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42 results on '"Shi, Wenzhao"'

1. Fine-mapping across diverse ancestries drives the discovery of putative causal variants underlying human complex traits and diseases

Author

Yuan, Kai, Longchamps, Ryan J., Pardiñas, Antonio F., Yu, Mingrui, Chen, Tzu-Ting, Lin, Shu-Chin, Chen, Yu, Lam, Max, Liu, Ruize, Xia, Yan, Guo, Zhenglin, Shi, Wenzhao, Shen, Chengguo, Daly, Mark J., Neale, Benjamin M., Feng, Yen-Chen A., Lin, Yen-Feng, Chen, Chia-Yen, O’Donovan, Michael C., Ge, Tian, and Huang, Hailiang

Published
2024
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2. A comprehensive AI model development framework for consistent Gleason grading.

Author

Huo, Xinmi, Ong, Kok, Lau, Kah, Gole, Laurent, Young, David, Tan, Char, Zhu, Xiaohui, Zhang, Chongchong, Zhang, Yonghui, Li, Longjie, Han, Hao, Lu, Haoda, Zhang, Jing, Hou, Jun, Zhao, Huanfen, Gan, Hualei, Yin, Lijuan, Wang, Xingxing, Chen, Xiaoyue, Lv, Hong, Cao, Haotian, Yu, Xiaozhen, Shi, Yabin, Huang, Ziling, Marini, Gabriel, Xu, Jun, Liu, Bingxian, Chen, Bingxian, Wang, Qiang, Gui, Kun, Shi, Wenzhao, Sun, Yingying, Chen, Wanyuan, Cao, Dalong, Lee, Hwee, Hue, Susan, Yu, Weimiao, Tan, Soo, and Sanders, Stephan

Abstract

BACKGROUND: Artificial Intelligence(AI)-based solutions for Gleason grading hold promise for pathologists, while image quality inconsistency, continuous data integration needs, and limited generalizability hinder their adoption and scalability. METHODS: We present a comprehensive digital pathology workflow for AI-assisted Gleason grading. It incorporates A!MagQC (image quality control), A!HistoClouds (cloud-based annotation), Pathologist-AI Interaction (PAI) for continuous model improvement, Trained on Akoya-scanned images only, the model utilizes color augmentation and image appearance migration to address scanner variations. We evaluate it on Whole Slide Images (WSI) from another five scanners and conduct validations with pathologists to assess AI efficacy and PAI. RESULTS: Our model achieves an average F1 score of 0.80 on annotations and 0.71 Quadratic Weighted Kappa on WSIs for Akoya-scanned images. Applying our generalization solution increases the average F1 score for Gleason pattern detection from 0.73 to 0.88 on images from other scanners. The model accelerates Gleason scoring time by 43% while maintaining accuracy. Additionally, PAI improve annotation efficiency by 2.5 times and led to further improvements in model performance. CONCLUSIONS: This pipeline represents a notable advancement in AI-assisted Gleason grading for improved consistency, accuracy, and efficiency. Unlike previous methods limited by scanner specificity, our model achieves outstanding performance across diverse scanners. This improvement paves the way for its seamless integration into clinical workflows.

Published
2024

8. Genetic architecture of the inflammatory bowel diseases across East Asian and European ancestries

Author

Liu, Zhanju, Liu, Ruize, Gao, Han, Jung, Seulgi, Gao, Xiang, Sun, Ruicong, Liu, Xiaoming, Kim, Yongjae, Lee, Ho-Su, Kawai, Yosuke, Nagasaki, Masao, Umeno, Junji, Tokunaga, Katsushi, Kinouchi, Yoshitaka, Masamune, Atsushi, Shi, Wenzhao, Shen, Chengguo, Guo, Zhenglin, Yuan, Kai, Zhu, Shu, Li, Dalin, Liu, Jianjun, Ge, Tian, Cho, Judy, Daly, Mark J., McGovern, Dermot P. B., Ye, Byong Duk, Song, Kyuyoung, Kakuta, Yoichi, Li, Mingsong, and Huang, Hailiang

Published
2023
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9. Using brain cell-type-specific protein interactomes to interpret neurodevelopmental genetic signals in schizophrenia

