Identification of a Putative Autocrine Bone Morphogenetic Protein-Signaling Pathway in Human Ovarian Surface Epithelium and Ovarian Cancer Cells
Bibliographic record
Abstract
Bone morphogenetic proteins (BMPs) are members of the TGFbeta superfamily of cytokines that are involved in development, differentiation, and disease. In an analysis of normal ovarian surface epithelium (OSE) and ovarian cancer (OC) cells, we observed BMP4 mRNA expression and found that primary OC cells produce mature BMP4. In addition, each member of the downstream signaling pathway was expressed in primary OSE and OC cells. Smad1 was phosphorylated and underwent nuclear translocation in normal OSE and OC cells upon treatment with BMP4. Interestingly, the BMP target genes ID1 and ID3 were up-regulated 10- to 15-fold in primary OC cells, compared with a 2- to 3-fold increase in normal OSE. The growth of several primary OC cells was relatively unaltered by BMP4 treatment; however, long-term BMP4 treatment of primary OC cells resulted in decreased cell density as well as increased cell spreading and adherence. These data demonstrate the existence and putative function of BMP signaling in normal OSE and OC cells, and thus the continued examination of BMP4 signaling in the regulation of these two processes will be critical to further our current understanding of the role of BMP biology in OC pathogenesis.
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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) | 0.002 | 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".