The Pathology of an Autoimmune Astrocytopathy: Lessons Learned from Neuromyelitis Optica
Bibliographic record
Abstract
Neuromyelitis optica (NMO) is a disabling autoimmune astrocytopathy characterized by typically severe and recurrent attacks of optic neuritis and longitudinally extensive myelitis. Until recently, NMO was considered an acute aggressive variant of multiple sclerosis (MS), despite the fact that early studies postulated that NMO and MS may be two distinct diseases with a common clinical picture. With the discovery of a highly specific serum autoantibody (NMO-IgG), Lennon and colleagues provided the first unequivocal evidence distinguishing NMO from MS and other central nervous system (CNS) inflammatory demyelinating disorders. The target antigen of NMO-IgG was confirmed to be aquaporin-4 (AQP4), the most abundant water channel protein in the CNS, mainly expressed on astrocytic foot processes at the blood-brain barrier, subpial and subependymal regions. Pathological studies demonstrated that astrocytes were selectively targeted in NMO as evidenced by the extensive loss of immunoreactivities for the astrocytic proteins, AQP4 and glial fibrillary acidic protein (GFAP), as well as perivascular deposition of immunoglobulins and activation of complement even within lesions with a relative preservation of myelin. In support of these pathological findings, GFAP levels in the cerebrospinal fluid (CSF) during acute NMO exacerbations were found to be remarkably elevated in contrast to MS where CSF-GFAP levels did not substantially differ from controls. Additionally, recent experimental studies showed that AQP4 antibody is pathogenic, resulting in selective astrocyte destruction and dysfunction in vitro, ex vivo and in vivo. These findings strongly suggest that NMO is an autoimmune astrocytopathy where damage to astrocytes exceeds both myelin and neuronal damage. This chapter will review recent neuropathological studies that have provided novel insights into the pathogenic mechanisms, cellular targets, as well as the spectrum of tissue damage in NMO.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.001 | 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".