Scleraxis is a mechanoresponsive regulator of the cardiac myofibroblast phenotype
Bibliographic record
Abstract
Cardiac fibrosis is the excess deposition of myocardial extracellular matrix components, which increases tissue stiffness and heterogeneity, causing impaired diastolic/systolic function and arrhythmias, and eventually leading to heart failure and death. There are no available treatments for cardiac fibrosis. Myofibroblasts mediate fibrosis, and are characterized by hypersynthesis of collagens, decreased migration, and increased α-smooth muscle actin, which is incorporated into stress fibers, imparting contractility. Scleraxis is a transcriptional regulator of collagen-rich tissues, increased in response to the same stimuli that drive the myofibroblast phenotype, such as cyclic stretch. We show that Scleraxis mediates the conversion of cardiac fibroblasts to myofibroblasts, by increasing myofibroblast marker expression and contraction, and decreasing migration. Additionally, a proximal 1500 bp human SCLERAXIS promoter is activated by stretch and is responsive to transforming growth factor-β1. Thus, Scleraxis is a specific mechanoresponsive regulator of the myofibroblast, representing a novel target for the treatment of cardiac fibrosis.
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) | 0.008 | 0.001 |
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".