Park Jc

Effect of Atorvastatin-Eluting Stents in a Rabbit Iliac Artery Restenosis Model

Statins have pleiotropic effects, which include the inhibition of neointima hyperplasia, the inhibition of vascular inflammation, and platelet inhibition. The aim of this study was to examine the effect of an atorvastatin-eluting stent (AES) in a rabbit iliac artery overstretch restenosis model. Ten rabbits were used in this study (10 rabbits, 10 iliac arteries for each stent). An AES and paclitaxel-eluting stent (PES) were implanted in the left and right iliac arteries in a rabbit (2 stents in each rabbit). The stents were deployed with oversizing (stent/artery ratio 1.3:1), and histopathologic analysis was assessed at 28 days after stenting. There were no significant differences in the injury score, lumen area, or inflammation score. There were significant differences in the neointimal area (0.7±0.18 mm2 in the AES group vs. 0.4±0.25 mm2 in the PES group, p<0.01), in the percentage stenosis area (14.8±5.06% in the AES group vs. 10.5±6.80% in the PES group, p<0.05), and in the fibrin score (0.4±0.51 in the AES group vs. 2.7±0.48 in the PES group, p<0.001). Although the AES did not suppress neointimal hyperplasia compared with the PES, it showed a superior arterial healing effect in a rabbit iliac artery overstretch restenosis model.

Effect of Stents Coated with Artemisinin or Dihydroartemisinin in a Porcine Coronary Restenosis Model

Background and Objectives Artemisinin and dihydroartemisinin are drugs used to treat malaria. These drugs suppress inflammatory reactions. The aim of this study was to examine the anti-intima hyperplasia effect of a novel drug-eluting stent with artemisinin or dihydroartemisinin in a porcine coronary restenosis model. Materials and Methods Pigs were randomized into four groups; in the first, the coronary arteries (20 pigs, a total of 40 coronary arteries, with 10 coronary arteries in each group) was implanted with bare metal stents (BMS, n=10); the second group was given polymer-coated stents (PCS, n=10); the third group was treated with artemisinin-eluting stents (AES, n=10); and the fourth group was given dihydroartemisinin-eluting stents (DAES, n=10). Histopathologic analysis was performed 28 days after stenting. Results The injury and fibrin scores among the four groups were not significantly different. However, the internal elastic lamina, lumen area, and neointima area were significantly different. Moreover, the percent area of stenosis (46.2±18.66% in BMS vs. 89.4±10.92% in PCS vs. 83.3±17.07% in AES vs. 36.7±11.20% in DAES, p<0.0001) and inflammation score (1.0 [range: 1.0-1.0] vs. 3.0 [range: 2.25-3.0] vs. 3.0 [range: 1.0-3.0] vs. 2.0 [range: 1.75-3.0] in BMS, PCS, AES, and DAES, respectively; p<0.001) were markedly decreased in the DAES group compared to the PCS group. Conclusion DES, which uses a natural substance, dihydroartemisinin, showed a neointima and inflammatory suppressive effect in a porcine coronary restenosis model.

A Fast Search Algorithm for Raman Spectrum using Singular Value Decomposition

In this paper, we propose new search algorithms using SVD(Singular Value Decomposition) for fast search of Raman spectrum. In the proposed algorithms, small number of the eigen vectors obtained by SVD are chosen in accordance with their respective significance to achieve computation reduction. By introducing pilot test, we exclude large number of data from search and then, we apply partial distance search(PDS) for further computation reduction. We prepared 14,032 kinds of chemical Raman spectrum as the library for comparisons. Experiments were carried out with 7 methods, that is Full Search, PDS, 1DMPS modified MPS for applying to 1-dimensional space data with PDS(1DMPS+PDS), 1DMPS with PDS by using descending sorted variance of data(1DMPS Sort with Variance+PDS), 250-dimensional components of the SVD with PDS(250SVD+PDS) and proposed algorithms, PSP and PSSP. For exact comparison of computations, we compared the number of multiplications and additions required for each method. According to the experiments, PSSP algorithm shows 64.8% computation reduction when compared with 250SVD+PDS while PSP shows 157% computation reduction.

Improvement in the classification performance of Raman spectra using a hierarchical tree structure

This paper proposes a method in which classes are grouped as a hierarchical tree structure for the effective classification of the Raman spectra. As experimental data, the Raman spectra of 28 chemical compounds were obtained, and pre-treated with noise removal and normalization. The spectra that induced a classification error were grouped into the same class and the hierarchical structure class was composed. Each high and low class was classified using a PCA-MAP method. According to the experimental results, the classification of 100% was achieved with 2.7 features on average when the proposed method was applied. Considering that the same classification rates were achieved with 6 features using the conventional method, the proposed method was found to be much better than the conventional one in terms of the total computational complexity and practical application.