Polydopamine-Inspired Surface Modification of Polypropylene Hernia Mesh Devices via Cold Oxygen Plasma: Antibacterial and Drug Release Properties
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mesh infection is a major complication of hernia surgery after polypropylene (PP) mesh implantation. Modifying the PP mesh with antibacterial drugs is an effective way to reduce the chance of infection, but the hydrophobic characteristic of PP fibers has obstructed the drug adhesion. Therefore, to prepare antimicrobial PP mesh with a stable drug coating layer and to slow the drug release property during the hernia repair process has a great practical meaning. In this work, PP meshes were coated by bio-inspired polydopamine (PDA), which can load and release levofloxacin. PP meshes were activated with cold oxygen plasma and then plasma activated PP fibers were coated with PDA. The PDA coated meshes were further soaked in levofloxacin. The levofloxacin loaded PP meshes demonstrate excellent antimicrobial properties for 6 days and the drug release has lasted for at least 24 h. Moreover, a control PP mesh sample without plasma treatment was also prepared, after coating with PDA and loading levofloxacin. The antimicrobial property was sustained only for two days. The maximum inhibition zone of PDA coated meshes with and without plasma treatment was 12.5 and 9 mm, respectively. On all accounts, the modification strategy can facilely lead to long-term property of infection prevention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 it