Antibacterial Efficacy of Salvia Officinalis Extract Against Staphylococcus Aureus and Escherichia Coli
Bibliographic record
Abstract
This study's objective is to evaluate the antibacterial activity of ethanol extracts of Salvia officinalis L., which have been employed as traditional medicines by local healers, against two multidrug-resistant bacteria, Escherichia coli and Staphylococcus aureus. In the present investigation, fifty samples were collected from burn patients, and isolates were identified from smears taken from the burn department in hospitals, including the floors, walls, light sources, and beds at the Alsaader Hospital in Missan City, using morphological, cultural, and the VITEK 2 Compact device. Besides, the antibiotic sensitivity test for Staphylococcus aureus and Escherichia coli is tested against seven antibiotics. The results show that this isolate showed resistance to most antibiotics used in the experiment, and therefore it is regarded as MDR. Agar well diffusion methods are employed to detect the antibacterial susceptibility test versus Staphylococcus aureus and Escherichia coli at four concentrations: 62.5, 125, 250, and 500 mg/ml. The results show that the alcoholic extract had high inhibitory activity against Staphylococcus aureus and E. coli at all concentrations compared to all seven tested antibiotics. The results also reveal the inhibition zone diameter of the extract against the growth of bacteria increased significantly with concentration increase. At 500 mg/ml, the highest inhibitory zone was 41.66 mm, while at 62.5 mg/ml, it was 30.66 mm.
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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 | 0.000 | 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".