Eukaryotic translation initiation factor 2A protects pancreatic beta cells during endoplasmic reticulum stress while rescuing translation inhibition
Bibliographic record
Abstract
ABSTRACT The endoplasmic reticulum (ER) stress-induced unfolded protein response (UPR) helps decide β cell survival in diabetes. The alternative eukaryotic initiation factor 2A (EIF2A) has been proposed to mediate EIF2S1-independent translation during cellular stress and viral infection, but its role in β cells is unknown. EIF2A abundance is high in human and mouse islets relative to other tissues, and both thapsigargin and palmitate significantly increased EIF2A mRNA and EIF2A protein levels in MIN6 cells, mouse islets and human islets. Knockdowns of EIF2A, the related factor EIF2D, or both EIF2A and EIF2D, were not sufficient to cause apoptosis. On the other hand, transient or stable EIF2A over-expression protected MIN6 cells, primary mouse islets, and human islets from ER stress-induced, caspase-3-dependent apoptosis. Mechanistically, EIF2A overexpression decreased ERN1 (also known as IRE1α) expression in thapsigargin-treated MIN6 cells or human islets. In vivo , β cell specific EIF2A viral overexpression reduced ER stress, improved insulin secretion, and abrogated hyperglycemia in Ins2 Akita/WT mice. EIF2A overexpression significantly increased expression of genes involved in protein translation and reduced expression of pro-apoptotic genes (e.g. ALDH1A3). Remarkably, the decrease in global protein synthesis during UPR was prevented by EIF2A, despite ER stress-induced EIF2S1 phosphorylation. The protective effects of EIF2A were additive to those of ISRIB, a drug that counteracts the effects of EIF2S1 phosphorylation. Cells overexpressing EIF2A showed higher expression of translation factor EIF2B5, which may contribute to the lack of translational inhibition in these cells. We conclude that EIF2A is a novel target for β cell protection and the circumvention of EIF2S1-mediated translational repression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.001 | 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".