Multi-step Th17 differentiation in response to segmented filamentous bacteria in the mouse intestine
Bibliographic record
Abstract
Abstract Th17 cells have significant roles in maintaining homeostasis and regulating host defense against various pathogens in our bodies. Our laboratory initially identified segmented filamentous bacteria (SFB) as a unique commensal that is sufficient for Th17 cell differentiation and promotion of Th17-dependent autoimmune diseases such as a mouse model of spontaneous arthritis. The molecular and cellular requirements of SFB-induced Th17 cell differentiation are still unclear. To understand the whole process of Th17 cells differentiation in vivo, we developed SFB-specific T cell receptor transgenic (7B8) mice. We can trace SFB-specific Th17 cell differentiation and response by transferring fluorescently-labeled 7B8 naïve T cells into SFB-gavaged host mice. Using this approach, we have elucidated the requirements for cytokines and antigen presenting cells (APCs) to understand the process of Th17 cell differentiation. Here, we describe that initial induction and expansion of Th17 cells occurs in mesenteric lymph nodes (MLN), and their subsequent migration to intestine is integrin β7-dependent. Although RORγt expression in Th17 cells is mainly dependent on IL-6 signaling in the MLN, IL-23R signaling also contributes to RORγt expression in Th17 cells in the ileum in the absence of IL-6. CD103+ CD11b+ APCs are not important for induction and initial expansion of SFB-specific Th17 cells in MLN, but play important roles in maintenance of SFB-specific Th17 cells in the ileum. Taken together, these results indicate that Th17 cell differentiation proceeds in multiple discrete stages.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".