Early-life immune activation is a vulnerability factor for adult epileptogenesis in neurofibromatosis type 1 in male mice
Bibliographic record
Abstract
Introduction Patients with Neurofibromatosis type 1 (NF1), the most common neurocutaneous disorder, can develop several neurological manifestations that include cognitive impairments and epilepsy over their lifetime. It is unclear why certain patients with NF1 develop these conditions while others do not. Early-life immune activation promotes later-life seizure susceptibility, neurocognitive impairments, and leads to spontaneous seizures in some animal models of neurodevelopmental disorders, but the central nervous system immune profile and the enduring consequences of early-life immune activation on the developmental trajectory of the brain in NF1 have not yet been explored. We tested the hypothesis that early-life immune activation promotes the development of spatial memory impairments and epileptogenesis in a mouse model of NF1. Methods Male wild-type (WT) and Nf1+/− mice received systemic lipopolysaccharide (LPS) or saline at post-natal day 10 and were assessed in adulthood for learning and memory deficits in the Barnes maze and underwent EEG recordings to look for spontaneous epileptiform abnormalities and susceptibility to challenge with pentylenetetrazole (PTZ). Results Whereas early-life immune activation by a single injection of LPS acutely elicited a comparable brain cytokine signature in WT and Nf1+/− mice, it promoted spontaneous seizure activity in adulthood only in the Nf1+/− mice. Early-life immune activation affected susceptibility to PTZ-induced seizures similarly in both WT and Nf1+/−mice. There was no effect on spatial learning and memory regardless of mouse genotype. Discussion Our findings suggest second-hit environmental events such as early-life immune activation may promote epileptogenesis in the Nf1+/− mouse and may be a risk-factor for NF1-associated epilepsy.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".