Innate immune functions during chronic infections
Bibliographic record
Abstract
About 10% of the world population suffers from chronic virus infections such as infections with hepatitis B virus, hepatitis C virus, and human immunodeficiency virus. Chronic virus infection is associated with the loss of functional cytotoxic T cells. Recent studies uncovered several mechanisms that play a central role in T cell exhaustion and thus development of chronic infections. The role of the innate immune system in the development of chronic virus infections remains unclear. Here we show that type I interferons trigger not only inhibition of virus replication but also immunoregulatory functions. The antiviral effects of type I interferons in the liver were dependent on the presence of macrophages. Macrophage depletion led to excessive virus replication and the development of chronic infection. Moreover, specific deletion of the type I interferon receptor on macrophages led to a decreased innate immune response. The regulatory functions of type I interferons were carried out by natural killer cells. Activated natural killer cells inhibited the virus specific cytotoxic T cell response and therefore delayed virus control. Depletion of natural killer cells prevented development of chronic infections and immunopathology. Moreover, type I interferons acted directly on the cytotoxic T cell response. Treatment with interferon 3 lead to increased T cell function. This resulted in induction of autoimmune diabetes in transgenic mice. \nIn conclusion, the nature of the innate immune response triggers the development of chronic virus infection. These results uncover new mechanisms that might provide the foundation for new therapeutic approaches for patients with chronic infections.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".