ObjectiveWe conducted a systematic review and meta-analysis aiming to assess the relationship between apolipoprotein E (APOE) gene ε2/ε3/ε4 polymorphism and breast cancer risk.MethodsYun-Long Liu and Hao-Min Zhang independently completed literature retrieval and data collection, and statistical analyses were performed by Stata. Individual odds ratio (OR) and 95% confidence interval (CI) were pooled in a random-effects model using the DerSimonian–Laird method. Heterogeneity was evaluated by I2 statistic at a significance level of 50%. Publication bias was assessed by Egger’s test.ResultsEleven articles including 2,074 breast cancer patients and 2,372 controls were summarized. Using the most common allele ε3 as a reference, the ε2 (OR =0.87, 95% CI =0.72–1.05, P=0.154, I2=0.0%) and ε4 (OR =1.07, 95% CI =0.80–1.42, P=0.654, I2=71.8%) alleles were not found to be significantly associated with breast cancer risk in the overall analyses. Subgroup analyses revealed that the comparison of allele ε4 with ε3 was significant in Asians (OR =1.58, 95% CI =1.17–6.32, P=0.003, I2=12.1%) and in studies that used the restriction fragment length polymorphism (RFLP) genotyping method (OR =1.27; 95% CI =1.01–1.61, P=0.045, I2=34.3%), and was marginally significant in hospital-based studies (OR =1.33; 95% CI =0.98–1.79, P=0.065, I2=30.2%), without heterogeneity. Moreover, the presence of the ε2 allele was significantly associated with breast cancer in small studies (total sample size <500) (OR =0.73, 95% CI =0.54–1.00, P=0.052, I2=0.0%) without heterogeneity. The Egger’s test indicated low probabilities of publication bias.ConclusionWe observed a significant association between APOE gene ε4 allele and breast cancer risk in Asian populations. Moreover, the findings of our subgroup analyses suggest that source of controls, genotyping platform, and sample size might be the potential causes of heterogeneity.

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Increasingly, individuals and companies are developing applications and selling them online. Competition between different companies has led to tens of thousands of applications being put on the market for users to choose from. There are numerous functions on the market to give app evaluation. For users, they do not need to contemplate how to select an app for a long time, because user comments and ratings can give them a clear instruction for user to select an app they need from abundant apps. As a result, we would like to explore the possibility. Hence, we think that we can make a prediction function for the prospect of the app market of whether we can make a prediction function for the app market, akin to a weather forecast or stock market forecast. Our group not only wants to know what the future of the app market is, but also want to find out why some high-quality apps are not getting the downloads they should. With the development of AR and VR technology, the future application will combine with these technology to bring user a immersive experience. In addition, high quality application without AR or VR are less competitive. We plan to answer these questions by using machine learning techniques.

Diabetic nephropathy (DN) is a severe microvascular complication of diabetes mellitus that is one of the main causes of end-stage renal disease, causing considerable health problems as well as significant financial burden worldwide. The pathological features of DN include loss of normal nephrons, massive fibroblast and myofibroblast hyperplasia, accumulation of extracellular matrix proteins, thickening of the basement membrane, and tubulointerstitial fibrosis. Renal fibrosis is a final and critical pathological change in DN. Although progress has been made in understanding the pathogenesis of DN fibrosis, current conventional treatment strategies may not be completely effective in preventing the disease's progression. Traditionally, Chinese herbal medicines (CHMs) composed of natural ingredients have been used for symptomatic relief of DN. Increasing numbers of studies have confirmed that CHMs can exert a renoprotective effect in DN, and antifibrosis has been identified as a key mechanism. In this review, we summarize the antifibrotic efficacy of CHM preparations, single herbal medicines, and their bioactive compounds based on their effects on diminishing the inflammatory response and oxidative stress, regulating transforming growth factor, preventing epithelial-mesenchymal transition, and modulating microRNAs. We intend to provide patients of DN with therapeutic interventions that are complementary to existing options.