Evidence map›Paper›PMID 32295081›Full record

ReviewCells2020

Insights from In Vivo Studies of Cellular Senescence.

Luis I Prieto, Sara I Graves, Darren J Baker

Abstract readReview
In one paragraph

Review in Cells, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Senolytic Therapy as a Preventive Strategy for Spine Degeneration and Pain.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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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.

Luis I PrietoDepartment of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN 55905, USA.
Sara I GravesDepartment of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN 55905, USA.
Darren J BakerDepartment of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0001-9006-1939

Funding

The contribution of p16-expressing cells to tauopathyR01AG053229 · NIA · MAYO CLINIC ROCHESTER · PI BAKER, DARREN · 2017 to 2021
$2.0M
NIA NIH HHS R01 AG053229
6 · The paper itself

Abstract

Cellular senescence is the dynamic process of durable cell-cycle arrest. Senescent cells remain metabolically active and often acquire a distinctive bioactive secretory phenotype. Much of our molecular understanding in senescent cell biology comes from studies using mammalian cell lines exposed to stress or extended culture periods. While less well understood mechanistically, senescence in vivo is becoming appreciated for its numerous biological implications, both in the context of beneficial processes, such as development, tumor suppression, and wound healing, and in detrimental conditions, where senescent cell accumulation has been shown to contribute to aging and age-related diseases. Importantly, clearance of senescent cells, through either genetic or pharmacological means, has been shown to not only extend the healthspan of prematurely and naturally aged mice but also attenuate pathology in mouse models of chronic disease. These observations have prompted an investigation of how and why senescent cells accumulate with aging and have renewed exploration into the characteristics of cellular senescence in vivo. Here, we highlight our molecular understanding of the dynamics that lead to a cellular arrest and how various effectors may explain the consequences of senescence in tissues. Lastly, we discuss how exploitation of strategies to eliminate senescent cells or their effects may have clinical utility.

Indexed as

AgingAnimalsCellular SenescenceMiceMice, Transgenicagingmousesenescencesenolytics

Identifiers

PMID32295081
PMCPMC7226957

What OpenQuestion holds

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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.