Targeted delivery of an Mecp2 transgene to forebrain neurons improves the behavior of female Mecp2-deficient mice
Bibliographic record
Abstract
Rett syndrome is an X-linked neurological condition affecting almost exclusively girls that is caused by mutations of the MECP2 gene. Recent studies have shown that transgenic delivery of MeCP2 function to Mecp2-deficient male mice can improve their Rett-like behavior. However, as the brain of a Rett girl contains a mosaic of MeCP2 expressing and non-expressing neurons, and the over-expression of MeCP2 in neurons can induce a severe progressive neurological phenotype, testing whether functional rescue can be achieved by gene re-introduction strategies in a female model of Rett syndrome is warranted. To address this, we generated transgenic mice expressing an epitope-tagged Mecp2 transgene in forebrain neurons. These mice over-express MeCP2 protein at about 1.6 times normal levels in cortex and develop impaired motor behavior by 9-12 months of age. To test whether forebrain-targeted MeCP2 restoration would improve behavior in female Mecp2(-/+) mice, we crossed these transgenics with Mecp2(-/+) mice and examined the behavioral properties of the female rescue mice for 1 year. These assessments revealed that the diminished rearing activity, impaired mobility and the diminished locomotive activity of female Mecp2(-/+) mice were restored to wild-type levels in the rescue mice. These results show that improvement of Rett-like behavior can be achieved in Mecp2(-/+) females by targeted gene re-introduction without inducing deficits relating to MeCP2 over-expression.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".