Cardiovascular disease (CVD) is the leading cause of death worldwide, especially in developed countries, and atherosclerosis (AS) is the common pathological basis of many cardiovascular diseases (CVDs) such as coronary heart disease (CHD). The role of the gut microbiota in AS has begun to be appreciated in recent years. Trimethylamine N-oxide (TMAO), an important gut microbe-dependent metabolite, is generated from dietary choline, betaine, and L-carnitine. Multiple studies have suggested a correlation between plasma TMAO levels and the risk of AS. However, the mechanism underlying this relationship is still unclear. In this review, we discuss the TMAO-involved mechanisms of atherosclerotic CVD from the perspective of inflammation, inflammation-related immunity, cholesterol metabolism, and atherothrombosis. We also summarize available clinical studies on the role of TMAO in predicting prognostic outcomes, including major adverse cardiovascular events (MACE), in patients presenting with AS. Finally, since TMAO may be a novel therapeutic target for AS, several therapeutic strategies including drugs, dietary, etc. to lower TMAO levels that are currently being explored are also discussed.

Abstract. Genomic and radiomic imaging profiles of invasive breast carcinomas from The Cancer Genome Atlas and The Cancer Imaging Archive were integrated and a comprehensive analysis was conducted to predict clinical outcomes using the radiogenomic features. Variable selection via LASSO and logistic regression were used to select the most-predictive radiogenomic features for the clinical phenotypes, including pathological stage, lymph node metastasis, and status of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Cross-validation with receiver operating characteristic (ROC) analysis was performed and the area under the ROC curve (AUC) was employed as the prediction metric. Higher AUCs were obtained in the prediction of pathological stage, ER, and PR status than for lymph node metastasis and HER2 status. Overall, the prediction performances by genomics alone, radiomics alone, and combined radiogenomics features showed statistically significant correlations with clinical outcomes; however, improvement on the prediction performance by combining genomics and radiomics data was not found to be statistically significant, most likely due to the small sample size of 91 cancer cases with 38 radiomic features and 144 genomic features. © 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)

Supplementary data are available at Bioinformatics online.

Atherosclerosis and its associated cardiovascular diseases (CVDs) are serious threats to human health and have been reported to be associated with the gut microbiota. Recently, the role of berberine (BBR) in atherosclerosis and gut microbiota has begun to be appreciated. The purposes of this study were to observe the effects of high or low doses of BBR on atherosclerosis and gut microbiota modulation, and to explore their correlation in ApoE −/− mice fed a high-fat diet. A significant decrease in atherosclerotic lesions was observed after treatment with BBR, with the effect of the high dose being more obvious. Both BBR treatments significantly reduced total cholesterol, APOB100, and very low-density lipoprotein cholesterol levels but levels of high/lowdensity lipoprotein cholesterol and lipoprotein (a) were only reduced by high-dose BBR. Decreased pro-inflammatory cytokines tumor necrosis factor-alpha, interleukin (IL)-1β, IL-6 and increased anti-inflammatory IL-10 and adiponectin levels were observed in the high-dose BBR group, but no decrease in IL-6 or increase in IL-10 was evident using the low-dose of BBR. 16S rRNA sequencing showed that BBR significantly altered the community compositional structure of gut microbiota. Specifically, BBR enriched the abundance of Roseburia, Blautia, Allobaculum, Alistipes, and Turicibacter, and changed the abundance of Bilophila. These microbiota displayed good anti-inflammatory effects related to the production of short-chain fatty acids (SCFAs) and were related to glucolipid metabolism. Alistipes and Roseburia were significantly enriched in high-dose BBR group while Blautia and Allobaculum were more enriched in low-dose, and Turicibacter was enriched in both BBR doses. Metagenomic analysis further showed an elevated potential for lipid and glycan metabolism and synthesis of SCFAs, as well as reduced potential of TMAO production after BBR treatment. The findings demonstrate that both high and low-dose BBR can improve serum lipid and systemic inflammation levels, and alleviate atherosclerosis induced by high-fat diet in ApoE −/− mice. The effects are more pronounced for the high dose. This anti-atherosclerotic effect of BBR may be partly attributed to changes in composition and functions of gut microbiota which may be associated with anti-inflammatory and metabolism of glucose and lipid. Notably, gut microbiota alterations showed different sensitivity to BBR dose.

There has been an increasing interest in using interval-based Bayesian designs for dose finding, one of which is the modified toxicity probability interval (mTPI) method. We show that the decision rules in mTPI correspond to an optimal rule under a formal Bayesian decision theoretic framework. However, the probability models in mTPI are overly sharpened by the Ockham's razor, which, while in general helps with parsimonious statistical inference, leads to suboptimal decisions in small-sample inference such as dose finding. We propose a new framework that blunts the Ockham's razor, and demonstrate the superior performance of the new method, called mTPI-2. An online web tool is provided for users who can generate the design, conduct clinical trials, and examine operating characteristics of the designs through big data and crowd sourcing.

The findings from this meta-analysis strongly support that the conditions of EBW, overweight, and obesity are all associated with an increased risk of endometrial cancer. Also, the strength of the association increases with increasing BMI.

Results:We develop TCGA-Assembler 2 (TA2) to automatically download and integrate data from GDC and CPTAC. We make substantial improvement on the functionality of TA2 to enhance user experience and software performance. TA2 together with its previous version have helped more than 2,000 researchers from 64 countries to access and utilize TCGA and CPTAC data in their research. Availability of TA2 will continue to allow existing and new users to conduct reproducible research based on TCGA and CPTAC data.

An activity-directed fractionation and purification process was used to isolate antitumor compounds from the roots of Belamcanda chinensis (L.) DC. The ethyl acetate extract showed greater antitumor activities than the other extracts, consequently leading to the isolation of 18 compounds identified as -sitosterol (1), dausterol (2), quercetin (3), kampferol (4), shikimic acid (5), gallic acid (6), ursolic acid (7), betulin (8), betulonic acid (9), betulone (10), tectoridin (11), irisflorentin (12), 4′,5,6-trihydroxy-7-methoxyisoflavone (13), tectorigenin (14), irilins A (15), iridin (16), irigenin (17), and iristectongenin A (18). Compounds 3-10, 13, and 15 were isolated from B. chinensis for the first time. Compounds 4 and 7-10 showed potent cytotoxic activities against PC3, MGC-803, Bcap-37, and MCF-7 cell lines. The mechanism of the antitumor action of compound 7 was preliminarily investigated through acridine orange/ethidium bromide (AO/EB) staining, Hoechst 33258 staining, and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay, which indicated the growth inhibition of MGC-803 cells via the induction of tumor cell apoptosis.