UVC-Induced Stress Granules in Mammalian Cells
Bibliographic record
Abstract
Stress granules (SGs) are well characterized cytoplasmic RNA bodies that form under various stress conditions. We have observed that exposure of mammalian cells in culture to low doses of UVC induces the formation of discrete cytoplasmic RNA granules that were detected by immunofluorescence staining using antibodies to RNA-binding proteins. UVC-induced cytoplasmic granules are not Processing Bodies (P-bodies) and are bone fide SGs as they contain TIA-1, TIA-1/R, Caprin1, FMRP, G3BP1, PABP1, well known markers, and mRNA. Concomitant with the accumulation of the granules in the cytoplasm, cells enter a quiescent state, as they are arrested in G1 phase of the cell cycle in order to repair DNA damages induced by UVC irradiation. This blockage persists as long as the granules are present. A tight correlation between their decay and re-entry into S-phase was observed. However the kinetics of their formation, their low number per cell, their absence of fusion into larger granules, their persistence over 48 hours and their slow decay, all differ from classical SGs induced by arsenite or heat treatment. The induction of these SGs does not correlate with major translation inhibition nor with phosphorylation of the α subunit of eukaryotic translation initiation factor 2 (eIF2α). We propose that a restricted subset of mRNAs coding for proteins implicated in cell cycling are removed from the translational apparatus and are sequestered in a repressed form in SGs.
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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 | 0.001 |
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".