Low-dose ketamine pretreatment reduces oxidative damage and inflammatory response following CO2 pneumoperitoneum in rats
Bibliographic record
Abstract
PURPOSE: The duration of pneumoperitoneum during laparoscopic procedures may contribute to post-surgical oxidative stress. Previous studies have shown that low-dose ketamine, an anesthetic with anti-inflammatory properties, protects various organs from ischemia-reperfusion injury. This study investigated the effects of low-dose ketamine on the overproduction of oxidants and the tissue damage caused by intra-abdominal pressure during CO2 pneumoperitoneum. METHODS: Male Sprague Dawley rats received a CO2 pneumoperitoneum of 15 mmHg and preceded by either low-dose ketamine (KP1, 5 mg/kg; KP2, 10 mg/kg) or 0.9% saline (PR, 3 ml). General anethesia was provided by pentobarbital and sevoflurane. The control group (CR) received an intraperitoneal saline injection and sham surgery. Three hours after pneumoperitoneum, serum concentrations of interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), malondialdehyde (MDA), superoxide dismutase (SOD) and intestinal fatty acid binding protein (iFABP) were measured and liver, kidney, lung, and intestine were evaluated for tissue damage. RESULTS: The highest plasma MDA, TNF-α, IL-6 and iFABP values were observed at T1 (after 3 hours of pneumoperitoneum) in the PR group, followed by the KP1, KP2, and CR groups (P < 0.01). SOD concentrations showed an opposite trend and were highest in the CR group, followed by the KP2, KP1, and PR groups (P < 0.01). TNF-α concentration was significantly lower in the KP2 than the KP1 group (P < 0.05). Histopathologic scoring of organ sections demonstrated the lowest scores in the KP2 group, followed by the KP1 and PR groups, in an increasing order (P < 0.05). CONCLUSION: Pretreatment with low-dose ketamine before general anaesthesia protects against potential oxidative damage and inflammatory response caused by CO2 pneumoperitoneum.
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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) | 0.001 | 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".