Evidence map›Paper›PMID 40279419›Full record

ArticleScience advances2025

Single-cell morphology encodes functional subtypes of senescence in aging human dermal fibroblasts.

Pratik Kamat, Nico Macaluso, Yukang Li, Anshika Agrawal, Aaron Winston, Lauren Pan, Teasia Stewart, Bartholomew Starich, Nicholas Milcik, Chanhong Min and 4 more

Abstract read
In one paragraph

Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Behavioral and Functional Profiling ofbioRxiv : the preprint server for biology · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Monocytes are biological sensors of aging and frailty in humans.bioRxiv : the preprint server for biology · 2026
    Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Review
  13. Article
  14. The states of senescent cells.Biochemical Society transactions · 2025
    Review
  15. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Pratik KamatDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0002-2028-6136
Nico MacalusoDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0002-1648-1588
Yukang LiInstitute for Nanobiotechnology, Johns Hopkins University, Baltimore, MD, USA.
Anshika AgrawalDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA.
Aaron WinstonDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA.
Lauren PanDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.ORCID 0009-0007-5910-1921
Teasia StewartDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA.
Bartholomew StarichDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0002-0006-0236
Nicholas MilcikInstitute for Nanobiotechnology, Johns Hopkins University, Baltimore, MD, USA.ORCID 0009-0006-1072-491X
Chanhong MinInstitute for Nanobiotechnology, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0003-1018-9057
Pei-Hsun WuDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0002-7371-2960
Jeremy WalstonDepartment of Geriatric Medicine and Gerontology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Jean FanDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0002-0212-5451
Jude M PhillipDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0002-2999-5254

Funding

Technological Assessment and Solutions Core - RC4P30AG021334 · NIA · JOHNS HOPKINS UNIVERSITY · PI Jeremy D Walston · 2003 to 2026
$33.2M
T32: Predoctoral and Postdoctoral Training Program in Nanotechnology for Cancer ResearchT32CA153952 · NCI · JOHNS HOPKINS UNIVERSITY · PI Denis Wirtz · 2015 to 2026
$3.5M
Computational methods for delineating subcellular and cellular spatial transcriptional heterogeneity along developmental trajectoriesR35GM142889 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI FAN, JEAN · 2021 to 2025
$2.0M
Three-dimensional maps of senescence in the human pancreasUH3CA275681 · NCI · JOHNS HOPKINS UNIVERSITY · PI WU, PEI-HSUN · 2024 to 2025
$1.7M
Three-dimensional maps of senescence in the human pancreasUG3CA275681 · NCI · JOHNS HOPKINS UNIVERSITY · PI WU, PEI-HSUN · 2022 to 2023
$1.1M
Defining a biophysical basis for cell types, cell states and cellular heterogeneity at single-cell resolutionR35GM157099 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI Jude Marvin Phillip · 2025 to 2026
$762k
NCI NIH HHS T32 CA153952NCI NIH HHS UG3 CA275681NCI NIH HHS UH3 CA275681NIA NIH HHS P30 AG021334NIGMS NIH HHS R35 GM142889NIGMS NIH HHS R35 GM157099
6 · The paper itself

Abstract

Cellular senescence, a hallmark of aging, reveals context-dependent phenotypes across multiple biological length scales. Despite its mechanistic importance, identifying and characterizing senescence across cell populations is challenging. Using primary dermal fibroblasts, we combined single-cell imaging, machine learning, several induced senescence conditions, and multiple protein biomarkers to define functional senescence subtypes. Single-cell morphology analysis revealed 11 distinct morphology clusters. Among these, we identified three as bona fide senescence subtypes (C7, C10, and C11), with C10 exhibiting the strongest age dependence within an aging cohort. In addition, we observed that a donor's senescence burden and subtype composition were indicative of susceptibility to doxorubicin-induced senescence. Functional analysis revealed subtype-dependent responses to senotherapies, with C7 being most responsive to the combination of dasatinib and quercetin. Our single-cell analysis framework, SenSCOUT, enables robust identification and classification of senescence subtypes, offering applications in next-generation senotherapy screens, with potential toward explaining heterogeneous senescence phenotypes based on the presence of senescence subtypes.

Indexed as

AgingCellular SenescenceDermisFibroblastsSingle-Cell AnalysisSkinAdultAgedBiomarkersCells, CulturedDasatinibDoxorubicinFemaleHumansMaleMiddle AgedBiomarkersDasatinibDoxorubicinSenotherapeutics

Identifiers

PMID40279419
PMCPMC12024660

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

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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.