Exposure to surgical plumes induces histo-hepato-renal and ovarian disruptions, and the protective role of an antioxidant cocktail in experimental rats
Bibliographic record
Abstract
Objective: Among the leading causes of liver/kidney disease and ovarian failure in reproductive-aged women, inflammation and oxidative stress have been reported to aggravate organ complications induced by several factors, including surgical plumes. Vitamins A, C and E are well documented to improve the antioxidant defence system. This study hypothesised the toxic exposure of ovaries to surgical plume and the therapeutic effect of antioxidants. Method: Adult female Wistar rats were randomly assigned into four groups: control (CONT), surgical plume (SUPM), antioxidant (ANTO), and SUPM + ANTO groups. Surgical plume was simulated in an enclosed chamber, while administration of the antioxidant was for 28 days (20 mg/kg, p.o.). Thereafter, the animals were sacrificed, and the liver, kidney and ovaries were collected for histological examination. Result: Histological analysis revealed the SUPM group exhibited severe expression of Kupffer cells (hepatic inflammation) as well as macrophage infiltration in the Bowman’s space (renal inflammation. Similarly, ovarian tissue showed degenerated follicles when compared with control animals. Nevertheless, administration of an antioxidant cocktail decreased the Kupffer cells and macrophages in the liver and kidney, respectively, and reversed degenerated ovarian follicles when compared with the untreated SUPM group. Conclusion: Surgical plume exposure compromises hepatic/renal and ovarian tissue to cellular inflammation and oxidative stress, which contributes to cellular apoptosis. The present study revealed that antioxidant administration elicited protective effects in mitigating plume-induced hepatorenal and ovarian toxicity. The findings further highlight the urgent need for plume evacuation systems, enhanced ventilation, and protective measures to safeguard reproductive health among healthcare workers.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".