The noninvasive evaluation of the cardiac function presents a great interest for the diagnosis of cardiovascular diseases. Tagged cardiac MRI allows the measurement of anatomical and functional myocardial parameters. ...The noninvasive evaluation of the cardiac function presents a great interest for the diagnosis of cardiovascular diseases. Tagged cardiac MRI allows the measurement of anatomical and functional myocardial parameters. This protocol generates a dark grid which is deformed with the myocardium displacement on both Short-Axis (SA) and Long-Axis (LA) frames in a time sequence. Visual evaluation of the grid deformation allows the estimation of the displacement inside the myocardium. The work described in this paper aims to make robust and reliable the visual enhancement of the grid tags on cardiac MRI sequences, thanks to an informational formalism based on Extreme Physical Informational (EPI). This approach leads to the development of an original diffusion pre-processing allowing us to make better the robustness of the visual detection and the following of the grid of tags.展开更多
Long noncoding RNAs(lncRNAs)play important roles in human diseases including vascular disease.Given the large number of lncRNAs,however,whether the majority of them are associated with vascular disease remains unknown...Long noncoding RNAs(lncRNAs)play important roles in human diseases including vascular disease.Given the large number of lncRNAs,however,whether the majority of them are associated with vascular disease remains unknown.For this purpose,here we present a genomic location based bioinformatics method to predict the lncRNAs associated with vascular disease.We applied the presented method to globally screen the human lncRNAs potentially involved in vascular disease.As a result,we predicted 3043 putative vascular disease associated lncRNAs.To test the accuracy of the method,we selected 10 lncRNAs predicted to be implicated in proliferation and migration of vascular smooth muscle cells(VSMCs)for further experimental validation.The results confirmed that eight of the 10 lncRNAs(80%)are validated.This result suggests that the presented method has a reliable prediction performance.Finally,the presented bioinformatics method and the predicted vascular disease associated lncRNAs together may provide helps for not only better understanding of the roles of lncRNAs in vascular disease but also the identification of novel molecules for the diagnosis and therapy of vascular disease.展开更多
文摘The noninvasive evaluation of the cardiac function presents a great interest for the diagnosis of cardiovascular diseases. Tagged cardiac MRI allows the measurement of anatomical and functional myocardial parameters. This protocol generates a dark grid which is deformed with the myocardium displacement on both Short-Axis (SA) and Long-Axis (LA) frames in a time sequence. Visual evaluation of the grid deformation allows the estimation of the displacement inside the myocardium. The work described in this paper aims to make robust and reliable the visual enhancement of the grid tags on cardiac MRI sequences, thanks to an informational formalism based on Extreme Physical Informational (EPI). This approach leads to the development of an original diffusion pre-processing allowing us to make better the robustness of the visual detection and the following of the grid of tags.
基金supported by the National Natural Science Foundation of China(91339106)National High Technology Research and Development Program of China(2014AA021102)
文摘Long noncoding RNAs(lncRNAs)play important roles in human diseases including vascular disease.Given the large number of lncRNAs,however,whether the majority of them are associated with vascular disease remains unknown.For this purpose,here we present a genomic location based bioinformatics method to predict the lncRNAs associated with vascular disease.We applied the presented method to globally screen the human lncRNAs potentially involved in vascular disease.As a result,we predicted 3043 putative vascular disease associated lncRNAs.To test the accuracy of the method,we selected 10 lncRNAs predicted to be implicated in proliferation and migration of vascular smooth muscle cells(VSMCs)for further experimental validation.The results confirmed that eight of the 10 lncRNAs(80%)are validated.This result suggests that the presented method has a reliable prediction performance.Finally,the presented bioinformatics method and the predicted vascular disease associated lncRNAs together may provide helps for not only better understanding of the roles of lncRNAs in vascular disease but also the identification of novel molecules for the diagnosis and therapy of vascular disease.
