Balance of Commensal Bacteria-Specific Th17 and RORγt+ Treg Cells in Intestinal Homeostasis and Inflammation
Bibliographic record
Abstract
Abstract A number of Helicobacter species, including Helicobacter hepaticus, have been isolated as the etiological agents of ulcerative inflammatory bowel disease and cancer in their respective hosts. H. hepaticus induces severe Th17-Th1 mediated colitis in a number of immuno-compromised mouse strains, but does not usually cause disease in most wild-type mouse strains. However, how the inflammatory response is carefully contained to be harmless under homeostatic conditions and how perturbations lead to pathogenicity remain elusive questions. To understand this, we developed new research tools, including TCR transgenic mice, as well as MHCII tetramers to interrogate the regulation of H. hepaticus-specific CD4+ T cell function. Interestingly, in contrast to Segmented Filamentous Bacteria (SFB), which induces Th17 cells in the small intestinal lamina propria (SILP) of both IL10+/− and IL-10−/− mice, H. hepaticus mainly induces RORgt+ Treg cells in the large intestinal lamina propria (LILP) of IL-10-sufficient mice, but induces a Th17-Th1 response in the absence of IL-10. We propose that the balance between self/commensal antigen-induced RORgt+ Treg and Th17 cells may be a general strategy to control autoimmune inflammation.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".