The contribution of protein kinase C and CPI‐17 signaling pathways to hypercontractility in murine experimental colitis
Bibliographic record
Abstract
BACKGROUND: Colonic smooth muscle contractility is altered in colitis, and several protein kinase pathways can mediate colonic smooth muscle contraction. In the present study, we investigated whether protein kinase C (PKC) pathways also play a role in colonic hypercontractility observed during T(H) 2 colitis in BALB/c mice. METHODS: Colitis was induced in BALB/c mice by provision of 5% dextran sodium sulfate (DSS) for 7 days. Changes in smooth muscle contractility were examined using dissected circular smooth muscle preparations from the distal colon. The contribution of conventional and novel PKC isozymes to the hypercontractile response was examined with pharmacological PKC inhibitors. Western blot analyses were used to examine protein expression and phosphorylation changes. KEY RESULTS: Colonic smooth muscle was associated with inflammation-induced hypercontractility and altered PKC expression. Carbachol-induced peak (phasic) and sustained (tonic) contractions were increased. Chelerythrine was the most effective PKC inhibitor of both phasic and tonic contractions. There was no general difference in the percent contribution of conventional and novel PKC isozymes toward the DSS-induced hypercontractility, but inhibition of sustained force with GF109203x was higher for inflamed muscle. The CPI-17 phosphorylation was equally suppressed in both normal and DSS conditions by Gö6976 and chelerythrine, but only for the phasic component of contraction. CONCLUSIONS & INFERENCES: The outcomes suggest that both conventional and novel PKC isozymes contribute to the phasic and tonic contractile components of BALB/c colonic circular smooth muscle under normal conditions, with novel PKC isozymes having a greater contribution to the tonic contraction. However, no effect of inflammation was observed on the relative contribution of PKC and CPI-17 toward the observed hypercontractility.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".