Jinnan Huo

Hepatocellular carcinoma (HCC) lacks effective therapies. Compound Muji Granules (MJ), a traditional Chinese medicine, shows potential anti‐HCC activity, but its material basis and synergistic mechanism with exosomal delivery remain unclear. Using UPLC‐Q‐TOF‐MS/MS, 98 compounds were identified in MJ, including 25 blood‐absorbed and 23 tissue‐distributed components, with gallic acid (GA) as the core active constituent. hUC‐MSC‐derived exosomes (hUC‐MSCs‐Exos) were prepared and combined with MJ or GA. In HepG2 cells and rat HCC organoids, exosome‐combined treatment significantly reduced IC50, increased apoptosis and necrosis, and inhibited ATP production. Transcriptomic analysis and qPCR revealed regulation of the IL‐17/MAPK/p53 axis, with downregulation of MEK1/2, CREB1, and IL17A, and activation of TP53. These findings indicate that MJ exerts anti‐HCC efficacy through multi‐component synergy, with GA as the main material basis, and hUC‐MSCs‐Exos enhance these effects by modulating IL‐17/MAPK/p53 signaling, inhibiting tumor proliferation and energy metabolism, and promoting apoptosis.

Heart failure (HF) is an end stage of cardiovascular diseases. Tongmai Qiangshen Medicinal Liquor (TMQSJ) is an over‐the‐counter traditional Chinese medicinal liquor, but its efficacy‐related material basis and mechanisms in HF remain unclear. In this study, UPLC‐Q‐TOF‐MS/MS was used to characterize TMQSJ constituents and prototype compounds in rat plasma. HPLC fingerprinting, spectrum‐effect relationship analysis, single‐compound activity evaluation, and integrative bioinformatics were combined to screen efficacy‐related candidate quality markers and HF‐associated candidate genes. A total of 223 compounds were characterized, including 33 prototype plasma components. Chemometric analysis identified caffeic acid, Epimedin A, Epimedin B, Epimedin C, and icariin as characteristic constituents. Spectrum‐effect analysis based on 10 batches of TMQSJ and validation in DOX‐injured AC16 cells highlighted Epimedin A, Epimedin B, and Epimedin C. Among them, Epimedin A and Epimedin C showed prototype plasma exposure and were prioritized as efficacy‐related candidate quality markers. Integration of predicted targets of prototype plasma components with HF transcriptomic data and machine‐learning analysis identified BCL2L1, STAT3, HIF1A, MAPK8, and ESR1 as five candidate core genes. Immune cell estimation and molecular docking provided computational clues. Overall, this study establishes an integrated framework linking chemical quality, pharmacological association, in vivo exposure, and mechanistic prediction for TMQSJ quality evaluation.