Polyphenolic Extract from Maple Syrup Potentiates Antibiotic Susceptibility and Reduces Biofilm Formation of Pathogenic Bacteria
Bibliographic record
Abstract
Phenolic compounds are believed to be promising candidates as complementary therapeutics. Maple syrup, prepared by concentrating the sap from the North American maple tree, is a rich source of natural and process-derived phenolic compounds. In this work, we report the antimicrobial activity of a phenolic-rich maple syrup extract (PRMSE). PRMSE exhibited antimicrobial activity as well as strong synergistic interaction with selected antibiotics against Gram-negative clinical strains of Escherichia coli, Proteus mirabilis, and Pseudomonas aeruginosa. Among the phenolic constituents of PRMSE, catechol exhibited strong synergy with antibiotics as well as with other phenolic components of PRMSE against bacterial growth. At sublethal concentrations, PRMSE and catechol efficiently reduced biofilm formation and increased the susceptibility of bacterial biofilms to antibiotics. In an effort to elucidate the mechanism for the observed synergy with antibiotics, PRMSE was found to increase outer membrane permeability of all bacterial strains and effectively inhibit efflux pump activity. Furthermore, transcriptome analysis revealed that PRMSE significantly repressed multiple-drug resistance genes as well as genes associated with motility, adhesion, biofilm formation, and virulence. Overall, this study provides a proof of concept and starting point for investigating the molecular mechanism of the reported increase in bacterial antibiotic susceptibility in the presence of PRMSE.
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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".