Evidence map›Paper›PMID 32959067›Full record

ArticleJournal of mathematical biology2020

A continuation method for spatially discretized models with nonlocal interactions conserving size and shape of cells and lattices.

Shin-Ichiro Ei, Hiroshi Ishii, Makoto Sato, Yoshitaro Tanaka, Miaoxing Wang, Tetsuo Yasugi

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in Journal of mathematical biology, 2020. 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
0.1field-weighted citation impact, top 55% 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, 3 citations in OpenAlex.

  1. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Shin-Ichiro EiDepartment of Mathematics, Faculty of Science, Hokkaido University, Sapporo, 060-0810, Japan.
Hiroshi IshiiDepartment of Mathematics, Faculty of Science, Hokkaido University, Sapporo, 060-0810, Japan.
Makoto SatoMathematical Neuroscience Unit, Institute for Frontier Science Initiative, Kanazawa University, 13-1 Takaramachi, Kanazawa-shi, Ishikawa, 920-8640, Japan.
Yoshitaro TanakaDepartment of Complex and Intelligent Systems, Future University Hakodate, 116-2 Kamedanakano-cho, Hakodate, Hokkaido, 041-8655, Japan. yoshitaro.tanaka@gmail.com.ORCID http://orcid.org/0000-0002-9312-0946
Miaoxing WangMathematical Neuroscience Unit, Institute for Frontier Science Initiative, Kanazawa University, 13-1 Takaramachi, Kanazawa-shi, Ishikawa, 920-8640, Japan.
Tetsuo YasugiMathematical Neuroscience Unit, Institute for Frontier Science Initiative, Kanazawa University, 13-1 Takaramachi, Kanazawa-shi, Ishikawa, 920-8640, Japan. tetsuo.yasugi@staff.kanazawa-u.ac.jp.
Kanazawa University · JPHokkaido University · JPFuture University Hakodate · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we introduce a continuation method for the spatially discretized models, while conserving the size and shape of the cells and lattices. This proposed method is realized using the shift operators and nonlocal operators of convolution types. Through this method and using the shift operator, the nonlinear spatially discretized model on the uniform and nonuniform lattices can be systematically converted into a spatially continuous model; this renders both models point-wisely equivalent. Moreover, by the convolution with suitable kernels, we mollify the shift operator and approximate the spatially discretized models using the nonlocal evolution equations, rendering suitable for the application in both experimental and mathematical analyses. We also demonstrate that this approximation is supported by the singular limit analysis, and that the information of the lattice and cells is expressed in the shift and nonlocal operators. The continuous models designed using our method can successfully replicate the patterns corresponding to those of the original spatially discretized models obtained from the numerical simulations. Furthermore, from the observations of the isotropy of the Delta-Notch signaling system in a developing real fly brain, we propose a radially symmetric kernel for averaging the cell shape using our continuation method. We also apply our method for cell division and proliferation to spatially discretized models of the differentiation wave and describe the discrete models on the sphere surface. Finally, we demonstrate an application of our method in the linear stability analysis of the planar cell polarity model.

Indexed as

Nonlinear DynamicsContinuation methodDelta–Notch signalingNonlocal interactionsSingular limit analysisSpatially discretized model

Identifiers

PMID32959067
PMCPMC7560951
OpenAlexW3087095257

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.