Biopsy-derived colonoid air-liquid interface monolayers reveal persistent mucosal defects in ulcerative colitis patients
Bibliographic record
Abstract
BACKGROUND: The inflammatory bowel disease (IBD) ulcerative colitis (UC) is characterized by colonic mucosal inflammation and barrier dysfunction. We hypothesized that UC causes persistent defects in mucosal homeostasis, evident even in the absence of active inflammation, contributing to disease chronicity. METHODS: To test our hypothesis, we grew patient biopsy-derived sigmoid colonoids into air-liquid interface (ALI) monolayers, characterizing them through microscopy, proteomics, bulk RNA Sequencing (RNAseq), and their susceptibility to UC patient-isolated Escherichia coli pathobiont p19A. RESULTS: Non-IBD ALI monolayers formed uniform crypt-like structures and a thick mucus layer containing all epithelial-derived proteins previously identified in human colonic mucus. In contrast, ALI monolayers from UC patients displayed a range of impairments, with classification ranging from a mild phenotype with distorted architecture and a thinner, more permeable mucus layer to a severe phenotype with defects in cellular differentiation and an inability to produce a mucus layer. With the use of transcriptome analysis, we identified activated pathways associated with extracellular matrix formation and cell signaling, including numerous cancer-associated genes in UC ALI monolayers, which also proved significantly more susceptible to E. coli p19A. CONCLUSIONS: Taken together, the culturing of patient biopsies into ALI colonoid monolayers provides a powerful model to assess human colonic mucosal development, healing, homeostasis, and mucus barrier function, revealing that UC-derived colonoid monolayers display a range of developmental and functional defects that persist in the absence of inflammation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.001 | 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".