Localizing value of α-methyl- <scp>L</scp> -tryptophan PET in intractable epilepsy of neocortical origin
Bibliographic record
Abstract
BACKGROUND: [(11)C] alpha-methyl-L-tryptophan (alpha-MTrp) has been developed as a tracer for the study of the synthesis of serotonin in the brain with PET. However, it has been shown that in pathologic conditions the tracer may reflect the activation of kynurenine metabolism. Increased levels of serotonin and quinolinic acid have been described in resected epileptogenic cortex, raising the possibility that alpha-MTrp can localize seizure foci in patients with intractable partial epilepsy. The authors assessed the uptake of alpha-MTrp in 18 patients (11 men, mean +/- SD age 27.1 +/- 10.1 years, range 13 to 54) with intractable partial epilepsy to correlate the PET findings with the epileptogenic area defined by electroclinical and neuroimaging data. METHOD: Seven patients with cortical dysplasia (CD) and 11 with partial epilepsy in which conventional MRI and fluorine-18-deoxyglucose ((18)FDG)-PET studies failed to detect any abnormality were studied. All underwent scalp EEG monitoring during the PET scan to exclude ictal events and estimate the interictal epileptic activity. RESULTS: In seven patients (39%; CD four and cryptogenic partial epilepsy three), PET showed focal increased uptake of alpha-MTrp corresponding to the epileptogenic area. alpha-MTrp uptake in the epileptic focus correlated with the frequency of interictal spikes (r = 0.7, p < 0.05). CONCLUSIONS: alpha-MTrp-PET may be of value in the localization of the epileptogenic area not only in patients with visible dysplastic lesions, but also in those with cryptogenic partial epilepsy.
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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".