Long Non-coding RNA SNHG12, a New Therapeutic Target, Regulates miR-199a-5p/Klotho to Promote the Growth and Metastasis of Intrahepatic Cholangiocarcinoma Cells.

Background: Small nucleolar RNA host gene 12 (SNHG12) is a newly identified long non-coding RNA (lncRNA) whose involvements have been explored in several cancers. Our study aimed to explore the functions of SNHG12 on intrahepatic cholangiocarcinoma (ICC) progression and its interaction with miR-199a-5p and Klotho. Methods: RT-PCR was performed to examine the expressions of SNHG12, miR-199a-5p and Klotho in ICC cells. Cell counting kit-8 (CCK-8), colony formation assays and transwell assays were applied to analyze the proliferation, migration and invasion of ICC cells. Luciferase assays, RIP assays and RNA pull-down assays were carried out to demonstrate the direct binding relationships among SNHG12, miR-199a-5p and Klotho. The xenograft nude models were applied to test the effects of SNHG12 on ICC tumor growth. Results: The expression of SNHG12 and Klotho was distinctly increased in ICC cells, while miR-199a-5p expressions were decreased. Functionally, the silence of SNHG12 inhibited the proliferation and metastasis of ICC cells, while miR-199a-5p overexpression exhibited an opposite result. Mechanistically, Knockdown of SNHG12 significantly suppressed the expressions of miR-199a-5p by sponging it, and then increased Klotho expression. The final in vivo experiments suggested that the silence of SNHG12 distinctly inhibited tumor growth. Conclusion: Our findings indicated that SNHG12 inhibited cell proliferation and metastasis process of ICC cells through modulating the miR-199a-5p/Klotho axis and it is expected to become a potential therapeutic target for ICC.

Cone Beam Breast CT with a Flat Panel Detector- Simulation, Implementation and Demonstration.

This paper describes our experiences in the simulation, implementation and application of a flat panel detector based cone beam computed tomography (CT) imaging system for dedicated 3-D breast imaging. In our simulation study, the breast was analytically modeled as a cylinder of breast tissue loosely molded into cylindrical shape with embedded soft tissue masses and calcifications. Attenuation coefficients for various types of breast tissue, soft tissue masses and calcifications were estimated for various kVp's to generate simulated image signals. Projection images were computed to incorporate x-ray attenuation, geometric magnification, x-ray detection, detector blurring, image pixelization and digitization. Based on the x-ray kVp/filtration used, transmittance through the phantom, detective quantum efficiency (DQE), exposure level, and imaging geometry, the photon fluence was estimated and used to compute the quantum noise level on a pixel-by-pixel basis for various dose levels at the isocenter. This estimated noise level was then used with a random number generator to generate and add a fluctuation component to the noiseless transmitted image signal. The noise carrying projection images were then convolved with a Gaussian-like kernel, computed from measured 1-D line spread function (LSF) to simulate detector blurring. Additional 2-D Gaussian filtering was applied to the projection images and tested for improving the detection of soft tissue masses and calcifications in the reconstructed images. Reconstruction was performed using the Feldkamp filtered backprojection algorithm. All simulations were performed on a 24 PC (2.4 GHz Dual-Xeon CPU) cluster with MPI parallel programming.