An effective and biocompatible antibiofilm coating for central venous catheter
Bibliographic record
Abstract
The aim of this study was to investigate the in vitro and in vivo efficacy and the tissue reaction of an antibiofilm coating composed of xylitol, triclosan, and polyhexamethylene biguanide. The antimicrobial activity was analyzed by a turbidimetric method. Scanning electron microscopy was used to evaluate the antiadherent property of central venous catheter (CVC) fragments impregnated with an antibiofilm coating (I-CVC) in comparison with noncoated CVC (NC-CVC) fragments. Two in vivo assays using subcutaneous implantation of NC-CVC and I-CVC fragments in the dorsal area of rats were performed. The first assay comprised hematological and microbiological analysis. The second assay evaluated tissue response by examining the inflammatory reactions after 7 and 21 days. The formulation displayed antimicrobial activity against all tested strains. A biofilm disaggregation with significant reduction of microorganism's adherence in I-CVC fragments was observed. In vivo antiadherence results demonstrated a reduction of early biofilm formation of Staphylococcus aureus ATCC 25923, mainly in an external surface of the I-CVC, in comparison with the NC-CVC. All animals displayed negative hemoculture. No significant tissue reaction was observed, indicating that the antibiofilm formulation could be considered biocompatible. The use of I-CVC could decrease the probability of development of localized or systemic infections.
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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".