Autophagy is altered in skeletal and cardiac muscle of spontaneously hypertensive rats
Bibliographic record
Abstract
AIM: Autophagy is a subcellular degradation mechanism important for muscle maintenance. Hypertension induces well-characterized pathological changes to the heart and is associated with impaired function and increased apoptotic signalling in skeletal muscle. We examined whether essential hypertension affects several autophagy markers in skeletal and cardiac muscle. METHODS: Immunoblotting and qRT-PCR were used to measure autophagy-related proteins/mRNA in multiple skeletal muscles as well as left ventricle (LV) of spontaneously hypertensive rats (SHR) and normotensive Wistar-Kyoto rats (WKY). RESULTS: Skeletal muscles of hypertensive rats had decreased (P < 0.01) cross-sectional area of type I fibres (e.g. soleus WKY: 2952.9 ± 64.4 μm(2) vs. SHR: 2579.9 ± 85.8 μm(2)) and a fibre redistribution towards a 'fast' phenotype. Immunoblot analysis revealed that some SHR skeletal muscles displayed a decreased LC3II/I ratio (P < 0.05), but none showed differences in p62 protein. LC3 and LAMP2 mRNA levels were increased approx. 2-3-fold in all skeletal muscles (P < 0.05), while cathepsin activity, cathepsin L mRNA and Atg7 protein were increased 16-17% (P < 0.01), 2-3-fold (P < 0.05) and 29-49% (P < 0.01), respectively, in fast muscles of hypertensive animals. Finally, protein levels of BAG3, a marker of chaperone-assisted selective autophagy, were 18-25% lower (P < 0.05) in SHR skeletal muscles. In the LV of SHR, LC3I and p62 protein were elevated 34% (P < 0.05) and 47% (P < 0.01), respectively. Furthermore, p62 mRNA was 68% higher (P < 0.05), while LAMP2 mRNA was 45% lower (P < 0.05), in SHR cardiac muscle. There was no difference in Beclin1, Atg7, Bnip3 or BAG3 protein in the LV between strains. CONCLUSION: These results suggest that autophagy is altered in skeletal and cardiac muscle during hypertension.
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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".