Batf3-dependent dendritic cells impact T-cell responses differently between adult and neonatal mice in an intestinal viral infection.
Bibliographic record
Abstract
Abstract The role of dendritic cells (DCs) in shaping the immunity against bacterial infections in the colon (e.g. Citrobacter rodentium) has been well investigated; however, what subset modulates the immune response against viral infections in the small bowel is less known. Rotavirus (RV) almost exclusively infects and replicates in the small intestinal villi resulting in both cellular and humoral adaptive immunity, and RV infection serves as a model to study the DC-elicited antiviral responses in adult and neonatal mice. Batf3 −/− adult and neonatal mice lack CD103+CD11b− DCs in the small intestinal lamina propria (SILP) and displayed a delay in viral clearance. CD8+ T cells have a role in the resolution of primary RV infection, and indeed, we found that while no antigen-specific CD8+ T cell response was detected in the Batf3 −/− neonatal mice, a residual CD8+ T cell response was observed in the Batf3 −/− adult mice, suggesting compensatory antigen-presentation from other adult DC subsets in the SILP (such as CD103+CD11b+ DCs). In terms of the CD4+ T cell response, no Th1 response was found in adult Batf3-deficient or –sufficient mice, however, a robust Th1 response was present in neonatal mice which was dependent on Batf3, implying a requirement of CD103+CD11b−DCs for priming/maintaining a Th1 response only in the neonatal period. Both the local and systemic anti-RV IgA response was normal in adult Batf3 −/− mice, however, neonatal Batf3 −/− mice displayed a stronger systemic IgA response than littermate controls. Our results demonstrate a requirement for Batf3-dependent DCs in antiviral responses which differs between neonates and adults, and these results may shed light on vaccine design.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".