Author

Ripke, Stephan, Neale, Benjamin M., Corvin, Aiden, Walters, James T.R., Farh, Kai-How, Holmans, Peter A., Lee, Phil, Bulik-Sullivan, Brendan, Collier, David A., Huang, Hailiang, Pers, Tune H., Agartz, Ingrid, Agerbo, Esben, Albus, Margot, Alexander, Madeline, Amin, Farooq, Bacanu, Silviu A., Begemann, Martin, Belliveau, Richard A., Jr., Bene, Judit, Bergen, Sarah E., Bevilacqua, Elizabeth, Bigdeli, Tim B., Black, Donald W., Bruggeman, Richard, Buccola, Nancy G., Buckner, Randy L., Byerley, William, Cahn, Wiepke, Cai, Guiqing, Campion, Dominique, Cantor, Rita M., Carr, Vaughan J., Carrera, Noa, Catts, Stanley V., Chambert, Kimberley D., Chan, Raymond C.K., Chan, Ronald Y.L., Chen, Eric Y.H., Cheng, Wei, Cheung, Eric FC., Chong, Siow Ann, Cloninger, C. Robert, Cohen, David, Cohen, Nadine, Cormican, Paul, Craddock, Nick, Crowley, James J., Curtis, David, Davidson, Michael, Davis, Kenneth L., Degenhardt, Franziska, Del Favero, Jurgen, Demontis, Ditte, Dikeos, Dimitris, Dinan, Timothy, Djurovic, Srdjan, Donohoe, Gary, Drapeau, Elodie, Duan, Jubao, Dudbridge, Frank, Durmishi, Naser, Eichhammer, Peter, Eriksson, Johan, Escott-Price, Valentina, Essioux, Laurent, Fanous, Ayman H., Farrell, Martilias S., Frank, Josef, Franke, Lude, Freedman, Robert, Freimer, Nelson B., Friedl, Marion, Friedman, Joseph I., Fromer, Menachem, Genovese, Giulio, Georgieva, Lyudmila, Giegling, Ina, Giusti-Rodríguez, Paola, Godard, Stephanie, Goldstein, Jacqueline I., Golimbet, Vera, Gopal, Srihari, Gratten, Jacob, de Haan, Lieuwe, Hammer, Christian, Hamshere, Marian L., Hansen, Mark, Hansen, Thomas, Haroutunian, Vahram, Hartmann, Annette M., Henskens, Frans A., Herms, Stefan, Hirschhorn, Joel N., Hoffmann, Per, Hofman, Andrea, Hollegaard, Mads V., Hougaard, David M., Ikeda, Masashi, Joa, Inge, Julià, Antonio, Kahn, René S., Kalaydjieva, Luba, Karachanak-Yankova, Sena, Karjalainen, Juha, Kavanagh, David, Keller, Matthew C., Kennedy, James L., Khrunin, Andrey, Kim, Yunjung, Klovins, Janis, Knowles, James A., Konte, Bettina, Kucinskas, Vaidutis, Kucinskiene, Zita Ausrele, Kuzelova-Ptackova, Hana, Kähler, Anna K., Laurent, Claudine, Lee, Jimmy, Lee, S. Hong, Legge, Sophie E., Lerer, Bernard, Li, Miaoxin, Li, Tao, Liang, Kung-Yee, Lieberman, Jeffrey, Limborska, Svetlana, Loughland, Carmel M., Lubinski, Jan, Lönnqvist, Jouko, Macek, Milan, Magnusson, Patrik K.E., Maher, Brion S., Maier, Wolfgang, Mallet, Jacques, Marsal, Sara, Mattheisen, Manuel, Mattingsdal, Morten, McCarley, Robert W., McDonald, Colm, McIntosh, Andrew M., Meier, Sandra, Meijer, Carin J., Melegh, Bela, Melle, Ingrid, Mesholam-Gately, Raquelle I., Metspalu, Andres, Michie, Patricia T., Milani, Lili, Milanova, Vihra, Mokrab, Younes, Morris, Derek W., Mors, Ole, Murphy, Kieran C., Murray, Robin M., Myin-Germeys, Inez, Müller-Myhsok, Bertram, Nelis, Mari, Nenadic, Igor, Nertney, Deborah A., Nestadt, Gerald, Nicodemus, Kristin K., Nikitina-Zake, Liene, Nisenbaum, Laura, Nordin, Annelie, O'Callaghan, Eadbhard, O'Dushlaine, Colm, O'Neill, F. Anthony, Oh, Sang-Yun, Olincy, Ann, Olsen, Line, Van Os, Jim, Pantelis, Christos, Papadimitriou, George N., Papiol, Sergi, Parkhomenko, Elena, Pato, Michele T., Paunio, Tiina, Pejovic-Milovancevic, Milica, Perkins, Diana O., Pietiläinen, Olli, Pimm, Jonathan, Pocklington, Andrew