Evidence map›Paper›PMID 31728621›Full record

ArticleJournal of mathematical biology2020

Mathematical modelling of telomere length dynamics.

Jonathan A D Wattis, Qi Qi, Helen M Byrne

Open access · hybridAbstract read
In one paragraph

Article in Journal of mathematical biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-weighted citation impact, top 45% 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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. On Discretely Structured Growth Models and Their Moments.Bulletin of mathematical biology · 2025
    Article
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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 2 institutions in 1 country.

Jonathan A D WattisSchool of Mathematical Sciences, University of Nottingham, Nottingham, NG7 2RD, UK. Jonathan.Wattis@nottingham.ac.uk.ORCID 0000-0002-6490-1938
Qi QiSchool of Mathematical Sciences, University of Nottingham, Nottingham, NG7 2RD, UK.
Helen M ByrneMathematics Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, UK.
University of Nottingham · GBUniversity of Oxford · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Telomeres are repetitive DNA sequences located at the ends of chromosomes. During cell division, an incomplete copy of each chromosome's DNA is made, causing telomeres to shorten on successive generations. When a threshold length is reached replication ceases and the cell becomes 'senescent'. In this paper, we consider populations of telomeres and, from discrete models, we derive partial differential equations which describe how the distribution of telomere lengths evolves over many generations. We initially consider a population of cells each containing just a single telomere. We use continuum models to compare the effects of various mechanisms of telomere shortening and rates of cell division during normal ageing. For example, the rate (or probability) of cell replication may be fixed or it may decrease as the telomeres shorten. Furthermore, the length of telomere lost on each replication may be constant, or may decrease as the telomeres shorten. Where possible, explicit solutions for the evolution of the distribution of telomere lengths are presented. In other cases, expressions for the mean of the distribution are derived. We extend the models to describe cell populations in which each cell contains a distinct subpopulation of chromosomes. As for the simpler models, constant telomere shortening leads to a linear reduction in telomere length over time, whereas length-dependent shortening results in initially rapid telomere length reduction, slowing at later times. Our analysis also reveals that constant telomere loss leads to a Gaussian (normal) distribution of telomere lengths, whereas length-dependent loss leads to a log-normal distribution. We show that stochastic models, which include a replication probability, also lead to telomere length distributions which are skewed.

Indexed as

Models, GeneticAgingCell DivisionCellular SenescenceChromosomes, HumanComputer SimulationDNA ReplicationHumansMathematical ConceptsModels, StatisticalNormal DistributionStochastic ProcessesTelomereTelomere HomeostasisTelomere ShorteningAgingEnd-replication problemMathematicalTelomere dynamics

Identifiers

PMID31728621
PMCPMC7028829
OpenAlexW2988048925

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.