Bibliographic record
Abstract
Of all the organ systems in the body, the gastrointestinal tract is the most complicated in terms of the numbers of structures involved, each with different functions, and the numbers and types of signaling molecules utilized. The digestion of food and absorption of nutrients, electrolytes, and water occurs in a hostile luminal environment that contains a large and diverse microbiota. At the core of regulatory control of the digestive and defensive functions of the gastrointestinal tract is the enteric nervous system (ENS), a complex system of neurons and glia in the gut wall. In this review, we discuss 1) the intrinsic neural control of gut functions involved in digestion and 2) how the ENS interacts with the immune system, gut microbiota, and epithelium to maintain mucosal defense and barrier function. We highlight developments that have revolutionized our understanding of the physiology and pathophysiology of enteric neural control. These include a new understanding of the molecular architecture of the ENS, the organization and function of enteric motor circuits, and the roles of enteric glia. We explore the transduction of luminal stimuli by enteroendocrine cells, the regulation of intestinal barrier function by enteric neurons and glia, local immune control by the ENS, and the role of the gut microbiota in regulating the structure and function of the ENS. Multifunctional enteric neurons work together with enteric glial cells, macrophages, interstitial cells, and enteroendocrine cells integrating an array of signals to initiate outputs that are precisely regulated in space and time to control digestion and intestinal homeostasis.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.010 |
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".