Molecular and mechano-biology of collagen gel contraction mediated by human MG-63 cells: involvement of specific intracellular signaling pathways and the cytoskeleton
Bibliographic record
Abstract
Culture of human osteoblast-like MG-63 cells within collagen gels results in the generation of intrinsic stress. Release of such collagen gels from attachment results in gel contraction and enhanced MMP-1, MMP-3, and alpha2 integrin mRNA levels. To understand the potential role of microtubules and signaling pathways involved in MG-63 cell-mediated contraction and gene expression, cells were cultured in collagen gels. After 24 h collagen gels were released, then immediately treated with nocodazole or specific protein kinase inhibitors. Contraction was assessed, RNA isolated, and real-time PCR analysis performed. Treatment with high concentrations of a microtubule depolymerization agent, nocodazole, enhanced early contraction and led to elevated mRNA levels for MMP-3, whereas low concentrations inhibited contraction at later time points and did not affect mRNA levels. ROCK inhibitor treatment (Y27632) inhibited collagen gel contraction and led to depressed mRNA levels. The ERK1/2 inhibitor U0126 did not affect contraction, but treatment led to depressed MMP-1, MMP-3, and alpha2 mRNA levels. The p38MAPK inhibitor SB203580 modestly affected contraction, but did not affect mRNA levels. These results suggest the potential role of cytoskeletal integrity and multiple kinase signaling pathways in specific bone-remodeling events.
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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) | 0.001 | 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".