Evidence map›Paper›PMID 12770871›Full record

ArticleBiophysical journal2003

Discrete models of autocrine cell communication in epithelial layers.

Michal Pribyl, Cyrill B Muratov, Stanislav Y Shvartsman

Abstract readComparative StudyEvaluation StudyValidation Study
In one paragraph

Article in Biophysical journal, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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  17. Intercellular coupling amplifies fate segregation during Caenorhabditis elegans vulval development.Proceedings of the National Academy of Sciences of the United States of America · 2006
    Article
  18. Emergent patterns of growth controlled by multicellular form and mechanics.Proceedings of the National Academy of Sciences of the United States of America · 2005
    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

3 authors.

Michal PribylDepartment of Chemical Engineering and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA.
Cyrill B Muratov
Stanislav Y Shvartsman

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pattern formation in epithelial layers heavily relies on cell communication by secreted ligands. Whereas the experimentally observed signaling patterns can be visualized at single-cell resolution, a biophysical framework for their interpretation is currently lacking. To this end, we develop a family of discrete models of cell communication in epithelial layers. The models are based on the introduction of cell-to-cell coupling coefficients that characterize the spatial range of intercellular signaling by diffusing ligands. We derive the coupling coefficients as functions of geometric, cellular, and molecular parameters of the ligand transport problem. Using these coupling coefficients, we analyze a nonlinear model of positive feedback between ligand release and binding. In particular, we study criteria of existence of the patterns consisting of clusters of a few signaling cells, as well as the onset of signal propagation. We use our model to interpret recent experimental studies of the EGFR/Rhomboid/Spitz module in Drosophila development.

Indexed as

Models, BiologicalAnimalsAutocrine CommunicationBiological TransportBody PatterningCell CommunicationComputer SimulationDiffusionDrosophilaEpidermal Growth FactorEpitheliumFeedback, PhysiologicalNonlinear DynamicsOocytesParacrine CommunicationReceptors, Cell SurfaceEpidermal Growth FactorReceptors, Cell Surface

Identifiers

PMID12770871
PMCPMC1302947

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.