TNF‐α‐mediated signal transduction pathway is a major determinant of apoptosis in dilated cardiomyopathy
Bibliographic record
Abstract
Although J2N-k strain of cardiomyopathic hamsters is an excellent model of dilated cardiomyopathy, the presence and mechanisms of apoptosis in the hearts of these genetically modified animals have not been investigated. This study examined the hypothesis that cardiac dysfunction and apoptosis in the cardiomyopathic hamsters were associated with tumour necrosis factor-alpha (TNF-alpha)-mediated signalling pathway involving the activation of some pro-apoptotic proteins and/or deactivation of some antiapoptotic proteins. Echocardiographic assessment of 31-week-old hamsters indicated an increase in the internal dimension of the left ventricle as well as decreases in the ejection fraction, fractional shortening and cardiac output without any evidence of cardiac hypertrophy. Increased level of TNF-alpha and apoptosis in cardiomyopathic hearts were accompanied by increased protein content for protein kinase C (PKC) -alpha and -epsilon isozymes as well as caspases 3 and 9. Phosphorylated protein content for p38 MAPK and NF kappaB was increased whereas that for Erk1/2, BAD and Bcl-2 was decreased in cardiomyopathic hearts. These results support the view that TNF-alpha and PKC isozymes may promote apoptosis due to the activation of p38 MAPK and deactivation of Erk1/2 pathways, and these changes may contribute toward the development of cardiac dysfunction in dilated cardiomyopathy.
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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) | 0.001 | 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".