Cerebral ischemia is a cerebrovascular disease with symptoms caused by insufficient blood or oxygen supply to the brain. When blood supplied is restored after cerebral ischemia, secondary brain injury may occur, which is called cerebral ischemia-reperfusion injury (CIRI). In this process, the Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling pathway plays an important role. It mediates neuroinflammation and participates in the regulation of physiological activities, such as cell proliferation, differentiation, and apoptosis. After CIRI, M1 microglia is activated and recruited by the damaged tissue. The inflammatory factors are produced by M1 microglia through the JAK/STAT pathway, eventually leading to cell apoptosis. Meanwhile, the JAK2/STAT3 signaling pathway and the expression of lipocalin-2 and caspase-3 could increase. In the pathway, phosphorylated JAK2 and phosphorylated STAT3 function of 2 ways. They not only promote the proliferation of neurons, but also affect the differentiation direction of neural stem cells by further acting on the Notch signaling pathway. Recently, traditional Chinese medicine (TCM) is a key player in CIRI, through JAK2, STAT3, STAT1 and their phosphorylation. Therefore, the review focuses on the JAK/STAT signaling pathway and its relationship with CIRI as well as the influence of the TCM on this pathway. It is aimed at providing the basis for future clinical research on the molecular mechanism of TCM in the treatment of CIRI.

Tetrastigma hemsleyanum (Tetrastigma hemsleyanum Diels et Gilg) is a valuable traditional Chinese medicine with various applications. In this study, we aimed to optimize the extraction process for the total extraction yield of five flavonoid components, namely kaempferol, quercetin, rutin, kaempferol-3-O-rutinoside, and astragalin from the Tetrastigma hemsleyanum root (THR), and explore its potential molecular mechanisms in treating oxidative diseases as well as antioxidant activity. To achieve these objectives, we employed the genetic algorithm-back propagation neural network (GA-BPNN), the Box-Behnken design (BBD) with 4-factors and 3-levels to establish the optimal ethanol extraction process for the total extraction yield of the 5 components. Using public databases, the “component core targets-disease core target genes” networks were built, as well as molecular docking. Furthermore, DPPH was used to examine the antioxidant activity of the extracts obtained from THR under the optimal extraction process. The experimental value of the total extraction yield of the 5 components achieved a maximum of 788.12 mg/kg when the ethanol concentration was 73%, the solid-liquid ratio was 26 g/mL, and the ultrasonic duration was 30 min, and the ultrasonic temperature was 76 °C. When docked with protein molecules such as 6Y8I, quercetin, and other components received moderate to high scores. When the total concentration of the 5 components was 3.033 μg/mL, the DPPH radical scavenging rate was 89.81%. Compared with the BBD method, the GA-BPNN method is more efficient and reliable for optimizing the extraction process of active ingredients in THR because of its good data-fitting ability.

We extracted Sal B and TIIA from Salvia miltiorrhiza using enzymatic-assisted ethanol extraction. ACONN predicted optimal process conditions. Enzymolysis and alcohol extraction were used, optimizing conditions and evaluating antioxidant activity. ACONN analyzed data and ACO optimized conditions. Lab verification comprehensively evaluated the conditions. The correlation between Sal B, TIIA, and their antioxidant activities was examined. Weights of 0.5739 and 0.4260 evaluated Sal B and TIIA. ACONN had a 97.46% fitting degree. Optimized extraction conditions improved yield and quality, yielding a comprehensive evaluation value of 27.69 with 4.46% average errors. This approach enhances extraction and compound quality. Antioxidant activity strongly correlated with component yield, influenced by extraction conditions. ACONN-optimized extraction improved Sal B and TIIA yield and quality, with potential as natural antioxidants. Integrating machine learning and optimization algorithms in industrial extraction enhances efficiency and environmental preservation.

Recent reports have shown that metabolites derived from gut microbiota play a vital role in intestinal diseases, immune regulation, and neuroinflammation. Nowadays, calycosin has been revealed the protective mechanism from different perspectives on cerebral ischemia-reperfusion injury (CIRI), while the effect of gut microbiota-bile acid-farnesoid X receptor (FXR) axis on the inflammatory protection of CIRI has not been explored. To this end, we established a middle cerebral artery occlusion (MCAO) model firstly to assess the protection of calycosin in CIRI through neurological deficit scoring, TTC staining, and HE staining. Secondly, 16s RNA sequencing, ELISA, real-time qPCR, Western blot, and total bile acid (TBA) detection kit were utilized to detect the pharmacology of calycosin on MCAO rats. Our data indicated that calycosin could significantly improve nerve function scores, reduce cerebral infarction volume, lower serum levels of IL-10, IL-17 inflammatory factors, and TBA, increase mRNA and protein levels of ZO-1 and Occludin in brain, as well as FXR, ZO-1 and Occludin levels in colon. In summary, calycosin can exert a neuroinflammatory protective effect on CIRI in rats via regulating the gut microbiota to improve bile acid metabolism.

Background: Non-alcoholic steatohepatitis (NASH) commonly complicates coronary artery disease (CAD), yet the interaction mechanism remains unclear. Our research seeks to investigate the common mechanisms and key signature genes between CAD and NASH.Methods: RNA sequence information for CAD and NASH was screened from the GEO database. Weighted gene co-expression network analysis (WGCNA) and differentially expressed gene analysis identified key genes, followed by functional enrichment analysis of these shared genes. Three machine learning methods—LASSO, random forest, and SVM-RFE—were used to identify signature genes. Gene set enrichment analysis (GSEA) was then performed to explore potential mechanisms associated with the signature genes. In addition, single-sample gene set enrichment analysis (ssGSEA) evaluated immune infiltration in CAD and NASH and its correlation with the signature genes.Results: WGCNA has revealed two key modules for CAD and NASH. The intersection of the CAD modules and their differential genes narrowed the key genes down to 2,808 shared genes. Finally, 44 shared genes were selected for both CAD and NASH. Kyoto Encyclopedia of Genes and Genomes analysis showed that these genes were primarily enriched in insulin resistance and inflammation pathways. Machine learning identified the signature genes BATF3, SOCS2, and GPER, all with ROC values above 0.7, validated in external datasets. GSEA revealed that these genes act through common mechanisms in CAD and NASH, regulating metabolic, inflammatory, and cardiovascular pathways. In addition, ssGSEA suggested their involvement in immune cell infiltration.Conclusion: BATF3, SOCS2, and GPER have emerged as promising gene candidates that may serve as biomarkers or potential therapeutic targets for CAD combined with NASH, linked to the regulation of metabolic, inflammatory, and cardiovascular pathways. We also identified insulin resistance and inflammation pathways as common mechanisms underlying both diseases.