML-EO has high potential to be used as an alternative for preserving food and stored grain and protecting them against microbes and insect pests in the food and pharmaceutical sectors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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".