The Characteristic Spectral Selection Method Based on Forward and Backward Interval Partial Least Squares.

In the near-infrared spectroscopy, the Forward Interval Partial Least Squares (FiPLS) and Backward Interval Partial Least Squares (BiPLS) are commonly used modeling methods, which are based on the wavelength variable selection. These methods are usually of high prediction accuracy, but are strongly characteristic of greedy search, which causes that the intervals selected are not good enough to indicate the analyte information. To solve the problem, a spectral characteristic intervals selection strategy (FB-iPLS) based on the combination of FiPLS and BiPLS is proposed. On the basis of spectral segmentation, both FiPLSs are used to select useful intervals, and BiPLS is used to delete useless intervals, so as to perform the selection and deletion of the characteristic variables alternatively, which conducts a two-way choice of the target characteristic variables, and is used to improve the robustness of the model. The experiments on determining the ethanol concentration in pure water are conducted by modeling with FiPLS, BiPLS and the proposed method. Since different size of intervals will affect the result of the model, the experiments here will also examine the model results with different intervals of these three models. When the spectrum is divided into 60 segments, the FB-iPLS method obtains the best prediction performance. The correlation coefficients (r) of the calibration set and validation set are 0.967 7 and 0.967 0 respectively, and the cross-validation root mean square errors (RMSECV) are 0.088 8 and 0.057 1, respectively. Compared with FiPLS and BiPLS, the overall prediction performance of the proposed model is better. The experiments show that the proposed method can further improve the predictive performance of the model by resolving the greedy search feature against BiPLS and FiPLS, which is more efficient for and representative of the selection of characteristic intervals.

Mesenchymal stem cells: a new trend for cell therapy.

Mesenchymal stem cells (MSCs), the major stem cells for cell therapy, have been used in the clinic for approximately 10 years. From animal models to clinical trials, MSCs have afforded promise in the treatment of numerous diseases, mainly tissue injury and immune disorders. In this review, we summarize the recent opinions on methods, timing and cell sources for MSC administration in clinical applications, and provide an overview of mechanisms that are significant in MSC-mediated therapies. Although MSCs for cell therapy have been shown to be safe and effective, there are still challenges that need to be tackled before their wide application in the clinic.

Proliferative ductular reactions correlate with hepatic progenitor cell and predict recurrence in HCC patients after curative resection.

BACKGROUND: Ductular reactions (DRs) are well documented in many acute and chronic liver disease.The DRs are thought to be the transit amplifying cells deriving from activation of the stem/progenitor cell compartments of the liver. The aim of this study was to examine the presence of proliferative index of DR (PI-DR) and HPC markers' expression in HCCs after curative hepatectomy, as well as their relationship with clinicopathological features and prognosis. RESULTS: Tissue microarray with peritumoral and intratumoral tissue samples of 120 HCCs after hepatectomy was analysed for peritumoral expression of proliferating cell nuclear antigen for PI-DR. Peritumoral and intratumoral expression status of HPC markers including EpCAM, OV6, CD133 and c-kit were also examined by immunohistochemistry. TMA analysis of HCCs revealed that peritumoral PI-DR strongly correlated with the degree of inflammation and fibrosis. The peritumoral PI-DR positively correlated with peritumoral HPC markers EpCAM, OV6, CD133 and c-kit expression. Moreover, there were highly significant correlations between peritumoral PI-DR and intratumoral HPC markers EpCAM, OV6, CD133 and c-kit expression. Further, multivariate analysis showed that peritumoral PI-DR was the independent prognostic factor for overall survival (HR; 3.316, P < 0.001), and peritumoral PI-DR had a better power to predict disease-free survival (HR; 2.618, P < 0.001). CONCLUSIONS: Peritumoral PI-DR, as a valid surrogate for peritumoral and intratumoral expression of HPC markers, could be served as a potential prognostic marker for recurrence and survival in HCC after hepatectomy.