Neuronal nitric oxide inhibits intestinal smooth muscle growth
Bibliographic record
Abstract
Hyperplasia of smooth muscle contributes to the thickening of the intestinal wall that is characteristic of inflammation, but the mechanisms of growth control are unknown. Nitric oxide (NO) from enteric neurons expressing neuronal NO synthase (nNOS) might normally inhibit intestinal smooth muscle cell (ISMC) growth, and this was tested in vitro. In ISMC from the circular smooth muscle of the adult rat colon, chemical NO donors inhibited [(3)H]thymidine uptake in response to FCS, reducing this to baseline without toxicity. This effect was inhibited by the guanylyl cyclase inhibitor ODQ and potentiated by the phosphodiesterase-5 inhibitor zaprinast. Inhibition was mimicked by 8-bromo (8-Br)-cGMP, and ELISA measurements showed increased levels of cGMP but not cAMP in response to sodium nitroprusside. However, 8-Br-cAMP and cilostamide also showed inhibitory actions, suggesting an additional role for cAMP. Via a coculture model of ISMC and myenteric neurons, immunocytochemistry and image analysis showed that innervation reduced bromodeoxyuridine uptake by ISMC. Specific blockers of nNOS (7-NI, NAAN) significantly increased [(3)H]thymidine uptake in response to a standard stimulus, showing that nNOS activity normally inhibits ISMC growth. In vivo, nNOS axon number was reduced threefold by day 1 of trinitrobenzene sulfonic acid-induced rat colitis, preceding the hyperplasia of ISMC described earlier in this model. We conclude that NO can inhibit ISMC growth primarily via a cGMP-dependent mechanism. Functional evidence that NO derived from nNOS causes inhibition of ISMC growth in vitro predicts that the loss of nNOS expression in colitis contributes to ISMC hyperplasia in vivo.
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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) | 0.001 | 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".