Specific Microbiota-Induced Intestinal Th17 Differentiation Requires MHC Class II but Not GALT and Mesenteric Lymph Nodes
Bibliographic record
Abstract
IL-17-expressing CD4+ T lymphocytes (Th17 cells) naturally reside in the intestine where specific cytokines and microbiota, such as segmented filamentous bacteria (SFB), promote their differentiation. Intestinal Th17 cells are thought to initially differentiate in the GALT and/or mesenteric lymph nodes upon Ag encounter and subsequently home to the lamina propria (LP) where they mediate effector functions. However, whether GALT and/or mesenteric lymph nodes are required for intestinal Th17 differentiation as well as how microbiota containing SFB regulate Ag-specific intestinal Th17 cells remain poorly defined. In this study, we observed that naive CD4+ T cells were abundant in the intestinal LP prior to weaning and that the accumulation of Th17 cells in response to microbiota containing SFB occurred in the absence of lymphotoxin-dependent lymphoid structures and the spleen. Furthermore, the differentiation of intestinal Th17 cells in the presence of microbiota containing SFB was dependent on MHC class II expression by CD11c+ cells. Lastly, the differentiation of Ag-specific Th17 cells required both the presence of cognate Ag and microbiota containing SFB. These findings suggest that microbiota containing SFB create an intestinal milieu that may induce Ag-specific Th17 differentiation against food and/or bacterial Ags directly in the intestinal LP.
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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 | 0.001 | 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".