Abstract Background: The aim of this study was to investigate the effect role and mechanism of miR-30b-3p on ovarian cancer cells biological function. Methods: The expression of miR-30b-3p was detected in ovarian cancer cell lines and normal ovarian epithelial cell line by qRT-PCR. Mir-30b-3p mimic was transfected into OVCAR3 cells. Cell-counting kit-8 (CCK-8) assay was conducted to explore the effect of mir-30b-3p on the OVCAR3 cells’ proliferation. Cell cycle and apoptosis were detected by Flow cytometry. Cell invasion ability was detected by Transwell test. The regulation of putative target of miR-30b-3p was verified by double luciferase reporter assays and Western blot. Result: We found that miR-30b-3p was downregulated in OVCAR3 cells. Overexpression of miR-30b-3p suppressed proliferation, promoted apoptosis, slowed cell cycle and inhibited migration and invasion of OVCAR3 cells. Bioinformatics analysis identified 3′-untranslated region (3′UTR) of Collagen triple helix repeat-containing 1 (CTHRC1) as the presumed binding site for miR-30b-3p. Detection of double luciferase reporter and Western-Blot result confirmed that CTHRC1 was the target gene of miR-30b-3p. Furthermore, E-cadherin, β-cadherin and Vimentin protein expression level were changed after transfection of miR-30b-3p. Conclusion: miR-30b-3p function as an anti-cancer gene. Overexpression of miR-30b-3p can inhibit the biological function of ovarian cancer cells. MiR-30b-3p targets CTHRC1 gene plays an important role in epithelial–mesenchymal transformation (EMT), and supports miR-30b-3p as a potential biological indicator for ovarian cancer in the future.

ABSTRACT Objective: Recently, a new obesity index (A Body Shape Index, ABSI) based on waist circumference (WC) was developed, and high ABSI corresponds to a more central concentration of body volume. It is well known that central obesity is closely linked with insulin resistance (IR). Therefore, our study aimed to examine the discriminatory power of ABSI for IR in Chinese adults and elderly without diabetes. Subjects and methods: In 2007, a cross-sectional study was made. In this study, 570 individuals without diabetes were available for analysis (male: 56.1%, mean age: 62.3 ± 6.5 years). Insulin resistance was assessed by homeostasis model assessment (HOMA-IR). Areas under the receiver operating characteristic (ROC) curves were determined to identify variables/models that could predict insulin resistance. Results: ABSI was associated with IR, the cut-off points was 0.0785 m11/6kg-2/3 to identifying IR and the area under the ROC (AUC) curve was 0.618 (95%CI: 0.561-0.675), which was not better than body mass index BMI (AUC = 0.753; 95%CI: 0.706-0.801), WC (AUC = 0.749; 95%CI: 0.700-0.797), and fasting plasma glucose (FPG, AUC = 0.752; 95%CI: 0.705-0.799). Furthermore, combination with ABSI could improve the discriminatory power of other variables for IR. The AUC curve increased from 0.753 to 0.771for BMI, 0.749 to 0.754 for WC, 0.752 to 0.769 for FPG, respectively. Conclusions: ABSI is associated with IR in the general Chinese adults and elderly without diabetes, but the discriminatory power for IR is poor. It is recommended that ABSI be used in combination with other variables.

Abstract The deposition of crystallized ammonium salt particles presents serious damage to the hydrogenation reactor effluent air cooler (REAC) in petrochemical engineering. The correlation technology process was analyzed for predicting the particle deposition situation in air coolers. Moreover, the particle crystallization and deposition were revealed, and a mathematical model for flow field simulation was established by computational fluid dynamics (CFD). In addition, the fast search clustering algorithm (FSCA) realized in Matlab software was applied to detect tube anomaly. The relatively greater risk of deposition or blockage in the tube area was detected, and this finding is consistent with the distribution of the surface temperature field in air coolers. Meanwhile, good qualitative agreement was found between the distribution rule of particle deposition rate as simulated by CFD and the situation of opened header box on the spot. Therefore, the combined method of CFD simulation and FSCA detection can be utilized for predicting the condition of particle deposition in the air-cooling systems.