Role of IL-17-producing lymphocytes in severity of multiple sclerosis upon natalizumab treatment
Bibliographic record
Abstract
OBJECTIVE: Natalizumab is known to prevent T-helper cells entering the central nervous system (CNS). We hypothesize that more pathogenic T-helper cells are present outside the CNS and a possible relationship to disease severity. METHODS: Characterization and enrichment of human CD4+IL-17+ cells were performed ex vivo using peripheral blood mononuclear cells from natalizumab-treated relapsing-remitting multiple sclerosis (RRMS) patients ( n = 33), untreated RRMS patients ( n = 13), and healthy controls ( n = 33). Magnetic resonance imaging (MRI) scans were performed routinely for patients. RESULTS: Lymphocytes were elevated in peripheral blood of natalizumab-treated patients compared to untreated patients and healthy controls. Whereas group comparison for CD4+IL-17+ numbers also differed, CD4+IFN-γ+ and CD4+IL-22+ counts were not increased. CD4+IL-17+ cells not only expressed but also secreted IL-17. In natalizumab-treated patients, IL-17+ cell frequency was found to correlate with T1-hypointense lesions, but was not an indicator for rebound activity after treatment discontinuation, except in one patient who experienced a fulminant rebound, and interestingly, in whom the highest IL-17+ cell levels were observed. CONCLUSION: Increased lymphocytes and CD4+IL-17+ cells in the blood of RRMS patients receiving natalizumab corroborate the drug's mechanism of action, that is, blocking transmigration to CNS. Correlation between IL-17-expressing lymphocytes and T1-hypointense lesions underlines the important role of these cells in the disease pathology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".