Evidence map›Paper›PMID 36010584›Full record

ArticleCells2022

Simple Detection of Unstained Live Senescent Cells with Imaging Flow Cytometry.

Marco Malavolta, Robertina Giacconi, Francesco Piacenza, Sergio Strizzi, Maurizio Cardelli, Giorgia Bigossi, Serena Marcozzi, Luca Tiano, Fabio Marcheggiani, Giulia Matacchione and 7 more

Open access · goldAbstract read
In one paragraph

Article in Cells, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.4field-weighted citation impact, top 10% 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

9 citing papers in PubMed, 20 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Cellular senescence in cancer: clinical detection and prognostic implications.Journal of experimental & clinical cancer research : CR · 2022
    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

17 authors at 5 institutions in 3 countries.

Marco MalavoltaAdvanced Technology Center for Aging Research, IRCCS INRCA, 60121 Ancona, Italy.ORCID 0000-0002-8442-1763
Robertina GiacconiAdvanced Technology Center for Aging Research, IRCCS INRCA, 60121 Ancona, Italy.ORCID 0000-0002-1468-2140
Francesco PiacenzaAdvanced Technology Center for Aging Research, IRCCS INRCA, 60121 Ancona, Italy.
Sergio StrizziAdvanced Technology Center for Aging Research, IRCCS INRCA, 60121 Ancona, Italy.ORCID 0000-0003-3203-4523
Maurizio CardelliAdvanced Technology Center for Aging Research, IRCCS INRCA, 60121 Ancona, Italy.
Giorgia BigossiAdvanced Technology Center for Aging Research, IRCCS INRCA, 60121 Ancona, Italy.ORCID 0000-0002-3445-4401
Serena MarcozziAdvanced Technology Center for Aging Research, IRCCS INRCA, 60121 Ancona, Italy.ORCID 0000-0001-5873-5753
Luca TianoDepartment of Life and Environmental Sciences, Polytechnical University of Marche, 60121 Ancona, Italy.ORCID 0000-0002-7519-7106
Fabio MarcheggianiDepartment of Life and Environmental Sciences, Polytechnical University of Marche, 60121 Ancona, Italy.
Giulia MatacchioneDepartment of Clinical and Molecular Sciences, DISCLIMO, Polytechnical University of Marche, 60121 Ancona, Italy.
Angelica GiulianiDepartment of Clinical and Molecular Sciences, DISCLIMO, Polytechnical University of Marche, 60121 Ancona, Italy.ORCID 0000-0002-8477-8519
Fabiola OlivieriDepartment of Clinical and Molecular Sciences, DISCLIMO, Polytechnical University of Marche, 60121 Ancona, Italy.
Ilaria CrivellariDepartment of Medicine (DAME), University of Udine, 33100 Udine, Italy.
Antonio Paolo BeltramiDepartment of Medicine (DAME), University of Udine, 33100 Udine, Italy.ORCID 0000-0002-0679-2710
Alessandro SerraLuminex B.V., Het Zuiderkruis 1, 5215 MV 's-Hertogenbosch, The Netherlands.
Marco DemariaEuropean Research Institute for the Biology of Ageing (ERIBA), University Medical Center Groningen (UMCG), 9713 AV Groningen, The Netherlands.ORCID 0000-0002-8429-4813
Mauro ProvincialiAdvanced Technology Center for Aging Research, IRCCS INRCA, 60121 Ancona, Italy.ORCID 0000-0002-0568-3002
Istituti di Ricovero e Cura a Carattere Scientifico · ITMarche Polytechnic University · ITUniversity of Udine · ITLuminex (United States) · USUniversity Medical Center Groningen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cellular senescence is a hallmark of aging and a promising target for therapeutic approaches. The identification of senescent cells requires multiple biomarkers and complex experimental procedures, resulting in increased variability and reduced sensitivity. Here, we propose a simple and broadly applicable imaging flow cytometry (IFC) method. This method is based on measuring autofluorescence and morphological parameters and on applying recent artificial intelligence (AI) and machine learning (ML) tools. We show that the results of this method are superior to those obtained measuring the classical senescence marker, senescence-associated beta-galactosidase (SA-β-Gal). We provide evidence that this method has the potential for diagnostic or prognostic applications as it was able to detect senescence in cardiac pericytes isolated from the hearts of patients affected by end-stage heart failure. We additionally demonstrate that it can be used to quantify senescence "in vivo" and can be used to evaluate the effects of senolytic compounds. We conclude that this method can be used as a simple and fast senescence assay independently of the origin of the cells and the procedure to induce senescence.

Indexed as

Artificial IntelligenceCellular SenescenceAgingBiomarkersFlow CytometryHumansBiomarkersartificial intelligence and machine learningcellular senescenceimaging flow cytometryreplicative senescencesenolytics

Identifiers

PMID36010584
PMCPMC9406876
OpenAlexW4291390269

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.