Cathepsin‐L Ameliorates Cardiac Hypertrophy Through Activation of the Autophagy–Lysosomal Dependent Protein Processing Pathways
Bibliographic record
Abstract
BACKGROUND: Autophagy is critical in the maintenance of cellular protein quality control, the final step of which involves the fusion of autophagosomes with lysosomes. Cathepsin-L (CTSL) is a key member of the lysosomal protease family that is expressed in the murine and human heart, and it may play an important role in protein turnover. We hypothesized that CTSL is important in regulating protein processing in the heart, particularly under pathological stress. METHODS AND RESULTS: Phenylephrine-induced cardiac hypertrophy in vitro was more pronounced in CTSL-deficient neonatal cardiomyocytes than in in controls. This was accompanied by a significant accumulation of autophagosomes, increased levels of ubiquitin-conjugated protein, as well as impaired protein degradation and decreased cell viability. These effects were partially rescued with CTSL1 replacement via adeno-associated virus-mediated gene transfer. In the in vivo murine model of aortic banding (AB), a deficiency in CTSL markedly exacerbated cardiac hypertrophy, worsened cardiac function, and increased mortality. Ctsl(-/-) AB mice demonstrated significantly decreased lysosomal activity and increased sarcomere-associated protein aggregation. Homeostasis of the endoplasmic reticulum was also altered by CTSL deficiency, with increases in Bip and GRP94 proteins, accompanied by increased ubiquitin-proteasome system activity and higher levels of ubiquitinated proteins in response to AB. These changes ultimately led to a decrease in cellular ATP production, enhanced oxidative stress, and increased cellular apoptosis. CONCLUSIONS: Lysosomal CTSL attenuates cardiac hypertrophy and preserves cardiac function through facilitation of autophagy and proteasomal protein processing.
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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) | 0.000 | 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 | 0.001 |
| 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".