Plasticity of the mammalian integrated stress response
Bibliographic record
Abstract
An increased level of phosphorylation of eukaryotic translation initiation factor 2 subunit-α (eIF2α, encoded by EIF2S1; eIF2α-p) coupled with decreased guanine nucleotide exchange activity of eIF2B is a hallmark of the ‘canonical’ integrated stress response (c-ISR)1. It is unclear whether impaired eIF2B activity in human diseases including leukodystrophies2, which occurs in the absence of eIF2α-p induction, is synonymous with the c-ISR. Here we describe a mechanism triggered by decreased eIF2B activity, distinct from the c-ISR, which we term the split ISR (s-ISR). The s-ISR is characterized by translational and transcriptional programs that are different from those observed in the c-ISR. Opposite to the c-ISR, the s-ISR requires eIF4E-dependent translation of the upstream open reading frame 1 and subsequent stabilization of ATF4 mRNA. This is followed by altered expression of a subset of metabolic genes (for example, PCK2), resulting in metabolic rewiring required to maintain cellular bioenergetics when eIF2B activity is attenuated. Overall, these data demonstrate a plasticity of the mammalian ISR, whereby the loss of eIF2B activity in the absence of eIF2α-p induction activates the eIF4E–ATF4–PCK2 axis to maintain energy homeostasis. A study describes the split integrated stress response, a cellular stress response mechanism characterized by reduced eIF2B activity without eIF2α phosphorylation, which activates the eIF4E–ATF4–PCK2 axis, enabling metabolic reprogramming.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".