Coordinate Expression of Novel Genes During Osteoblast Differentiation
Bibliographic record
Abstract
To achieve new insights into the coordinate regulation of gene expression during osteoblast differentiation we utilized an approach involving global analysis of gene expression to obtain the identities of messenger RNAs (mRNAs) expressed using an established in vitro model of bone development. MC3T3-E1 osteoblast-like cells were induced to differentiate by the addition of beta-glycerophosphate (beta-GP) and ascorbic acid. RNA samples derived from induced and uninduced control MC3T3-E1 cells were used to prepare complementary DNA (cDNA) for serial analysis of gene expression (SAGE). A preliminary SAGE database was produced and used to prepare a hybridization array to further facilitate the characterization of changes in the expression levels of 92 of the SAGE-mRNA assignments after induction of osteoblast differentiation, specifically after 6 days and 14 days of ascorbate treatment. SAGE-array hybridization analysis revealed coordinate induction of a number of mRNAs including Rab24, calponin, and calcyclin. Levels of MSY-1, SH3P2, fibronectin, alpha-collagen, procollagen, and LAMPI mRNAs, present at day 6 postinduction, were markedly reduced by day 14 postinduction. A number of unanticipated and potentially important developmental genes were identified including the transforming growth factor beta (TGF-beta) superfamily member Lefty-1. Lefty-1 transcript and translation product were found to be induced during the course of MC3T3-E1 cell differentiation. We present evidence, using transient transfection and antibody neutralization approaches, that Lefty-1 modulates the induction of alkaline phosphatase (ALP) after treatment of MC3T3-E1 cells with ascorbate and beta-GP. These data should provide useful new information for future analysis of transcriptional events in osteoblast differentiation and mineralization.
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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 | 0.001 | 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".