Type 5 phosphodiesterase terminates the action of nitric oxide (NO) induced 3',5'-cyclic monophosphate (cGMP). Sildenafil inhibits this phosphodiesterase, increases cellular cGMP concentrations and enhances NO-induced smooth muscle relaxation. We investigated the effect of sildenafil on the oesophageal motor function of healthy subjects and patients with nutcracker oesophagus. Eight healthy volunteers and nine patients with nutcracker oesophagus participated in this study. The participants underwent oesophageal manometries on two separate days after either 20 mL of distilled water or 0.8 mg kg-1 sildenafil dissolved in 20 mL of water was infused into the stomach. Lower oesophageal sphincter (LOS) resting pressure, the duration of LOS relaxation and the amplitudes of oesophageal pressure waves were examined before, and 7.5, 15, 30 and 60 min after either placebo or sildenafil. In both healthy subjects and patients with nutcracker oesophagus, sildenafil decreased resting LOS pressure and the amplitude of peristaltic pressure waves at 3, 8 and 13 cm above LOS. Sildenafil also prolonged the duration of LOS relaxation. It had no effect on the velocity of peristalsis or the amplitude of peristaltic pressure waves 18 cm above LOS. Sildenafil may be considered as an alternative treatment in nutcracker oesophagus although there are several limitations to be overcome.
Automated image co-registration is a process of matching an image to a reference image by deriving transformation parameters to shift co-incident points in the real world to match in the image space. In order to improve efficiency and effectiveness of the co-registration approach, the author proposed a pre-qualified area matching algorithm which is composed of feature extraction with Canny operator and area matching algorithm with cross correlation coefficient. 1 For refining matching points, outlier detection using studentized residual was used to iteratively remove outliers at the level of three standard deviations. Through the prequalification and refining processes, the computation time was significantly improved and the registration accuracy enhanced. A prototype of the proposed algorithm was implemented and the performance test of 14 TM/ETMz images in the USA showed: (1) average RMSE of the approach was 0.42 dependent upon terrain and features; (2) the average number of matching points was over 36 000; (3) the average processing time was less than 9.2 min per image using a workstation equipped with a 3.2 GHz Intel Pentium 4 CPU and 1 Gb Ram. The proposed approach achieved robustness, complete automation and reduced computation time.
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