<i>ACTA2</i>-Related Dysgyria: An Under-Recognized Malformation of Cortical Development
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Pathogenic variants in the ACTA2 gene cause a distinctive arterial phenotype that has recently been described to be associated with brain malformation. Our objective was to further characterize gyral abnormalities in patients with ACTA2 pathogenic variants as per the 2020 consensus recommendations for the definition and classification of malformations of cortical development. MATERIALS AND METHODS: We performed a retrospective, multicentric review of patients with proved ACTA2 pathogenic variants, searching for the presence of malformations of cortical development. A consensus read was performed for all patients, and the type and location of cortical malformation were noted in each. The presence of the typical ACTA2 arterial phenotype as well as demographic and relevant clinical data was obtained. RESULTS: We included 13 patients with ACTA2 pathogenic variants (Arg179His mutation, n = 11, and Arg179Cys mutation, n = 2). Ninety-two percent (12/13) of patients had peri-Sylvian dysgyria, 77% (10/13) had frontal dysgyria, and 15% (2/13) had generalized dysgyria. The peri-Sylvian location was involved in all patients with dysgyria (12/12). All patients with dysgyria had a characteristic arterial phenotype described in ACTA2 pathogenic variants. One patient did not have dysgyria or the characteristic arterial phenotype. CONCLUSIONS: Dysgyria is common in patients with ACTA2 pathogenic variants, with a peri-Sylvian and frontal predominance, and was seen in all our patients who also had the typical ACTA2 arterial phenotype.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".