Antibacterial activity and metabolomic profile of Zanthoxylum caribaeum Lam. aqueous extract against multidrug-resistant Staphylococcus aureus
Bibliographic record
Abstract
Improved antimicrobial medication or treatments are solutions that need to be combined to limit the impact of antibiotic resistance. Plants have historically been the source of many effective medicines. Zanthoxylum caribaeum is typically found in tropical regions and known for its wide range of plant metabolites that can be attributed to antibacterial activity. The aim of this study was to identify the metabolites potentially involved in the antibacterial activity of Z. caribaeum against resistant bacteria. The antibacterial effect of dried microwave-treated aqueous extracts of Z. caribaeum was tested in vitro against Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii, Enterococcus faecalis, Staphylococcus aureus, Pseudomonas aeruginosa. Determination of the minimum inhibitory concentration (MIC) confirmed the inhibitory effect observed by the disc method. This showed that Z. caribaeum had a more pronounced effect on methicillin-resistant S. aureus (MRSA) at a high concentration with a MIC value of 1.6 × 104 µg/mL, reflecting a weak activity. In parallel, this study provided a global characterization of Z. caribaeum aqueous extract by GC×GC-TOFMS. The 24 most abundant compounds tentatively identified in the derivatized dried aqueous extract of Z. caribaeum, such as 4-hydroxybenzyl alcohol and 1-monopalmitin, are known precursor molecules for important biological functions and proteins. In addition, the low dose inhibitory effect of Z. caribaeum aqueous extract makes it a candidate for phytochemical isolation of these molecules and improvement of their antibacterial activity.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".