Microbial recognition regulates intestinal epithelial growth in homeostasis and disease
Bibliographic record
Abstract
The intestine is constantly exposed to a dynamic community of microbes. Intestinal epithelial cells respond to microbes through evolutionarily conserved recognition pathways, such as the immune deficiency (IMD) pathway of Drosophila, the Toll-like receptor (TLR) response of flies and vertebrates, and the vertebrate nucleotide-binding oligomerization domain (NOD) pathway. Microbial recognition pathways are tightly controlled to respond effectively to pathogens, tolerate the microbiome, and limit intestinal disease. In this review, we focus on contributions of different model organisms to our understanding of how epithelial microbe recognition impacts intestinal proliferation and differentiation in homeostasis and disease. In particular, we compare how microbes and subsequent recognition by the intestine influences barrier integrity, intestinal repair and tumorigenesis in Drosophila, zebrafish, mice, and organoids. In addition, we discuss the importance of microbial recognition in homeostatic intestinal growth and discuss how immune pathways directly impact stem cell and crypt dynamics.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".