Tumor Necrosis Factor-α Mediates Cardiac Remodeling and Ventricular Dysfunction After Pressure Overload State
Bibliographic record
Abstract
BACKGROUND: Pressure overload is accompanied by cardiac myocyte apoptosis, hypertrophy, and inflammatory/fibrogenic responses that lead to ventricular remodeling and heart failure. Despite incomplete understanding of how this process is regulated, the upregulation of tumor necrosis factor (TNF)-alpha after aortic banding in the myocardium is known. In the present study, we tested our hypothesis that TNF-alpha regulates the cardiac inflammatory response, extracellular matrix homeostasis, and ventricular hypertrophy in response to mechanical overload and contributes to ventricular dysfunction. METHODS AND RESULTS: C57/BL wild-type mice and TNF-knockout (TNF-/-) mice underwent descending aortic banding or sham operation. Compared with sham-operated mice, wild-type mice with aortic banding showed a significant increase in cardiac TNF-alpha levels, which coincided with myocyte apoptosis, inflammatory response, and cardiac hypertrophy in week 2 and a significant elevation in matrix metalloproteinase-9 activity and impaired cardiac function in weeks 2 and 6. Compared with wild-type mice with aortic banding, TNF-/- mice with aortic banding showed attenuated cardiac apoptosis, hypertrophy, inflammatory response, and reparative fibrosis. These mice also showed reduced cardiac matrix metalloproteinase-9 activity and improved cardiac function. CONCLUSIONS: Findings from the present study have suggested that TNF-alpha contributes to adverse left ventricular remodeling during pressure overload through regulation of cardiac repair and remodeling, leading to ventricular dysfunction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".