Novel findings regarding the role of the endocannabinoid system in pediatric functional gastrointestinal disorders
Bibliographic record
Abstract
Abstract Introduction: Pain constitutes the chief complaint of some functional gastrointestinal disorders (FGIDs). The endocannabinoid (EC) and peroxisome proliferator–activated receptors (PPARs) agonist systems have not been explored as possible contributors. Objective: To determine if EC and PPAR agonist abnormalities occur in adolescents with FGID. Methods: Institutional Review Board approved study compared 33 children (12-18 years) with a FGID to 18 healthy controls (HC). Clinical measures: functional disability inventory and pediatric pain questionnaire (PPQ). Endocannabinoid and PPAR agonist concentrations were determined in serum from blood. Data were analyzed using Mann–Whitney and Fisher exact tests (2-sided P < 0.05 considered significant). Results: When compared to HC, FGID subjects used different terms to describe their pain, which also occurred in more body areas. Functional gastrointestinal disorder subjects exhibited higher palmitoylethanolamide (PEA) and N-oleoylethanolamide, while EC did not differ. Interestingly, PEA correlated significantly with PPQ “worst pain the week before” in the HC group with Spearman ρ = 0.519, P = 0.003, but not in the FGID group (ρ = 0.079, P = 0.66). Conclusion: Children with FGID exhibit significant pain in nongastrointestinal regions. The higher concentrations of PEA found in the FGID subjects, also occurring in other chronic pain conditions, could reflect a compensatory response due to feedback loops from a downregulated or nonresponsive PPAR system, while the absence of the expected relationship between pain intensity and PEA levels in the FGID group suggests that the PPAR system may not be functioning normally.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".