Vitamin D<sub>3</sub> protects against prednisolone-induced liver injury associated with the impairment of the hepatic NF-κB/iNOS/NO pathway
Bibliographic record
Abstract
The study was carried out to define whether prednisolone-induced damage to hepatic cells is accompanied by excessive nitric oxide (NO) levels associated with nuclear factor kappa B (NF-κB)/inducible NO synthase (iNOS) activation and evaluate the efficacy of the treatment with vitamin D3. Histopathological examination, activities of liver transaminases (alanine aminotransferase and aspartate aminotransferase), and cell death assays consistently showed that prednisolone (5 mg/kg body weight, 30 days) induces chronic liver injury in female Wistar rats. Specifically, increased hepatocellular necrosis and caspase-3-dependent apoptosis were observed. Prednisolone enhanced iNOS protein expression, NO generation, and tyrosine nitration in liver cells. Despite unchanged hepatic level of the NF-κB/p65 protein, prednisolone increased inhibitory κB-α (IκB-α) degradation, nuclear translocation, and phosphorylation of NF-κB/p65 at Ser311, indicating that NF-κB activation can be involved in the induction of iNOS/NO. All changes were associated with a 2.9-fold decrease in the serum content of 25-hydroxyvitamin D3 and significant reduction of hepatic vitamin D3 receptor (VDR) expression that points reliably to vitamin D3 deficiency and failures in VDR signaling. Vitamin D3 co-administration (100 IU/rat, 30 days) prevented glucocorticoid-evoked abnormalities in hepatic tissue. In conclusion, prednisolone-induced liver disturbances were associated with the impairment of NF-κB/iNOS/NO responses that can be ameliorated by vitamin D3 treatment through VDR-mediated mechanisms.
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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".