eIF2α Phosphorylation Tips the Balance to Apoptosis during Osmotic Stress
Bibliographic record
Abstract
Regulation of cell volume is of great importance because persistent swelling or shrinkage leads to cell death. Tissues experience hypertonicity in both physiological (kidney medullar cells) and pathological states (hypernatremia). Hypertonicity induces an adaptive gene expression program that leads to cell volume recovery or apoptosis under persistent stress. We show that the commitment to apoptosis is controlled by phosphorylation of the translation initiation factor eIF2alpha, the master regulator of the stress response. Studies with cultured mouse fibroblasts and cortical neurons show that mutants deficient in eIF2alpha phosphorylation are protected from hypertonicity-induced apoptosis. A novel link is revealed between eIF2alpha phosphorylation and the subcellular distribution of the RNA-binding protein heterogeneous nuclear ribonucleoprotein A1 (hnRNP A1). Stress-induced phosphorylation of eIF2alpha promotes apoptosis by inducing the cytoplasmic accumulation of hnRNP A1, which attenuates internal ribosome entry site-mediated translation of anti-apoptotic mRNAs, including Bcl-xL that was studied here. Hypertonic stress induced the eIF2alpha phosphorylation-independent formation of cytoplasmic stress granules (SGs, structures that harbor translationally arrested mRNAs) and the eIF2alpha phosphorylation-dependent accumulation of hnRNP A1 in SGs. The importance of hnRNP A1 was demonstrated by induction of apoptosis in eIF2alpha phosphorylation-deficient cells that express exogenous cytoplasmic hnRNP A1. We propose that eIF2alpha phosphorylation during hypertonic stress promotes apoptosis by sequestration of specific mRNAs in SGs in a process mediated by the cytoplasmic accumulation of hnRNP A1.
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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 | 0.000 |
| 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 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".