Evidence map›Paper›PMID 33752266›Full record

ReviewThe FEBS journal2022

Computational modelling of stem cell-niche interactions facilitates discovery of strategies to enhance tissue regeneration and counteract ageing.

Ilya Potapov, Laura García-Prat, Srikanth Ravichandran, Pura Muñoz-Cánoves, Antonio Del Sol

Open access · greenAbstract readReview
In one paragraph

Review in The FEBS journal, 2022. 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
0.3field-weighted citation impact, top 50% 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

4 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Review
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

5 authors at 4 institutions in 3 countries.

Ilya PotapovComputational Biology Group, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg.ORCID 0000-0003-3800-8895
Laura García-PratDepartment of Experimental and Health Sciences, CIBER on Neurodegenerative Diseases (CIBERNED), Pompeu Fabra University (UPF), Barcelona, Spain.
Srikanth RavichandranComputational Biology Group, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg.
Pura Muñoz-CánovesDepartment of Experimental and Health Sciences, CIBER on Neurodegenerative Diseases (CIBERNED), Pompeu Fabra University (UPF), Barcelona, Spain.
Antonio Del SolComputational Biology Group, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg.
University of Luxembourg · LUBiomedical Research Networking Center on Neurodegenerative Diseases · ESCIC bioGUNE · ESSpanish National Centre for Cardiovascular Research · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The stem cell niche is a specialized microenvironment for stem cells in an adult tissue. The niche provides cues for the maintenance and regulation of stem cell activities and thus presents a target for potential rejuvenating strategies. García-Prat et al. found that in the heterogeneous population of quiescent stem cells of skeletal muscles, a fraction of cells responsible for regeneration and having genuine 'stemness' properties deteriorates only in extremely old age. An essential tool used in this analysis of stem cell-niche interactions is the computational tool, NicheHotSpotter, which proved to be instrumental for identifying niche and cell signalling factors that contribute to the maintenance of the pool of genuine quiescent stem cells. NicheHotSpotter predicts candidate factors by analysing signalling interactome and gene regulatory network data in combination with expression profiles. The effect of the niche environment on stem cells is modelled as a mean field of niche cues that induce sustained activation or inhibition of signalling pathways. In this way, NicheHotSpotter has been successful in delineating novel strategies to enhance stemness, which may rejuvenate skeletal muscle cells at the extreme old age.

Indexed as

Stem Cell NicheStem CellsAdultAgingComputer SimulationHumansMuscle, Skeletalageingcomputational modellinglimb musclestem cellstissue regeneration

Identifiers

PMID33752266
PMCPMC9292515
OpenAlexW3137921885

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.