J., Powell, John, Price, Alkes, Pulver, Ann E., Purcell, Shaun M., Quested, Digby, Rasmussen, Henrik B., Reichenberg, Abraham, Reimers, Mark A., Richards, Alexander L., Roffman, Joshua L., Roussos, Panos, Ruderfer, Douglas M., Salomaa, Veikko, Sanders, Alan R., Schall, Ulrich, Schubert, Christian R., Schulze, Thomas G., Schwab, Sibylle G., Scolnick, Edward M., Scott, Rodney J., Seidman, Larry J., Shi, Jianxin, Sigurdsson, Engilbert, Silagadze, Teimuraz, Silverman, Jeremy M., Sim, Kang, Slominsky, Petr, Smoller, Jordan W., So, Hon-Cheong, Spencer, Chris C.A., Stahl, Eli A., Stefansson, Hreinn, Steinberg, Stacy, Stogmann, Elisabeth, Straub, Richard E., Strengman, Eric, Strohmaier, Jana, Stroup, T Scott, Subramaniam, Mythily, Suvisaari, Jaana, Svrakic, Dragan M., Szatkiewicz, Jin P., Söderman, Erik, Thirumalai, Srinivas, Toncheva, Draga, Tosato, Sarah, Veijola, Juha, Waddington, John, Walsh, Dermot, Wang, Dai, Wang, Qiang, Webb, Bradley T., Weiser, Mark, Wildenauer, Dieter B., Williams, Nigel M., Williams, Stephanie, Witt, Stephanie H., Wolen, Aaron R., Wong, Emily H.M., Wormley, Brandon K., Xi, Hualin Simon, Zai, Clement C., Zheng, Xuebin, Zimprich, Fritz, Wray, Naomi R., Stefansson, Kari, Visscher, Peter M., Adolfsson, Rolf, Andreassen, Ole A., Blackwood, Douglas H.R., Bramon, Elvira, Buxbaum, Joseph D., Børglum, Anders D., Cichon, Sven, Darvasi, Ariel, Domenici, Enrico, Ehrenreich, Hannelore, Esko, Tõnu, Gejman, Pablo V., Gill, Michael, Gurling, Hugh, Hultman, Christina M., Iwata, Nakao, Jablensky, Assen V., Jönsson, Erik G., Kendler, Kenneth S., Kirov, George, Knight, Jo, Lencz, Todd, Levinson, Douglas F., Li, Qingqin S., Liu, Jianjun, Malhotra, Anil K., McCarroll, Steven A., McQuillin, Andrew, Moran, Jennifer L., Mortensen, Preben B., Mowry, Bryan J., Nöthen, Markus M., Ophoff, Roel A., Owen, Michael J., Palotie, Aarno, Pato, Carlos N., Petryshen, Tracey L., Posthuma, Danielle, Rietschel, Marcella, Riley, Brien P., Rujescu, Dan, Sham, Pak C., Sklar, Pamela, St Clair, David, Weinberger, Daniel R., Wendland, Jens R., Werge, Thomas, Daly, Mark J., Sullivan, Patrick F., O'Donovan, Michael C., Qin, Shengying, Sawa, Akira, Kahn, Rene, Hong, Kyung Sue, Shi, Wenzhao, Tsuang, Ming, Itokawa, Masanari, Feng, Gang, Glatt, Stephen J., Ma, Xiancang, Tang, Jinsong, Ruan, Yunfeng, Liu, Ruize, Zhu, Feng, Horiuchi, Yasue, Lee, Byung Dae, Joo, Eun-Jeong, Myung, Woojae, Ha, Kyooseob, Won, Hong-Hee, Baek, Ji Hyung, Chung, Young Chul, Kim, Sung-Wan, Kusumawardhani, Agung, Chen, Wei J., Hwu, Hai-Gwo, Hishimoto, Akitoyo, Otsuka, Ikuo, Sora, Ichiro, Toyota, Tomoko, Yoshikawa, Takeo, Kunugi, Hiroshi, Hattori, Kotaro, Ishiwata, Sayuri, Numata, Shusuke, Ohmori, Tetsuro, Arai, Makoto, Ozeki, Yuji, Fujii, Kumiko, Kim, Se Joo, Lee, Heon-Jeong, Ahn, Yong Min, Kim, Se Hyun, Akiyama, Kazufumi, Shimoda, Kazutaka, Kinoshita, Makoto, Hsu, Yu-Han H., Pintacuda, Greta, Nacu, Eugeniu, Kim, April, Tsafou, Kalliopi, Petrossian, Natalie, Crotty, William, Suh, Jung Min, Riseman, Jackson, Martin, Jacqueline M., Biagini, Julia C., Mena, Daya, Ching, Joshua K.T., Malolepsza, Edyta, Li, Taibo, Singh, Tarjinder, Ge, Tian, Egri, Shawn B., Tanenbaum, Benjamin, Stanclift, Caroline R., Apffel, Annie M., Carr, Steven A., Schenone, Monica, Jaffe, Jake, Fornelos, Nadine, Eggan, Kevin C., and Lage, Kasper

