Neurogenic and Myogenic Properties of Pan-Colonic Motor Patterns and Their Spatiotemporal Organization in Rats
Bibliographic record
Abstract
BACKGROUND AND AIMS: Better understanding of intrinsic control mechanisms of colonic motility will lead to better treatment options for colonic dysmotility. The aim was to investigate neurogenic and myogenic control mechanisms underlying pan-colonic motor patterns. METHODS: Analysis of in vitro video recordings of whole rat colon motility was used to explore motor patterns and their spatiotemporal organizations and to identify mechanisms of neurogenic and myogenic control using pharmacological tools. RESULTS: Study of the pan-colonic spatiotemporal organization of motor patterns revealed: fluid-induced or spontaneous rhythmic propulsive long distance contractions (LDCs, 0.4-1.5/min, involving the whole colon), rhythmic propulsive motor complexes (RPMCs) (0.8-2.5/min, dominant in distal colon), ripples (10-14/min, dominant in proximal colon), segmentation and retrograde contractions (0.1-0.8/min, prominent in distal and mid colon). Spontaneous rhythmic LDCs were the dominant pattern, blocked by tetrodotoxin, lidocaine or blockers of cholinergic, nitrergic or serotonergic pathways. Change from propulsion to segmentation and distal retrograde contractions was most prominent after blocking 5-HT3 receptors. In the presence of all neural blockers, bethanechol consistently evoked rhythmic LDC-like propulsive contractions in the same frequency range as the LDCs, indicating the existence of myogenic mechanisms of initiation and propulsion. CONCLUSIONS: Neurogenic and myogenic control systems orchestrate distinct and variable motor patterns at different regions of the pan-colon. Cholinergic, nitrergic and serotonergic pathways are essential for rhythmic LDCs to develop. Rhythmic motor patterns in presence of neural blockade indicate the involvement of myogenic control systems and suggest a role for the networks of interstitial cells of Cajal as pacemakers.
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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 | 0.001 |
| 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".