Shuttling of information between the mucosal and luminal environment drives intestinal homeostasis
Bibliographic record
Abstract
The gastrointestinal tract is a passageway for dietary nutrients, microorganisms and xenobiotics. The gut is home to diverse bacterial communities forming the microbiota. While bacteria and their metabolites maintain gut homeostasis, the host uses innate and adaptive immune mechanisms to cope with the microbiota and luminal environment. In recent years, multiple bi-directional instructive mechanisms between microbiota, luminal content and mucosal immune systems have been uncovered. Indeed, epithelial and immune cell-derived mucosal signals shape microbiota composition, while microbiota and their by-products shape the mucosal immune system. Genetic and environmental perturbations alter gut mucosal responses which impact on microbial ecology structures. On the other hand, changes in microbiota alter intestinal mucosal responses. In this review, we discuss how intestinal epithelial Paneth and goblet cells interact with the microbiota, how environmental and genetic disorders are sensed by endoplasmic reticulum stress and autophagy responses, how specific bacteria, bacterial- and diet-derived products determine the function and activation of the mucosal immune system. We will also discuss the critical role of HDAC activity as a regulator of immune and epithelial cell homeostatic responses.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".