Characterization of differentially activated human B cells and effects of their soluble products on regulatory T cell suppressive function: assay development and design
Bibliographic record
Abstract
B cell depletion therapy with rituximab significantly decreases new disease activity in multiple sclerosis (MS) patients; however, these benefits do not correlate with a reduction in circulating or cerebrospinal fluid antibody levels. These findings implicate antibody-independent, pro-inflammatory roles of B cells in MS. Furthermore, in other autoimmune diseases, such as systemic lupus erythematosus (SLE), B cell depletion reportedly resulted in increased function of circulating regulatory T (Treg) cells. Since MS patients have been found to exhibit deficient Treg function, we hypothesized that activated B cells in MS patients can abnormally suppress the function of Treg cells. Therefore, B cell depletion with rituximab allows for restored Treg function, and the prevention of new autoimmune disease activity. In particular, we postulated that the abnormal pro-inflammatory cytokine profile secreted by MS B cells was responsible for defective Treg function. To begin studying the potential relationship between B and Treg cells, I optimized and validated an in vitro human B cell activation assay, as well as a human Treg suppression assay in healthy controls, to subsequently determine the effects of supernatants from differentially activated B cells on Treg suppressive function.Human B cells were isolated using magnetic-activated cell sorting (MACS), then stimulated with B cell crosslinking antibody (X), CD40 ligand (40), a combination of the two (X40), or CpG-nucleotides. Their supernatants were collected and responses found to support previously published findings. Treg and T responder (Tresp) cells were isolated using both MACS and fluorescence-activated cell sorting (FACS) techniques; then stimulated in coculture with and without B cell supernatants; and proliferation was determined by either standard beta scintillation counting (3H-TdR) or carboxyl-fluorescein succinimidyl ester (CFSE) dilution of Tresp cells. We found that Treg cells isolated using the MACS technique contain high numbers of contaminating CD4+CD25neg Tresp cells; are non-proliferative when stimulated alone; and do not robustly suppress Tresp cell proliferation. In contrast, FACS-isolated Treg cells have higher purity and are suppressive of Tresp cell proliferation and cytokine secretion. Suppression could be modulated by treating cells with either IL-10 to promote suppression, or Pam3Cys to decrease suppression, establishing the dynamic range of the suppression assay. When supernatants from B cells activated with CpG-nucleotides or CD40 ligation were added to the suppression assay, we did not find any significant changes. As such, this may reflect a more subtle biology than can be captured within this assay and still requires further investigation.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".