Profiles of Lamina Propria T Helper Cell Subsets Discriminate Between Ulcerative Colitis and Crohnʼs Disease
Bibliographic record
Abstract
BACKGROUND: Distinction between 2 forms of inflammatory bowel disease (IBD), ulcerative colitis (UC) and Crohn's disease (CD), can be challenging. Aberrant mucosal immunity suggests that CD is a T helper type 1 cell (Th1)-driven disease, whereas UC as Th2-driven response. However, whether this paradigm truly distinguishes CD from UC is controversial. We aimed to clarify the discriminating potential of lamina propria Th subsets in patients with IBD. METHODS: Biopsies from 79 patients with IBD and 20 healthy controls were collected for Th subsets analysis (Th1:interferon γ [IFN-γ], T-bet; Th2:interleukin 13 [IL-13], Gata3; Th17:IL-17, RORγt; Treg:FoxP3). The receiver-operating characteristic curves were constructed to assess the discriminating ability by calculating the area under the receiver-operating characteristic curve. The equation with the highest area under the receiver-operating characteristic curve was applied to newly diagnosed patients to evaluate discriminating ability. RESULTS: Patients with CD showed increased IFN-γ or T-bet cells and decreased IL-13 or Gata3 cells compared with UC. A discriminant equation composed of 4 markers (IFN-γ, T-bet, IL-13, and Gata3) yielded the highest area under the receiver-operating characteristic curve. In 36 established CD or UC, the sensitivity, specificity, positive and negative predictive probabilities were 92.6%, 55.6%, 86.2%, and 71.4% and in 14 newly diagnosed patients were 100.0%, 42.9%, 63.6%, and 100.0%. Furthermore, Gata3 cells were increased in tumor necrosis factor inhibitor therapy nonresponders compared with responders in CD. IFN-γ cells were directly and inversely proportional to disease activity in patients with CD and UC, respectively. CONCLUSIONS: The Th1/Th2 paradigm can distinguish CD from UC and may be further associated with response to tumor necrosis factor inhibitor in CD and disease activity in patients with IBD.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".