Potassium bromate (KBrO<sub>3</sub>) modulates oxidative stress and inflammatory biomarkers in sodium hydroxide (NaOH) – induced Crohn’s colitis in Wistar rats
Bibliographic record
Abstract
Potassium bromate (KBrO3) present in consumed ozonised water was recently documented to exacerbate experimental gastric ulcer. Information, however, is vague as regards its effects in the colon where water reabsorption occurs. In this study, we observed the possible effects of KBrO3 on oxidative stress and inflammatory biomarkers in sodium hydroxide (NaOH) – induced Crohn’s colitis (CC). Wistar rats (180–200 g) were divided into six groups (n = 10): (i) control; (ii) untreated CC (induced by 1.4% NaOH; intra-rectal administration); and (iii–vi) CC treated with vitamin E, KBrO3, vitamin E+KBrO3, and sulphazalazine, respectively, for 7 days. Body weight and stool score were monitored daily. By day 3 and 7, excised colon was evaluated for ulcer scores and biochemical and histological analysis. Blood samples collected on days 3 and 7 were assayed for haematological indices using standard methods. Data were subjected to analysis of variance (ANOVA) and p ≤ 0.05 considered significant. Platelet/lymphocyte ratio, colonic ulcer score, malondialdehyde, and mast cells were significantly decreased while colonic sulfhydryl, and Ca2+- and Na+/K+-ATPase activities were increased following KBrO3 treatment compared with untreated CC. These findings suggest that KBrO3 may mitigate against NaOH-induced CC via inhibiting mast cell population and oxidative and inflammatory content but stimulating colonic sulfhydryl and Ca2+- and Na+/K+-ATPase activities.
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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 | 0.001 | 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".