Transcriptional Control of Collagen I Gene Expression
Bibliographic record
Abstract
Cardiac fibrosis is the pathological remodeling of the extracellular matrix (ECM) in response to stresses such as pressure overload or injury. While initially adaptive, myocardial remodeling and subsequent fibrosis causes increased wall stiffness, arrhythmias, cardiac dysfunction, and eventually heart failure. Though the disease processes and origins may differ, excess deposition of fibrillar collagens type I and III characterizes fibrosis in the heart, lungs, kidneys, liver, and skin. Under normal physiological conditions, high tensile strength collagen fibers maintain cardiac structural integrity, connect individual cardiomyocytes, transmit contractile force, and resist deformation and rupture of the ventricle during systole. Various factors contribute to the development of fibrosis by altering expression of ECM genes, including increased synthesis of pro-inflammatory cytokines, alterations in the levels of circulating hormones, and mechanical strain resulting from ECM degradation. This review focuses on the transcriptional mechanisms governing expression of the major cardiac collagen, type I. Key cis- and trans-acting regulators of collagen I gene expression are discussed. Surprisingly, relatively few transcriptional regulators of collagen synthesis have been identified specifically in cardiac fibroblasts. However, key players have been identified in other tissue and cell types, and are important to consider in elucidating the molecular mechanisms underpinning collagen gene expression in the heart in both health and disease.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".