Evidence map›Paper›PMID 30723401›Full record

ArticleFrontiers in computational neuroscience2018

A General Model of Ion Passive Transmembrane Transport Based on Ionic Concentration.

Vincent Qiqian Wang, Shenquan Liu

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Frontiers in computational neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 49% 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

1 citing paper in PubMed, 8 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Vincent Qiqian WangSchool of Mathematics, South China University of Technology, Guangzhou, China.
Shenquan LiuSchool of Mathematics, South China University of Technology, Guangzhou, China.
South China University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current mainstream neural computing is based on the electricity model proposed by Hodgkin and Huxley in 1952, the core of which is ion passive transmembrane transport controlled by ion channels. However, studies on the evolutionary history of ion channels have shown that some neuronal ion channels predate the neurons. Thus, to deepen our understanding of neuronal activities, ion channel models should be applied to other cells. Expanding the scope of electrophysiological experiments from nerve to muscle, animal to plant, and metazoa to protozoa, has lead the discovery of a number of ion channels. Moreover, the properties of these newly discovered ion channels are too complex to be described by current common models. Hence this paper has presented a convenient method for estimating the distribution of ions under an electric field and established a general ionic concentration-based model of ion passive transmembrane transport that is simple but capable of explaining and simulating the complex phenomena of patch clamp experiments, is applicable to different ion channels in different cells of different species, and conforms to the current general understanding of ion channels. Finally, we designed a series of mathematical experiments, which we have compared with the results of typical electrophysiological experiments conducted on plant cells, oocytes, myocytes, cardiomyocytes, and neurocytes, to verify the model.

Indexed as

electrophysiologyfiltergateion channelionic concentration and fluxmembraneneurosciences

Identifiers

PMID30723401
PMCPMC6349753
OpenAlexW2911721925

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.