Transcriptional profiling of human osteoblast differentiation
Bibliographic record
Abstract
Osteoblast differentiation is a key aspect of bone formation and remodeling. To further our understanding of the differentiation process, we have developed a collection of conditionally immortalized adult human osteoblast cell lines representing discrete stages of differentiation. To evaluate changes in gene expression associated with differentiation, polyA((+)) RNA from pre-osteoblasts, early and late osteoblasts, and pre-osteocytes was subjected to gene chip analysis using the Affymetrix Hu6800 chip in conjunction with an Affymetrix custom chip enriched in bone and cartilage cDNAs. Overall, the expression of 47 genes was found to change threefold or more on both chips between the pre-osteoblastic and pre-osteocytic stages of differentiation. Many of the observed differences, including down-regulation of collagen type I and collagen-processing enzymes, reflect expected patterns and support the relevance of our results. Other changes have not been reported and offer new insight into the osteoblast differentiation process. Thus, we observed regulation of factors controlling cell cycle and proliferation, reflecting decreased proliferation, and increased apoptosis in pre-osteocytic cells. Elements maintaining the cytoskeleton, extracellular matrix, and cell-cell adhesion also changed with differentiation reflecting profound alterations in cell architecture associated with the differentiation process. We also saw dramatic down-regulation of several components of complement and other immune response factors that may be involved in recruitment and differentiation of osteoclasts. The decrease in this group of genes may provide a mechanism for controlling bone remodeling of newly formed bone. Our screen also identified several signaling proteins that may control osteoblast differentiation. These include an orphan nuclear receptor DAX1 and a small ras-related GTPase associated with diabetes, both of which increased with increasing differentiation, as well as a high mobility group-box transcription factor, SOX4, that was down-regulated during differentiation. In summary, our study provides a comprehensive transcriptional profile of human osteoblast differentiation and identifies several genes of potential importance in controlling differentiation of osteoblasts.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 0.001 |
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".