Montelukast reduces sepsis-induced lung and renal injury in rats
Bibliographic record
Abstract
This study was undertaken to examine the effects of montelukast (MNT) on lung and kidney injury in lipopolysaccharide (LPS) induced systemic inflammatory response. Rats were randomized into 5 groups (n = 8 rats/group): (i) Control; (ii) LPS treated (10 mg/kg body mass, by intraperitoneal (i.p.) injection); (iii) LPS + MNT (10 mg/kg, per oral (p.o.)); (iv) LPS + MNT (20 mg/kg, p.o); (v) LPS + dexamethasone (DEX; 1 mg/kg, i.p.). Twenty-four hours after sepsis was induced, the lung or kidney:body mass ratio and percent survival of rats were determined. Creatinine, blood urea nitrogen (BUN), albumin, total protein, and LDH activity were measured. Lung and kidney samples were taken for histological assessment and for determination of their malondialdehyde (MDA) and glutathione (GSH) contents. The expression of tumour necrosis factor α (TNF-α) in tissue was evaluated immunohistochemically. LPS significantly increased the organ:body mass ratio, serum creatinine, BUN, and LDH, and decreased serum albumin and total protein levels. MDA levels increased in lung and kidney tissues after treatment with LPS, and there was a concomitant reduction in GSH levels. Immunohistochemical staining of lung and kidney specimens from LPS-treated rats revealed high expression levels of TNF-α. MNT suppresses the release of inflammatory and oxidative stress markers. Additionally, MNT effectively preserved tissue morphology as evidenced by histological evaluation. These results demonstrate that MNT could have lung and renoprotective effects against the inflammatory process during endotoxemia. This effect can be attributed to its antioxidant and (or) anti-inflammatory properties.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.001 | 0.002 |
| 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 teacher head, 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".