Evidence map›Paper›PMID 27494114›Full record

ArticleJournal of computational biology : a journal of computational molecular cell biology2017

Nonparametric Model of Smooth Muscle Force Production During Electrical Stimulation.

Marc Cole, Steffen Eikenberry, Takahide Kato, Roman A Sandler, Stanley M Yamashiro, Vasilis Z Marmarelis

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of computational biology : a journal of computational molecular cell biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Marc Cole1 Department of Biomedical Engineering, University of Southern California Viterbi School of Engineering , Los Angeles, California.
Steffen Eikenberry1 Department of Biomedical Engineering, University of Southern California Viterbi School of Engineering , Los Angeles, California.
Takahide Kato3 Department of General Education, National Institute of Technology, Toyota College, Toyota, Japan .
Roman A Sandler1 Department of Biomedical Engineering, University of Southern California Viterbi School of Engineering , Los Angeles, California.
Stanley M Yamashiro1 Department of Biomedical Engineering, University of Southern California Viterbi School of Engineering , Los Angeles, California.
Vasilis Z Marmarelis1 Department of Biomedical Engineering, University of Southern California Viterbi School of Engineering , Los Angeles, California.

Funding

TrainingP41EB001978 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI KHOO, MICHAEL C K · 2003 to 2017
$18.1M
NIBIB NIH HHS P41 EB001978
6 · The paper itself

Abstract

A nonparametric model of smooth muscle tension response to electrical stimulation was estimated using the Laguerre expansion technique of nonlinear system kernel estimation. The experimental data consisted of force responses of smooth muscle to energy-matched alternating single pulse and burst current stimuli. The burst stimuli led to at least a 10-fold increase in peak force in smooth muscle from Mytilus edulis, despite the constant energy constraint. A linear model did not fit the data. However, a second-order model fit the data accurately, so the higher-order models were not required to fit the data. Results showed that smooth muscle force response is not linearly related to the stimulation power.

Indexed as

Models, StatisticalAnimalsElectric StimulationMuscle ContractionMuscle, SmoothMytilus edulisThermodynamicselectrical stimulationLaguerre expansionmodel predictionnonlinear systemVolterra kernels

Identifiers

PMID27494114
PMCPMC5586159

What OpenQuestion holds

Textmetadata
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.