The role of mechanical signals in regulating chondrogenesis and osteogenesis of mesenchymal stem cells
Bibliographic record
Abstract
It is becoming increasingly clear that mesenchymal stem cell (MSC) differentiation is regulated by mechanical signals. Mechanical forces generated intrinsically within the cell in response to its extracellular environment, and extrinsic mechanical signals imposed upon the cell by the extracellular environment, play a central role in determining MSC fate. This article reviews chondrogenesis and osteogenesis during skeletogenesis, and then considers the role of mechanics in regulating limb development and regenerative events such as fracture repair. However, observing skeletal changes under altered loading conditions can only partially explain the role of mechanics in controlling MSC differentiation. Increasingly, understanding how epigenetic factors, such as the mechanical environment, regulate stem cell fate is undertaken using tightly controlled in vitro models. Factors such as bioengineered surfaces, substrates, and bioreactor systems are used to control the mechanical forces imposed upon, and generated within, MSCs. From these studies, a clearer picture of how osteogenesis and chondrogenesis of MSCs is regulated by mechanical signals is beginning to emerge. Understanding the response of MSCs to such regulatory factors is a key step towards understanding their role in development, disease and regeneration.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".