Hemiplegic migraine, seizures, progressive spastic paraparesis, mood disorder, and coma in siblings with low systemic serotonin
Bibliographic record
Abstract
BACKGROUND: Serotonin has an important role in vascular resistance and blood pressure control, and a functional serotonin transporter polymorphism has been associated with migraine. Disturbances in serotonin metabolism have been associated with autism, depression, and myoclonus related conditions, but serotonin has far more functions in the body. Familial hemiplegic migraine is a rare autosomal dominant subtype of migraine with aura in which attacks are associated with hemiparesis. CASES: We present two siblings with hemiplegic migraine, depression, progressive spastic paraparesis, myelopathy, and spinal cord atrophy. One of the sisters presented with prolonged coma after a migraine episode. Both sisters were found to have low cerebrospinal fluid serotonin metabolite (5-hydroxyindoleacetic acid), low platelet serotonin levels, and diminished serotonin transport capacity. Their clinical symptoms improved on 5-hydroxytryptophan replacement therapy. Mutational analysis of the CACNA1A and ATP1A2 genes was negative. CONCLUSION: This is the first time that systemic serotonin deficiency has been described in familial hemiplegic migraine. We hypothesize that the deficiency of serotonin transport may be part of a complex cellular membrane trafficking dysfunction involving not only the serotonin transporter but also other transporters and ion channels.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".