SARS-CoV-2-specific B cell responses in non-draining lymph nodes and antibody functionalities in immunized end-stage renal disease patients
Bibliographic record
Abstract
The degree to which COVID-19 vaccination induces B-cell responses in non-draining lymph nodes (LNs) is unknown. Therefore, non-draining iliac LNs and paired peripheral blood (PB) of end-stage renal disease patients were retrieved during kidney transplantation. Prior, participants received two (n = 5), three (n = 4), or four mRNA-based vaccinations (n = 3) and 4 patients had previous SARS-CoV-2 infection, of whom 2 received two vaccinations. Samples were obtained on average 79 days post-vaccination and 162 days post-infection. Spike S1(S)-binding B-cells were detected in LNs and PB 210 and 243 days after vaccination and infection, respectively. These B-cells predominantly consisted of IgG-secreting plasmablasts. In serum, a decreased IgG1/IgG4 ratio upon repeated vaccination, coherent with high fractions of S-binding IgG4 in LNs, correlated with reduced Fc-mediated functionalities but not neutralization capacity. Thus, mRNA-based COVID-19 vaccination could induce a systemic and long-lived, highly functional virus-specific B-cell response. Understanding IgG4 skewing is important for future vaccination strategies, especially in immunocompromised populations.
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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 | 0.000 |
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".