Barbed compared with standard suture: Effects on cellular composition and proliferation of the healing wound in the ovine uterus
Bibliographic record
Abstract
OBJECTIVE: To compare cellular composition (fibroblasts vs. smooth muscle cells) and proliferation in uterine healing wounds after application of barbed compared with standard suture in a sheep model. DESIGN: Randomized trial (Canadian Task Force classification I) using each animal as its own control. SETTING: Certified animal research facility. Population or sample. 23 non-pregnant ewes. METHODS: A myometrial incision was created with the harmonic scalpel in each horn of the bicornuate uterus. The incisions were randomly allocated to be closed using either polyglactin 210 (Vicryl®) or barbed suture. Three months later, uterine tissues were collected, fixed and used for determination of cellular composition and proliferation using histochemistry (Masson trichrome staining) and immunohistochemistry (staining of smooth muscle cell actin and Ki67, a marker of proliferating cells) followed by image analysis. MAIN OUTCOME MEASURES: Evaluation and comparison of the cellular composition and proliferation of uterine wounds after application of barbed vs. standard suture. RESULTS: The ratio between connective tissue elements and smooth muscle cells, expression of smooth muscle cell actin and labeling index were similar in wounds after application of barbed compared with standard suture, but were different (p < 0.0001-0.05) in wounds than in non-wounded areas in uterus. CONCLUSION: Both barbed and standard sutures had similar effects on cellular composition and proliferation of uterine wounds in an animal model.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".