CD137-Mediated Pathogenesis from Chronic Hepatitis to Hepatocellular Carcinoma in Hepatitis B Virus-Transgenic Mice
Bibliographic record
Abstract
Chronic hepatitis B virus (HBV) infection is characterized by sustained liver inflammation with an influx of lymphocytes, which contributes to the development of cirrhosis and hepatocellular carcinoma. The mechanisms underlying this immune-mediated hepatic pathogenesis remain ill defined. We report in this article that repetitive infusion of anti-CD137 agonist mAb in HBV-transgenic mice closely mimics this process by sequentially inducing hepatitis, fibrosis, cirrhosis, and, ultimately, liver cancer. CD137 mAb initially triggers hepatic inflammatory infiltration due to activation of nonspecific CD8(+) T cells with memory phenotype. CD8(+) T cell-derived IFN-γ plays a central role in the progression of chronic liver diseases by actively recruiting hepatic macrophages to produce fibrosis-promoting cytokines and chemokines, including TNF-α, IL-6, and MCP-1. Importantly, the natural ligand of CD137 was upregulated significantly in circulating CD14(+) monocytes in patients with chronic hepatitis B infection and closely correlated with development of liver cirrhosis. Thus, sustained CD137 stimulation may be a contributing factor for liver immunopathology in chronic HBV infection. Our studies reveal a common molecular pathway that is used to defend against viral infection but also causes chronic hepatic diseases.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".