Potent surface antimicrobial activity of hydrolyzable tannins from Aleppo oak galls
Bibliographic record
Abstract
Surface antimicrobial agents provide a first line of defense against pathogens, especially for immunocompromised individuals. Insect-induced plant galls, tumor-like structures formed on plant surfaces by insect larvae, have long been used as sources of antimicrobial compounds. Building on existing knowledge, this study evaluated the surface antimicrobial activity of a standardized, ethanolic extract of Aleppo oak galls (AGE) on agar, abiotic, and biotic surfaces. Using a novel surface antimicrobial assay, we demonstrated that the anti-Escherichia coli, -Staphylococcus aureus, -Candida albicans, and -Aspergillus brasiliensis activity of AGE approached that of common antibiotics and econazole. However, AGE had a comparatively lower antimicrobial activity in liquid cultures. AGE maintained strong antibacterial activity on non-nutritive surfaces, including stainless steel, collagen membranes, and cadaver skin. Untargeted and targeted metabolomic analyses revealed that hydrolyzable tannins and their precursors are the predominant constituents in AGE, and that hydrolyzable tannins are largely responsible for its potent surface activity. Tannic acid, a hydrolyzable tannin present in AGE, showed surface antibacterial effects similar to AGE. These findings support the potential of AGE and its hydrolyzable tannins as natural surface sterilants for reducing microbial load on skin and materials used in healthcare and food industry settings.
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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) | 0.000 | 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".