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Supplemental material, sj-docx-1-onc-10.1177_11795549221110522 for Hysteroscopic Curettage Followed by Megestrol Acetate Plus Metformin as a Fertility-Sparing Treatment for Women with Atypical Endometrial Hyperplasia or Well-Differentiated Endometrioid Endometrial Carcinoma by Chu-Yu Jing, Sheng-Nan Li, Bo-Er Shan, Wei Zhang, Wen-Juan Tian, Yu-Lan Ren and Hua-Ying Wang in Clinical Medicine Insights: Oncology

Supplemental Digital Content is available in the text, Since body fatness is a convincing risk factor for endometrial cancer, dietary fat intake was speculated to be associated with endometrial cancer risk. However, epidemiological studies are inconclusive. We aimed to conduct a meta-analysis to assess the associations between dietary fat intake and endometrial cancer risk. We searched the PubMed, Embase, and Web of science databases updated to September 2015. In total, 7 cohort and 14 case–control studies were included. Pooled analysis of case–control studies suggested that endometrial cancer risk was significantly increased by 5% per 10% kilocalories from total fat intake (P=0.02) and by 17% per 10 g/1000 kcal of saturated fat intake (P

Aurora kinase A (AurA) regulates genomic instability and tumorigenesis in multiple cancer types. Although some studies have reported that Aur A may predict cervical cancer outcomes, its precise function and molecular mechanism in cervical cancer pathogenesis remain unclear. In this study, by overexpression or silencing of Aur A in cervical cancer cell lines, we found that overexpression of Aur A promoted cell proliferation through G1/S cell cycle transition and anti-apoptosis, xenograft tumor growth and chemoresistance to Taxol. We further found that inhibition of Aur A with its specific inhibitor VX-680 enhanced the antitumor effect of Taxol via inducing apoptosis. Moreover, the clinical analysis from tissue samples demonstrated that Aur A was overexpressed, and the expression of Aur A and pERK1/2 was negatively correlated in cervical cancer tissues. The above results may provide some potential insights in treatment of cervical cancer in clinic.

To determine the diagnostic accuracy, sensitivity and specificity of magnetic resonance imaging (MRI) in detecting myometrial invasion, cervical involvement and disease stage in endometrial cancer.168 consecutive patients with endometrial carcinoma underwent preoperative MRI. We classified myometrial invasion as no invasion, ≤50% invasion or50% invasion and cervical involvement as positive or negative. The preoperative MRI findings and stagings were compared with final surgical and histological staging; the latter was taken as the gold standard. Standard statistical calculations were used.The sensitivity, specificity, and accuracy of MRI for the detection of myometrial invasion50% were 64.7, 92.5, and 86.9%, respectively. Positive and negative predictive values were 68.8 and 91.2%, respectively. The sensitivity, specificity, and accuracy of MRI for the detection of cervical invasion were 52.63, 93.08, and 83.93%, respectively. Positive and negative predictive values were 68.97 and 87.05%, respectively. 102 cases were classified as stage IA (early disease) by histology. MRI accurately predicted the degree of invasion in 88 cases and overestimated in 14, giving a sensitivity of 86.3% and specificity of 69.1%. However, MRI showed reduced sensitivity for predicting stage IB and advanced endometrial cancer (stages III and IV) at 33.3 and 30.3%, respectively, but was found to be specific for predicting these stages; the specificity were 94.7 and 85.1%, respectively. MRI also showed good accuracy for predicting stage IA, IB, II and advanced endometrial cancer at 80.4, 86.9, 91.7, and 83.9, respectively.MRI assists in planning the surgical treatment of endometrial cancer with good accuracy and specificity, although sensitivity is suboptimal.

Driver fatigue and loosing alertness is the major reason of severe traffic accidents. In this research field, the method based on vision has been a leading technique. This paper presents a real time system which can alert drivers when they feel drowsy or lose alertness through monitoring the state of eyes, mouth and face orientation. Test results show that the system can monitor the face features effectively and realize warning based on specified roles.