Selective emergence of antibody-secreting cells in the multiple sclerosis brain
Bibliographic record
Abstract
BACKGROUND: Although distinct brain-homing B cells have been identified in multiple sclerosis (MS), it is unknown how these further evolve to contribute to local pathology. We explored B-cell maturation in the central nervous system (CNS) of MS patients and determined their association with immunoglobulin (Ig) production, T-cell presence, and lesion formation. METHODS: Ex vivo flow cytometry was performed on post-mortem blood, cerebrospinal fluid (CSF), meninges and white matter from 28 MS and 10 control brain donors to characterize B cells and antibody-secreting cells (ASCs). MS brain tissue sections were analysed with immunostainings and microarrays. IgG index and CSF oligoclonal bands were measured with nephelometry, isoelectric focusing, and immunoblotting. Blood-derived B cells were cocultured under T follicular helper-like conditions to evaluate their ASC-differentiating capacity in vitro. FINDINGS: memory T cells positively correlated with ASC presence, reflected by local interplay with T cells. INTERPRETATION: memory T cells. FUNDING: Stichting MS Research (19-1057 MS; 20-490f MS), National MS Fonds (OZ2018-003).
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".