Post-infectious irritable bowel syndrome: Mechanistic insights into chronic disturbances following enteric infection
Bibliographic record
Abstract
Irritable bowel syndrome (IBS) is a commonly encountered chronic functional gastrointestinal (GI) disorder. Approximately 10% of IBS patients can trace the onset of their symptoms to a previous a bout of infectious dysentery. The appearance of new IBS symptoms following an infectious event is defined as post-infectious-IBS. Indeed, with the World Health Organization estimating between 2 and 4 billion cases annually, infectious diarrheal disease represents an incredible international healthcare burden. Additionally, compounding evidence suggests many commonly encountered enteropathogens as unique triggers behind IBS symptom generation and underlying pathophysiological features. A growing body of work provides evidence supporting a role for pathogen-mediated modifications in the resident intestinal microbiota, epithelial barrier integrity, effector cell functions, and innate and adaptive immune features, all proposed physiological manifestations that can underlie GI abnormalities in IBS. Enteric pathogens must employ a vast array of machinery to evade host protective immune mechanisms, and illicit successful infections. Consequently, the impact of infectious events on host physiology can be multidimensional in terms of anatomical location, functional scope, and duration. This review offers a unique discussion of the mechanisms employed by many commonly encountered enteric pathogens that cause acute disease, but may also lead to the establishment of chronic GI dysfunction compatible with IBS.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 0.001 |
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".