Neurodevelopment in Seizure‐prone and Seizure‐resistant Rat Strains: Recognizing Conflicts in Management
Bibliographic record
Abstract
Cytoarchitectural alterations during central nervous system (CNS) development are believed to underlie aberrations in brain morphology that lead to epilepsy. We have recently reported marked reductions in hippocampal and white matter volumes along with relative ventriculomegaly in a rat strain bred to be seizure-prone (FAST) compared to a strain bred to be seizure-resistant (SLOW) (Gilby et al., 2002, American Epilepsy Society 56th Annual Meeting). This study was designed to investigate deviations in gene expression during late-phase embryogenesis within the brains of FAST and SLOW rats. In this way, we hoped to identify molecular mechanisms operating differentially during neurodevelopment that might ultimately create the observed differences in brain morphology and/or seizure susceptibility. Using Superarray technology, we compared the expression level of 112 genes, known to play a role in neurodevelopment, within whole brains of embryonic day 21 (E21) FAST and SLOW rats. Results revealed that while most genes investigated showed near equivalent expression levels, both Apolipoprotein E (APOE) and the beta2 subunit of the voltage-gated sodium channel (SCN2beta) were significantly underexpressed in brains of the seizure-prone embryos. Currently, these transcripts have no known interactions during embryogenesis; however, they have both been independently linked to seizure disposition and/or neurodevelopmental aberrations leading to epilepsy. Thus, alterations in the timing and/or degree of expression for APOE and SCN2beta may be important to developmental cascades that ultimately give rise to the differing brain morphologies, behaviors, and/or seizure vulnerabilities that characterize these strains.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".