Inactivity of nitric oxide synthase gene in the atherosclerotic human carotid artery

OBJECTIVE: Nitric oxide (NO) inhibits thrombus formation, vascular contraction, and smooth muscle cell proliferation. We investigated whether NO release is enhanced after endothelial NO synthase (eNOS) gene transfer in atherosclerotic human carotid artery ex vivo. METHODS AND RESULTS: Western blotting and immunohistochemistry revealed that transduction enhanced eNOS expression; however, neither nitrite production nor NO release measured by porphyrinic microsensor was altered. In contrast, transduction enhanced NO production in non-atherosclerotic rat aorta and human internal mammary artery. In transduced carotid artery, calcium-dependent eNOS activity was minimal and did not differ from control conditions. Vascular tetrahydrobiopterin concentrations did not differ between the experimental groups.Treatment of transduced carotid artery with FAD, FMN, NADPH, L-arginine, and either sepiapterin or tetrahydrobiopterin did not alter NO release. Superoxide formation was similar in transduced carotid artery and control. Treatment of transduced carotid artery with superoxide dismutase (SOD), PEG-SOD, PEG-catalase did not affect NO release. CONCLUSIONS: eNOS transduction in atherosclerotic human carotid artery results in high expression without any measurable activity of the recombinant protein. The defect in the atherosclerotic vessels is neither caused by cofactor deficiency nor enhanced NO breakdown. Since angioplasty is performed in atherosclerotic arteries,eNOS gene therapy is unlikely to provide clinical benefit.

Unifying energy minimization and mutual information maximization for robust 2D/3D registration of X-ray and CT images

Similarity measure is one of the main factors that affect the accuracy of intensity-based 2D/3D registration of X-ray fluoroscopy to CT images. Information theory has been used to derive similarity measure for image registration leading to the introduction of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. However, it is known that the standard mutual information measure only takes intensity values into account without considering spatial information and its robustness is questionable. Previous attempt to incorporate spatial information into mutual information either requires computing the entropy of higher dimensional probability distributions, or is not robust to outliers. In this paper, we show how to incorporate spatial information into mutual information without suffering from these problems. Using a variational approximation derived from the Kullback-Leibler bound, spatial information can be effectively incorporated into mutual information via energy minimization. The resulting similarity measure has a least-squares form and can be effectively minimized by a multi-resolution Levenberg-Marquardt optimizer. Experimental results are presented on datasets of two applications: (a) intra-operative patient pose estimation from a few (e.g. 2) calibrated fluoroscopic images, and (b) post-operative cup alignment estimation from single X-ray radiograph with gonadal shielding.