Chronic inhibition of cGMP‐specific phosphodiesterase 5 suppresses endoplasmic reticulum stress in heart failure
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Inhibition of the cGMP-specific phosphodiesterase 5 (PDE5) exerts profound beneficial effects on failing hearts. However, the mechanisms underlying the therapeutic effects of PDE5 inhibition on heart failure are unclear. The purpose of this study was to investigate whether PDE5 inhibition decreases endoplasmic reticulum (ER) stress, a key event in heart failure. EXPERIMENTAL APPROACH: Heart failure was induced by isoprenaline s.c. injection in Sprague-Dawley rats and transverse aortic constriction (TAC) in mice. PDE5 was inhibited with sildenafil. Heart function was detected by invasive pressure-volume analysis and echocardiography. ER stress markers were analysed by Western blotting. Apoptosis was measured by flow cytometric analysis. KEY RESULTS: PDE5 inhibition markedly attenuated isoprenaline-induced and TAC-induced cardiac hypertrophy and dysfunction, and reduced ER stress and apoptosis. Further, PDE5 inhibition with sildenafil largely prevented ER stress and reduced apoptosis in isoprenaline- or thapsigargin-treated cardiomyocytes. PKG inhibition markedly prevented the protective effects of sildenafil in vivo and in vitro. To further understand the mechanism of the effect of PDE5 inhibition on ER stress, we demonstrated that PDE5 inhibitor increased sarco-(endo)-plasmic reticulum Ca(2+) -ATPase activity via phosphorylation of phospholamban at Ser(16) . This may contribute to the attenuation of ER stress induced by PDE5 inhibition. CONCLUSION AND IMPLICATIONS: These results suggest that PDE5 inhibition can attenuate ER stress and improve cardiac function in vivo and in vitro. Suppression of ER stress by inhibiting PDE5 may contribute to the therapeutic effects on heart failure.
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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) | 0.001 | 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 | 0.001 |
| 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".