Intracellular Signaling of Cardiac Fibroblasts
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Long regarded as a mere accessory cell for the cardiomyocyte, the cardiac fibroblast is now recognized as a critical determinant of cardiac function in health and disease. A recent renaissance in fibroblast-centered research has fostered a better understanding than ever before of the biology of fibroblasts and their contractile counterparts, myofibroblasts. While advanced methodological approaches, including transgenics, lineage fate mapping, and improved cell marker identification have helped to facilitate this new work, the primary driver is arguably the contribution of myofibroblasts to cardiac pathophysiology including fibrosis and arrhythmogenesis. Fibrosis is a natural sequel to numerous common cardiac pathologies including myocardial infarction and hypertension, and typically exacerbates cardiovascular disease and progression to heart failure, yet no therapies currently exist to specifically target fibrosis. The regulatory processes and intracellular signaling pathways governing fibroblast and myofibroblast behavior thus represent important points of inquiry for the development of antifibrotic treatments. While steady progress is being made in uncovering the signaling pathways specific for cardiac fibroblast function (including proliferation, phenotype conversion, and matrix synthesis), much of what is currently known of fibroblast signaling mechanisms is derived from noncardiac fibroblast populations. Given the heterogeneity of fibroblasts across tissues, this dearth of information further underscores the need for progress in cardiac fibroblast biological research.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it