Immune signaling mediates stromal changes to support epithelial reprogramming in celiac duodenum
Bibliographic record
Abstract
Celiac disease is a chronic autoimmune disorder affecting 0.5%-1% of the population. Here, we assembled the most comprehensive single-cell RNA sequencing (scRNA-seq) dataset in celiac disease (CeD) to date, including 203,555 cells across 21 active CeD and 11 control duodenal samples. CeD was characterized by single-cell differential changes in abundance, gene expression, and cell-cell interactions across cellular compartments versus control. Epithelial changes included increased stem/crypt and secretory epithelial cells in CeD and decreased absorptive enterocytes, reflecting crypt hyperplasia and villus atrophy. Distinct changes in stromal populations correlated with epithelial changes, particularly increased abundance and transcriptional activity of NRG1 and SMOC2 fibroblasts. Cell-cell interaction analysis proposed a distinct increased role of fibroblasts to support epithelial reprogramming of the increased stem/crypt epithelial fraction in CeD, mediated by myeloid derived interleukin-1β (IL-1β) and lymphoid-derived interferon γ (IFN-γ). This dataset reveals a role for T-myeloid-stromal-epithelial cell communication in CeD, highlighting key mechanisms of the tissue-level cellular dynamics in response to gluten ingestion.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".