Uroprotective Potential of Campesterol in Cyclophosphamide Induced Interstitial Cystitis; Molecular Docking Studies
Bibliographic record
Abstract
Abstract Cyclophosphamide (CYP) is commonly used to treat cancer of the ovaries, breast, lymph, and blood system and produces interstitial cystitis (IC) via its urotoxic metabolite: i. e., acrolein. The present study was aimed to investigate the uroprotective effect of campesterol (a steroidal phytochemical) in cyclophosphamide induced IC. IC was induced by CYP (150 mg/kg, i. p .) in rats. The Enzyme linked immunosorbent assays for oxidative stress markers and Polymerase Chain Reaction (PCR) for inflammatory cytokines were carried out. The Tissue Organ Bath Technique was used for the evaluation of the spasmolytic effect of campesterol. Different pharmacological antagonists have been used to explore the mechanism of action of campesterol. Treatment with campesterol (70 mg/kg) reduced nociception (55 %), edema (67 %), hemorrhage (67 %), and protein leakage significantly (94 %). The antioxidant activity of campesterol was exhibited by a fall in MDA, NO, and an elevation in SOD, CAT, and GPX levels. Campesterol presented anti‐inflammatory potential by decreasing IL‐1, TNF‐α, and TGF‐β expression levels. Histologically, it preserved urothelium from the deleterious effect of CYP. Campesterol showed a spasmolytic effect by reducing bladder overactivity that was dependent on muscarinic receptors, voltage‐gated calcium and K ATP channels, and cyclo‐oxygenase pathways. In silico studies confirmed the biochemical findings. The findings suggest that campesterol could be valorized as a possible therapeutic agent against cyclophosphamide‐induced interstitial cystitis.
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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 | 0.001 |
| 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) | 0.003 | 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".