Phenotypic Changes of Lymphocytes in Patients with Systemic Lupus Erythematosus Who Are in Longterm Remission After B Cell Depletion Therapy with Rituximab
Bibliographic record
Abstract
OBJECTIVE: Rituximab has recently emerged as a novel treatment strategy for systemic lupus erythematosus (SLE). We investigated longitudinally the differentiation and phenotypic changes of peripheral B cells and T cells in patients with SLE after rituximab treatment. METHODS: Phenotypic changes on B cells and T cells in 10 patients with SLE treated with rituximab were analyzed before, 28 days after, and 2 years after rituximab treatment, and at relapse. RESULTS: Rituximab rapidly depleted naive and memory B cells from the peripheral blood. In the patients with prolonged remission, the memory B cells remained depleted while naive B cells recovered within 3-9 months, and the expression levels of CD40 and CD80 remained downregulated for 2 years. There was also a decrease of memory T cells relative to naive T cells, and the expression of CD40L and inducible costimulator (ICOS) on CD4-positive T cells rapidly decreased and remained downregulated for 2 years. In 1 patient, an increase in the number of memory B cells with upregulation of CD40 and CD80 expression was noted just before relapse. In another patient with relapse, however, recovery of CD4-positive memory T cells with upregulation of ICOS expression was noted, with no change in the number of memory B cells. CONCLUSION: Our results suggest that the phenotypic changes of peripheral B cells result in inhibition of T cell differentiation and activation mediated by B cells and thereby bring about longterm remission of SLE. Activated memory B cells or ICOS-positive CD4-positive memory T cells reappeared in association with relapse, probably reflecting the heterogeneity of SLE.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".