mTOR Pathway Somatic Pathogenic Variants in Focal Malformations of Cortical Development
Bibliographic record
Abstract
Background and Objectives: Somatic and germline pathogenic variants in genes of the mammalian target of rapamycin (mTOR) signaling pathway are a common mechanism underlying a subset of focal malformations of cortical development (FMCDs) referred to as mTORopathies, which include focal cortical dysplasia (FCD) type II, subtypes of polymicrogyria, and hemimegalencephaly. Our objective is to screen resected FMCD specimens with mTORopathy features on histology for causal somatic variants in mTOR pathway genes, describe novel pathogenic variants, and examine the variant distribution in relation to neuroimaging, histopathologic classification, and clinical outcomes. Methods: variant. Results: (c.2802-1G>C). Discussion: The AAF of somatic pathogenic variants correlated with the topographic distribution, histopathology, and postsurgical outcomes. Moreover, cortical regions with absent histologic FCD features had negligible or undetectable pathogenic variant loads. By contrast, specimens with frank histologic abnormalities had detectable pathogenic variant loads, which raises important questions as to whether there is a tolerable variant threshold and whether surgical margins should be clean, as performed in tumor resections. In addition, we describe 2 novel pathogenic variants, expanding the mTORopathy genetic spectrum. Although most pathogenic somatic variants are located at mutation hotspots, screening the full-coding gene sequence remains necessary in a subset of patients.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".