Lung dendritic cells induce migration of protective T cells to the gastrointestinal tract
Bibliographic record
Abstract
Developing efficacious vaccines against enteric diseases is a global challenge that requires a better understanding of cellular recruitment dynamics at the mucosal surfaces. The current paradigm of T cell homing to the gastrointestinal (GI) tract involves the induction of α4β7 and CCR9 by Peyer's patch and mesenteric lymph node (MLN) dendritic cells (DCs) in a retinoic acid-dependent manner. This paradigm, however, cannot be reconciled with reports of GI T cell responses after intranasal (i.n.) delivery of antigens that do not directly target the GI lymphoid tissue. To explore alternative pathways of cellular migration, we have investigated the ability of DCs from mucosal and nonmucosal tissues to recruit lymphocytes to the GI tract. Unexpectedly, we found that lung DCs, like CD103(+) MLN DCs, up-regulate the gut-homing integrin α4β7 in vitro and in vivo, and induce T cell migration to the GI tract in vivo. Consistent with a role for this pathway in generating mucosal immune responses, lung DC targeting by i.n. immunization induced protective immunity against enteric challenge with a highly pathogenic strain of Salmonella. The present report demonstrates novel functional evidence of mucosal cross talk mediated by DCs, which has the potential to inform the design of novel vaccines against mucosal pathogens.
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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) | 0.001 | 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".