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To restrict indication for stenting of the inferior vena cava and liver transplantation in patients with

WANG Zhonggao

《医学前沿（英文）》 2007年第1卷第2期页码 130-135 doi: 10.1007/s11684-007-0025-3

摘要： The Budd-Chiari syndrome (BCS) used to be a very rare disorder and lacked a means of relieving. However, various shuntings and radical procedures have emerged in the last three decades with quite encouraging outcomes. Recent minimally invasive therapies, such as stenting of the inferior vena cava (IVC), are simple and easy to handle. However, it has been realized that the IVC stent may compromise the hepatic veins and cause catastrophic consequences, thus the indication for IVC stenting should be reevaluated and especially not to be overused. Instead, it should be applied by percutaneous transangiography (PTA) only, which may be repeated when necessary. The BCS in China predominantly belongs to the IVC type rather than the intrahepatic type in Western; the outcome from its conventional therapy, at least for the moment, is better than that of liver transplantation. It is thus suggested that, before liver transplantation is decided, the conventional means for managing BCS be considered. The final suggestion is to restrict the indication both for stenting of the IVC and liver transplantation. In this paper, ten examples are given with figures.

关键词： Budd-Chiari syndrome conventional intrahepatic percutaneous transangiography necessary

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Soil enzyme activities and their indication for fertility of urban forest soil

SHAN Qihua, YU Yuanchun, ZHANG Jinchi, YU Jian

《环境科学与工程前沿（英文）》 2008年第2卷第2期页码 218-223 doi: 10.1007/s11783-008-0037-5

摘要： To reveal the biological characteristics of urban forest soil and the effects of soil enzyme on soil fertility as well as the correlation between physicochemical properties and enzyme activities, 44 urban forest soil profiles in Nanjing were investigated. Basic soil physicochemical properties and enzyme activities were analyzed in the laboratory. Hydrogen peroxidase, dehydrogenase, alkaline phosphatase, and cellulase were determined by potassium permanganate titration, TTC (CHN·Cl) colorimetry, phenyl phosphate dinatrium colorimetry, and anthrone colorimetry, respectively. The result showed that soil pH, organic carbon (C), and total nitrogen (N) had great effects on hydrogen peroxidase, dehydrogenase, and alkaline phosphatase activities in 0–20 cm thick soil. However, pH only had great effect on hydrogen peroxidase, dehydrogenase, and alkaline phosphatase activities in 20–40 cm thick soil. Hydrogen peroxidase, dehydrogenase, and alkaline phosphatase were important biological indicators for the fertility of urban forest soil. Both in 0–20 cm and 20–40 cm soil, soil enzyme system (hydrogen peroxidase, dehydrogenase, alkaline phosphatase, and cellulase) had a close relationship with a combination of physicochemical indicators (pH, organic C, total N, available K, available P, cation exchange capacity (CEC), and microbial biomass carbon (C)). The more soil enzyme activities there were, the higher the fertility of urban forest soil.

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Characterization of hidden rules linking symptoms and selection of acupoint using an artificial neural network model

Won-Mo Jung, In-Soo Park, Ye-Seul Lee, Chang-Eop Kim, Hyangsook Lee, Dae-Hyun Hahm, Hi-Joon Park, Bo-Hyoung Jang, Younbyoung Chae

《医学前沿（英文）》 2019年第13卷第1期页码 112-120 doi: 10.1007/s11684-017-0582-z

摘要： Comprehension of the medical diagnoses of doctors and treatment of diseases is important to understand the underlying principle in selecting appropriate acupoints. The pattern recognition process that pertains to symptoms and diseases and informs acupuncture treatment in a clinical setting was explored. A total of 232 clinical records were collected using a Charting Language program. The relationship between symptom information and selected acupoints was trained using an artificial neural network (ANN). A total of 11 hidden nodes with the highest average precision score were selected through a tenfold cross-validation. Our ANN model could predict the selected acupoints based on symptom and disease information with an average precision score of 0.865 (precision, 0.911; recall, 0.811). This model is a useful tool for diagnostic classification or pattern recognition and for the prediction and modeling of acupuncture treatment based on clinical data obtained in a real-world setting. The relationship between symptoms and selected acupoints could be systematically characterized through knowledge discovery processes, such as pattern identification.

关键词： acupuncture indication neural network pattern identification prediction