Emerging evidence for the role of cardiotrophin-1 in cardiac repair in the infarcted heart
Bibliographic record
Abstract
Ischemic heart disease is the most common cause of mortality worldwide. Cardiac fibroblasts and myofibroblasts, i.e., the hypersecretory, muscular, and contractile fibroblastic phenotype variant, play an important role in myocardial healing and are responsible for accumulation of collagen in the infarct scar as well as in viable myocardium. Thus, cardiac fibroblasts and myofibroblasts directly contribute to cardiac stiffness, altered performance, and ultimately to the onset of systolic and diastolic heart failure. Cardiotrophin-1 (CT-1) is a member of the IL-6 superfamily and is elevated in the serum of patients with ischemic heart disease and valvular heart disease; it is also known to induce cardiomyocyte hypertrophy in vitro. The recent, burgeoning awareness of the functions of IL-6 superfamily of cytokines within cardiovascular diseases predicates this summary of CT-1's effect in cardiac wound healing, and particularly after the induction of myocardial infarction. Further, we summarize recent results of cardiac CT-1 expression post-myocardial infarction (post-MI) as well as the effect of CT-1 on cultured primary adult rat cardiac fibroblasts with respect to proliferation and collagen secretion. It would appear that CT-1 plays an important and heretofore largely unrecognized role in infarct scar formation and angiogenesis in the rat model of chronic MI. Further work is required to determine factors that induce CT-1 expression, its interplay with other mediators of cardiac infarct wound healing in the setting of acute cardiac ischemia and chronic post-MI heart failure, and ultimately whether it confers a beneficial effect or contributes to maladaptive cardiac fibrosis.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".