hsp70 mRNA temporal localization in rat skeletal myofibers and blood vessels post-exercise
Bibliographic record
Abstract
Rapid transcription of the survival transcript, inducible heat shock protein 70 (hsp70), is critical for mounting cytoprotection against severe cellular stress, like elevated temperature. Previous investigations have demonstrated that exercise-induced expression of Hsp70 protein occurs in a fiber-specific pattern; however, the activation pattern of hsp70 mRNA expression remains unclear in skeletal muscle. Consequentially, the temporal localization of hsp70 mRNA was characterized via in situ hybridization (ISH) experiments examining fast-muscle, white vastus: 1, 3, 10, and 24 h after a single bout of intense treadmill running (1 h, 30 m/min, 6% grade) in rats. The role that the physiologic temperature stress associated with exercise (raising core body temperature to 40.0°C for 15 min (HS-40.0°C)) might play in inducing hsp70 mRNA expression was also explored. In skeletal muscle myofibers (SkM), hsp70 mRNA ISH signal was observed to be concentrated in a punctate manner that was associated with nuclei post-exercise. HS-40°C treatment produced minimal detectable hsp70 mRNA ISH signal in SkM. In large intermyofibrillar blood vessels (BV), peak hsp70 mRNA signal, distributed throughout the vessel wall, was observed 1 h post-exercise. In BV, no differences in hsp70 mRNA signal were observed between HS-40°C and EX-1 h. Results indicate that the majority of hsp70 mRNA is retained in a perinuclear localization in SkM post-exercise. They further suggest a muscle-type specific time course for peak hsp70 mRNA expression. This investigation suggests that the physiologic rise in core temperature associated with exercise per se is not the key stimulus responsible for inducing hsp70 mRNA transcription in SkM.
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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 | 0.001 | 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 | 0.000 |
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".