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Your search keyword '"Lu, Yi-Cheng"' showing total 26 results
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26 results on '"Lu, Yi-Cheng"'

3. Preparation and characterization of microrod hydroxyapatite bundles obtained from oyster shells through microwave irradiation

Author

Wu, Shih-Ching, Kao, Yu-Lin, Lu, Yi-Cheng, Hsu, Hsueh-Chuan, and Ho, Wen-Fu

Abstract

Hydroxyapatite (HA) is similar to the inorganic component of human bone and teeth. Because of its excellent biocompatibility, bioactivity, and osteoconductivity, HA is widely used as a biomedical material. However, its biodegradability is poor. Oyster shells are mainly composed of CaCO3and other trace elements, such as Mg, Sr, K, and Na. As a raw material for synthesizing HA, oyster shells not only serve as biowaste for efficient utilization but also contain various trace elements that are beneficial to the growth of bone tissue; they can thus enhance the overall biological performance of the bioceramic. In this study, microrod HA bundles were successfully synthesized using microwave irradiation with the aid of ethylene diamine tetra-acetic acid disodium salt (Na2EDTA) as a chelating agent. The formation of microrod HA bundles was expected to promote the material’s biodegradability, and the bundles could have potential in the field of bone tissue repair. The optimal parameters for synthesis of microrod HA bundles were a Na2EDTA-to-oyster-shell-powder ratio of 2/2 and a microwave power of 700 W. The microrod HA bundles degraded more easily than did the irregular HA aggregates, indicating that the morphology of the microrod bundles resulted in a higher HA degradation rate. Bioactivity tests revealed that numerous spherical apatite particles formed on the surface of the microrod HA bundles, indicating that they had excellent bioactivity. Finally, the microrod HA bundles had high protein adsorption capability, which facilitates the control of cell attachment and proliferation and is thus beneficial to tissue regeneration.

Published
2024
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11. Classifying Liver Fibrosis Stage Using Gadoxetic Acid-Enhanced MR Images

Author

Lu, Yi Cheng

Subjects
MR images, Medical Image Processing, Deep Learning, Medicinsk bildbehandling, Liver Fibrosis, CNN
Abstract

The purpose is trying to classify the Liver Fibrosis stage using Gadoxetic Acid-EnhancedMR Images. In the very beginning, a method proposed by one Korean group is being examined and trying to reproduce their result. However, the performance is not as impressive as theirs. Then, some gray-scale image feature extraction methods are used. Last but not least, the hottest method in recent years - ConvolutionNeural Network(CNN) was utilized. Finally, the performance has been evaluated in both methods. The result shows that with manual feature extraction, the Adaboost model works pretty well that AUC achieves 0.9. Besides, the AUC of ResNet-18 network - a deep learning architecture, can reach 0.93. Also, all the hyperparameters and training settings used on ResNet-18 can be transferred to ResNet-50/ResNet-101/InceptionV3 very well. The best model that can be obtained is ResNet-101which has an AUC of 0.96 - higher than all current publications for machine learning methods for staging liver fibrosis.

Published
2019

20. Culture conditions tailored to the cell of origin are critical for maintaining native properties and tumorigenicity of glioma cells

Author

Ledur, Pítia F., primary, Liu, Chong, additional, He, Hua, additional, Harris, Alexandra R., additional, Minussi, Darlan C., additional, Zhou, Hai-Yan, additional, Shaffrey, Mark E., additional, Asthagiri, Ashok, additional, Lopes, Maria Beatriz S., additional, Schiff, David, additional, Lu, Yi-Cheng, additional, Mandell, James W., additional, Lenz, Guido, additional, and Zong, Hui, additional

Published
2016
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21. Effect of ATorvastatin On Chronic subdural Hematoma (ATOCH): a study protocol for a randomized controlled trial

Author

Jiang, Rongcai, primary, Wang, Dong, additional, Poon, Wai Sang, additional, Lu, Yi Cheng, additional, Li, Xin Gang, additional, Zhao, Shi Guang, additional, Wang, Ren Zhi, additional, You, Chao, additional, Yuan, Xian Rui, additional, Zhang, Jian Min, additional, Feng, Hua, additional, Fei, Zhou, additional, Yu, Xin Guang, additional, Zhao, Yuan Li, additional, Hu, Jin, additional, Kang, De Zhi, additional, Yu, Ru Tong, additional, Gao, Guo Dong, additional, De Zhu, Xi, additional, Sun, Tao, additional, Hao, Jie He, additional, Liu, Xian Zhi, additional, Su, Ning, additional, Yue, Shu Yuan, additional, and Zhang, Jian Ning, additional

Published
2015
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22. Does Early Postsurgical Temozolomide Plus Concomitant Radiochemotherapy Regimen Have Any Benefit in Newly-diagnosed Glioblastoma Patients? A Multi-center, Randomized, Parallel, Open-label, Phase II Clinical Trial

Author

Mao, Ying, primary, Yao, Yu, additional, Zhang, Li-Wei, additional, Lu, Yi-Cheng, additional, Chen, Zhong-Ping, additional, Zhang, Jian-Min, additional, Qi, Song-Tao, additional, You, Chao, additional, Wang, Ren-Zhi, additional, Yang, Shu-Yuan, additional, Zhang, Xiang, additional, Wang, Ji-Sheng, additional, Chen, Ju-Xiang, additional, Yang, Qun-Ying, additional, Shen, Hong, additional, Li, Zhi-Yong, additional, Wang, Xiang, additional, Ma, Wen-Bin, additional, Yang, Xue-Jun, additional, Zhen, Hai-Ning, additional, and Zhou, Liang-Fu, additional

Published
2015
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26. High PIVKA-II level and ASAP score predict 1-year risk of hepatocellular carcinoma in non-cirrhotic chronic hepatitis B patients.

Author

Lu YC, Su TH, Tseng TC, Hsu SJ, Liao SH, Hong CM, Liu CH, Yang HC, Liu CJ, and Kao JH

Abstract

Protein induced by Vitamin K absence or antagonists-II (PIVKA-II) is a diagnostic marker of hepatocellular carcinoma (HCC). We aimed to investigate the predictive role of PIVKA-II and ASAP score for development of HCC in 1 year among untreated patients of chronic hepatitis B (CHB). We conducted this case-control study to include untreated CHB patients followed at the National Taiwan University Hospital and grouped into HCC and matched non-HCC groups. Their archived serum samples were assayed for PIVKA-II levels 1 year before HCC, at HCC or their last serum sample. A total of 69 HCC cases and 102 non-HCC controls were recruited. Baseline PIVKA-II level was significantly higher in the HCC group than in the control group and it could predict HCC development in 1 year with an area under the receiver operating characteristic curve of 0.76. Multivariable analysis adjusting age, sex, liver function and alpha-fetoprotein level showed that baseline PIVKA-II ≥31 mAU/mL (vs. <31 mAU/mL) increased 12.5-fold risk (95% CI: 4.9-31.7) of HCC in 1 year, and even in patients with normal alpha-fetoprotein levels. The ASAP score, a combination of age, sex, alpha-fetoprotein and PIVKA-II, increases the predictability for HCC in 1 year. We concluded that both high PIVKA-II level and ASAP score may predict HCC development in 1 year in untreated CHB patients, especially in patients with normal alpha-fetoprotein level., Competing Interests: None., (AJCR Copyright © 2023.)

Published
2023

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