Differential Pathogenic Th17 Profile in Mesenteric Lymph Nodes of Crohn's Disease and Ulcerative Colitis Patients
Bibliographic record
Abstract
The drug targets IL23 and IL12 regulate pathogenicity and plasticity of intestinal Th17 cells in Crohn’s disease (CD) and ulcerative colitis (UC), the two most common inflammatory bowel diseases (IBD). However, studies examining Th17 dysregulation in mesenteric lymph nodes (mLNs) of these patients are rare. We showed that in mLNs, CD could be distinguished from UC by increased frequencies of CCR6+CXCR3-ROR+Tbet-CD4+ (Th17) memory T cells enriched in CD62Llow effector memory T cells (TEM), and their differentially expressed molecular profile. Th17 TEM cells (expressing IL17A, IL17F, RORC and STAT3) displayed a higher pathogenic/cytotoxic (IL23R, IL18RAP, and GZMB, CD160, PRF1) gene signature in CD relative to UC, while non-pathogenic/regulatory genes (IL9, FOXP3, CTLA4) were more elevated in UC. In both CD and UC, IL12 but not IL23, augmented IFN expression in Th17 TEM and switched their molecular profile towards an ex-Th17 (Th1*)-biased transcriptomic signature (increased IFNG, and decreased TCF7, IL17A), suggesting that Th17 plasticity occurs in mLNs before their recruitment to inflamed colon. We propose that differences observed between Th17 cell frequencies and their molecular profile in CD and UC might have implications in understanding disease pathogenesis, and thus, therapeutic management of patients with IBD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".