BackgroundMetabolic syndrome (MS) comprises a set of conditions that are risk factors for cardiovascular diseases and diabetes. Numerous epidemiological studies on MS have been conducted, but there has not been a systematic analysis of the prevalence of MS in the Chinese population. Therefore, the aim of this study was to estimate the pooled prevalence of MS among subjects in Mainland China.MethodsWe performed a systematic review by searching both English and Chinese literature databases. Random or fixed effects models were used to summarize the prevalence of MS according to statistical tests for heterogeneity. Subgroup, sensitivity, and meta-regression analyses were performed to address heterogeneity. Publication bias was evaluated using Egger’s test.ResultsThirty-five papers were included in the meta-analysis, with a total population of 226,653 Chinese subjects. Among subjects aged 15 years and older, the pooled prevalence was 24.5 % (95 % CI: 22.0–26.9 %). By sex, the prevalences were 19.2 % (95 % CI: 16.9–21.6 %) in males and 27.0 % (95 % CI: 23.5–30.5 %) in females. The pooled prevalence of MS increased with age (15–39 years: 13.9 %; 40–59 years: 26.4 %; and ≥60 years: 32.4 %). Individuals living in urban areas (24.9 %, 95 % CI: 18.5–31.3 %) were more likely to suffer from MS than those living in rural areas (19.2 %, 95 % CI: 14.8–23.7 %). Hypertension was the most prevalent component of MS in males (52.8 %), while the most prevalent component of MS for females was central obesity (46.1 %).ConclusionsOur systematic review suggested a high prevalence of MS among subjects in Mainland China, indicating that MS is a serious public health problem. Therefore, more attention should be paid to the prevention and control of MS.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-016-2870-y) contains supplementary material, which is available to authorized users.

Background: Ginsenoside Rg3, a saponin extracted from ginseng, inhibits angiogenesis. The combination of low-dose chemotherapy and anti-angiogenic inhibitors suppresses growth of experimental tumors more effectively than conventional therapy or anti-angiogenic agent alone. The present study was designed to evaluate the efficacy of low-dose gemcitabine combined with ginsenoside Rg3 on angiogenesis and growth of established Lewis lung carcinoma in mice.

Gut microbiota refers to the diverse community of more than 100 trillion microorganisms residing in our intestines. It is now known that any shift in the composition of gut microbiota from that present during the healthy state in an individual is associated with predisposition to multiple pathological conditions, such as diabetes, autoimmunity, and even cancer. Currently, therapies targeting programmed cell death protein 1/programmed cell death 1 ligand 1 or cytotoxic T-lymphocyte antigen-4 are the focus of cancer immunotherapy and are widely applied in clinical treatment of various tumors. Owing to relatively low overall response rate, however, it has been an ongoing research endeavor to identify the mechanisms or factors for improving the therapeutic efficacy of these immunotherapies. Other than causing mutations that affect gene expression, some gut bacteria may also activate or repress the host's response to immune checkpoint inhibitors. In this review, we have described recent advancements made in understanding the regulatory relationship between gut microbiome and cancer immunotherapy. We have also summarized the potential molecular mechanisms behind this interaction, which can serve as a basis for utilizing different kinds of gut bacteria as promising tools for reversing immunotherapy resistance in cancer.

To develop injectable formulation and improve the stability of curcumin (Cur), Cur was encapsulated into monomethyl poly (ethylene glycol)-poly (ε-caprolactone)-poly (trimethylene carbonate) (MPEG-P(CL-co-TMC)) micelles through a single-step solid dispersion method. The obtained Cur micelles had a small particle size of 27.6 ± 0.7 nm with polydisperse index (PDI) of 0.11 ± 0.05, drug loading of 14.07 ± 0.94%, and encapsulation efficiency of 96.08 ± 3.23%. Both free Cur and Cur micelles efficiently suppressed growth of CT26 colon carcinoma cells in vitro. The results of in vitro anticancer studies confirmed that apoptosis induction and cellular uptake on CT26 cells had completely increased in Cur micelles compared with free Cur. Besides, Cur micelles were more effective in suppressing the tumor growth of subcutaneous CT26 colon in vivo, and the mechanisms included the inhibition of tumor proliferation and angiogenesis and increased apoptosis of tumor cells. Furthermore, few side effects were found in Cur micelles. Overall, our findings suggested that Cur micelles could be a stabilized aqueous formulation for intravenous application with improved antitumor activity, which may be a potential treatment strategy for colon cancer in the future.

With the rapid development of new technologies, including artificial intelligence and genome sequencing, radiogenomics has emerged as a state-of-the-art science in the field of individualized medicine. Radiogenomics combines a large volume of quantitative data extracted from medical images with individual genomic phenotypes and constructs a prediction model through deep learning to stratify patients, guide therapeutic strategies, and evaluate clinical outcomes. Recent studies of various types of tumors demonstrate the predictive value of radiogenomics. And some of the issues in the radiogenomic analysis and the solutions from prior works are presented. Although the workflow criteria and international agreed guidelines for statistical methods need to be confirmed, radiogenomics represents a repeatable and cost-effective approach for the detection of continuous changes and is a promising surrogate for invasive interventions. Therefore, radiogenomics could facilitate computer-aided diagnosis, treatment, and prediction of the prognosis in patients with tumors in the routine clinical setting. Here, we summarize the integrated process of radiogenomics and introduce the crucial strategies and statistical algorithms involved in current studies.