CRACR2A-Mediated TCR Signaling Promotes Local Effector Th1 and Th17 Responses
Bibliographic record
Abstract
/NFAT and JNK/AP1 pathways. CRACR2A has been linked to human diseases in numerous genome-wide association studies and was shown to be one of the most sensitive targets of the widely used statin drugs. However, the physiological role of CRACR2A in T cell functions remains unknown. In this study, using transgenic mice for tissue-specific deletion, we show that CRACR2A promotes Th1 responses and effector function of Th17 cells. CRACR2A was abundantly expressed in Th1 and Th17 cells. In vitro, deficiency of CRACR2A decreased Th1 differentiation under nonpolarizing conditions, whereas the presence of polarizing cytokines compensated this defect. Transcript analysis showed that weakened TCR signaling by deficiency of CRACR2A failed to promote Th1 transcriptional program. In vivo, conditional deletion of CRACR2A in T cells alleviated Th1 responses to acute lymphocytic choriomeningitis virus infection and imparted resistance to experimental autoimmune encephalomyelitis. Analysis of CNS from experimental autoimmune encephalomyelitis-induced mice showed impaired effector functions of both Th1 and Th17 cell types, which correlated with decreased pathogenicity. Collectively, our findings demonstrate the requirement of CRACR2A-mediated TCR signaling in Th1 responses as well as pathogenic conversion of Th17 cells, which occurs at the site of inflammation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.001 |
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".