Selective Translation Under Heat Shock: Integrating HSP70 mRNA Regulation with Cellular Stress Responses in Yeast and Mammals
Bibliographic record
Abstract
Under stress, cells orchestrate a complex regulatory response to maintain protein homeostasis, leveraging differential translational regulation for constitutively expressed mRNAs and the transcriptionally induced heat shock protein HSP70 transcripts. Constitutive mRNAs typically experience partial translational suppression, consistent with their partitioning into stress-induced phase-separated condensates and the global reduction in protein synthesis. In contrast, inducible HSP70 mRNAs bypass this repression to remain in the cytosol where they recruit the available components of the translational machinery to ensure the rapid synthesis of HSP70. Although the components involved in the preferential translation of HSP70 mRNA during heat stress have not been fully elucidated, differences in the mRNA and translation factors between yeast and mammals suggest organism-specific mechanisms of HSP70 mRNA translation. In this review, we consider these differences to discuss the current knowledge on heat shock regulation of translation. We extend the discussion to go beyond the cytosolic needs of HSP70 to ponder the important interplay between the cytosol and mitochondria in activating HSP70 accumulation, which becomes vital for preserving intercompartmental proteostasis and cell survival.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".