c-Jun NH2-Terminal Kinase (JNK)1 and JNK2 Signaling Pathways Have Divergent Roles in CD8+ T Cell–mediated Antiviral Immunity
Bibliographic record
Abstract
c-Jun NH(2)-terminal kinases (JNK) play important roles in T helper cell (Th) proliferation, differentiation, and maintenance of Th1/Th2 polarization. To determine whether JNKs are involved in antiviral T cell immunity, and whether JNK1 and JNK2 bear biological differences, we investigated the immune responses of JNK1-deficient and JNK2-deficient mice to lymphocytic choriomeningitis virus (LCMV). After LCMV infection, wild-type (JNK(+/+)) mice had a 5- to 10-fold increase in splenic CD8(+) T cells. In contrast, infected JNK1(-/-) mice showed a significantly lower virus-specific CD8(+) T cell expansion. However, JNK1(-/-) mice cleared LCMV infection with similar kinetics as JNK(+/+) mice. Splenic T cells from LCMV-infected JNK1(-/-) animals produced interferon gamma after stimulation with viral peptides. However, fewer JNK1(-/-) T cells acquired an activated phenotype (CD44(hi)) and more JNK1(-/-)CD8(+)CD44(hi) cells underwent apoptosis than JNK(+/+) cells at the peak of the primary response. In contrast, LCMV-infected JNK2(-/-) mice generated more virus-specific CD8(+) T cells than JNK(+/+) mice. These results indicate that JNK1 and JNK2 signal pathways have distinct roles in T cell responses during a viral infection. JNK1 is involved in survival of activated T cells during immune responses, and JNK2 plays a role in control of CD8(+) T cell expansion in vivo.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".