Functional skewing of the global CD8 T cell population in chronic hepatitis B virus infection
Bibliographic record
Abstract
The inflamed liver in chronic hepatitis B virus (HBV) infection (CHB) is characterized by a large influx of non-virus-specific CD8 T cells. Little is known about the functional capacity of these lymphocytes, which could provide insights into mechanisms of failure of viral control and liver damage in this setting. We compared the effector function of total circulating and intrahepatic CD8 T cells in CHB patients and healthy donors. We demonstrated that CD8 T cells from CHB patients, regardless of their antigen specificity, were impaired in their ability to produce interleukin-2 and proliferate upon TCR-dependent stimulation. In contrast, these CD8 T cells had preserved production of the proinflammatory cytokines interferon-gamma and tumor necrosis factor-alpha. This aberrant functional profile was partially attributable to down-regulation of the proximal T cell receptor signaling molecule CD3zeta, and could be corrected in vitro by transfection of CD3zeta or replenishment of the amino acid arginine required for its expression. We provide evidence for depletion of arginine in the inflamed hepatic microenvironment as a potential mechanism for these defects in global CD8 T cell signaling and function. These data imply that polarized CD8 T cells within the HBV-infected liver may impede proliferative antiviral effector function, while contributing to the proinflammatory cytokine environment.
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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 | 0.000 | 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) | 0.001 | 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".