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Science Advances
Article . 2025 . Peer-reviewed
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Science Advances
Article . 2025
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Senolytic treatment for low back pain

Authors: Mannarino, Matthew; Cherif, Hosni; Ghazizadeh, Saber; Martinez, Oliver Wu; Sheng, Kai; Cousineau, Elsa; Lee, Seunghwan; +8 Authors

Senolytic treatment for low back pain

Abstract

Senescent cells (SnCs) accumulate because of aging and external cellular stress throughout the body. They adopt a senescence-associated secretory phenotype (SASP) and release inflammatory and degenerative factors that actively contribute to age-related diseases, such as low back pain (LBP). The senolytics, o -vanillin and RG-7112, remove SnCs in human intervertebral discs (IVDs) and reduce SASP release, but it is unknown whether they can treat LBP. sparc −/− mice, with LBP, were treated orally with o -vanillin and RG-7112 as single or combination treatments. Treatment reduced LBP and SASP factor release and removed SnCs from the IVD and spinal cord. Treatment also lowered degeneration scores in the IVDs, improved vertebral bone quality, and reduced the expression of pain markers in the spinal cord. Together, our data suggest RG-7112 and o -vanillin as potential disease-modifying drugs for LBP and other painful disorders linked to cell senescence.

Country
France
Keywords

Mice, Knockout, Male, [SDV.MHEP.RSOA] Life Sciences [q-bio]/Human health and pathology/Rhumatology and musculoskeletal system, [SDV.NEU.NB] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology, Mice, Disease Models, Animal, Spinal Cord, Senotherapeutics, [SDV.SP.PHARMA] Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology, Animals, Humans, Biomedicine and Life Sciences, Intervertebral Disc, Low Back Pain, Cellular Senescence

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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Top 10%
Top 10%
Green
gold
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