Role of the Intracellular Domain of the Human Type I Interferon Receptor 2 Chain (IFNAR2c) in Interferon Signaling
Bibliographic record
Abstract
A human cell line (U5A) lacking the type I interferon (IFN) receptor chain 2 (IFNAR2c) was used to determine the role of the IFNAR2c cytoplasmic domain in regulating IFN-dependent STAT activation, interferon-stimulated gene factor 3 (ISGF3) and c-sis-inducible factor (SIF) complex formation, gene expression, and antiproliferative effects. A panel of U5A cells expressing truncation mutants of IFNAR2c on their cell surface were generated for study. Janus kinase (JAK) activation was detected in all mutant cell lines; however, STAT1 and STAT2 activation was observed only in U5A cells expressing full-length IFNAR2c and IFNAR2c truncated at residue 462 (R2.462). IFNAR2c mutants truncated at residues 417 (R2. 417) and 346 (R2.346) or IFNAR2c mutant lacking tyrosine residues in its cytoplasmic domain (R2.Y-F) render the receptor inactive. A similar pattern was observed for IFN-inducible STAT activation, STAT complex formation, and STAT-DNA binding. Consistent with these data, IFN-inducible gene expression was ablated in U5A, R2.Y-F, R2.417, and R2.346 cell lines. The implications are that tyrosine phosphorylation and the 462-417 region of IFNAR2c are independently obligatory for receptor activation. In addition, the distal 53 amino acids of the intracellular domain of IFNAR2c are not required for IFN-receptor mediated STAT activation, ISFG3 or SIF complex formation, induction of gene expression, and inhibition of thymidine incorporation. These data demonstrate for the first time that both tyrosine phosphorylation and a specific domain of IFNAR2c are required in human cells for IFN-dependent coupling of JAK activation to STAT phosphorylation, gene induction, and antiproliferative effects. In addition, human and murine cells appear to require different regions of the cytoplasmic domain of IFNAR2c for regulation of IFN responses.
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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 | 0.000 | 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 | 0.001 |
| 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 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".