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Backgrounds: Polycystic ovary syndrome (PCOS) is a common endocrine disorder in women and can lead to serious social burdens associated with various reproductive and metabolic abnormalities. Studies have demonstrated that metformin can reduce liver glucose in PCOS, lower testosterone levels and increase peripheral insulin sensitivity. There has been also evidence suggesting acupuncture may influence ovulation (release of the egg) by affecting levels of various hormones. We will conduct a systematic review and meta-analysis is to compare the efficacy and safety of metformin with or without acupuncture in PCOS. Methods and analysis: We will search publications from Web of Science, PubMed, Science Direct, Wan Fang Data Knowledge Service Platform, Chinese Biomedical Literature Database (CBM), Chinese Scientific Journal Database (VIP database), China National Knowledge Infrastructure (CNKI) and EMBASE, which should be published from inception to February 2020. Two researchers will independently perform the selection of the studies, data extraction, and synthesis. The Cochrane Risk of Bias Tool will be used to evaluate the risk of bias of the randomized controlled trials. Statistical analysis will be performed by using the Cochrane Review Manager (RevMan 5.3) software. The I 2 test will be used to identify the extent of heterogeneity. We will use the Egger funnel chart to evaluate possible publication biases, in addition, when possible we will perform a subgroup/meta-regression analysis. The strength of the evidence will be assessed according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE). Results and conclusion: This study will systematically evaluate the efficacy and safety of Metformin combined with acupuncture in the treatment of PCOS, thus providing evidence to the clinical application of this combination therapy. The results will be published in a peer-reviewed journal.

In recent years, many data sets are accessed for the purposes of research, cooperation and e-business, and so on. Publishing data about individuals without revealing their private information has become an active issue, and k-Anonymous-based models are effective techniques that prevent linking attack. We analyzed the privacy leakage problem in data publishing environment. Then we concluded the privacy preserving technologies, and clarified the k-anonymity models. Finally we conclude the directions of this area.