Contribution of CD137 signaling to Hepatic Fibrosis via T cell and Macrophage Mediated Chronic Liver Inflammation (43.5)
Bibliographic record
Abstract
Abstract It is accepted that viral clearance and disease pathogenesis during HBV infection are mediated by the immune responses. Molecular mechanisms of the emergence or regulation of the immune response in this process remain largely unknown. Here we characterized that CD137 signaling acted as a potential pathogenic factor in progression of chronic hepatitis B. CD137 signaling successively stimulated by agonist anti-CD137 mAb could induce persistent hepatic infiltration and IFN-¦Ã production of CD8 T cells in HBV tansgenic mice. Through secreted IFN-¦Ã, the activated CD8 T cells subsequently recruited macrophage into liver to produce pro-inflammatory cytokines, which caused chronic liver inflammation and hepatic fibrogenesis, and promoted hepatocarcinoma development. Moreover, expression of CD137L was indeed up-regulated in peripheral monocytes of CHB patients and closely correlated with liver cirrhosis and the plasma level of IL-8, but not with ALT. Stimulation of monocytes from cirrhotic patients with recombinant human CD137 ligand induced IL-8 secretion in vitro, a chemokine closely associated with enhanced liver fibrosis in chronic HBV patients. These resutls support an important role of CD137 signaling in liver inflammation and fibrosis, indicating that CD137 pathway may be a target for immunotherapy of chronic hepatitis B. Our findings also suggest that IFN-¦Ã,secreted by CD8 T cells, plays pivotal roles in mediating chronic liver inflammation and fibrosis. Further elucidation on this question will be of great significance for the immunotherapy of chronic hepatitis B.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".