Effect of mechanical bowel preparation in fibroblast, collagen density and histopathology analysis in colon anastomosis site of Wistar rat
Bibliographic record
Abstract
Backgrounds: Mechanical bowel preparation (MBP) was almost considered dogmatic in colorectal surgery. There are several methods known to perform MBP. Anastomotic leakage is considered higher in patients who had MBP, and it is thought due to alteration colonic morphologic, electrolyte and fluid imbalance.Methods: This is an experimental study divided into two groups. This study aims to determine the difference in collagen density, amount of fibroblast and histopathologic features in the anastomotic site between Wistar rats that had MBP and without MBP to the colonic anastomosis. The first group consists of 6 Wistar rats who had colonic anastomosis without MBP, and the second group consists of 6 Wistar rats who had colonic anastomosis with BMP. On the 10th day after surgery, histopathology examination is performed with regards to collagen density, the number of fibroblasts, infiltration of inflammatory cells and the degree of bowel wall damage at the anastomotic site. Independent t-test is used to analyze the data if it is normally distributed and Mann-Whitney test is used if the data is not normally distributed.Results: The amount of fibroblast was significant difference between two groups (p=0.02), which is amount of fibroblast in the second group (3.83 ± 0.408) is higher than the first group (2.33 ± 0.816). Meanwhile, there is no significant difference regarding collagen density, infiltration of inflammatory cells and the degree of bowel wall damage (p=0.59, p=0.082 dan p=1.00).Conclusion: The conclusion of this research is by performing MBP prior to colonic anastomosis will exert the effect of more abundant fibroblast.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".