Sequential Changes in NOX4 Expression, Oxidative Stress Indices, PIIINP, and Liver Histopathology During Hepatocellular Carcinogenesis Induced in Mice
Bibliographic record
Abstract
BACKGROUND AND AIM: Hepatocellular carcinoma (HCC) is a chronic disease caused by complex histological and biochemical changes related to oxidative stress leading to fibrosis, cirrhosis, and malignancy. Knowing the sequential changes in different stages of HCC development is essential for understanding the mechanisms of HCC pathogenesis. METHODS: This study was designed to evaluate alterations in NADPH oxidase 4 (NOX4) expression and oxidative stress during HCC progression in mice, induced with administration of diethylnitrosamine (DEN, 50 mg/kg) and phenobarbitone (PB, 500 mg/L via drinking water). The correlation of N-terminal propeptide type III collagen (PIIINP) as a serum indicator of fibrosis with HCC progression was also assessed. Newborn C57/bl6 mice were divided into four groups (n = 12/group): control, PB, DEN, and HCC. Then they were euthanized at different time schedules 2, 4, and 7 months (n = 4/subgroup). Blood and liver tissues were collected for estimation of serum PIIINP and total antioxidant capacity (TAC) liver NOX4 mRNA and protein expression, total oxidative stress, and glutathione (GSH). RESULTS: The results showed that NOX4 protein expression increased in the first months of HCC induction. Accordingly, liver NOX4-specific mRNA was substantially elevated (2.4 fold). Circulating fibrosis marker, the PIIINP levels together with total oxidative stress increased during HCC induction. TAC and GSH were increased over time during HCC induction. CONCLUSIONS: Based on the sequential changes observed following HCC induction by DEN, we conclude that increased expression of NOX4 in the liver precedes other changes such as other oxidative stress factors and fibrosis markers during HCC progression.
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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 | 0.000 |
| 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 | 0.000 | 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".