Correlations between the level of antibody against peptide of glutamate receptor NR3B subunit in the CSF and cognitive comorbidities of patients with epilepsy.
Bibliographic record
Abstract
OBJECTIVE: Autoimmune epilepsy is an under-recognized condition, and the mechanisms of antibody-mediated epileptogenesis are unknown. The N-methyl-D-aspartate (NMDA) receptor subunit 3 peptide B (NR3B) modulates Mg2+ sensitivity and Ca2+ mobilization of glutamate responses in the central nervous system (CNS). The levels of antibodies against NR3B (NR3B Ab's) in the cerebrospinal fluid (CSF) and the correlations between NR3B Ab's and cognitive comorbidities of epilepsy patients remain unclear. PATIENTS AND METHODS: CSF samples were collected from 36 patients with consecutive epilepsy and 17 healthy controls. The levels of NR3B Ab's in the CSF were measured by ELISA. The cognitive function was assessed by Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE). RESULTS: The results showed that the levels of NR3B Ab's were significantly higher in patients with epilepsy than those in the controls (p<0.01). Thirteen of 36 patients had higher levels of NR3B Ab's exceeding mean+ 2SD of all patients, and the scores of MMSE and MoCA of these 13 patients were significantly lower than the other 23 patients and controls (p<0.01; p<0.001). However, there were no significant differences in the scores of MMSE and MoCA between the 23 patients and the controls. Correlation analysis indicated a significant negative correlation between the levels of NR3B Ab's and the scores of MMSE (correlation coefficient: r=-0.543; p<0.01) or the scores of MoCA (correlation coefficient: r=-0.548; p<0.01). CONCLUSIONS: We suggest that some patients with epilepsy may have immune process after onset and the presence of NR3B Ab's may be associated with cognitive comorbidities in patients with 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".