Identifying cellular signalling molecules in developmental disorders of the brain: Evidence from focal cortical dysplasia and tuberous sclerosis
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Bibliographic record
Abstract
AIMS: We understand little of the pathogenesis of developmental cortical lesions, because we understand little of the diversity of the cell types that contribute to the diseases or how those cells interact. We tested the hypothesis that cellular diversity and cell-cell interactions play an important role in these disorders by investigating the signalling molecules in the commonest cortical malformations that lead to childhood epilepsy, focal cortical dysplasia (FCD) and tuberous sclerosis (TS). METHODS: Transcriptional profiling clustered cases into molecularly distinct groups. Using gene expression data, we identified the secretory signalling molecules in FCD/TS and characterised the cell types expressing these molecules. We developed a functional model using organotypic cultures. RESULTS: We identified 113 up-regulated secretory molecules in FCDIIB/TS. The top 12 differentially expressed genes (DEGs) were validated by immunohistochemistry. This highlighted two molecules, Chitinase 3-like protein 1 (CHI3L1) and C-C motif chemokine ligand 2 (CCL2) (MCP1) that were expressed in a unique population of small cells in close proximity to balloon cells (BC). We then characterised these cells and developed a functional model in organotypic slice cultures. We found that the number of CHI3L1 and CCL2 expressing cells decreased following inhibition of mTOR, the main aberrant signalling pathway in TS and FCD. CONCLUSIONS: Our findings highlight previously uncharacterised small cell populations in FCD and TS which express specific signalling molecules. These findings indicate a new level of diversity and cellular interactions in cortical malformations and provide a generalisable approach to understanding cell-cell interactions and cellular heterogeneity in developmental neuropathology.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it