Neuromyelitis optica lesions may inform multiple sclerosis heterogeneity debate
Bibliographic record
Abstract
OBJECTIVE: Neuromyelitis optica (NMO) and multiple sclerosis (MS) are considered inflammatory demyelinating diseases with distinguishing pathological characteristics. NMO pathology shows perivascular immunoglobulin G and complement deposition, as well as an astrocytopathy with aquaporin-4 (AQP4) loss. MS lesions reveal a profound, interindividual heterogeneity in immunopathological patterns of active demyelination, which has been challenged by the description of stage-dependent sequences of pathological features. The aim of our study was to compare the histological characteristics of early active demyelinating NMO and MS brain lesions. METHODS: Thirteen cases with supraspinal active demyelinating NMO lesions were analyzed using immunohistochemistry. Results were compared with the published characteristics of MS lesions. RESULTS: A subset of supraspinal lesions from AQP4-IgG-seropositive NMO patients revealed both (1) complement activation products within macrophages at sites of active demyelination and (2) oligodendrocyte apoptosis and a preferential loss of myelin-associated glycoprotein. These characteristics resemble features previously associated with MS lesion patterns II and III, and were present in addition to characteristic histopathological NMO features, namely loss of AQP4 and astrocytes. INTERPRETATION: Early active demyelinating NMO lesions may show complement within macrophages and oligodendrocyte apoptosis associated with a selective loss of minor myelin proteins, in addition to typical NMO features. We hypothesize these findings occur simultaneously only in a subset of active demyelinating NMO lesions. These observations plausibly explain the findings of Barnett and Prineas and further support the concept of interindividual heterogeneity in MS.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".