C-type lectin receptor agonists elicit functional IL21-expressing Tfh cells and induce primary B cell responses in neonates
Bibliographic record
Abstract
Introduction C-type lectin receptor (CLR) agonists emerged as superior inducers of primary B cell responses in early life compared with Toll-like receptor (TLR) agonists, while both types of adjuvants are potent in adults. Methods Here, we explored the mechanisms accounting for the differences in neonatal adjuvanticity between a CLR-based (CAF®01) and a TLR4-based (GLA-SE) adjuvant administered with influenza hemagglutinin (HA) in neonatal mice, by using transcriptomics and systems biology analyses. Results On day 7 after immunization, HA/CAF01 increased IL6 and IL21 levels in the draining lymph nodes, while HA/GLA-SE increased IL10. CAF01 induced mixed Th1/Th17 neonatal responses while T cell responses induced by GLA-SE had a more pronounced Th2-profile. Only CAF01 induced T follicular helper (Tfh) cells expressing high levels of IL21 similar to levels induced in adult mice, which is essential for germinal center (GC) formation. Accordingly, only CAF01- induced neonatal Tfh cells activated adoptively transferred hen egg lysozyme (HEL)-specific B cells to form HEL+ GC B cells in neonatal mice upon vaccination with HEL-OVA. Discussion Collectively, the data show that CLR-based adjuvants are promising neonatal and infant adjuvants due to their ability to harness Tfh responses in early life.
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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".