Diamond-like carbon coating to inner surface of polyurethane tube reduces Staphylococcus aureus bacterial adhesion and biofilm formation
Bibliographic record
Abstract
Staphylococcus aureus is one of the main causative bacteria for polyurethane catheter and artificial graft infection. Recently, we developed a unique technique for coating diamond-like carbon (DLC) inside the luminal resin structure of polyurethane tubes. This study aimed to elucidate the infection-preventing effects of diamond-like carbon (DLC) coating on a polyurethane surface against S. aureus. We applied DLC to polyurethane tubes and rolled polyurethane sheets with our newly developed DLC coating technique for resin tubes. The DLC-coated and uncoated polyurethane surfaces were tested in smoothness, hydrophilicity, zeta-potential, and anti-bacterial properties against S. aureus (biofilm formation and bacterial attachment) by contact with bacterial fluids under static and flow conditions. The DLC-coated polyurethane surface was significantly smoother, more hydrophilic, and had a more negative zeta-potential than did the uncoated polyurethane surface. Upon exposure to bacterial fluid under both static and flow conditions, DLC-coated polyurethane exhibited significantly less biofilm formation than uncoated polyurethane, based on absorbance measurements. In addition, the adherence of S. aureus was significantly lower for DLC-coated polyurethane than for uncoated polyurethane under both conditions, based on scanning electron microscopy. These results show that applying DLC coating to the luminal resin of polyurethane tubes may impart antimicrobial effects against S. aureus to implantable medical polyurethane devices, such as vascular grafts and central venous catheters.
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How this classification was reachedexpand
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 | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".