Influence of Protein Deposition on Bacterial Adhesion to Contact Lenses
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: The aim of the study is to determine the adhesion of Gram positive and Gram negative bacteria onto conventional hydrogel (CH) and silicone hydrogel (SH) contact lens materials with and without lysozyme, lactoferrin, and albumin coating. METHODS: Four lens types (three SH-balafilcon A, lotrafilcon B, and senofilcon A; one CH-etafilcon A) were coated with lysozyme, lactoferrin, or albumin (uncoated lenses acted as controls) and then incubated in Staphylococcus aureus (Saur 31) or either of two strains of Pseudomonas aeruginosa (Paer 6294 and 6206) for 24 h at 37 °C. The total counts of the adhered bacteria were determined using the H-thymidine method and viable counts by counting the number of colony-forming units on agar media. RESULTS: All three strains adhered significantly lower to uncoated etafilcon A lenses compared with uncoated SH lenses (p < 0.05). Lysozyme coating on all four lens types increased binding (total and viable counts) of Saur 31 (p < 0.05). However, lysozyme coating did not influence P. aeruginosa adhesion (p > 0.05). Lactoferrin coating on lenses increased binding (total and viable counts) of Saur 31 (p < 0.05). Lactoferrin-coated lenses showed significantly higher total counts (p < 0.05) but significantly lower viable counts (p < 0.05) of adhered P. aeruginosa strains. There was a significant difference between the total and viable counts (p < 0.05) that were bound to lactoferrin-coated lenses. Albumin coating of lenses increased binding (total and viable counts) of all three strains (p < 0.05). CONCLUSIONS: Lysozyme deposited on contact lenses does not possess antibacterial activity against certain bacterial strains, whereas lactoferrin possess an antibacterial effect against strains of P. aeruginosa.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 it