Evidence map›Paper›PMID 29045427›Full record

ArticlePloS one2017

More or less-On the influence of labelling strategies to infer cell population dynamics.

Michael Gabel, Roland R Regoes, Frederik Graw

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 48% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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 2 countries.

Michael GabelCenter for Modelling and Simulation in the Biosciences, BioQuant-Center, Heidelberg University, 69120 Heidelberg, Germany.
Roland R RegoesInstitute for Integrative Biology, ETH Zurich, CH-8092 Zurich, Switzerland.
Frederik GrawCenter for Modelling and Simulation in the Biosciences, BioQuant-Center, Heidelberg University, 69120 Heidelberg, Germany.ORCID http://orcid.org/0000-0002-1198-6632
Heidelberg University · DEETH Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The adoptive transfer of labelled cell populations has been an essential tool to determine and quantify cellular dynamics. The experimental methods to label and track cells over time range from fluorescent dyes over congenic markers towards single-cell labelling techniques, such as genetic barcodes. While these methods have been widely used to quantify cell differentiation and division dynamics, the extent to which the applied labelling strategy actually affects the quantification of the dynamics has not been determined so far. This is especially important in situations where measurements can only be obtained at a single time point, as e.g. due to organ harvest. To this end, we studied the appropriateness of various labelling strategies as characterised by the number of different labels and the initial number of cells per label to quantify cellular dynamics. We simulated adoptive transfer experiments in systems of various complexity that assumed either homoeostatic cellular turnover or cell expansion dynamics involving various steps of cell differentiation and proliferation. Re-sampling cells at a single time point, we determined the ability of different labelling strategies to recover the underlying kinetics. Our results indicate that cell transition and expansion rates are differently affected by experimental shortcomings, such as loss of cells during transfer or sampling, dependent on the labelling strategy used. Furthermore, uniformly distributed labels in the transferred population generally lead to more robust and less biased results than non-equal label sizes. In addition, our analysis indicates that certain labelling approaches incorporate a systematic bias for the identification of complex cell expansion dynamics.

Indexed as

Cell DifferentiationCell ProliferationCellsHomeostasisModels, BiologicalStaining and LabelingTime Factors

Identifiers

PMID29045427
PMCPMC5646766
OpenAlexW2765880923

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.