CXCL13 is a plasma biomarker of germinal center activity
Bibliographic record
Abstract
Significantly higher levels of plasma CXCL13 [chemokine (C-X-C motif) ligand 13] were associated with the generation of broadly neutralizing antibodies (bnAbs) against HIV in a large longitudinal cohort of HIV-infected individuals. Germinal centers (GCs) perform the remarkable task of optimizing B-cell Ab responses. GCs are required for almost all B-cell receptor affinity maturation and will be a critical parameter to monitor if HIV bnAbs are to be induced by vaccination. However, lymphoid tissue is rarely available from immunized humans, making the monitoring of GC activity by direct assessment of GC B cells and germinal center CD4(+) T follicular helper (GC Tfh) cells problematic. The CXCL13-CXCR5 [chemokine (C-X-C motif) receptor 5] chemokine axis plays a central role in organizing both B-cell follicles and GCs. Because GC Tfh cells can produce CXCL13, we explored the potential use of CXCL13 as a blood biomarker to indicate GC activity. In a series of studies, we found that plasma CXCL13 levels correlated with GC activity in draining lymph nodes of immunized mice, immunized macaques, and HIV-infected humans. Furthermore, plasma CXCL13 levels in immunized humans correlated with the magnitude of Ab responses and the frequency of ICOS(+) (inducible T-cell costimulator) Tfh-like cells in blood. Together, these findings support the potential use of CXCL13 as a plasma biomarker of GC activity in human vaccine trials and other clinical settings.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".