Treatment response to dimethyl fumarate is characterized by disproportionate CD8+ T cell reduction in MS
Bibliographic record
Abstract
BACKGROUND: The effect of dimethyl fumarate (DMF) on circulating lymphocyte subsets and their contribution as predictors of clinical efficacy have not yet been investigated in multiple sclerosis (MS). OBJECTIVE: To evaluate lymphocytes and lymphocyte subsets (analyzed 6 months after DMF start) in MS patients with and without disease activity after 1 year of treatment in a retrospective study. METHODS: Peripheral blood lymphocyte subsets were analyzed by flow cytometry. Untreated MS patients ( n = 40) were compared to those 6 months after onset of DMF treatment ( n = 51). Clinical and magnetic resonance imaging (MRI) disease activity of DMF-treated patients were assessed in the first year under treatment. RESULTS: Stable patients showed significantly lower lymphocytes, CD4+ and CD8+ T cells as well as CD19+ B cells compared to active patients under DMF treatment. Furthermore, an increased CD4/CD8 ratio ( p < 0.025) in stable patients indicated a disproportionate reduction of CD8+ T cells relative to CD4+ T cells. Reduced lymphocytes, CD8+ T cells, and CD19+ B cells 6 months after DMF start allowed prediction of the treatment response in the first year. CONCLUSION: DMF treatment response is reflected by lower circulating lymphocytes and specific lymphocyte subsets. Changes in the cellular immune profiles under DMF treatment are clinically relevant and might serve as a surrogate marker of treatment response.
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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 | 0.000 | 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".