Divergent phenotypes in germline versus conditional mutant mouse models of Sifrim-Hitz-Weiss Syndrome
Bibliographic record
Abstract
Abstract Chromatin remodellers are among the most important risk genes associated with neurodevelopmental disorders (NDDs), however, their functions during brain development are not fully understood. Here, we focused on Sifrim-Hitz-Weiss Syndrome (SIHIWES) – a brain overgrowth/intellectual disability disorder caused by mutations in the CHD4 chromodomain helicase gene. We utilized mouse genetics to excise the Chd4 ATPase/helicase domain – either in the germline, or conditionally in the developing telencephalon. Conditional heterozygotes exhibited little change in cortical size and cellular composition, and had only subtle behavioral phenotypes. Telencephalon-specific conditional knockouts had marked reductions in cortical growth, reduced numbers of upper-layer neurons, and exhibited alterations in anxiety and repetitive behaviors. Despite the fact that germline heterozygotes exhibited comparable growth defects, they were unaffected in these behaviors, but instead exhibited female-specific alterations in learning and memory. These data reveal unexpected phenotypic divergence arising from differences in the spatiotemporal deployment of loss-of-function manipulations, underscoring the importance of context in chromatin remodeller function during neurodevelopment. Graphical Abstract.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".