Evidence map›Paper›PMID 29392399›Full record

ArticleJournal of mathematical biology2018

Bayesian inference of agent-based models: a tool for studying kidney branching morphogenesis.

Ben Lambert, Adam L MacLean, Alexander G Fletcher, Alexander N Combes, Melissa H Little, Helen M Byrne

Open access · hybridAbstract read
In one paragraph

Article in Journal of mathematical biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
8.1field-weighted citation impact, top 2% 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

23 citing papers in PubMed, 50 citations in OpenAlex.

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  19. Toward Engineering Biosystems With Emergent Collective Functions.Frontiers in bioengineering and biotechnology · 2020
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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 4 institutions in 3 countries.

Ben LambertDepartment of Zoology, University of Oxford, Oxford, UK. ben.c.lambert@gmail.com.ORCID 0000-0003-4274-4158
Adam L MacLeanMathematical Institute, University of Oxford, Andrew Wiles Building, Woodstock Road, Oxford, UK.
Alexander G FletcherSchool of Mathematics and Statistics, University of Sheffield, Hicks Building, Hounsfield Road, Sheffield, S3 7RH, UK.
Alexander N CombesDepartment of Anatomy and Neuroscience, University of Melbourne, Melbourne, VIC, 3010, Australia.
Melissa H LittleMurdoch Childrens Research Institute, Flemington Rd, Parkville, Melbourne, VIC, 3052, Australia.
Helen M ByrneMathematical Institute, University of Oxford, Andrew Wiles Building, Woodstock Road, Oxford, UK.
The University of Melbourne · AUUniversity of Oxford · GBUniversity of California, Irvine · USUniversity of Sheffield · GB

Funding

Engineering and Physical Sciences Research Council (GB) EP/F500394/1
6 · The paper itself

Abstract

The adult mammalian kidney has a complex, highly-branched collecting duct epithelium that arises as a ureteric bud sidebranch from an epithelial tube known as the nephric duct. Subsequent branching of the ureteric bud to form the collecting duct tree is regulated by subcellular interactions between the epithelium and a population of mesenchymal cells that surround the tips of outgrowing branches. The mesenchymal cells produce glial cell-line derived neurotrophic factor (GDNF), that binds with RET receptors on the surface of the epithelial cells to stimulate several subcellular pathways in the epithelium. Such interactions are known to be a prerequisite for normal branching development, although competing theories exist for their role in morphogenesis. Here we introduce the first agent-based model of ex vivo kidney uretic branching. Through comparison with experimental data, we show that growth factor-regulated growth mechanisms can explain early epithelial cell branching, but only if epithelial cell division depends in a switch-like way on the local growth factor concentration; cell division occurring only if the driving growth factor level exceeds a threshold. We also show how a recently-developed method, "Approximate Approximate Bayesian Computation", can be used to infer key model parameters, and reveal the dependency between the parameters controlling a growth factor-dependent growth switch. These results are consistent with a requirement for signals controlling proliferation and chemotaxis, both of which are previously identified roles for GDNF.

Indexed as

Models, BiologicalAlgorithmsAnimalsBayes TheoremCell ProliferationComputational BiologyComputer SimulationGlial Cell Line-Derived Neurotrophic FactorHumansKidneyMathematical ConceptsMiceMice, TransgenicMorphogenesisOrgan Culture TechniquesSignal TransductionGlial Cell Line-Derived Neurotrophic FactorCellular automatonDevelopmental processesMathematical modellingMorphologyOrganogenesis

Identifiers

PMID29392399
PMCPMC5906521
OpenAlexW2950361325

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.