The platelet‐derived growth factor receptor alpha promoter‐directed expression of cre recombinase in mouse placenta
Bibliographic record
Abstract
BACKGROUND: Numerous pathologies of pregnancy originate from placental dysfunction. It is essential to understand the functions of key genes in the placenta in order to discern the etiology of placental pathologies. A paucity of animal models that allow conditional and inducible expression of a target gene in the placenta is a major limitation for studying placental development and function. RESULTS: To study the platelet-derived growth factor receptor alpha (PDGFRα)-directed and tamoxifen-induced Cre recombinase expression in the placenta, PDGFRα-CreER mice were crossed with mT/mG dual-fluorescent reporter mice. The expression of endogenous membrane-localized enhanced green fluorescent protein (mEGFP) and/or dTomato in the placenta was examined to identify PDGFRα promoter-directed Cre expression. Pregnant PDGFRα-CreER;mT/mG mice were treated with tamoxifen at various gestational ages. Upon tamoxifen treatment, reporter protein mEGFP was observed in the junctional zone (JZ) and chorionic plate (CP). Furthermore, a single dose of tamoxifen was sufficient to induce the recombination. CONCLUSIONS: PDGFRα-CreER expression is restricted to the JZ and CP of mouse placentas. PDGFRα-CreER mice provide a useful tool to conditionally knock out or overexpress a target gene in these regions of the mouse placenta.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.004 | 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".