A case of NMO seropositive for aquaporin-4 antibody more than 10 years before onset
Bibliographic record
Abstract
Neuromyelitis optica (NMO) is characterized by severe optic neuritis and longitudinally extended transverse myelitis (LETM). The clinical and laboratory features of NMO are different from multiple sclerosis (MS).1 An autoantibody to aquaporin-4 (AQP4) has been detected exclusively in the NMO sera.1 Moreover, we demonstrated an extensive loss of AQP4 and glial fibrillary acidic protein immunoreactivities in the perivascular regions with complement and immunoglobulin deposition in NMO that suggests astrocytic impairment. However, when AQP4 antibody is produced in patients with NMO is unknown, and thus it remains unresolved whether there are long-term asymptomatic AQP4 antibody–positive carriers, whether AQP4 antibody alone can be pathogenic, and whether AQP4 antibody is produced secondarily as a result of tissue destruction in attacks of NMO. We herein report a case of NMO in which AQP4 antibody was detected years before the NMO onset. ### Case report. A 34-year-old healthy woman without previous history of inflammatory or neurologic diseases noticed temporary skin eruptions on her chest and shoulders in June 2007. A dermatologist made the diagnosis of eczema. Three weeks later, when the skin eruptions subsided, she noted progressive paresthesia in the chest and toes. Within a few days, she could not walk well due to right leg weakness, and then she was hospitalized. Neurologic examination on …
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".