Evidence map›Paper›PMID 34828077›Full record

ArticleEntropy (Basel, Switzerland)2021

Model-Based Prediction of an Effective Adhesion Parameter Guiding Multi-Type Cell Segregation.

Philipp Rossbach, Hans-Joachim Böhme, Steffen Lange, Anja Voss-Böhme

Open access · goldAbstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 51% 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, 2 citations in OpenAlex.

  1. Article
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 1 institution in 1 country.

Philipp RossbachDataMedAssist, HTW Dresden, 01062 Dresden, Germany.
Hans-Joachim BöhmeDataMedAssist, HTW Dresden, 01062 Dresden, Germany.ORCID 0000-0001-5283-2691
Steffen LangeDataMedAssist, HTW Dresden, 01062 Dresden, Germany.ORCID 0000-0002-0511-8011
Anja Voss-BöhmeDataMedAssist, HTW Dresden, 01062 Dresden, Germany.ORCID 0000-0001-6510-8694
Hochschule für Technik und Wirtschaft Dresden – University of Applied Sciences · DE

Funding

Co-financed by the EU, the European Social Fund (ESF) and by tax funds on the basis of the budget passed by the Saxon state parliament SAB-Nr. 100382145
6 · The paper itself

Abstract

The process of cell-sorting is essential for development and maintenance of tissues. Mathematical modeling can provide the means to analyze the consequences of different hypotheses about the underlying mechanisms. With the Differential Adhesion Hypothesis, Steinberg proposed that cell-sorting is determined by quantitative differences in cell-type-specific intercellular adhesion strengths. An implementation of the Differential Adhesion Hypothesis is the Differential Migration Model by Voss-Böhme and Deutsch. There, an effective adhesion parameter was derived analytically for systems with two cell types, which predicts the asymptotic sorting pattern. However, the existence and form of such a parameter for more than two cell types is unclear. Here, we generalize analytically the concept of an effective adhesion parameter to three and more cell types and demonstrate its existence numerically for three cell types based on in silico time-series data that is produced by a cellular-automaton implementation of the Differential Migration Model. Additionally, we classify the segregation behavior using statistical learning methods and show that the estimated effective adhesion parameter for three cell types matches our analytical prediction. Finally, we demonstrate that the effective adhesion parameter can resolve a recent dispute about the impact of interfacial adhesion, cortical tension and heterotypic repulsion on cell segregation.

Indexed as

cell sortingcellular automatondifferential adhesion hypothesisdifferential migration modelhigh heterotypic interfacial tension hypothesispattern formationstatistical learning methods

Identifiers

PMID34828077
PMCPMC8624153
OpenAlexW3209021094

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.