Octylcyanoacrylate Tissue Adhesive as an Alternative to Mechanical Fixation of Expanded Polytetrafluoroethylene Prosthesis
Bibliographic record
Abstract
In minimally invasive incisional hernia repair positioning and fixation of the expanded polytetrafluoroethylene (ePTFE) mesh prosthesis on the deep surface of the abdominal wall may be facilitated using tissue adhesives. Octylcyanoacrylate (OCTYL), a new adhesive, forms a strong flexible bond with antimicrobial properties. In a rabbit model for incisional hernia we investigated characteristics of the bond created by OCTYL between ePTFE and abdominal wall musculature. We studied initial bond strength and the postoperative host response to the adhesive over a 6-week period. We compared sutured, stapled, and glued mesh prostheses and examined the tissue-prosthesis interface. The ePTFE mesh was fixed successfully to the abdominal wall with OCTYL and remained tightly attached at 6 weeks. Prostheses fixed with OCTYL and spiral tacks induced few intra-abdominal adhesions compared with sutured mesh. All prostheses were completely reperitonealized at 2 weeks. The force required to displace mesh fixed with sutures and staples was greater than mesh fixed with OCTYL. Analysis of the ePTFE/tissue interface by light and scanning electron microscopy showed host cellular migration into the interstices of the mesh with fixation by tacks and suture, whereas an inflammatory infiltrate was seen on the muscular surface with OCTYL fixation of the mesh.
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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 | 0.000 | 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".