Neuroimmunophysiology of the gastrointestinal tract
Bibliographic record
Abstract
Gut physiology is the epicenter of a web of internal communication systems (i.e., neural, immune, hormonal) mediated by cell-cell contacts, soluble factors, and external influences, such as the microbiome, diet, and the physical environment. Together these provide the signals that shape enteric homeostasis and, when they go awry, lead to disease. Faced with the seemingly paradoxical tasks of nutrient uptake (digestion) and retarding pathogen invasion (host defense), the gut integrates interactions between a variety of cells and signaling molecules to keep the host nourished and protected from pathogens. When the system fails, the outcome can be acute or chronic disease, often labeled as "idiopathic" in nature (e.g., irritable bowel syndrome, inflammatory bowel disease). Here we underscore the importance of a holistic approach to gut physiology, placing an emphasis on intercellular connectedness, using enteric neuroimmunophysiology as the paradigm. The goal of this opinion piece is to acknowledge the pace of change brought to our field via single-cell and -omic methodologies and other techniques such as cell lineage tracing, transgenic animal models, methods for culturing patient tissue, and advanced imaging. We identify gaps in the field and hope to inspire and challenge colleagues to take up the mantle and advance awareness of the subtleties, intricacies, and nuances of intestinal physiology in health and disease by defining communication pathways between gut resident cells, those recruited from the circulation, and "external" influences such as the central nervous system and the gut microbiota.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".