Bibliographic record
Abstract
Rapid expression of the survival gene, inducible heat shock protein 70 (hsp70), is critical for mounting cytoprotection against severe cellular stress, like elevated temperature. Hsp70 protein chaperones the refolding of heat-denatured peptides to minimize proteolytic degradation as a part of an eukaryotically conserved phenomenon referred to as the heat shock response. The physiologic stress associated with exercise, which can include elevated temperature, mechanical damage, hypoxia, lowered pH, and reactive oxygen species generation, may promote protein unfolding, leading to hsp70 gene expression in skeletal myofibers. Although the pre-transcriptional activation of hsp70 gene expression has been thoroughly reviewed, discussion of downstream hsp70 gene regulation is less extensive. The purpose of this brief review was to examine all levels of hsp70 gene regulation in response to heat stress and exercise with a special focus on skeletal myofibers where data are available. In general, while heat stress represses bulk gene expression, hsp70 mRNA expression is enhanced. Post-transcriptionally, intronless hsp70 mRNA circumvents a host of decay pathways, as well as heat stress-repressed pre-mRNA splicing and nuclear export. Pre-translationally, hsp70 mRNA is excluded from stress granules and preferentially translated during heat stress-repressed global cap-dependent translation. Post-translationally, nascent Hsp70 protein is thermodynamically stable at elevated temperatures, allowing for the commencement of chaperoning activity early after synthesis to attenuate the heat shock response and protect against subsequent injury. This review demonstrates that hsp70 mRNA expression is closely coupled with functional protein translation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".