B-Cell Maturation Phenotypes and Time Post-Transplant
Bibliographic record
Abstract
Background: Over the past decade, B cell participation in allograft response has been progressively elucidated. Beside the occurrence of DSA (donor-specific alloantibodies), different patterns of B cell phenotypes are also being related to graft outcome. Loss of naive B cells and appearance of memory B cells have been linked to chronic rejection and ultimately to graft loss. Here we show the impact of time post-transplant on phenotypic B cell changes, particularly regarding different distributions of naive B cells. Methods: Single-center, observational cohort of 82 kidney transplant recipients (KTr), adults and clinically stable. Blood samples were collected between January 2015 and November 2018. Peripheral blood mononuclear cells (PBMCs) were isolated and analyzed on flow cytometry. B cells (CD19+) were stained for CD38 and IgD and classified according to Bm classification (IgD vs CD38). Results: The median time post-transplant was 2.9 [0.9-9.89] years and the mean age was 54±13 years. 63% of the patients were males and mean eGFR was 49±17mL/min. B cells absolute counts were lower in later phases post-transplant (R -0.4, p<0.01). Among all B cell subtypes, Bm2 compartment (comprised mainly by naive B cells) had the most significant reduction in both absolute counts (R -0.62, p<0.01) and relative percentage (R -0.58, p<0.01) over time. On the opposite, mature B cells (both Bm5 and early Bm5 compartments) absolute counts did not differ over time (R -0.04 and 0.11 respectively, p>0.05) whereas the percentages of them were positively correlated with time posttransplant (R 0.40 and 0.56 respectively, p<0.01). Linear regression model showed that the absolute reduction in Bm2 cell compartment (i.e. naive B cells) was independent of age, sex, graft function and immunosuppression scheme. Conclusions: Patients with longer time post-transplant have fewer circulating peripheral B cells. Phenotypic analysis of B cell subsets reveals that this reduction is due to an absolute decrease in naive B cells counts. Mature B cell absolute numbers, on the other hand, did not change significantly. Either exhaustion due to long-term immunosuppression or immunologic accommodation due to chronic alloantigen exposure could explain these observations.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".