Evidence map›Paper›PMID 33617836›Full record

ArticleBiophysical journal2021

Synchronized oscillations in growing cell populations are explained by demographic noise.

Enrico Gavagnin, Sean T Vittadello, Gency Gunasingh, Nikolas K Haass, Matthew J Simpson, Tim Rogers, Christian A Yates

Abstract read
In one paragraph

Article in Biophysical journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

7 authors.

Enrico GavagninSchool of Biological Sciences, University of Bristol, Bristol, United Kingdom. Electronic address: gavagnin.enrico@gmail.com.
Sean T VittadelloSchool of BioSciences, University of Melbourne, Melbourne, Victoria, Australia.
Gency GunasinghThe University of Queensland, The University of Queensland Diamantina Institute, Brisbane, Queensland, Australia.
Nikolas K HaassThe University of Queensland, The University of Queensland Diamantina Institute, Brisbane, Queensland, Australia.
Matthew J SimpsonSchool of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
Tim RogersDepartment of Mathematical Sciences, University of Bath, Bath, United Kingdom.
Christian A YatesDepartment of Mathematical Sciences, University of Bath, Bath, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding synchrony in growing populations is important for applications as diverse as epidemiology and cancer treatment. Recent experiments employing fluorescent reporters in melanoma cell lines have uncovered growing subpopulations exhibiting sustained oscillations, with nearby cells appearing to synchronize their cycles. In this study, we demonstrate that the behavior observed is consistent with long-lasting transient phenomenon initiated and amplified by the finite-sample effects and demographic noise. We present a novel mathematical analysis of a multistage model of cell growth, which accurately reproduces the synchronized oscillations. As part of the analysis, we elucidate the transient and asymptotic phases of the dynamics and derive an analytical formula to quantify the effect of demographic noise in the appearance of the oscillations. The implications of these findings are broad, such as providing insight into experimental protocols that are used to study the growth of asynchronous populations and, in particular, those investigations relating to anticancer drug discovery.

Indexed as

Cell CycleCell LineDemography

Identifiers

PMID33617836
PMCPMC8105735

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.