Synergistic Antibacterial Effects of Gallate Containing Compounds with Silver Nanoparticles in Gallate Crossed Linked PVA Hydrogel Films
Bibliographic record
Abstract
Currently available silver-based antiseptic wound dressings have limited patient effectiveness. There exists a need for wound dressings that behave as comfortable degradable hydrogels with a strong antibiotic potential. The objectives of this project were to investigate the combined use of gallates (either epi gallo catechin gallate (EGCG), Tannic acid, or Quercetin) as both PVA crosslinking agents and as potential synergistic antibiotics in combination with silver nanoparticles. Crosslinking was assessed gravimetrically, silver and gallate release was measured using inductively coupled plasma and HPLC methods, respectively. Synergy was measured using 96-well plate FICI methods and in-gel antibacterial effects were measured using planktonic CFU assays. All gallates crosslinked PVA with optimal extended swelling obtained using EGCG or Quercetin at 14% loadings (100 mg in 500 mg PVA with glycerol). All three gallates were synergistic in combination with silver nanoparticles against both gram-positive and -negative bacteria. In PVA hydrogel films, silver nanoparticles with EGCG or Quercetin more effectively inhibited bacterial growth in CFU counts over 24 h as compared to films containing single agents. These biocompatible natural-product antibiotics, EGCG or Quercetin, may play a dual role of providing stable PVA hydrogel films and a powerful synergistic antibiotic effect in combination with silver nanoparticles.
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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".