Hydrostatic pressures promote initial osteodifferentiation with ERK1/2 not p38 MAPK signaling involved
Bibliographic record
Abstract
Mechanical stress has been considered to be an important factor in bone remodeling and recent publications have shown that mechanical stress can regulate the direction of stem cell differentiation. The exact mechanobiological effects of pressure on initial osteodifferentiation of mesenchymal stem cells (MSCs) have not been determined. These mechanobiological mechanisms may be important both in biological responses during orthodontic tooth movement and in the development of new mechanobiological strategies for bone tissue engineering. We investigated the effects of static (23 kPa) or dynamic (10-36 kPa and at 0.25 Hz frequency) pressure on MSCs during the initial process of osteoblastic differentiation following treatment with dexamethasone, beta-glycerophosphate and ascorbic acid (for 0, 3, and 7 days, respectively). The following parameters were analyzed in the ALPase activity, mRNA level of osteogenesis-related transcription factors (Runx2, Osterix, Msx2, and Dlx5), and phosphorylation of ERK1/2 and p38 MAPK. The results showed that exposure to either dynamic or static pressure induced initial osteodifferentiation of MSCs. Particularly both types of pressure strongly stimulated the expression of osteogenesis-related factors of totally undifferentiated MSCs. ERK signaling participated in early osteodifferentiation and played a positive but non-critical role in mechanotransduction, whereas p38 MAPK was not involved in this process. Furthermore, the undifferentiated MSCs were highly sensitive to pressure exposure; whereas after osteoinduction MSCs reacted to pressure in a lower response state. The findings should lead to further studies to unveil the complex initial biological mechanisms of bone remodeling and regeneration upon mechanical stimuli.
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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 | 0.000 | 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) | 0.003 | 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 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".