The expression of ETAR in liver cirrhosis and liver cancer.

Background: To investigate the expression of endothelin receptors in liver diseases and discuss its role in the process of liver cirrhosis and liver cancer.

Research Design And Methods: We examined the expressions of ETAR, ETBR and α-SMA in tissue samples using western blotting analysis. Furthermore, immunofluorescence was used to locate ETAR expression in hepatic stellate cells (HSCs) and hepatic sinusoidal endothelial cells (HSECs), we calculated the percentage of positive cells and then analyzed its relation with clinical indexes.

[Multidimensional Scaling Linear Regression Applied to FTIR Spectral Quantitative Analysis of Clinical Parameters of Human Blood Serum].

In the present paper it was proposed to establish multidimensional scaling linear regression (MDS-MLR) models by combining multidimensional scaling (MDS) with multiple linear regression (MLR), in which MDS owns the ability of dimensionality reduction on spectral variables. Thus the informative spectral wavelengths can be selected for each of the 4 clinical parameters (i. e.

FT-NIR spectroscopy and Whittaker smoother applied to joint analysis of duel-components for corn.

Protein and total fat are two ingredients to measure the quality of corn. The aim of this study is to evaluate the quality of corn by the dual-component join determination through Fourier transform near infrared (FT-NIR) spectroscopic analysis. The calibration models were established by the systematic study performed respectively in the four regions of the whole range, the second overtone, the first overtone, and the combination.

Latent factor analysis facilitates modelling of oncogenic genes for colon adenocarcinoma.

Identification of oncogenic genes from a large sample number of genomic data is a challenge. In this study, a well-established latent factor model, Bayesian factor and regression model, are applied to predict unknown colon cancer related genes from colon adenocarcinoma genomic data. Four important latent factors were addressed by the latent factor model, focusing on characterisation of heterogeneity of expression patterns of specific oncogenic genes by using microarray data of 174 colon cancer patients.