Cellular localization of HSF1 and Hsp70 in skeletal muscle following acute exercise
Bibliographic record
Abstract
Exercise induction of the inducible isoform of the 70 kDa heat shock protein (Hsp70) requires activation of the Heat Shock Transcription Factor (HSF1), possibly via its phosphorylation by intracellular protein kinases. However, phosphorylation of HSF1 (pHSF1), its localization and the potential fiber specific relationship between Hsp70 and pHSF1 in skeletal muscle following exercise (EX), is unknown. To address this issue, the plantaris (Plt) and the white portion of the vastus lateralis (WV) were harvested from adult male Sprague‐Dawley rats either 30mins or 24hr post‐EX (1hr treadmill run at 30m/min). These muscles were chosen for analysis because of previous reports indicating that the Plt is relatively refractory to exercise whereas the WV demonstrates a robust response. Indeed, western blots from the WV revealed an ∼4 fold increase in Hsp70 (24hr after EX) whereas Plt was unresponsive. Co‐localization of pHSF1 and Hsp70 with confocal microscopy, revealed strong nuclear staining of pHSF1 in those fibers inducing Hsp70 following EX. However, pHSF1 was also found in nuclei of fibers which did not demonstrate an increase in Hsp70. This suggests that nuclear localization of pHSF1 is essential but not sufficient to induce Hsp70 in skeletal muscle fibers post‐EX and supports a role for additional downstream regulation of this response. Supported by CIHR, CCT‐83029 and NSERC, 8170‐05 RGPIN.
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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) | 0.002 | 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".