Determination of Antibacterial Activity of St. John's Wort (Hypericum perforatum L.) Oil, Nigella Sativa Oil, Clove (Eugenia caryophyllata) Oil, Orange Peel (Citrus sinensis) and Garlic (Allium sativa) Oil Against Microorganisms Isolated From Clinical Samples
Bibliographic record
Abstract
Objective: The aim of this study is to detect St. John's Wort, Nigella sativa, Clove, Orange Peel and Garlic oil on bacteria isolated from blood culture to determine its antibacterial effect. Methods: One hundered blood samples sent to … Medical Microbiology Laboratory between 1 June 2021 and 1 January 2022 were analyzed with blood culture system. Bacteria isolated from blood culture were passaged into blood agar. Bacterial suspension was prepared from the bacterial colonies at 0.5 Mc Farland turbidity. In order to determine the antibacterial activity of plant extract oils, Minimum Inhibition Concentration and Minimal Bactericidal Concentration values were determined by liquid microdilution method. Also, the zone diameters of the disc diffusion method were measured. Results: The antibacterial effect of plant extract oils was detected on only 10 of the 100 clinical samples included in the study. St. John's Wort oil used in these 10 samples showed the most effective antibacterial effect of 7.81 µg/mL against Staphylococcus haemolyticus and Enterobacter aerogenes. Garlic oil showed the most effective antibacterial effect against Escherichia coli and Staphylococcus haemolyticus at 7.81 µg/mL. Nigella sativa oil showed the most effective antibacterial effect against Staphylococcus haemolyticus at 3.9 µg/mL. Orange Peel oil showed the most effective antibacterial effect against Enterococcus faecalis at 1.95 µg/mL. The minimum inhibition concentration at which the oils were effective on microorganisms was determined by comparing them with standard control strains. Conclusion: More clinical isolates and high-dose studies are needed to determine the effectiveness of plant extract oils. Garlic oil Escherichia coli, Staphylococcus haemolyticus and Enterobacter aerogenes, St. John's wort oil Staphylococcus haemolyticus and Enterobacter aerogenes, Nigella sativa) oil on Staphylococcus haemolyticus has been found to be effective
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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) | 0.000 | 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".