Annexin V Associates with the IFN-γ Receptor and Regulates IFN-γ Signaling
Bibliographic record
Abstract
Many of the biological activities of IFN-gamma are mediated through the IFN-gammaR3-linked Jak-Stat1alpha pathway. However, regulation of IFN-gamma signaling is not fully understood, and not all responses to IFN-gamma are Stat1alpha dependent. To identify novel elements involved in IFN-gamma cell regulation, the cytoplasmic domain of the R2 subunit of the human IFN-gammaR was used as bait in a yeast two-hybrid screen of a human monocyte cDNA library. This identified annexin A5 (AxV) as a putative IFN-gammaR binding protein. The interaction was confirmed in pull-down experiments in which a GST-R2 cytoplasmic domain fusion protein was incubated with macrophage lysates. Furthermore, immunoprecipitation using anti-IFN-gammaR2 Abs showed that AxV interacted with IFN-gammaR2 to form a stable complex following incubation of cells with IFN-gamma. In 293T cells with reduced expression of AxV, brought about by small interfering RNA targeting, activation of Jak2 and Stat1alpha in response to IFN-gamma was enhanced. Inhibition of cell proliferation, a hallmark of the IFN-gamma response, also was potentiated in HeLa cells treated with small interfering RNA directed at AxV. Taken together, these results suggest that through an inducible association with the R2 subunit of the IFN-gammaR, AxV modulates cellular responses to IFN-gamma by modulating signaling through the Jak-Stat1 pathway.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".