Evaluation of Levofloxacin and Yahom-Navakot Remedy Extract Combination Therapy Against Antibiotic Resistant Bacteria In Vitro
Bibliographic record
Abstract
Introduction: Antibiotic resistant bacteria are being considered a serious public health challenge. Levofloxacin is a broad-spectrum antibiotic, developed to replace previously resistant antimicrobials. The use of natural products as an antimicrobial drug is an alternative way to reduce bacterial resistance by synthesized drugs and enhance their efficacy. Yahom-Navakot (YN) is a Thai remedy in the Thai essential drug list. The indications for YN treatment are to relieve fatigue, dizziness, malaise, and vomiting after alleviation of fever. Previous studies have reported antibiotic enhancing effects of YN. This study was aimed to evaluate the antibacterial activities of levofloxacin and Yahom-Navakot Remedy Extract. Methods: YN remedy was macerated with 95% ethanol, after solvent evaporation the extract was combined with levofloxacin (1:1). By using modified resazurin in the broth micro-dilution assay, the antibacterial activities of the combination were evaluated against the pathogenic bacteria; Staphylococcus aureus (DMST 20651), Methicillin-Resistant Staphylococcus aureus (ATCC 25923), Staphylococcus epidermidis (ATCC 12228), Pseudomonas aeruginosa (ATCC 27853), Klebsiella pneumoniae (ATCC BAA 2789), Salmonella typhi (DMST 22842), Shigella dysenteriae (DMST 15111), and Escherichia coli (ATCC 25922). P. aeruginosa, MRSA, S. typhi, S. dysenteriae, and E. coli were antibiotic resistant bacteria strains according to WHO criteria. Levofloxacin was used as a control in this study. Results: In vitro YN extract showed potent antibacterial effect against S. aureus (MIC = 0.625, MBC = 0.39 mg/mL), MRSA (MIC = 0.625, MBC = 25 mg/mL), and S. epidermidis (MIC = 0.3125, MBC = 50 mg/mL). YN extract (At MICs against selected bacteria strains) demonstrated enhanced antibacterial activities of levofloxacin against MRSA (MIC < 3×10-8, MBC < 3×10-8 µg/mL) and S. epidermidis (MIC = 0.048, MBC = 25 µg/mL) as determined by reduced MICs and MBCs. However, it did not affect other selected bacteria strains; P. aeruginosa, K. pneumoniae, S. typhi, S. dysenteriae, and E. coli (MIC > 5 mg/mL). Conclusions: YN showed evidence of antibacterial activity. It had potential antibiotic enhanced activity with levofloxacin; however, further in vivo and clinical studies are essential to evaluate YN’s efficacy and safety.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".