Essential Oils from Leaves of Juniperus thurifera L., Exhibiting Antioxidant, Antifungal and Antibacterial Activities against Antibiotic-Resistant Microbes
Bibliographic record
Abstract
The antioxidant, antibacterial and antifungal properties of essential oils (EOs) of Juniperus thurifera L., a plant utilized in traditional, herbal medicine, were investigated. The EOs were extracted by use of a Clevenger apparatus and phytochemicals identified by gas chromatography coupled with mass spectrometry (GC/MS/MS). The antioxidant capacity of EOs of J. thurifera was determined by 2,2-diphenyl-1-picrylhydrazil (DPPH), total antioxidant capacity (TAC), and ferric reducing antioxidant power (FRAP). Antimicrobial activity of EOs of J. thurifera was determined against four fungal strains, Candida albicans; ATCC 10231, Aspergillus niger; MTCC 282, Aspergillus flavus; MTCC 9606 and Fusarium oxysporum; MTCC 9913 and four bacterial strains, Staphylococcus aureus; ATCC 6633, Escherichia coli; K12, Bacillus subtilis; DSM 6333, and Pseudomonas aeruginosa; CIP A22, by use of the disk diffusion method, and microdilution method used to determine the minimum inhibitory concentration (MIC). EOs of J. thurifera consisted of 31 compounds and were dominated by α-thujene (25%), elemol (12%) and muurolol (12%). Antioxidant activity recorded an IC50 of 24 ± 0.71 µg/mL (DPPF), EC50 of 0.19 ± 0.01 mg/mL (FRAP), and 9.3 × 102 ± 38 mg EAA/g (TAC). The EOs of J. thurifera exhibited significant antibacterial activity against all bacterial strains under investigation, especially P. aeruginosa; CIP A22 with an inhibition diameter of 28 ± 1.5 mm and MIC of 4.8 × 10−2 ± 0. 001 µg/mL. EOs of J. thurifera also exhibited significant antifungal activity against C. albicans; ATCC 10231 and F. oxysporum; MTCC 9913 with an activity of 21 ± 2.1 mm, 32 ± 2.3%, and MIC of 9.5 × 10−2 ± 0.001 Bioactive molecules found in EOs of J. thurifera could be used as an alternative solution to antibiotics available on the market to combat microbial resistance.
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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) | 0.001 | 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".