Promising antioxidant and antimicrobial effects of essential oils extracted from fruits of <i>Juniperus thurifera</i>: <i>In vitro</i> and <i>in silico</i> investigations
Bibliographic record
Abstract
Abstract The objective of this work was to characterize the phytochemical composition of essential oil from Juniperus thurifera (L.) fruits (EOFT) and study its antioxidant, antibacterial, and antifungal effects. EOFT was extracted by hydrodistillation and fingerprinted by using GC–MS. The antioxidant effect of EOFT was evaluated using 2,2-diphenylpicrylhydrazyl (DPPH), ferric iron reduction assay (FRAP), and total antioxidant capacity (TAC) assays. Importantly, the antimicrobial activity of EOFT was performed against Candida albicans, Aspergillus niger, Aspergillus flavus, Fusarium oxysporum, Staphylococcus aureus, Escherichia coli, Bacillus subtilis, and Proteus mirabilis. In addition, the inhibitory capacity of NADPH oxidase and human acetylcholinesterase was also investigated using molecular docking. The results of the chemical composition reveal that EOFT constituted 11 terpenic compounds with dominance of elemol (33.86%), terpinen-4-ol (27.80%), and cryptomeridiol (18.36%). The antioxidant power of EOFT recorded IC50 values of 197.07 ± 0.09 μg/mL (DPPH) and 216.34 ± 0.06 μg/mL (FRAP), while TAC of EOFT was determined to be 181.06 μg AAE/mg. The antibacterial potency on solid medium revealed that EOFT induced inhibition zone diameters reaching 14 mm, and a minimum concentration up to 2.78 µg/mL against the studied bacterial strains. The EOFT also showed an important antifungal effect as the inhibition reached 42%, and the MIC was between 7.50 and 22.25 µg/mL. The in silico study showed that o-Cymene was the most active molecule against NAD(P)H oxidase followed by cadinol with a Glide score of −5.344 and −5.143 kcal/mol, respectively. Due to their promising results, the outcome of this work suggests that EOFT could be used as an interesting natural weapon to control microbial and freed radical-related diseases.
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 | 0.000 |
| 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) | 0.001 | 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".