Control of Pathogenic CD4 T Cells and Lethal Immunopathology by Signaling Immunoadaptor DAP12 during Influenza Infection
Bibliographic record
Abstract
Immunopathology is a major cause of influenza-associated morbidity and mortality worldwide. However, the role and regulatory mechanisms of CD4 T cells in severe lung immunopathology following acute influenza infection are poorly understood. In this paper, we report that the emergence of immunopathogenic CD4 T cells is under the control of a transmembrane immunoadaptor DAP12 pathway during influenza infection. We find that the mice lacking DAP12 have unaltered viral clearance but easily succumb to influenza infection as a result of uncontrolled immunopathology. Such immunopathology is associated with markedly increased CD4 T cells displaying markedly increased cytotoxicity and Fas ligand expression. Furthermore, the immunopathogenic property of these CD4 T cells is transferrable. Thus, depletion of CD4 T cells or abrogation of Fas/Fas ligand signaling pathway improves survival and immunopathology. We further find that DAP12 expressed by dendritic cells plays an important role in controlling the immunopathogenic CD4 T cells during influenza infection. Our findings identify a novel pathway that controls the level of immune-pathogenic CD4 T cells during acute influenza infection.
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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".