GC–MS-Based Metabolites Profiling, In Vitro Antioxidant, Anticancer, and Antimicrobial Properties of Different Solvent Extracts from the Botanical Parts of Micromeria fruticosa (Lamiaceae)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The present study assessed the metabolites and bioactivities of Micromeria fruticosa plant parts extracted with various solvents (ethanol, n-hexane, and water) through the steeping extraction method. Thereafter, the extracts were analyzed using GC-MS. Moreover, the extracts were tested for their antioxidant, antimicrobial, and antitumor activities. The quali-quantitative analysis of Micromeria fruticosa crude extracts revealed the occurrence of 27 secondary metabolites. Some major bioactives identified were menthone, oleamide, pulegone, and menthol. Numerous antioxidant minerals, viz., Fe, Zn, and Mn, were present. The water extract of leaves exhibited the highest DPPH scavenging activity (89.73%), followed by the water extract of flowers (80.07%) at 100 μg/mL. The stems’ water extract demonstrated greater antimicrobial activity against all the bacteria species tested. The ethanolic leaf and aqueous stem extracts exhibited strong activity against C. albicans and E. coli. Flowers’ aqueous extract demonstrated the highest cytostatic effect on the colon cell line by reducing viability, followed by the leaves’ ethanol extract. The extraction solvents influenced the recovery of phytocompounds, and the highest pharmacological activities of the different extracts could be correlated to the presence of additional bioactives. Our results suggest that the Micromeria fruticosa plant is a favorable source of natural products with promising properties for potential nutraceutical and functional food applications.
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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 it