Pancreatic cancer is the fourth leading cause of cancer-related death in the United States, with increasing incidence. The mortality rate of pancreatic cancer is rising rapidly, and is projected to be the second most common of all malignant tumors by 2030. However, the diagnosis and therapy of pancreatic cancer remain a formidable challenge. Recently, enormous efforts have been made to develop several new methods for the early diagnosis and treatment of pancreatic cancer. We briefly introduce the most groundbreaking advances in pancreatic cancer diagnosis and clinical treatment strategies over the past 15 years, including surgery, chemotherapy, endoscopic therapy, immunotherapy and personalized medicine. The signaling pathways that are altered in the progression of pancreatic cancer, which may be used as therapeutic targets, are also discussed.

We conducted a dose–response meta-analysis of prospective studies to summarize evidence of the association between tea consumption and the risk of breast, colorectal, liver, prostate, and stomach cancer.

Thyroid autoimmunity (TAI) is prevalent in women of live-birthing age and has independently been associated with complications of fertility and pregnancy, in the case of spontaneous conception or after assisted reproductive technology (ART) treatment. However, it remains challenging to identify causation between infertility and TAI, even interventional trials looking at the impact of levothyroxine (LT4) treatment on fertility and pregnancy outcomes due to differences among study results which related to small scales, impropriate study designs, enrollment criteria of infertility cause and titer/hormone concentration measurements. Furthermore, many questions remain unsettled in ART management in AITD infertile women attempt pregnancy. Therefore, further observational and interventional trials are needed more comprehensive multiple-center, double blinded, and randomized.

// <![CDATA[ $('.header-date').hide();$('#titleAuthors').hide();$('#abstractHeader').hide(); // ]]> Tuo Li1,2,*, Jianguo Sheng3, Weiqin Li4, Xin Zhang5, Hongyu Yu4, Xueyun Chen5, Jianquan Zhang3, Quancai Cai6, Yongquan Shi1,2 and Zhimin Liu1,2 1 Department of Endocrinology, Changzheng Hospital, Second Military Medical University, Shanghai, P. R. Chinaa 2 Endocrine laboratory, Changzheng Hospital, Second Military Medical University, P. R. China 3 Department of Ultrasonography, Changzheng Hospital, Second Military Medical University, P. R. China 4 Department of Pathology, Changzheng Hospital, Second Military Medical University, P. R. China 5 Department of General Surgery, Changzheng Hospital, Second Military Medical University, P. R. China 6 Center for Clinical Epidemiology and Evidence-based Medicine, Second Military Medical University, Shanghai, P. R. China * This is the first author of this article Correspondence to: Zhimin Liu, email: // <![CDATA[ mail("zmliu_cz","hotmail",0,"") // ]]> Yongquan Shi, email: // <![CDATA[ mail("young.stone","163",0,"") // ]]> Quancai Cai, email: // <![CDATA[ mail("qccai","smmu.edu",23,"") // ]]> Jianquan Zhang, email: // <![CDATA[ mail("ultramez","sina",0,"") // ]]> Keywords: thyroid cancer, differential diagnosis, computational model Received: April 02, 2015 Accepted: June 10, 2015 Published: June 29, 2015