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With the increase of multisource data available from remote sensing platforms, it is demanding to develop unsupervised techniques for change detection from multisource data. The difference in imaging mechanism makes it difficult to carry out a direct comparison between multisource data in original observation spaces. Different sensors provide different descriptions on the same truth in low-dimension observation spaces, but the same truth indicates the comparability of multisource data in some high-dimensional feature spaces. Inspired by this, we try to solve this problem by transforming multisource data into a common high-dimension feature space. In this paper, an iterative coupled dictionary learning (CDL) model is proposed for multisource image change detection. This model aims to establish a pair of coupled dictionaries, one of which is responsible for the data from one sensor, whereas the other is responsible for the data from another sensor. The atoms from these two coupled dictionaries have a one-to-one correspondence at the same location. Such a property guarantees the transferability of the reconstruction coefficients between bitemporal patch pairs and provides us a desired mechanism to bridge multisource data and highlight changes. The contributions can be summarized as follows: CDL is designed to explore the intrinsic difference of multisource data for change detection in a high-dimension feature space, and an iterative scheme for unsupervised sample selection is proposed to keep the purity of training samples and gradually optimize the current coupled dictionaries. The experimental results have demonstrated the feasibility, effectiveness, and robustness of the proposed framework. [ABSTRACT FROM PUBLISHER]

5( S )-5-carboxystrictosidine (5-CS) is a compound found in the root of Mappianthus iodoides , a traditional Chinese medicine used for the treatment of coronary artery disease. The aim of the present study was to investigate the protective effect of 5-CS against oxidative stress-induced apoptosis in H9c2 cardiomyocytes and the underlying mechanisms. 5-CS pretreatment significantly protected against H 2 O 2 -induced cell death, LDH leakage, and malondialdehyde (MDA) production, which are indicators for oxidative stress injury. 5-CS also enhanced the activity of SOD and CAT. In addition, 5-CS pretreatment significantly inhibited H 2 O 2 -induced apoptosis, as determined by flow cytometer, suppressed the activity of caspase-3 and caspase-9, and attenuated the activation of cleaved caspase-3 and caspase-9. 5-CS also increased Akt and ERK activation altered by H 2 O 2 using Western blot analysis. The PI3K-specific inhibitor LY294002 abolished 5-CS-induced Akt activation. The ERK-specific inhibitor PD98059 abolished 5-CS-induced ERK activation. Both LY294002 and PD98059 attenuated the protective effect of 5-CS on H9c2 cardiomyocytes against H 2 O 2 -induced apoptosis and cell death. Taken together, these results demonstrate that 5-CS prevents H 2 O 2 -induced oxidative stress injury in H9c2 cells by enhancing the activity of the endogenous antioxidant enzymes, inhibiting apoptosis, and modulating PI3K/Akt and ERK signaling pathways., Competing Interests: The authors declare that they have no conflicts of interest., (Thieme. All rights reserved.)