Evidence mapPaperPMID 42089944Full record

ReviewBiogerontology2026

Towards a context-aware framework for cellular senescence.

Arnab Nath, Parul Mehrotra, Chiranjib Bhattacharyya, Deepak Kumar Saini

Abstract readReview
PubMed Publisher
In one paragraph

Review in Biogerontology, 2026. 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
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

0 citing papers in PubMed.

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

4 authors.

Arnab NathDepartment of Developmental Biology and Genetics, Indian Institute of Science, Bangalore, Karnataka, 560012, India.ORCID http://orcid.org/0000-0002-6514-385X
Parul MehrotraSchool of Biological Sciences, Indian Institute of Technology, New Delhi, India.ORCID http://orcid.org/0000-0002-2755-9336
Chiranjib BhattacharyyaDepartment of Computer Science and Automation, Indian Institute of Science, Bangalore, Karnataka, 560012, India.
Deepak Kumar SainiDepartment of Developmental Biology and Genetics, Indian Institute of Science, Bangalore, Karnataka, 560012, India. deepaksaini@iisc.ac.in.ORCID http://orcid.org/0000-0001-6671-7256

Funding

Indian Council of Medical Research IIRPSG-2024-01-02485Science and Engineering Research Board CRG/2022/005024
6 · The paper itself

Abstract

From a cellular perspective, senescence has been considered a binary state, wherein cells are either senescent or not. This reductionist notion, often defined as irreversible growth arrest, has guided efforts to identify universal biomarkers and senolytics, but both have consistently eluded us. This outcome is not surprising, given that the biological nature of senescence may not be strictly irreversible; the accumulated evidence suggests that growth arrest can become unstable over time, with cells acquiring alterations, occasionally regaining proliferative capacity, or undergoing partial reprogramming, and exhibiting a heterogeneous spectrum of phenotypes ("senotypes") influenced by tissue types, stressors, temporal dynamics, and disease states. We propose that such a shift towards a dynamic spectrum of cellular states, is necessary to develop tailored strategies for context-specific signatures rather than a hypothetical state of cells that qualify for universal markers. The future of senescence research should thus focus on mapping, understanding, and utilising the spectrum of senescence states to mitigate its onset or modulate its progression.

Indexed as

AgingCellular SenescenceAnimalsBiomarkersHumansPhenotypeBiomarkersCellular senescenceContext-dependent biomarkersSenescence heterogeneitySenescence spectrumSenolytic strategies

Identifiers

PMID42089944

What Socratic 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 Socratic graph.