Leveraging mechanobiology: Identifying mechanotransducers with potential applications for tendon repair
Bibliographic record
Abstract
Tendons are collagen-rich tissues that are necessary for movement and, as such, are exposed to mechanical forces. Mechanical loading impacts tendon formation, homeostasis and injury. Frequent injury and poor healing of tendon is a major clinical issue. An improved understanding of how tendon cells respond to mechanical forces is needed to advance new therapies to treat tendon injuries and limit degeneration caused by aberrant mechanical loading. In this review, we highlight recent discoveries in how mechanical stimulation impacts tendon and enthesis formation during development, as well as tendon maintenance and degradation during adulthood. We focus on understanding the cell-level mechanotransduction mechanisms, which include calcium signalling, activation of specific cell receptors and ion channels, and the effect on primary cilia and other downstream cell signalling pathways. These recently identified mechanotransducers in tendon cells show promise as future therapeutic targets, which can be leveraged for tendon healing.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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) | 0.000 | 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".