A <i>Pdgf‐c<sup>CreERT2</sup></i> knock‐in mouse model for tracing PDGF‐C cell lineages during development
Bibliographic record
Abstract
Summary PDGF‐C, a member of the platelet‐derived growth factor (PDGF) family, plays important roles in the development of craniofacial structures, the neural system, the vascular system, and tumors. PDGF‐C could also be required for the regulation of certain types of stem or progenitor cells as suggested by its expression in the regions where these cells are located. To further characterize the role of PDGF‐C in development, we generated a Pdgf‐cCreERT2 mouse strain, in which a tamoxifen‐inducible Cre (CreERT2) cDNA was specifically targeted into the Pdgf‐c genomic locus and controlled by the endogenous Pdgf‐c regulatory elements. We also showed that Cre activity in this mouse strain could be specifically induced by tamoxifen, which allowed the fate of PDGF‐C‐expressing cells to be traced at various stages of development. Using this model system, we demonstrated for the first time that PDGF‐C‐expressing cells could be multipotent, generating multiple cell lineages required for the formation of the cerebellum. Therefore, the Pdgf‐cCreERT2 mouse strain generated in this study will be a valuable transgenic tool for exploring the function of PDGF‐C in development and stem cell biology.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".