Induction of Protein Deletion Through <em>In Utero</em> Electroporation to Define Deficits in Neuronal Migration in Transgenic Models
Bibliographic record
Abstract
Genetic deletion using the Cre-Lox system in transgenic mouse lines is a powerful tool used to study protein function. However, except in very specific Cre models, deletion of a protein throughout a tissue or cell population often leads to complex phenotypes resulting from multiple interacting mechanisms. Determining whether a phenotype results from disruption of a cell autonomous mechanism, which is intrinsic to the cell in question, or from a non-cell autonomous mechanism, which would result from impairment of that cell's environment, can be difficult to discern. To gain insight into protein function in an in vivo context, in utero electroporation (IUE) enables gene deletion in a small subset of cells within the developing cortex or some other selected brain region. IUE can be used to target specific brain areas, including the dorsal telencephalon, medial telencephalon, hippocampus, or ganglionic eminence. This facilitates observation of the consequences of cell autonomous gene deletion in the context of a healthy environment. The goal of this protocol is to show how IUE can be used to analyze a defect in radial migration in a floxed transgenic mouse line, with an emphasis on distinguishing between the cell autonomous and non-cell autonomous effects of protein deletion. By comparing the phenotype resulting from gene deletion within the entire cortex versus IUE-mediated gene deletion in a limited cell population, greater insight into protein function in brain development can be obtained than by using either technique in isolation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".