Peripheral Mechanisms of Symptom Generation in Irritable Bowel Syndrome
Bibliographic record
Abstract
There is considerable interest in the mechanisms that underlie symptom generation in irritable bowel syndrome (IBS) and particularly those mechanisms peripheral to higher centres in the nervous system. While the central nervous system is important in IBS, it is restricted largely to the role of behaviour in stress perception and symptom reporting. The gut and the autonomic nervous system are principal areas of research in identifying mechanisms underlying symptom generation and in the identification of new targets for drug development. While motility changes occur in IBS, they are neither specific nor predictable, and this is one reason why drugs aimed at influencing motility patterns have enjoyed limited success to date. This success has prompted interest in sensory physiology to explain pain and other discomforts expressed by patients with IBS. Patients with IBS exhibit intolerance to rectal distension and other manoeuvres of the gut, while exhibiting normal or raised thresholds for somatic pain. The mechanisms underlying the development of hyperalgesia or allodynia in the gut remain to be determined. In other systems and experimental models, low grade inflammation is a predictable inducer of these states, and recent evidence suggests that a subpopulation of patients with IBS develop chronic symptoms after acute gastroenteritis. This and other inflammatory stimuli may induce a hyperalgesic state and alter motor function in patients with IBS. Substances that mediate these changes are not fully understood, but there is growing recognition of the role of serotonin as a sensitizing agent.
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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) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".