Interferon‐γ stimulates p11‐dependent surface expression of annexin A2 in lung epithelial cells to enhance phagocytosis
Bibliographic record
Abstract
Annexin A2 (p36) is usually present together with its natural ligand p11 as a heterotetramer complex, which has multiple biological functions depending on its cellular localization. However, the detailed mechanism of annexin A2 translocation and its physiological role in inflammation remain unclear. Here, we show that IFN-γ stimulation enhances surface translocation of annexin A2 on lung epithelial cells. While total annexin A2 protein remains unchanged, the expression of p11 is upregulated via the IFN-γ-activated JAK2/STAT1 signal pathway. Notably, IFN-γ-induced p11 expression is required for annexin A2 translocation to the cell surface. Since annexin A2 lacks a signal peptide for surface translocation by the classical endoplasmic reticulum-Golgi route, its mode of trafficking remains unclear. We observed that p11-dependent surface translocation of annexin A2 is associated with the exosomal secretion pathway. The IFN-γ-induced increase of annexin A2 in the exosomes is blocked in p11-silenced cells. Furthermore, IFN-γ-induced surface expression of annexin A2 mediates phagocytosis of apoptotic cells by lung epithelial cells. These findings provide insights into the surface translocation mechanism of annexin A2 and illustrate a pivotal function of surface annexin A2 in the phagocytic response to IFN-γ.
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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 | 0.001 |
| 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".