Published
2023
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14. Artificial Intelligence Supports Research Progress in the Diagnosis and Treatment of Rare Diseases

Author

GONG Mengchun, JIAO Yuanshi, MA Wuren, LIU Peng, JIN Ye, HU Jifa, NIU Ling, SHI Wenzhao, and ZHANG Shuyang

Subjects
artificial intelligence, machine learning, rare disease, diagnosis, treatment, drug repositioning, drug development, Medicine
Abstract

It is noteworthy that only 5% of more than 7000 described rare diseases are treated. In the era of big data, there is ever-increasing data for understanding biomedicine. The need for efficient and rapid data collection, analyses and characterization methods is pressing. Rare diseases can particularly benefit from artificial intelligence (AI) application. AI, with an emphasis on machine learning, creates a path for such efforts and is being applied to diagnosis and treatment. AI has demonstrated its potential to learn and analyze data from different sources with results in prediction。Presently, there are AI-driven technologies applied for rare diseases and this review aims to summarize these advances. Moreover, this review scrutinizes the limitation and identifies the pitfalls of AI applications in the diagnosis and treatment of rare diseases.

Published
2022
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15. A deep learning‐based 3D Prompt‐nnUnet model for automatic segmentation in brachytherapy of postoperative endometrial carcinoma

Author

Xue, Xian, primary, Liang, Dazhu, additional, Wang, Kaiyue, additional, Gao, Jianwei, additional, Ding, Jingjing, additional, Zhou, Fugen, additional, Xu, Juan, additional, Liu, Hefeng, additional, Sun, Quanfu, additional, Jiang, Ping, additional, Tao, Laiyuan, additional, Shi, Wenzhao, additional, and Cheng, Jinsheng, additional

Published
2024
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23. Comprehensive AI Model Development for Gleason Grading: From Scanning, Cloud-based Annotation to Pathologist-AI Interaction

Author

Huo, Xinmi, primary, ONG, KokHaur, additional, Lau, Kah Weng, additional, Gole, Laurent, additional, Young, David, additional, Tan, Char Loo, additional, Zhang, Chongchong, additional, Zhang, Yonghui, additional, Zhu, Xiaohui, additional, Li, Longjie, additional, Han, Hao, additional, Lu, Haoda, additional, Marini, Gabriel, additional, Xu, Jun, additional, Gui, Kun, additional, Chen, Bingxian, additional, Shi, Wenzhao, additional, Chen, Wanyuan, additional, Sanders, Stephan, additional, Lee, Hwee Kuan, additional, Hue, Susan Swee-Shan, additional, Yu, Weimiao, additional, and Tan, Soo Yong, additional

