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ObjectiveEmbryonic stem cell (ESC)-derived small extracellular vesicles (sEVs) exhibit considerable potential as an innovative therapeutic approach in the fields of regenerative medicine and disease management. This in vitro study aimed to evaluate the protective efficacy of ESC-sEVs against lead acetate (PbAc)-induced damage in cochlear spiral ganglion neurons (SGNs).MethodsCochlear SGNs of neonatal rats were primarily cultured and administrated with (i) serum-free medium (control); (ii) 25 μM PbAc; (iii) 0.05 μg/μl ESC-sEVs (ESC-sEVs); (iv) 25 μM PbAc + 0.05 μg/μl ESC-sEVs (PbAc + ESC-sEVs). After treatment, cell viability of SGNs was assessed by CCK-8 assay. The changes in levels of reactive oxygen species, lipid peroxides, and apoptosis were detected by immunofluorescence and flow cytometry. The protective mechanisms of ESC-sEVs against lead-induced SGNs damage were elucidated by RNA sequencing and western blot analysis.ResultsThe findings revealed that ESC-sEVs significantly increased the viability of SGNs subjected to PbAc exposure. Immunofluorescence and flow cytometry revealed that ESC-sEVs effectively attenuated oxidative stress, lipid peroxidation, and apoptotic processes in PbAc-exposed SGNs. Furthermore, RNA sequencing and western blot analysis demonstrated that ESC-sEVs activated the PI3 K/AKT signaling pathway, which plays a pivotal role in alleviating lead-induced neuronal injury.ConclusionIn conclusion, this study provides the first evidence supporting the therapeutic potential of ESC-sEVs in addressing lead-induced ototoxicity.
Pubmed ID: 40630004
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A commercial antibody supplier which supplies primary and secondary antibodies, biochemicals, proteins, peptides, lysates, immunoassays and other kits.
View all literature mentionsSoftware package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.
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