Interictal blood–brain barrier dysfunction in piriform cortex of people with epilepsy
Bibliographic record
Abstract
Abstract Objective The piriform cortex is considered to be highly epileptogenic. Its resection during epilepsy surgery is a predictor for postoperative seizure freedom in temporal lobe epilepsy. Epilepsy is associated with a dysfunction of the blood–brain barrier. We investigated blood–brain barrier dysfunction in the piriform cortex of people with temporal lobe epilepsy using quantitative T1‐relaxometry. Methods Gadolinium‐based contrast agent was administered ictally and interictally in 37 individuals before undergoing quantitative T1‐relaxometry. Postictal and interictal images were co‐registered, and subtraction maps were created as biomarkers for peri‐ictal (∆qT1interictal‐postictal) and interictal (∆qT1noncontrast‐interictal) blood–brain barrier dysfunction. Values were extracted for the piriform cortex, hippocampus, amygdala, and the whole cortex. Results In temporal lobe epilepsy (n = 14), ∆qT1noncontrast‐interictal was significantly higher in the piriform cortex than in the whole cortex (p = 0.02). In extratemporal lobe epilepsy (n = 23), ∆qT1noncontrast‐interictal was higher in the hippocampus than in the whole cortex (p = 0.05). Across all individuals (n = 37), duration of epilepsy was correlated with ∆qT1noncontrast‐interictal (ß = 0.001, p < 0.001) in all regions, while the association was strongest in the piriform cortex. Impaired verbal memory was associated with ∆qT1noncontrast‐interictal only in the piriform cortex (p = 0.04). ∆qT1interictal‐postictal did not show differences in any region. Interpretation Interictal blood–brain barrier dysfunction occurs in the piriform cortex in temporal lobe epilepsy. This dysfunction is linked to longer disease duration and worse cognitive deficits, emphasizing the central role of the piriform cortex in the epileptogenic network of temporal lobe 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 | 0.001 |
| 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 | 0.000 |
| 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".