• Asian Pacific Journal of Cancer Prevention
• /
• v.17 no.2
• /
• pp.667-671
• /
• 2016

Oridonin, an ent-kaurane diterpenoid compound isolated from the traditional Chinese herb Rabdosia rubescens, has shown various pharmacological and physiological effects such as anti-tumor, anti-bacterial, and anti-inflammatory properties. However, the effect of oridonin on human ovarian cancer cell lines has not been determined. In this study, we demonstrated that oridonin inhibited ovarian cancer cell proliferation, migration and invasion in a dose-dependent manner. Furthermore, we showed oridonin inhibited tumor growth of ovarian cancer cells (SKOV3) in vivo. We then assessed mechanisms and found that oridonin specifically abrogated the phosphorylation/activation of mTOR signaling. In summary, our results indicate that oridonin is a potential inhibitor of ovarian cancer by blocking the mTOR signaling pathway.

• Clinical and Experimental Pediatrics
• /
• v.49 no.11
• /
• pp.1140-1151
• /
• 2006

Inherited metabolic disorders are individually rare but as a whole, they are nor rare. Since Archibald Garrod introduced a concept of "inborn error of metabolism" or "chemical individuality", more than 500 diseases are currently known, affecting approximately one in 500 newborns cumulatively. They frequently manifest with acute, life-threatening crisis that require immediate specific intervention or they present with insidious diverse symptoms and signs involving multiple visceral organs or tissues as well as central nervous system, hampering a correct diagnosis. In addition, many pediatricians are not familiar with all diagnostic and therapeutic strategies for diverse inherited metabolic disorders. However, the prognosis of affected children are heavily dependent on rapid and effective treatment. In this lecture, practical guidelines for the specific diagnosis based on diverse clinical features of inherited metabolic disorders will be described. Many sophisticated laboratory tests are available for confirmatory diagnosis of each disease, which challenge to general pediatricians with respect to knowledge about biochemical metabolite assay test, enzymatic test and DNA diagnostic tests. Sample collections, indications, methods and interpretation of results in varying laboratory tests will be listed as well.

• Nuclear Engineering and Technology
• /
• v.55 no.6
• /
• pp.2096-2106
• /
• 2023

Rotating machinery is widely applied in important equipment of nuclear power plants (NPPs), such as pumps and valves. The research on intelligent fault diagnosis of rotating machinery is crucial to ensure the safe operation of related equipment in NPPs. However, in practical applications, data-driven fault diagnosis faces the problem of small and imbalanced samples, resulting in low model training efficiency and poor generalization performance. Therefore, a deep convolutional conditional generative adversarial network (DCCGAN) is constructed to mitigate the impact of imbalanced samples on fault diagnosis. First, a conditional generative adversarial model is designed based on convolutional neural networks to effectively augment imbalanced samples. The original sample features can be effectively extracted by the model based on conditional generative adversarial strategy and appropriate number of filters. In addition, high-quality generated samples are ensured through the visualization of model training process and samples features. Then, a deep convolutional neural network (DCNN) is designed to extract features of mixed samples and implement intelligent fault diagnosis. Finally, based on multi-fault experimental data of motor and bearing, the performance of DCCGAN model for data augmentation and intelligent fault diagnosis is verified. The proposed method effectively alleviates the problem of imbalanced samples, and shows its application value in intelligent fault diagnosis of actual NPPs.

• Journal of Interdisciplinary Genomics
• /
• v.2 no.1
• /
• pp.5-9
• /
• 2020

von Willebrand disease (VWD) is a genetic bleeding disorders caused by a deficiency of von Willebrand factor (VWF). Diagnosis or exclusion of VWD is not an easy task for most clinicians. These difficulties in diagnosis or exclusion of VWD may be due to preanalytic, analytical and postanalytic laboratory issues. Analytical systems to diagnose VWD may produce misleading results because of limitations in their dynamic range of measurement and low sensitivity. However, preanalytical issues such as sample collection, processing, and transportation affect the diagnosis of VWD profoundly. We will review here the common preanlytical issues that may impact the laboratory diagnosis of VWD.

