Abstract. The pathological mechanism of percutaneous transluminal coronary angioplastyinduced restenosis has been attributed to outgrowth of vascular smooth muscle cells. Pretreatment with antioxidants has been shown to reduce restenosis. Magnolol, an active compound of Magnolia officinalis, has exhibited approximately 1,000 times more potent antioxidant effects than alpha-tocopherol. In this study, we demonstrate, using cytometric analysis, an approximate 61% reduction of smooth muscle cells progressing to the S-phase by 0.05 mg / ml of magnolol. A BrdU incorporation assay also showed a significant reduction (73%) of DNA synthesis using 0.05 mg / ml of magnolol. The protein level of the proliferating cell nuclear antigen was suppressed by approximately 48% using 0.05 mg / ml of magnolol. This was in agreement with the promoter activity of nuclear factor-kappa B, which was also attenuated by 0.05 mg / ml of magnolol. Since receptor interacting protein and caspase-3 protein expression levels were both increased by magnolol in a dose-dependent manner, the apoptotic pathway may mediate the inhibition of cell growth. Our finding that malondialdehyde formation was significantly inhibited by 0.05 mg / ml of magnolol further supported the antioxidant effect of magnolol. These studies suggest that magnolol might be a potential pharmacological reagent in preventing balloon injuryinduced restenosis.
BACKGROUND: The size of medical datasets is usually very large, which directly affects the computational cost of the data mining process. Instance selection is a data preprocessing step in the knowledge discovery process, which can be employed to reduce storage requirements while also maintaining the mining quality. This process aims to filter out outliers (or noisy data) from a given (training) dataset. However, when the dataset is very large in size, more time is required to accomplish the instance selection task. OBJECTIVE: In this paper, we introduce an efficient data preprocessing approach (EDP), which is composed of two steps. The first step is based on training a model over a small amount of training data after preforming instance selection. The model is then used to identify the rest of the large amount of training data. METHODS: Experiments are conducted based on two medical datasets for breast cancer and protein homology prediction problems that contain over 100000 data samples. In addition, three well-known instance selection algorithms are used, IB3, DROP3, and genetic algorithms. On the other hand, three popular classification techniques are used to construct the learning models for comparison, namely the CART decision tree, k-nearest neighbor (k-NN), and support vector machine (SVM). RESULTS:The results show that our proposed approach not only reduces the computational cost by nearly a factor of two or three over three other state-of-the-art algorithms, but also maintains the final classification accuracy. CONCLUSIONS: To perform instance selection over large scale medical datasets, it requires a large computational cost to directly execute existing instance selection algorithms. Our proposed EDP approach solves this problem by training a learning model to recognize good and noisy data. To consider both computational complexity and final classification accuracy, the proposed EDP has been demonstrated its efficiency and effectiveness in the large scale instance selection problem.
In this paper we succeeded to develop a approach by using new material, named gray bump in stead of current bump material to achieve excellent contrast ratio(CR) of liquid crystal display(LCD) at normal direction for MVA mode. Meanwhile, we needn't change any processes, and surely no additional cost. Except CR enhancement at normal direction, it can also reduce the oblique light leakage of dark state and improve the viewing angle. We evaluate the response time and reliability for image sticking of this new bump design and it has the similar response time and image sticking performance as the original bump design. Finally, we also show the CR >3000:1 32" TV that adopting this new design and using higher CR polarizers with lower haze value surface treatment..
The function of mobile phone becomes more versatile as a personal assistant. In order to make display device optimized for different function of the mobile phone, this paper proposes a display device which can be switched among 2D direct view, 3D direct view and projection modes while using single liquid crystal(LC) panel as image source. The device features a highly collimated backlight unit and polymer dispersed liquid crystal(PDLC) diffuser at the back of the LC panel, and a switchable lenticular array as well as a stretchable projection lens in front. The ray tracing simulation has shown well controlled light path of the backlight module and sufficient image quality of the projection lens while maintaining the compactness of the device for mobile application.
& Our novel automated feedback temperature controlled cooling system consists of a temperature measurement circuit, a TE cooler, a thermistor, a microcontroller, and a digital-to-analog converter and PWM algorithms. The measurement accuracy of this temperature controlled TE system was better than 0.1 C and can be used for maintaining an instrument's isothermal applications. The experimental results of SWIR linear image shows that the temperature can be stably maintained at À20 C, the dark output current can be reduced almost 80 mV (Integration time: 100 ms) and the SNR of pixel can be improved from 48 dB to 83 dB as well.
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