Actin Polymerization Status Regulates Tendon Homeostasis through Myocardin-Related Transcription Factor-A
Bibliographic record
Abstract
The actin cytoskeleton is a potent regulator of tenocyte homeostasis. However, the mechanisms by which actin regulates tendon homeostasis are not entirely known. This study examined the regulation of tenocyte molecule expression by actin polymerization via the globular (G-) actin-binding transcription factor, myocardin-related transcription factor-a (MRTF). We determined that decreasing the proportion of G-actin in tenocytes by treatment with TGFβ1 increases nuclear MRTF. These alterations in actin polymerization and MRTF localization coincided with favorable alterations to tenocyte gene expression. In contrast, latrunculin A increases the proportion of G-actin in tenocytes and reduces nuclear MRTF, causing cells to acquire a tendinosis-like phenotype. To parse out the effects of F-actin depolymerization from regulation by MRTF, we treated tenocytes with cytochalasin D. Similar to latrunculin A treatment, exposure of cells to cytochalasin D increases the proportion of G-actin in tenocytes. However, unlike latrunculin A treatment, cytochalasin D increases nuclear MRTF. Compared to latrunculin A treatment, cytochalasin D led to opposing effects on the expression of a subset of genes. The differential regulation of genes by latrunculin A and cytochalasin D suggests that actin signals through MRTF to regulate a specific subset of genes. By targeting the deactivation of MRTF through the inhibitor CCG1423, we verify that MRTF regulates Type I Collagen, Tenascin C, Scleraxis, and α-smooth muscle actin in tenocytes. Actin polymerization status is a potent regulator of tenocyte homeostasis through the modulation of several downstream pathways, including MRTF. Understanding the regulation of tenocyte homeostasis by actin may lead to new therapeutic interventions against tendinopathies, such as tendinosis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".