Scleraxis and fibrosis in the pressure-overloaded heart
Bibliographic record
Abstract
AIMS: In response to pro-fibrotic signals, scleraxis regulates cardiac fibroblast activation in vitro via transcriptional control of key fibrosis genes such as collagen and fibronectin; however, its role in vivo is unknown. The present study assessed the impact of scleraxis loss on fibroblast activation, cardiac fibrosis, and dysfunction in pressure overload-induced heart failure. METHODS AND RESULTS: Scleraxis expression was upregulated in the hearts of non-ischemic dilated cardiomyopathy patients, and in mice subjected to pressure overload by transverse aortic constriction (TAC). Tamoxifen-inducible fibroblast-specific scleraxis knockout (Scx-fKO) completely attenuated cardiac fibrosis, and significantly improved cardiac systolic function and ventricular remodelling, following TAC compared to Scx+/+ TAC mice, concomitant with attenuation of fibroblast activation. Scleraxis deletion, after the establishment of cardiac fibrosis, attenuated the further functional decline observed in Scx+/+ mice, with a reduction in cardiac myofibroblasts. Notably, scleraxis knockout reduced pressure overload-induced mortality from 33% to zero, without affecting the degree of cardiac hypertrophy. Scleraxis directly regulated transcription of the myofibroblast marker periostin, and cardiac fibroblasts lacking scleraxis failed to upregulate periostin synthesis and secretion in response to pro-fibrotic transforming growth factor β. CONCLUSION: Scleraxis governs fibroblast activation in pressure overload-induced heart failure, and scleraxis knockout attenuated fibrosis and improved cardiac function and survival. These findings identify scleraxis as a viable target for the development of novel anti-fibrotic treatments.
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How this classification was reachedexpand
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 | 0.002 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".