Effects of glucocorticoids on B-cell subpopulations in patients with IgG4-related disease.
Bibliographic record
Abstract
OBJECTIVES: Glucocorticoids induce prompt clinical improvement in patients with IgG4-related disease (IgG4-RD) but their mechanisms of action in this specific condition are not fully understood. B lymphocytes appear central to IgG4-RD pathogenesis because B-cell depletion with rituximab leads to swift clinical responses. In the present work we aim to assess the effects of glucocorticoids on B-cell subpopulations in patients with IgG4-RD. METHODS: Fifty patients with active untreated IgG4-RD and 20 healthy controls were enrolled in the present study. Flow cytometry analysis for total circulating CD19+ and CD20+ cells, naïve B cells, memory B cells, plasmablasts, and plasma cells was performed at baseline in all patients, and after 6 months of glucocorticoid treatment in 30 patients. Correlation studies with biomarkers of disease activity were also performed. RESULTS: At baseline, patients with IgG4-RD showed reduced CD19+ and CD20+ B cells compared to healthy controls, but increased circulating plasmablasts and plasma cells. Circulating plasmablasts and plasma cells correlated with clinical and serological biomarkers of IgG4-RD activity. Glucocorticoid-induced disease remission was accompanied by a reduction of naïve B cell count, an increase of memory B cells, and by a depletion of circulating plasmablasts and plasma cells. CD19+ and CD20+ B cells, were not affected by glucocorticoids. CONCLUSIONS: The efficacy of glucocorticoids in IgG4-RD is associated with selective effects on different B-cell subpopulations. Further studies are warranted to fully understand possible perturbations of the naïve and memory B-cell compartments in patients with IgG4-RD.
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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 | 0.000 | 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) | 0.001 | 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".