Evidence map›Paper›PMID 37210381›Full record

ArticleNPJ systems biology and applications2023

A multiscale chemical-mechanical model predicts impact of morphogen spreading on tissue growth.

Alireza Ramezani, Samuel Britton, Roya Zandi, Mark Alber, Ali Nematbakhsh, Weitao Chen

Open access · goldAbstract read
In one paragraph

Article in NPJ systems biology and applications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.7field-weighted citation impact, top 18% 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

3 citing papers in PubMed, 8 citations in OpenAlex.

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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 at 1 institution in 1 country.

Alireza RamezaniDepartment of Physics and Astronomy, University of California, Riverside, CA, 92521, USA.ORCID 0000-0003-0570-9935
Samuel BrittonDepartment of Mathematics, University of California, Riverside, CA, 92521, USA.
Roya ZandiDepartment of Physics and Astronomy, University of California, Riverside, CA, 92521, USA.
Mark AlberInterdisciplinary Center for Quantitative Modeling in Biology, University of California, Riverside, CA, 92521, USA.ORCID 0000-0002-7153-1138
Ali NematbakhshDepartment of Mathematics, University of California, Riverside, CA, 92521, USA. nematba@ucr.edu.ORCID 0000-0001-7411-6039
Weitao ChenInterdisciplinary Center for Quantitative Modeling in Biology, University of California, Riverside, CA, 92521, USA. weitaoc@ucr.edu.ORCID 0000-0003-3362-5982
University of California, Riverside · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The exact mechanism controlling cell growth remains a grand challenge in developmental biology and regenerative medicine. The Drosophila wing disc tissue serves as an ideal biological model to study mechanisms involved in growth regulation. Most existing computational models for studying tissue growth focus specifically on either chemical signals or mechanical forces. Here we developed a multiscale chemical-mechanical model to investigate the growth regulation mechanism based on the dynamics of a morphogen gradient. By comparing the spatial distribution of dividing cells and the overall tissue shape obtained in model simulations with experimental data of the wing disc, it is shown that the size of the domain of the Dpp morphogen is critical in determining tissue size and shape. A larger tissue size with a faster growth rate and more symmetric shape can be achieved if the Dpp gradient spreads in a larger domain. Together with Dpp absorbance at the peripheral zone, the feedback regulation that downregulates Dpp receptors on the cell membrane allows for further spreading of the morphogen away from its source region, resulting in prolonged tissue growth at a more spatially homogeneous growth rate.

Indexed as

Drosophila ProteinsAnimalsCell ProliferationDrosophilaModels, BiologicalWings, Animaldpp protein, DrosophilaDrosophila Proteins

Identifiers

PMID37210381
PMCPMC10199952
OpenAlexW4377137200

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.