Immunological and pathological characterization of fatal rebound MS activity following natalizumab withdrawal
Bibliographic record
Abstract
BACKGROUND: Severe rebound multiple sclerosis (MS) activity is a life-threatening complication of natalizumab (NTZ) withdrawal, for which pathogenesis and treatment are still unclear. We report the immunological and pathological characterization of a case of central nervous system (CNS) inflammatory demyelination after NTZ discontinuation. OBJECTIVE: To understand the pathophysiology of this neuroinflammatory condition. METHODS: Antemortem blood and cerebrospinal fluid (CSF) analysis was compared with postmortem pathological studies, as well as with novel flow cytometry characterization of immune cells isolated from the CNS parenchyma. RESULTS: Pathological analysis of the brain revealed the presence of innumerable active inflammatory demyelinating lesions typical of immunopathological pattern II. Monocytes/macrophages and B cells were enriched in the CNS parenchyma compared to the CSF. Numerous plasma cells were present in the lesions, but CD8 T lymphocytes were predominant in the parenchyma, as opposed to CD4 in the CSF. CNS-infiltrating lymphocytes expressed high levels of adhesion molecules, granzyme B (GzB), interferon-gamma (IFN-γ), and interleukin (IL)-17. CONCLUSIONS: Our results underline the differences in immune cell populations between the CSF and the CNS parenchyma, and suggest that aggressive immunosuppressive therapy targeting both T and B lymphocytes is warranted to control the overwhelming CNS inflammation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".