Characterizing CD38 expression in terminally differentiated B cells using variable lymphocyte receptor B tetramers
Bibliographic record
Abstract
Introduction: CD38 is an ectoenzyme receptor found on hematopoietic cells and its expression is used in the flow cytometric analysis of sub-populations of circulating B cells among peripheral blood mononuclear cells (PBMC) to aid in diagnosing patients with different antibody production defects (AbD). Monoclonal antibodies derived from the sea lamprey Variable Lymphocyte Receptor B (VLRB) are emerging as an alternative to conventional mammalian antibodies. We hypothesized that VLRB MM3 (V-CD38) which specifically recognizes CD38 in a manner correlating with its enzymatic activity could identify terminally differentiated B cells in human PBMC. Here we investigate the ability of V-CD38 as a tool to diagnose patients with diverse immune abnormalities including AbD. Methods: transitional B cells in PBMC was analyzed by flow cytometry using V-CD38 and compared with a commercial conventional antibody to CD38 (C-CD38). Results: A highly significant correlation (p<0.001, r=0.99) between the percentages of plasmablasts recognized by V-CD38 and C-CD38 was observed among 36 healthy controls (HC), 7 patients with AbD and 24 allergic individuals (AI). The use of V-CD38 enabled improved gating of the CD38 expressing cells (CD38+), aiding in the observation that patients with AbD had significantly lower (p=0.002) CD38+ plasmablasts (0.13%±0.13%) than HC (0.52%±0.57%). Only 61.3% of the transitional B cells detected by C-CD38 were also recognized by V-CD38 (r=0.95, p<0.001) among the 67 participants. AI had significantly reduced V-CD38 and C-CD38 transitional cells compared to HC (p=0.026 and p=0.012, respectively). Conclusions: V-CD38 is a novel reagent that can assess B cells in human PBMC.
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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 | 0.000 |
| 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".