In recent years,a growing body of research has demonstrated that acupuncture can be used to effectively treat a diverse range of diseases,including functional gastrointestinal disorders,cardiovascular diseases,as well as anxiety and depression,through the modulation of the paraventricular hypothalamic nucleus(PVN).Acupuncture may exert its therapeutic effect either by modulating specific neurons within the PVN,such as corticotropin releasing hormone(CRH)neurons,or by regulating the release of hormones,such as oxytocin(OXT)and vasopressin(VP),and the activity of neural circuits associated with the PVN.This review summarizes the mechanisms by which PVN is involved in acupuncture treatment,including its regulatory mechanisms in gastrointestinal diseases,cardiovascular diseases,and negative emotions and pain.Future research should be conducted to further explore the precise mechanisms by which acupuncture regulates PVN to treat diseases,focusing on clarifying the specific processes of signaling pathway transduction,and exploring the specific effects of acupunture of different acupoint combinations and stimulation frequencies and intensity on PVN.

Malaria still threatens global health seriously today. While the current discoveries of antimalarials are almost totally focused on single mode-of-action inhibitors, multi-targeting inhibitors are highly desired to overcome the increasingly serious drug resistance. Here, we performed a structure-based drug design on mitochondrial respiratory chain of

Coronary artery disease (CAD) is a complex human disease, involving multiple genes and their nonlinear interactions, which often act in a modular fashion. Genome-wide single nucleotide polymorphism (SNP) profiling provides an effective technique to unravel these underlying genetic interplays or their functional involvements for CAD. This study aimed to identify the susceptible pathways and modules for CAD based on SNP omics. First, the Wellcome Trust Case Control Consortium (WTCCC) SNP datasets of CAD and control samples were used to assess the joint effect of multiple genetic variants at the pathway level, using logistic kernel machine regression model. Then, an expanded genetic network was constructed by integrating statistical gene–gene interactions involved in these susceptible pathways with their protein–protein interaction (PPI) knowledge. Finally, risk functional modules were identified by decomposition of the network. Of 276 KEGG pathways analyzed, 6 pathways were found to have a significant effect on CAD. Other than glycerolipid metabolism, glycosaminoglycan biosynthesis, and cardiac muscle contraction pathways, three pathways related to other diseases were also revealed, including Alzheimer’s disease, non-alcoholic fatty liver disease, and Huntington’s disease. A genetic epistatic network of 95 genes was further constructed using the abovementioned integrative approach. Of 10 functional modules derived from the network, 6 have been annotated to phospholipase C activity and cell adhesion molecule binding, which also have known functional involvement in Alzheimer’s disease. These findings indicate an overlap of the underlying molecular mechanisms between CAD and Alzheimer’s disease, thus providing new insights into the molecular basis for CAD and its molecular relationships with other diseases.