Refinement of inducible gene deletion in embryos of pregnant mice
Bibliographic record
Abstract
Abstract CreERT2‐mediated gene recombination is widely applied in developmental biology research. Activation of CreERT2 is typically achieved by injection of tamoxifen in an oily vehicle into the peritoneal cavity of mid‐gestation pregnant mice. This can be technically challenging and adversely impacts welfare. Here we characterize three refinements to this technique: Pipette feeding (not gavage) of tamoxifen, ex vivo CreERT2 activation in whole embryo culture and injection of cell‐permeable TAT‐Cre into Cre‐negative cultured embryos. We demonstrate that pipette feeding of tamoxifen solution to the mother on various days of gestation reliably activates embryonic CreERT2, illustrated here using β‐Actin CreERT2, Sox2 CreERT2, T CreERT2, and Nkx1.2 CreERT2. Pipette feeding of tamoxifen induces dose‐dependent recombination of Rosa26 mTmG reporters when administered at E8.5. Activation of two neuromesodermal progenitor‐targeting Cre drivers, T CreERT2, and Nkx1.2 CreERT2, produces comparable neuroepithelial lineage tracing. Dose‐dependent CreERT2 activation can also be achieved by brief exposure to 4OH‐tamoxifen in whole embryo culture, allowing temporal control of gene deletion and eliminating the need to treat pregnant mice. Rosa26 mTmG reporter recombination can also be achieved regionally by injecting TAT‐Cre into embryonic tissues at the start of culture. This allows greater spatial control over Cre activation than can typically be achieved with endogenous CreERT2, for example by injecting TAT‐Cre on one side of the midline. We hope that our description and application of these techniques will stimulate refinement of experimental methods involving CreERT2 activation for gene deletion and lineage tracing studies. Improved temporal (ex vivo treatment) and spatial (TAT‐Cre injection) control of recombination will also allow previously intractable questions to be addressed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".