Gut‐derived cholecystokinin contributes to visceral hypersensitivity via nerve growth factor‐dependent neurite outgrowth
Bibliographic record
Abstract
BACKGROUND AND AIM: Irritable bowel syndrome is characterized by abdominal pain and altered bowel habits and may occur following stressful events or infectious gastroenteritis such as giardiasis. Recent findings revealed a link between cholecystokinin (CCK), neurotrophin synthesis, and intestinal hyperalgesia. The aim was to investigate the role of CCK in visceral hypersensitivity using mouse models challenged with a bout of infection with Giardia lamblia or psychological stress, either alone or in combination. METHODS: Abdominal pain was evaluated by visceromoter response to colorectal distension. Nerve fibers in intestinal tissues were stained using immunohistochemistry (PGP9.5). Human neuroblastoma SH-SY5Y cells incubated with bacterial-free mouse gut supernatant or recombinant CCK-8S were assessed for neurite outgrowth and nerve growth factor (NGF) production. RESULTS: Intestinal hypersensitivity was induced by either stress or Giardia infection, and a trend of increased pain was seen following dual stimuli. Increased CCK levels and PGP9.5 immunoreactivity were found in colonic mucosa of mice following stress and/or infection. Inhibitors to the CCK-A receptor (L-364718) or CCK-B receptor (L-365260) blocked visceral hypersensitivity caused by stress, but not when induced by giardiasis. Nerve fiber elongation and NGF synthesis were observed in SH-SY5Y cells after incubation with colonic supernatants from mice given the dual stimuli, or after treatment with CCK-8S. Increased nerve fiber length by colonic supernatant and CCK-8S was attenuated by L-365260 or neutralizing anti-NGF. CONCLUSIONS: This new model successfully recapitulates intestinal hypernociception induced by stress or Giardia. Colonic CCK contributes to visceral hypersensitivity caused by stress, but not by Giardia, partly via NGF-dependent neurite outgrowth.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".