The DOI matches its Crossref record; 285 of the 285 references it cites were found in a registry or an index.
Cellular senescence: the good, the bad and the unknown
Open accessAbstract
Cellular senescence is a ubiquitous process with roles in tissue remodelling, including wound repair and embryogenesis. However, prolonged senescence can be maladaptive, leading to cancer development and age-related diseases. Cellular senescence involves cell-cycle arrest and the release of inflammatory cytokines with autocrine, paracrine and endocrine activities. Senescent cells also exhibit morphological alterations, including flattened cell bodies, vacuolization and granularity in the cytoplasm and abnormal organelles. Several biomarkers of cellular senescence have been identified, including SA-βgal, p16 and p21; however, few markers have high sensitivity and specificity. In addition to driving ageing, senescence of immune and parenchymal cells contributes to the development of a variety of diseases and metabolic disorders. In the kidney, senescence might have beneficial roles during development and recovery from injury, but can also contribute to the progression of acute kidney injury and chronic kidney disease. Therapies that target senescence, including senolytic and senomorphic drugs, stem cell therapies and other interventions, have been shown to extend lifespan and reduce tissue injury in various animal models. Early clinical trials confirm that senotherapeutic approaches could be beneficial in human disease. However, larger clinical trials are needed to translate these approaches to patient care.
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“TNF-α is a prominent immune and inflammatory regulator involved in cellular senescence.55,56”
From A pilot study of senolytics to improve cognition and mobility in older adults at risk for Alzheimer's disease (2025) · cites this paper as [55]
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“Senescence is triggered by stressors such as telomere shortening, DNA damage, oxidative stress, and oncogenic signals5,6,7,8”
From Cellular senescence in human liver under normal aging and cancer (2026) · cites this paper as [5]
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“senescent cells accumulate in aged tissues,31,32,33 including the brain.34,35,36”
From Uncovering the signatures of aging and senescence in the human dorsolateral prefrontal cortex (2026) · cites this paper as [33]
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Metadata
- Authors
- Huang, W., Hickson, L. J., Eirin, A., Kirkland, J. L., & Lerman, L. O.
- Affiliations
- Mayo Clinic (US)
- Corresponding author
- Lerman, Lilach O.
- Venue
- Nature Reviews Nephrology
- Published
- 2022-08-03
- Volume
- 18
- Issue
- 10
- Pages
- 611-627
- ISSN
- 1745-8323 (ISSN-L)
- 1759-5061
- 1759-507X
- PMC
- PMC9362342
- OpenAlex
- W4289545008
- Cited by
- 1,150
- References
- 285
- Citations by year
- 2026: 251 · 2025: 399 · 2024: 333 · 2023: 157 · 2022: 10
- FWCI
- 31.77
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Nature Reviews Nephrology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Noaber Foundation
- National Institutes of Health (AG013925)
- National Institute on Aging (R21AG062104, R01AG013925, R33AG061456, R37AG013925)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK120292, R01DK122734)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Telomeres, Telomerase, and Senescence
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Health Sciences › Medicine › Geriatrics and Gerontology › Sirtuins and Resveratrol in Medicine
- Keywords
- cellular senescence, senescence-associated secretory phenotype, senolytics, senotherapeutics, kidney injury, chronic kidney disease, acute kidney injury, tumor suppression, age-related diseases, senescence biomarkers, p16, p21, SA-β-galactosidase, stem cell therapy, tissue remodeling, wound healing, embryonic development
- MeSH terms
- Senotherapeutics, Aging, Animals, Humans, Biomarkers, Cytokines, Cellular Senescence
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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