Nerve growth factor content is increased in the rectal mucosa of children with diarrhea‐predominant irritable bowel syndrome
Bibliographic record
Abstract
BACKGROUND: The enteric nervous system is a complex network that includes, in the digestive mucosa, neuronal bodies and fibers interacting with the immune system and mucosal mast cells (MC). These interactions involve the secretion of messengers, such as the neurotrophin nerve growth factor (NGF), which influence colonic motility and sensitivity, both affected in irritable bowel syndrome (IBS). This study was designed to test the hypothesis that, in children with IBS, colonic mucosal innervation, NGF content, and MC infiltration are altered. We aimed to measure MC infiltration, number of neuronal bodies, distance from MC to nerve fibers, inflammation, and NGF content in rectal mucosa of pediatric patients with IBS as compared with controls. METHODS: Rectal biopsies from children (median age: 14 years) with diarrhea-predominant IBS (n = 11) and controls (n = 14) were studied. MC and neuronal mucosal structures were identified by tryptase, CD117 and PGP9.5 immunoreactivity. Inflammatory cells (neutrophils, eosinophils, and lymphocytes) were counted. NGF was quantified in situ by ELISA. KEY RESULTS: No mucosal inflammation was detected in IBS. MC infiltration and number of neuronal bodies were not significantly different between IBS and controls. The distance between MC and nerve fibers was not different in IBS compared with controls (5.2 ± 0.3 vs 5.0 ± 0.3 μm). Number of MC in close proximity to nerve fibers (<5 μm) was not different in the two groups. However, in IBS, NGF content was higher than controls (0.93 ± 0.3 vs 0.62 ± 0.3 pg mg(-1) protein, P < 0.05) and significantly correlated with MC number. CONCLUSIONS & INFERENCES: Regardless of inflammation, NGF content is increased in rectal mucosa of diarrhea-predominant IBS children.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".