Transcriptional Regulation of a Contractile Gene by Mechanical Forces Applied through Integrins in Osteoblasts
Bibliographic record
Abstract
We examined mechanotranscriptional regulation of the contractile gene, alpha-smooth muscle actin (SMA), in osteoblastic cells. Tensile forces were applied through collagen-coated magnetite beads to ROS17/2.8 cells. These cells were desmin-, vimentin+ and expressed low levels of SMA. After force application (480 piconewton/cell), SMA protein and mRNA were increased but beta-actin was unchanged. Beads coated with bovine serum albumin or poly-L-lysine produced no change of SMA. In cells transiently transfected with plasmids containing the SMA promoter fused to beta-galactosidase or green fluorescent protein coding sequences, SMA promoter activity was increased by approximately 60% after 4 h of force, whereas control (Rous sarcoma virus) promoter activity was unaffected. Transfections with beta-galactosidase or green fluorescent protein reporter constructs showed that force-loaded cells exhibited higher beta-galactosidase activity than cells without force. Cytochalasin D and latrunculin B inhibited force-induced increases of SMA promoter activity. Deletion analyses showed that SMA promoter activity was increased approximately 70% after force with a minimal construct containing 155 bp upstream of the translation start site. The force effect on the SMA promoter was abrogated in cells transfected with CArG-B box mutants. Gel mobility shift analyses of nuclear extracts showed strong binding to the CArG-B motif after force. We conclude that the CArG-B box is a force-responsive element in the SMA promoter.
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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".