Faculty Opinions recommendation of Investigating Developmental and Epileptic Encephalopathy Using Drosophila melanogaster.
Bibliographic record
Abstract
Developmental and epileptic encephalopathies (DEEs) are the spectrum of severe epilepsies characterized by early-onset, refractory seizures occurring in the context of developmental regression or plateauing. Early infantile epileptic encephalopathy (EIEE) is one of the earliest forms of DEE, manifesting as frequent epileptic spasms and characteristic electroencephalogram findings in early infancy. In recent years, next-generation sequencing approaches have identified a number of monogenic determinants underlying DEE. In the case of EIEE, 85 genes have been registered in Online Mendelian Inheritance in Man as causative genes. Model organisms are indispensable tools for understanding the in vivo roles of the newly identified causative genes. In this review, we first present an overview of epilepsy and its genetic etiology, especially focusing on EIEE and then briefly summarize epilepsy research using animal and patient-derived induced pluripotent stem cell (iPSC) models. The Drosophila model, which is characterized by easy gene manipulation, a short generation time, low cost and fewer ethical restrictions when designing experiments, is optimal for understanding the genetics of DEE. We therefore highlight studies with Drosophila models for EIEE and discuss the future development of their practical use. PMID: 32899411 Funding information This work was supported by: Japan Society for the Promotion of Science, Grant ID: JP18K07796
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.138 | 0.074 |
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".