Impact of electrocautery and hyperthermic intraperitoneal chemotherapy on intestinal microvasculature in a murine model
Bibliographic record
Abstract
BACKGROUND: Electrocautery (EC) is used during cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC). Using a murine model, we studied the effect of HIPEC on small bowel EC lesions and surrounding normal tissues. METHODS: Thirty-two rats were divided into five groups: a control group with EC lesions; EC plus intraperitoneal heated 5% dextrose (D5W); EC plus oxaliplatin (OXA, 460 mg/m(2)); EC plus mitomycin C 10 mg/m(2) (MMC10); EC plus MMC 35 mg/m(2) (MMC35). EC lesions and surrounding tissue microvasculature were analysed after intravenous injection of fluorescein. RESULTS: In the ileum OXA significantly reduced EC lesions microvasculature compared with the control group; MMC10 caused greater reduction than the control, D5W and MMC35 groups. Surrounding tissue microvasculature was significantly reduced by MMC35 exposure when compared to the control, OXA or MMC10 groups. In the jejunum EC injuries exposed to OXA or MMC10 had significantly reduced microvasculature compared to the control, heated D5W and MMC35 groups. Surrounding tissue microvasculature was significantly reduced by MMC35 exposure when compared to the OXA group. There was no significant microvasculature difference between the EC lesions made before or after HIPEC. CONCLUSION: HIPEC with OXA and MMC10 potentiates small bowel wall EC injuries. MMC35 reduces surrounding unharmed tissue microvasculature. There was no effect of hyperthermia alone on microvasculature.
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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) | 0.000 | 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 | 0.001 |
| 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".