Published
2022
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25. Ultraviolet blocking and antioxidant polyvinyl alcohol films incorporated with baicalin extraction from Scutellaria baicalensis Georgi

Author

Li Susong, Liu Jinshu, Shi Wenzhao, Xiaoyan Ma, Jianwei Xing, Ma Chaoqun, and Huang Yayi

Subjects
Antioxidant, Materials science, Polymers and Plastics, General Chemical Engineering, medicine.medical_treatment, 02 engineering and technology, medicine.disease_cause, 01 natural sciences, Polyvinyl alcohol, chemistry.chemical_compound, Materials Chemistry, medicine, Chromatography, integumentary system, biology, 010405 organic chemistry, Blocking (radio), Extraction (chemistry), 021001 nanoscience & nanotechnology, biology.organism_classification, 0104 chemical sciences, chemistry, Scutellaria baicalensis, 0210 nano-technology, Baicalin, Ultraviolet
Abstract

Baicalin, an active flavonoid ingredient of Scutellaria baicalensis Georgi, was extracted by heat reflux extraction and showed the same significance UV absorption property with standard baicalin. Active films were prepared from polyvinyl alcohol (PVA) containing baicalin extract by casting method. The effect of baicalin extracts on the UV-blocking, optical, antioxidant property, water vapor permeability, swelling and mechanical properties of the films were studied. UV–vis transmittance spectra showed that PVA films incorporated with baicalin extract blocked ultraviolet light range from 280–400 nm even with low concentration of baicalin (0.5 wt%) and maintain the high transparency in visible spectrum. The outstanding UV-blocking properties of PVA films incorporated with baicalin extract were also confirmed by Rhodamine B degradation. Baicalin conferred antioxidant properties to PVA films as determined by DPPH radical scavenging activity. Due to the interaction between hydroxy groups of baicalin and PVA molecule, water vapor permeability, swelling and elongation at break of the films were decreased accompanied with the increasing in tensile strength and Young’s modulus. FTIR reveal that the interaction between PVA molecules was significant changed by the introduction of baicalin. These results suggest that PVA film incorporated with baicalin extract can be used for the development of functional protective film.

Published
2021

27. Anti-ultraviolet properties of β-cyclodextrin-grafted cotton fabrics dyed by broadleaf holly leaf extract

Author

Jianwei Xing, Li Susong, Huang Yayi, Xiaoyan Ma, Ma Chaoqun, Liu Jinshu, and Shi Wenzhao

Subjects
chemistry.chemical_classification, Polymers and Plastics, Cyclodextrin, 010405 organic chemistry, technology, industry, and agriculture, 02 engineering and technology, 021001 nanoscience & nanotechnology, medicine.disease_cause, 01 natural sciences, 0104 chemical sciences, chemistry, medicine, Chemical Engineering (miscellaneous), 0210 nano-technology, Ultraviolet, Nuclear chemistry
Abstract

The aim of the study was to investigate the anti-ultraviolet properties of β-cyclodextrin-grafted cotton fabrics dyed with broadleaf holly leaf extract. Flavonoids were extracted from broadleaf holly leaf by maceration and a stoichiometry of 1:1 inclusion complex with β-cyclodextrin was formed. Characterized by the fluorescence spectrum and ultraviolet spectrophotometry, the fluorescence intensities and ultraviolet absorption of the macerated extract were enhanced by increasing the amount of cyclodextrin. Cotton fabrics were grafted with β-cyclodextrin through a crosslinking reaction based on citric acid in the presence of sodium hypophosphite then dyed with the macerated extract of broadleaf holly leaf used as a natural ultraviolet absorbent. The anti-ultraviolet property of fabrics dyed by a macerated extract was characterized in terms of the ultraviolet protection factor. It was noted that the cotton fabrics grafted with β-cyclodextrin exhibit enhanced anti-ultraviolet and wrinkle recovery properties compared to the unmodified samples and show an excellent durability against 30 washing cycles, accompanied by a loss of tensile strength.

