ReviewJournal of cellular and molecular medicine2026
Skin Aging: From Molecular Mechanisms to Therapeutic and Technological Innovations.
Review in Journal of cellular and molecular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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.
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0 citing papers in PubMed.
No citing paper in PubMed yet.
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Authors and funding
5 authors.
Funding
Abstract
Aging is a complex, pervasive biological process that causes irreversible declines in function across organ systems. The skin, the body's largest organ, interfaces directly with the external environment and undergoes aging driven by intrinsic (chronological) and extrinsic (environmental) factors, which result in functional deterioration and greater susceptibility to related disorders. Although numerous anti-aging strategies have been investigated, relatively few specifically target the skin. This review delineates the principal phenotypes and underlying mechanisms of skin aging. Phenotypic hallmarks include reduced regenerative capacity, chronic inflammation and impaired barrier function, whereas key mechanisms comprise oxidative stress, DNA damage, paracrine induction of cellular senescence and epigenetic alterations. The review evaluates recent research advances and associated clinical challenges in mitigating skin aging, with particular emphasis on pharmacological interventions and stem cell therapy. Finally, it briefly reviews delivery systems for natural anti-aging compounds and explores the potential of artificial intelligence (AI) to accelerate novel drug discovery.
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Registered trials
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.