Efficacy of Various Extracting Solvents on Phytochemical Composition, Antioxidant Potential, Total Phenolic Content, and Antibacterial Properties, of Moroccan Mentha longifolia L. Leaf Extracts against Multidrug-Resistant Pathogenic Bacteria
Bibliographic record
Abstract
Abstract The current work attempts to explore the influence of three extraction solvents on phytochemical composition, content of polyphenols, antioxidant potential, and antibacterial capacity of Moroccan Mentha longifolia L. leaves hydroethanolic, acetonic, and water extracts. To achieve this goal, the chemical composition was identified using an HPLC-DAD examination. The contents of polyphenolswere assessed, while the total antioxidant capacity (TAC), the DPPH test, and the reducing power test (RP) were utilized to determine antioxidant capacity. To assess the antibacterial activity, the microdilution technique was carried out to calculate the minimum inhibitory (MIC) and minimum bactericidal concentrations (MBC) ofextracts against four nosocomial bacteria (Bacillus cereus, Pseudomonas aeruginosa, Escherichia coli, andStaphylococcus aureus).Additionally, the antibacterial and antioxidant activities of all tested extracts were examined in silico against the proteins NADPH oxidaseand Bacillus cereusphospholipase C. Study reveals M. longifolia extracts contain high phenolicand flavonoids.Additionally, the hydroethanolic extract contained the highest amounts of phenolic and flavonoid content, with values of 23.52 ± 0.14 mg GAE/g DW and 17.62 ± 0.36 mg QE/g DW, respectively comparedto the other two extracts. The same extract showed the best antioxidant capacity(IC50 = 39 µg/mL ± 0.00), and the higher RP (EC50 of 0.261 ± 0.00 mg/mL), compared to the acetonic and water extractregarding these tests. Furthermore, the hydroethanolic and acetonic extracts expressed the highest TAC (74.40 ± 1.34, and 52.40 ± 0.20 mg EAA/g DW respectively), compared withthe water extract. Regarding antibacterial activity, the MIC value ranges between 1.17and 12.50 mg/mL. The in-silico results showed that the antibacterial activity of all extracts is principally attributed to kaempferol and ferulic acid, while antioxidant capacity is attributed to ferulic acid.
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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) | 0.000 | 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) | 0.002 | 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".