Published
2020

31. Research progress in electro-active shape memory composite materials.

Author

LIU Wen, SHI Wenzhao, LIU Jinshu, LU Shaofeng, and ZHOU Hongjuan

Subjects
COMPOSITE materials, PLANT fibers, AEROSPACE materials, ION channels, FREEZE-drying
Abstract

The shape memory process and mechanisms of electro-active shape memory composites were introduced from macro to micro perspectives. The classification and research of electro-active shape memory composites were summarized based on different conductive fillers, including nanoparticles, continuous fibers, short-cut fibers, and composite fillers. The preparation methods including physical compounding, in-situ polymerization, and freeze-drying were analyzed briefly. The electrically induced shape memory composites were introduced according to their conductive mechanisms from three aspects of homogeneous conductor units, interface bonding between conductor and substrate, and conductive network structure. An overview on the phenomena of nanoscale conductive networks and ion channels in the microstructure was presented. Finally, the applications of electro-active shape memory composite materials in aerospace, biomedicine, smart textiles, and electronic semiconductors were discussed and their future development direction was prospected. [ABSTRACT FROM AUTHOR]

Published
2022
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33. Development and Validation of a Deep Learning-Based Model Using Computed Tomography Imaging for Predicting Disease Severity of Coronavirus Disease 2019

Author

Xiao, Lu-shan, primary, Li, Pu, additional, Sun, Fenglong, additional, Zhang, Yanpei, additional, Xu, Chenghai, additional, Zhu, Hongbo, additional, Cai, Feng-Qin, additional, He, Yu-Lin, additional, Zhang, Wen-Feng, additional, Ma, Si-Cong, additional, Hu, Chenyi, additional, Gong, Mengchun, additional, Liu, Li, additional, Shi, Wenzhao, additional, and Zhu, Hong, additional

Published
2020
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37. Mordant dyeing of wool with Cortex fraxini natural dye.

Author

LIU Jinshu, MA Xiaoyanl, XING Jianwei, and SHI Wenzhao

Subjects
NATURAL dyes & dyeing, DYES & dyeing, WOOL, COPPER sulfate
Abstract

In order to explore the application of cortex fraxini natural dye in dyeing process, wool fibers were mordant dyed with cortex fraxini natural dye extracted by water extraction method. Dyeing properties of direct dyeing and mordant dyeing using different m()rdant were compared by K/S value of dyed samples. and the effect of dyeing process containing dyeing temperature and duration, pH value of dyeing bath, amount of the mordant, mordant dyeing temperature and duration on the dyeing properties were experimentally investigated. The better results were achieved by post mordant dyeing with copper sulfate as mordant. The post mordant dyeing process of wool with cortex fraxini natural dye was optimized as follow : dyeing wool at 100 °C for 45 min when pH value of dyeing bath was 4.0, and then post mordant dyeing with 2% ( owf) copper sulfate at 100 r for 30min. K/S value, friction resistance fastness and washing fastness increased obviously for post mordant dyed sample. [ABSTRACT FROM AUTHOR]

Published
2020
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40. Polarographic determination of Ce(III) and Tm(III) using rare earth-DBF-chlorophosphonazo complex

Author

Lu Xiaohua, Yan Rong, and Shi Wenzhao

Subjects
Detection limit, Polarography, Adsorption, Chemistry, Liquid–liquid extraction, Stereochemistry, Rare earth, Analytical chemistry, Selectivity, Electrochemistry, Earth (classical element), Analytical Chemistry
Abstract

The electrochemical behaviour of the DBF—chlorophosphonazo (DBF—CPA)—rare earth (RE) complex has been investigated in this paper. A highly sensitive polarographic adsorption wave was found in the RE(III)—DBF—CPA system and a new method for determination of trace total RE(III) has been established. The limit of detection was 1.8 × 10 −8 M . The results of determination of the total RE(III) content in Chinese standard reference materials of cast-iron and alloy steel were in good agreement with the certified values. The polarographic adsorptive waves of Ce(III) and Tm(III)—DBF—CPA overlap seriously. In order to improve the selectivity of determination, a non-linear regression model was employed to fit the peak height of the polarographic wave and the concentrations of Ce(III) and Tm(III). The predictive accuracy of this model for simulant mixtures was satisfied.

