Stimulus‐induced pacemaker activity in interstitial cells of Cajal associated with the deep muscular plexus of the small intestine
Bibliographic record
Abstract
BACKGROUND: The ICC-DMP have been proposed to generate stimulus-dependent pacemaker activity, rhythmic transient depolarizations, that take part in orchestrating segmentation and clustered propulsive motor patterns in the small intestine. However, little is known about the fundamental properties of ICC-DMP. METHODS: This study was undertaken to increase our understanding of intrinsic properties of the ICC-DMP through calcium imaging and intracellular electrical recordings. KEY RESULTS: Without stimulation, most ICC-DMP were quiescent. In some preparations ICC-DMP generated rhythmic low-frequency calcium oscillations (<10 cpm) with or without high frequency activity superimposed (>35 cpm). Immunohistochemistry proved the existence of NK1R on the ICC-DMP and close contacts between ICC-DMP and substance P-positive nerves. Substance P (25 nM) induced low-frequency calcium oscillations that were synchronized across the ICC-DMP network. Substance P also induced low frequency rhythmic transient depolarizations (<10cpm) in circular muscle cells close to the ICC-DMP. An intracellular recording from a positively identified ICC-DMP showed rhythmic transient depolarizations with superimposed high frequency activity. To investigate if quiescent ICC-DMP were chronically inhibited by nitrergic activity, nNOS was inhibited, but without effect. CONCLUSIONS & INFERENCES: Substance P changes non-synchronized high frequency flickering or quiescence in ICC-DMP into strong rhythmic calcium transients that are synchronized within the network; they are associated with rhythmic transient depolarizations within the same frequency range. We hypothesize that Substance P, released from nerves, can evoke rhythmicity in ICC-DMP, thereby providing it with potential pacemaker activity.
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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 | 0.000 |
| 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".