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Tetrahydropalmatine (THP) is an active component of Corydalis yanhusuo W. T. Wang. The current study investigates the possible cardioprotective effects of tetrahydropalmatine in acute myocardial ischemia (AMI) rats. The anterior descending coronary artery of SD rats was ligated to establish an AMI model. After two weeks of gavage of THP, cardiac function was determined by echocardiography. The organ index and the infarct size were assessed after the experiment, and the histopathological myocardial tissue changes were observed. In addition, the apoptosis index of myocardial cells was detected by the terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay. The levels of SOD, MDA, CAT, GSH-Px, BNP, and cTn-I were measured by enzyme-linked immunosorbent assay. To determine relevant proteins, the Western blot and molecular docking were applied. Compared with the model group, THP could enhance rat cardiac ejection function to improve cardiac function, drastically lessen the infarct size, reduce myocardial cell damage and inflammatory cell infiltration. THP might also prevent ischemic myocardial damage by inhibiting myocardial cell apoptosis and efficiently reducing oxidative stress. Specifically, THP could decrease MDA, BNP, c-TnI activities, as well as the expression of Bax and Caspase-3 protein, while increasing SOD, GSH-Px, CAT activities, and Bcl-2 level. Furthermore, THP could significantly promote the phosphorylation of PI3K and Akt proteins. The involved pathways and proteins have also been verified through molecular docking. According to these findings, THP may preserve the myocardium due to its anti-oxidant and anti-apoptotic properties. [ABSTRACT FROM AUTHOR]

We prove some lacunary convergent series representations for ζ(n). For example, we prove that ζ(7)=∑k=2∞(−1)k(2π)6k(6k+3)!⋅B6k−6k−1+π69451+12+⋯+19−log(2π), where Bn are the nth Bernoulli numbers. [ABSTRACT FROM AUTHOR]

Although face recognition technology has progressed substantially, its performance is still not satisfactory due to the challenges of great variations in illumination, expression and occlusion. This paper aims to improve the accuracy of personal identification, when only few samples are registered as templates, by integrating multiple modal biometrics, i.e. face and palmprint. We developed in this paper a feature code, namely FPCode, to represent the features of both face and palmprint. Though feature code has been used for palmprint recognition in literature, it is first applied in this paper for face recognition and multi-modal biometrics. As the same feature is used, fusion is much easier. Experimental results show that both feature level and decision level fusion strategies achieve much better performance than single modal biometrics. The proposed approach uses fixed length 1/0 bits coding scheme that is very efficient in matching, and at the same time achieves higher accuracy than other fusion methods available in literature. [ABSTRACT FROM AUTHOR]

Classification of gene expression samples is a core task in microarray data analysis. How to reduce thousands of genes and to select a suitable classifier are two key issues for gene expression data classification. This paper introduces a framework on combining both feature extraction and classifier simultaneously. Considering the non-negativity, high dimensionality and small sample size, we apply a discriminative mixture model which is designed for non-negative gene express data classification via non-negative matrix factorization (NMF) for dimension reduction. In order to enhance the sparseness of training data for fast learning of the mixture model, a generalized NMF is also adopted. Experimental results on several real gene expression datasets show that the classification accuracy, stability and decision quality can be significantly improved by using the generalized method, and the proposed method can give better performance than some previous reported results on the same datasets. [ABSTRACT FROM AUTHOR]