Obese patients with type 2 diabetes mellitus (T2DM), which is characterized by hyperglycemia, are liable to more severe myocardial infarction. Semen Cassiae is proven to reduce serum lipid levels. This study investigated whether the Semen Cassiae extract (SCE) reduces myocardial ischemia and reperfusion (MI/R) injury with or without diabetes and the underlying mechanisms. The high-fat diet-fed streptozotocin (HFD-STZ) rat model was created as a T2DM model. Normal and DM rats received SCE treatment orally (10 mg/kg/day) for one week. Subsequently these animals were subjected to MI/R. Compared with the normal animals, DM rats showed increased plasma total cholesterol (TC) and triacylglycerol (TG), and more severe MI/R injury and cardiac functional impairment. SCE treatment significantly reduced the plasma TC and TG, improved the instantaneous first derivation of left ventricle pressure and reduced infarct size, decreased plasma creatine kinase and lactate dehydrogenase levels, and apoptosis index at the end of reperfusion in diabetic rats. Moreover, SCE treatment increased the antiapoptotic protein Akt and ERK1/2 phosphorylation levels. Pretreatment with a PI3K inhibitor wortmannin or an ERK1/2 inhibitor PD98059 not only blocked Akt and ERK1/2 phosphorylation respectively, but also inhibited the cardioprotective effects of SCE. However, SCE treatment did not show any effects on the MI/R injury in the normal rats. Our data suggest that SCE effectively improves myocardial function and reduces MI/R-induced injury in diabetic but not normal animals, which is possibly attributed to the reduced TC/TG levels and the triggered cell survival signaling Akt and ERK1/2.
We address the problem of blind separation of multiple source layers from linear mixtures thereof, involving unknown linear mixing coefficients and unknown motions of layers in each mixture. Such mixtures can be caused in photography by the presence of a transparent medium, like a window glass, when the camera or the medium moves between snapshots. To understand how to achieve correct separation, we study the statistics of natural images in the Labelme data set. We not only confirm the well-known sparsity of image gradients, but also discover new joint behavior patterns of image gradients. Based on these statistical properties, we develop a sparse blind separation algorithm to estimate both layer motions and linear mixing coefficients and then recover all layers. This method can handle general parameterized motions, including translations, scalings, rotations and other transformations. In addition, the number of layers is automatically identified, and all layers can be recovered even in the under-determined case where mixtures are fewer than layers. The effectiveness of this technology is shown in both simulated and real superimposed images.
Transcription factors (TFs) regulate the expression of genes through sequence-specific interactions with DNA-binding sites. However, despite recent progress in identifying in vivo TF binding sites by microarray readout of chromatin immunoprecipitation (ChIP-chip), nearly half of all known yeast TFs are of unknown DNA-binding specificities, and many additional predicted TFs remain uncharacterized. To address these gaps in our knowledge of yeast TFs and their cis regulatory sequences, we have determined high-resolution binding profiles for 89 known and predicted yeast TFs, over more than 2.3 million gapped and ungapped 8-bp sequences ("k-mers"). We report 50 new or significantly different direct DNA-binding site motifs for yeast DNA-binding proteins and motifs for eight proteins for which only a consensus sequence was previously known; in total, this corresponds to over a 50% increase in the number of yeast DNA-binding proteins with experimentally determined DNA-binding specificities. Among other novel regulators, we discovered proteins that bind the PAC (Polymerase A and C) motif (GATGAG) and regulate ribosomal RNA (rRNA) transcription and processing, core cellular processes that are constituent to ribosome biogenesis. In contrast to earlier data types, these comprehensive k-mer binding data permit us to consider the regulatory potential of genomic sequence at the individual word level. These k-mer data allowed us to reannotate in vivo TF binding targets as direct or indirect and to examine TFs potential effects on gene expression in approximately 1,700 environmental and cellular conditions. These approaches could be adapted to identify TFs and cis regulatory elements in higher eukaryotes.
Related JoVE Video
Journal of Visualized Experiments
What is Visualize?
JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.
How does it work?
We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.
Video X seems to be unrelated to Abstract Y...
In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.