Oxidative stress can cause the excessive generation of reactive oxygen species (ROS) and has various adverse effects on muscular mitochondria. Qiangji Jianli decoction (QJJLD) is an effective traditional Chinese medicine (TCM) that is widely applied to improve muscle weakness, and it has active constituents that prevent mitochondrial dysfunction. To investigate the protective mechanism of QJJLD against hydrogen peroxide‐ (H₂O₂‐) mediated mitochondrial dysfunction in L6 myoblasts. Cell viability was determined with MTT assay. Mitochondrial ultrastructure was detected by transmission electron microscope (TEM). ROS and mitochondrial membrane potential (MMP) were analyzed by fluorescence microscope and flow cytometry. The superoxide dismutase (SOD), glutathione peroxidase (GSH‐Px) activity, and malondialdehyde (MDA) level were determined by WST‐1, TBA, and DTNB methods, respectively. The mRNA and protein levels were measured by quantitative real‐time PCR (qRT‐PCR) and Western blot. The cell viability was decreased, and the cellular ROS level was increased when L6 myoblasts were exposed to H₂O₂. After treatment with QJJLD‐containing serum, the SOD and GSH‐Px activities were increased. MDA level was decreased concurrently. ROS level was decreased while respiratory chain complex activity and ATP content were increased in L6 myoblasts. MMP loss was attenuated. Mitochondrial ultrastructure was also improved. Simultaneously, the protein expressions of p‐AMPK, PGC‐1α, NRF1, and TFAM were upregulated. The mRNA and protein expressions of Mfn1/2 and Opa1 were also upregulated while Drp1 and Fis1 were downregulated. These results suggest that QJJLD may alleviate mitochondrial dysfunction through the regulation of mitochondrial dynamics and biogenesis, the inhibition of ROS generation, and the promotion of mitochondrial energy metabolism.

Due to the narrow therapeutic window and high mortality of ischemic stroke, it is of great significance to investigate its diagnosis and therapy. We employed weighted gene coexpression network analysis (WGCNA) to ascertain gene modules related to stroke and used the maSigPro R package to seek the time-dependent genes in the progression of stroke. Three machine learning algorithms were further employed to identify the feature genes of stroke. A nomogram model was built and applied to evaluate the stroke patients. We analyzed single-cell RNA sequencing (scRNA-seq) data to discern microglia subclusters in ischemic stroke. The RNA velocity, pseudo time, and gene set enrichment analysis (GSEA) were performed to investigate the relationship of microglia subclusters. Connectivity map (CMap) analysis and molecule docking were used to screen a therapeutic agent for stroke. A nomogram model based on the feature genes showed a clinical net benefit and enabled an accurate evaluation of stroke patients. The RNA velocity and pseudo time analysis showed that microglia subcluster 0 would develop toward subcluster 2 within 24 h from stroke onset. The GSEA showed that the function of microglia subcluster 0 was opposite to that of subcluster 2. AZ_628, which screened from CMap analysis, was found to have lower binding energy with Mmp12, Lgals3, Fam20c, Capg, Pkm2, Sdc4, and Itga5 in microglia subcluster 2 and maybe a therapeutic agent for the poor development of microglia subcluster 2 after stroke. Our study presents a nomogram model for stroke diagnosis and provides a potential molecule agent for stroke therapy.