Bayesian consensus clustering for multivariate longitudinal data

In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co-existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker-specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data.     

Analysis on internal mechanism of zedoary turmeric in treatment of liver cancer based on pharmacodynamic substances and pharmacodynamic groups

Zedoary tumeric (Curcumae Rhizoma, Ezhu in Chinese) has a long history of application and has great potential in the treatment of liver cancer. The anti liver cancer effect of zedoary tumeric depends on the combined action of multiple pharmacodynamic substances. In order to clarify the specific mechanism of zedoary tumeric against liver cancer, this paper first analyzes the mechanism of its single pharmacodynamic substance against liver cancer, and then verifies the joint anti liver cancer mechanism of its "pharmacodynamic group". By searching the research on the anti hepatoma effect of active components of zedoary tumeric in recent years, we found that pharmacodynamic substances, including curcumol, zedoarondiol, curcumenol, curzerenone, curdione, curcumin, germacrone, β-elemene, can act on multi-target and multi-channel to play an anti hepatoma role. For example, curcumin can regulate miR, GLO1, CD133, VEGF, YAP, LIN28B, GPR81, HCAR-1, P53 and PI3K/Akt/mTOR, HSP70/TLR4 and NF-κB. Wnt/TGF/EMT, Nrf2/Keap1, JAK/STAT and other pathways play an anti hepatoma role. Network pharmacological analysis showed that the core targets of the "pharmacodynamic group" for anti-life cancer are AKT1, EGFR, MAPK8, etc, and the core pathways are neuroactive live receiver interaction, nitrogen metabolism, HIF-1 signaling pathway, etc. At the same time, by comparing and analyzing the relationship between the specific mechanisms of pharmacodynamic substance and "pharmacodynamic group", it is found that they have great reference significance in target, pathway, biological function, determination of core pharmacodynamic components, formation of core target protein interaction, in-depth research of single pharmacodynamic substance, increasing curative effect and so on. By analyzing the internal mechanism of zedoary tumeric pharmacodynamic substance and "pharmacodynamic group" in the treatment of liver cancer, this paper intends to provide some ideas and references for the deeper pharmacological research of zedoary tumeric and the relationship between pharmacodynamic substance and "pharmacodynamic group".