New views on the complex interplay between degeneration and autoimmunity in multiple sclerosis
Bibliographic record
Abstract
Multiple sclerosis (MS) is a frequently disabling neurological disorder characterized by symptoms, clinical signs and imaging abnormalities that typically fluctuate over time, affecting any level of the CNS. Prominent lymphocytic inflammation, many genetic susceptibility variants involving immune pathways, as well as potent responses of the neuroinflammatory component to immunomodulating drugs, have led to the natural conclusion that this disease is driven by a primary autoimmune process. In this Hypothesis and Theory article, we discuss emerging data that cast doubt on this assumption. After three decades of therapeutic experience, what has become clear is that potent immune modulators are highly effective at suppressing inflammatory relapses, yet exhibit very limited effects on the later progressive phase of MS. Moreover, neuropathological examination of MS tissue indicates that degeneration, CNS atrophy, and myelin loss are most prominent in the progressive stage, when lymphocytic inflammation paradoxically wanes. Finally, emerging clinical observations such as "progression independent of relapse activity" and "silent progression," now thought to take hold very early in the course, together argue that an underlying "cytodegenerative" process, likely targeting the myelinating unit, may in fact represent the most proximal step in a complex pathophysiological cascade exacerbated by an autoimmune inflammatory overlay. Parallels are drawn with more traditional neurodegenerative disorders, where a progressive proteopathy with prion-like propagation of toxic misfolded species is now known to play a key role. A potentially pivotal contribution of the Epstein-Barr virus and B cells in this process is also discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".