Yao Xue Xue Bao. 2009 May; 44(5): 449-55Li XY, Chen XGProtein kinase C beta (PKCbeta) is a multifunctional serine/threonine protein kinase, which plays an important role in many cell signaling pathways. PKCbeta takes part in multiple physiological processes, including regulation of the cell cycle, differentiation, proliferation, apoptosis and angiogenesis. Increased PKCbeta activity has been observed in many human cancers, such as colon, breast and haematological malignancies. At present, Enzastaurin is mostly studied in preclinical and clinical studies, which is a selective PKCbeta inhibitor. This review focuses on the functional properties of PKCbeta, its role played in tumors and Enzastaurin.

Yao Xue Xue Bao. 2009 May; 44(5): 443-8Ying J, Lü Y, Du GHAmorphous is a special physical state of solid compounds that the positions of the molecules or atoms have no long-range order. Sometimes amorphous compounds have better bioavailability, or achieve ultra-fast absorption in situation of acute and intermittent symptoms than that of morphous compounds, thus change drug efficacy. Besides, different pharmaceutical preparing methods can lead to different characters. Research of amorphous compounds has been a hotspot, both in research field and industry world. However, there are challenges as amorphous compounds could be unstable; unexpected adverse drug reactions may also exist. In this review, recent progress in the research of amorphous pharmaceutical compounds both in the research field and the pharmaceutical industry is reviewed. Factors which can influence the efficacy of amorphous pharmaceuticals are summarized. The prospect of amorphous techniques is also discussed.

Microsc Res Tech. 2009 Jul 20; Choy SK, Tong CS, Zhao ZZThis article presents a novel and effective multistage system for classifying Chinese Materia Medica microscopic starch grain images. The proposed classification system is constructed based on the Gaussian mixture model-based clustering, the feature assignment algorithm, and the similarity measurement. Several features for each starch grain image are extracted and every class of drug is represented by a set of characteristic features. For each stage of the system, only one feature is chosen and assigned to that stage via the feature assignment algorithm, and the corresponding characteristic features are subdivided into smaller subsets based on clustering techniques. At the final stage, each subset contains a certain class of drugs (with corresponding characteristic features) and similarity measurement is carried out for starch grain classification. Three sets of the current state-of-the-art starch grain features including the granulometric size distribution, the chord length distribution, and the wavelet signature are used to construct the system. Experimental results on a database of 240 images of 24 classes of drugs reveal the superior performance of the multistage system. Comparison with the traditional starch grain classification approaches indicates that our proposed multistage method produces a marked improvement in classification performance. Microsc. Res. Tech. 2009. (c) 2009 Wiley-Liss, Inc.