Published
1992

41. Effects of polyaminosiloxane on the structure and properties of modified waterborne polyurethane.

Author

Xu, Chengshu, Ren, Yan, Lu, Shaofeng, Shi, Wenzhao, OuYang, Lei, and Cai, Zaisheng

Subjects
POLYURETHANES, BLOCK copolymers, SILOXANES, THERMOGRAVIMETRY, GLASS transitions
Abstract

A waterborne polyurethane (WPU) prepolymer was synthesized with poly(tetramethylene glycol) to form the soft segment, dimethylolpropionic acid as a hydrophilic chain extender, and isophorone diisocyanate. Moreover, the graft and block copolymer emulsification of WPU–polysiloxane and their films was carried out through reactions between the WPU prepolymer, aminoethyl aminopropyl dimethicone (AEAPS), and a linear polyether‐blocked amino silicone (LEPS), respectively. The properties of the structure and formed films of the WPU were characterized with Fourier transform infrared spectrometry, gel permeation chromatography, X‐ray diffraction, thermogravimetric analysis, dynamic thermomechanical analysis, and X‐ray photoelectron spectroscopy; the measurement of the water contact angle; the testing of the water absorption; and so on. The WPU–polysiloxane emulsion showed a high stability, and the molecular weight of WPU increased. Moreover, the glass‐transition temperature (Tg) of the soft segment of polysiloxane that was incorporated into the WPU shifted to a lower temperature range, whereas the Tg of the hard segment shifted to a higher temperature range, and the crystallinity of the WPU–polysiloxane film was reduced. There was a greater degree of crosslinking and accumulation of polysiloxane segments on the surface of the WPU emulsion that was modified with AEAPS in comparison to the LEPS‐modified WPU emulsion. Therefore, the water resistance of the AEAPS‐modified WPU was higher than that of the LEPS‐modified WPU. The rigidity and elasticity of the WPU–polysiloxane film improved, whereas its tensile strength did not change much after AEAPS was used. However, this was not true after LEPS was used, as the tensile strength decreased significantly. Nevertheless, the flexibility and plasticity of the WPU–polysiloxane film were enhanced after LEPS was used. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 136, 47226. [ABSTRACT FROM AUTHOR]

Published
2019
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42. Fine-mapping across diverse ancestries drives the discovery of putative causal variants underlying human complex traits and diseases.

Author

Yuan K, Longchamps RJ, Pardiñas AF, Yu M, Chen TT, Lin SC, Chen Y, Lam M, Liu R, Xia Y, Guo Z, Shi W, Shen C, Daly MJ, Neale BM, Feng YA, Lin YF, Chen CY, O'Donovan M, Ge T, and Huang H

Abstract

Genome-wide association studies (GWAS) of human complex traits or diseases often implicate genetic loci that span hundreds or thousands of genetic variants, many of which have similar statistical significance. While statistical fine-mapping in individuals of European ancestries has made important discoveries, cross-population fine-mapping has the potential to improve power and resolution by capitalizing on the genomic diversity across ancestries. Here we present SuSiEx, an accurate and computationally efficient method for cross-population fine-mapping, which builds on the single-population fine-mapping framework, Sum of Single Effects (SuSiE). SuSiEx integrates data from an arbitrary number of ancestries, explicitly models population-specific allele frequencies and LD patterns, accounts for multiple causal variants in a genomic region, and can be applied to GWAS summary statistics. We comprehensively evaluated SuSiEx using simulations, a range of quantitative traits measured in both UK Biobank and Taiwan Biobank, and schizophrenia GWAS across East Asian and European ancestries. In all evaluations, SuSiEx fine-mapped more association signals, produced smaller credible sets and higher posterior inclusion probability (PIP) for putative causal variants, and captured population-specific causal variants., Competing Interests: COMPETING INTERESTS W.S. and C.S. are employees of Digital Health China Technologies Corp. Ltd.. M.J.D. is a founder of Maze Therapeutics. C.Y.C. is an employee of Biogen. H.H. received consultancy fees from Ono Pharmaceutical and honorarium from Xian Janssen Pharmaceutical.

Published
2023
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