Bacterial Capture Efficiency and Antimicrobial Activity of Phage-Functionalized Model Surfaces
Bibliographic record
Abstract
The rise of antibiotic-resistant bacteria has directed substantial attention toward the use of bacteriophages as a means to control bacterial populations. It has been proposed that bacteriophages can be applied as a coating on surfaces in healthcare settings or on indwelling medical devices to create an antimicrobial surface. In this study, antimicrobial model surfaces functionalized with five different types of bacteriophage were prepared and characterized with X-ray photoelectron spectroscopy and atomic force microscopy. The bacterial capture efficiency of these functionalized surfaces was studied for two common bacteria, Escherichia coli and Salmonella typhimurium. Binding of the phages to a solid surface affected their biofunctionality as expressed by the capture efficiency and rate of host membrane disruption. Moreover, the size and shape of the bacteriophage and positioning of its specific binding proteins significantly affected its bacterial capture capability in the immobilized state. Symmetric bacteriophages were found to be a better choice for antibacterial surfaces compared to more asymmetric tailed bacteriophages. Immobilized phages were found to disrupt the membranes of attached bacteria and are thus proposed as a candidate for antimicrobial surfaces.
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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 | 0.001 |
| 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 | 0.001 | 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".