Evidence map›Paper›PMID 24111242›Full record

ArticleAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference2013

A simplified biophysical cell model for gastric slow wave entrainment simulation.

Peng Du, Jerry Gao, Gregory O'Grady, Leo K Cheng

Abstract read
In one paragraph

Article in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
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  3. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Peng Du
Jerry Gao
Gregory O'Grady
Leo K Cheng
University of Auckland · NZVanderbilt University · US

Funding

Realistic models of gastrointestinal bioelectromagnetismR01DK064775 · NIDDK · VANDERBILT UNIVERSITY MEDICAL CENTER · PI CHENG, LEO · 2004 to 2014
$2.6M
NIDDK NIH HHS R01 DK064775NIDDK NIH HHS R01 DK64775
6 · The paper itself

Abstract

Gastric electrical activity, also termed slow wave activity, is generated by a class of pacemaker cells called the interstitial cells of Cajal (ICC), which are organized with decreasing intrinsic frequencies along the stomach. In the healthy stomach, slow waves of different intrinsic frequencies converge to a single frequency with a constant phase-lag, in a process called entrainment. The main aim of this study was to develop a simplified biophysical ICC model that is capable of modeling the self-excitatory behavior and standard morphology of gastric slow waves. Entrainment of gastric slow waves was simulated in a one-dimensional (1D) model, with a linear gradient of intrinsic slow wave frequencies. In a coupled 1D model, the simulated slow waves were entrained to a single frequency; whereas in an uncoupled 1D model, the simulated slow waves occurred at different frequencies, resulting in loss of entrainment. The new cell model presents an option for future large multi-scale simulations of gastric slow waves in intact ICC network and diseased conditions where the loss of entrainment may lead to slow wave dysrhythmias and diminished gastric motility.

Indexed as

CalciumGastrointestinal MotilityHumansInterstitial Cells of CajalIonsMembrane PotentialsModels, BiologicalStomachCalciumIons

Identifiers

PMID24111242
PMCPMC4071156
OpenAlexW2172231361

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.