The gene expression profile induced by Wnt 3a in NIH 3T3 fibroblasts
Bibliographic record
Abstract
Wnt proteins play important roles in regulating cell differentiation, proliferation and polarity. Wnts have been proposed to play roles in tissue repair and fibrosis, yet the gene expression profile of fibroblasts exposed to Wnts has not been examined. We use Affymetrix genome-wide expression profiling to show that a 6-h treatment of fibroblasts of Wnt3a results in the induction of mRNAs encoding known Wnt targets such as the fibrogenic pro-adhesive molecule connective tissue growth factor (CTGF, CCN2). Wnt3a also induces mRNAs encoding potent pro-fibrotic proteins such as TGFbeta and endothelin-1 (ET-1). Moreover, Wnt3a promotes genes associated with cell adhesion and migration, vasculature development, cell proliferation and Wnt signaling. Conversely, Wnt3a suppresses gene associated with skeletal development, matrix degradation and cell death. Results were confirmed using real-time polymerase chain reaction of cells exposed to Wnt3a and Wnt10b. These results suggest that Wnts induce genes promoting fibroblast differentiation towards angiogenesis and matrix remodeling, at the expense of skeletal development.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".