• Korean Journal of Clinical Laboratory Science
• /
• v.43 no.4
• /
• pp.150-155
• /
• 2011

It is a very important diagnosis and evalution of Hepatocellular carcinoma (HCC) in Korea where hepatitis B-virus is endemic. Protein induced by vitamin K absence or antagonist II (PIVKA-II) appears to be a useful tumor marker. This study was purposed to investigate usefulness of PIVKA-II in the diagnosis and fallow-up after treatment of HCC. A total of 418 patients were included in 187 patients (44.7%) of HCC, 83 patients (19.9%) of liver cirrhosis, 74 patients (17.7%) of chronic hepatitis and 74 patients (17.7%) of other liver diseases with serum PIVKA-II levels by Hicatch PIVKA-II kit. PIVKA-II level were analysed for difference of groups and the comparison of treatment responses. The sensitivity and specificity of PIVKA-II in the diagnosis of HCC were 80.2%, 87.0% at the cut-off value of 40 mAU/mL. There were statistically significant difference between the HCC and other groups (p<0.001), before and after PIVKA-II levels after treatment in HCC (p<0.001). PIVKA-II can be used as a useful tumor marker for patients with HCC, especially early diagnosis in high risk groups, treatment response assesment and monitoring of recurrence.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
• /
• 2002.10b
• /
• pp.455-456
• /
• 2002

Wear is one of the main factors causing breakdown and fault of machine, so ferrography technique analyzing wear particles can be an effective way for condition monitoring and fault diagnosis. On the base of the forward multilayer neural network, a nodes self-deleting neural network model is provided in this paper. This network can itself deletes the nodes to optimize its construction. On the basis of the nodes self-deleting neural network, an intelligent ferrography diagnosis expert system (IFDES) for wear particles recognition and wear diagnosis is described. This intelligent expert system can automatically slim lip knowledge by learning from samples and realize basically the entirely automatic processing from wear particles recognition to wear diagnosis.

• Journal of The Korean Society of Inherited Metabolic disease
• /
• v.5 no.1
• /
• pp.108-115
• /
• 2005

Inherited metabolic diseases (IMD) comprise a large class of genetic diseases involving disorders of metabolism. The majorities are due to defects of single genes that code for enzymes that facilitate conversion of various substances into others. Because of the multiplicity of conditions, many different diagnostic tests are used for screening of IMD. Molecular genetic diagnosis is the detection of pathogenic mutations in DNA and/or RNA samples and is becoming a much more common practice in medicine today. The purpose of molecular genetic testing in IMD includes diagnostic testing, pre-symptomatic testing, carrier screening, prenatal diagnosis, preimplantation testing, and population screening. However, because of the complexity, difficulty in interpreting the result, and the ethical considerations, an understanding of technical, conceptual, and practical aspects of molecular genetic diagnosis is mandatory.

• Journal of Power Electronics
• /
• v.17 no.3
• /
• pp.725-732
• /
• 2017

This paper proposed a real-time, low-cost, fast transistor open-circuit fault diagnosis method for voltage-source inverter fed induction motors. A transistor open-circuit changes the symmetry of the inverter topology, leading to different similarities among three phase load currents. In this paper, dynamic time warping is proposed to describe the similarities among load currents. The proposed diagnosis is independent of the system model and needs no extra sensors or electrical circuits. Both simulation and experimental results show the high efficiency of the proposed fault diagnosis method.

• Nuclear Engineering and Technology
• /
• v.50 no.3
• /
• pp.396-410
• /
• 2018

To assist operators to properly assess the current situation of the plant, accurate fault diagnosis methodology should be available and used. A reliable fault diagnosis method is beneficial for the safety of nuclear power plants. The major idea proposed in this work is integrating the merits of different fault diagnosis methodologies to offset their obvious disadvantages and enhance the accuracy and credibility of on-line fault diagnosis. This methodology uses the principle component analysis-based model and multi-flow model to diagnose fault type. To ensure the accuracy of results from the multi-flow model, a mechanical simulation model is implemented to do the quantitative calculation. More significantly, mechanism simulation is implemented to provide training data with fault signatures. Furthermore, one of the distance formulas in similarity measurement-Mahalanobis distance-is applied for on-line failure degree evaluation. The performance of this methodology was evaluated by applying it to the reactor coolant system of a pressurized water reactor. The results of simulation analysis show the effectiveness and accuracy of this methodology, leading to better confidence of it being integrated as a part of the computerized operator support system to assist operators in decision-making.

• Journal of Gastric Cancer
• /
• v.22 no.4
• /
• pp.306-318
• /
• 2022

Gastric cancer (GC) is associated with high morbidity and mortality rates. Thus, early diagnosis is important to improve disease prognosis. Endoscopic assessment represents the most reliable imaging method for GC diagnosis; however, it is semi-invasive and costly and heavily depends on the skills of the endoscopist, which limit its clinical applicability. Therefore, the search for new sensitive biomarkers for the early detection of GC using noninvasive sampling collection methods has attracted much attention among scientists. Urine is considered an ideal biofluid, as it is readily accessible, less complex, and relatively stable than plasma and serum. Over the years, substantial progress has been made in screening for potential urinary biomarkers for GC. This review explores the possible applications and limitations of urinary biomarkers in GC detection and diagnosis.