Incorporation of Silver Nanoparticles in Hydrogel Matrices for Controlling Wound Infection
Bibliographic record
Abstract
For centuries, silver has been recognized for its antibacterial properties. With the development of nanotechnology, silver nanoparticles (AgNPs) have garnered significant attention for their diverse uses in antimicrobial gel formulations, dressings for wound healing, orthopedic applications, medical catheters and instruments, implants, and contact lens coatings. A major focus has been determining AgNPs' physical, chemical, and biological characteristics and their potential to be incorporated in biocomposite materials, particularly hydrogel scaffolds, for burn and wound healing. Though AgNPs have been rigorously explored and extensively utilized in medical and nonmedical applications, important research is still needed to elucidate their antibacterial activity when incorporated in wound-healing scaffolds. In this review, we provide an up-to-date, 10-yr (2010-2019), comprehensive literature review on advancements in the understanding of AgNP characteristics, including the particles' preparation and mechanisms of activity, and we explore various hydrogel scaffolds for delivering AgNPs.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".