Evidence map›Paper›PMID 30478759›Full record

ArticleJournal of mathematical biology2019

A stochastic model of corneal epithelium maintenance and recovery following perturbation.

E Moraki, R Grima, K J Painter

Open access · greenAbstract read
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In one paragraph

Article in Journal of mathematical biology, 2019. 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
0.5field-weighted citation impact, top 30% 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, 9 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

3 authors at 3 institutions in 2 countries.

E MorakiDepartment of Mathematics, Maxwell Institute for Mathematical Sciences, Heriot-Watt University, Edinburgh, EH14 4AS, Scotland, UK. em281@hw.ac.uk.ORCID 0000-0001-6286-0311
R GrimaSchool of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3JH, Scotland, UK.
K J PainterDepartment of Mathematics, Maxwell Institute for Mathematical Sciences, Heriot-Watt University, Edinburgh, EH14 4AS, Scotland, UK.
Heriot-Watt University · GBPolitecnico di Torino · ITUniversity of Edinburgh · GB

Funding

Biotechnology and Biological Sciences Research Council BB/J015940/1Biotechnology and Biological Sciences Research Council BB/M025551/1Engineering and Physical Sciences Research Council EP/L016508/01
6 · The paper itself

Abstract

Various biological studies suggest that the corneal epithelium is maintained by active stem cells located in the limbus, the so-called limbal epithelial stem cell hypothesis. While numerous mathematical models have been developed to describe corneal epithelium wound healing, only a few have explored the process of corneal epithelium homeostasis. In this paper we present a purposefully simple stochastic mathematical model based on a chemical master equation approach, with the aim of clarifying the main factors involved in the maintenance process. Model analysis provides a set of constraints on the numbers of stem cells, division rates, and the number of division cycles required to maintain a healthy corneal epithelium. In addition, our stochastic analysis reveals noise reduction as the epithelium approaches its homeostatic state, indicating robustness to noise. Finally, recovery is analysed in the context of perturbation scenarios.

Indexed as

Models, BiologicalAnimalsCell CountCell MovementCell ProliferationCorneal InjuriesEpithelium, CornealHomeostasisHumansMathematical ConceptsMiceRabbitsRatsStem CellsStochastic ProcessesWound HealingChemical master equationCorneal epithelium homeostasis and recoveryODE and stochastic model

Identifiers

PMID30478759
OpenAlexW2899182790

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.