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195 results on '"Yi, Honggang"'

1. Effect of single blastocyst-stage versus single cleavage-stage embryo transfer on cumulative live births in women with good prognosis undergoing in vitro fertilization: Multicenter Randomized Controlled Trial

Author

Ma, Xiang, Wang, Jing, Shi, Yuhua, Tan, Jichun, Guan, Yichun, Sun, Yun, Zhang, Bo, Zhao, Junli, Liu, Jianqiao, Cao, Yunxia, Li, Hong, Zhang, Cuilian, Chen, Feng, Yi, Honggang, Wang, Ze, Xin, Xing, Kong, Pingping, Lu, Yao, Huang, Ling, Yuan, Yingying, Liu, Haiying, Li, Caihua, Mol, Ben Willem J., Hu, Zhibin, Zhang, Heping, Chen, Zi-Jiang, and Liu, Jiayin

Published
2024
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6. Potential mechanisms of Shenmai injection against POCD based on network pharmacology and molecular docking.

Author

Yi, Honggang, Zhang, Mengdie, Miao, Jiang, Mu, Lvfan, and Hu, Congli

Abstract

As the population ages, the number of patients with postoperative cognitive dysfunction increases. This study aims to investigate the mechanisms of Shenmai injection as a therapeutic strategy for postoperative cognitive dysfunction using a network pharmacology approach. Shenmai injection and its targets were retrieved from the Traditional Chinese Medicine Systems Pharmacology database. Postoperative cognitive dysfunction-associated protein targets were identified using the GeneCards and DisGeNET databases. Subsequently, a protein-protein interaction network was constructed using the String database. For treating postoperative cognitive dysfunction, the core targets of Shenmai injection were identified through topological analysis, followed by the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses performed for annotation. Molecular docking was performed on the screened core targets and components. One hundred and eighty-two related targets of Shenmai injection in treating postoperative cognitive dysfunction were identified. Eleven active ingredients in Shenmai injection were detected to have a close connection with postoperative cognitive dysfunction-related targets. Additionally, Gene Ontology analysis revealed 10 biological processes, 10 cellular components and 10 molecular functions. The Kyoto Encyclopedia of Genes and Genomes analysis identified 20 signaling pathways. The docking results indicated five active ingredients from Shenmai injection can fit in the binding pockets of all three candidate targets. Thus, the present work systematically explored the anti-postoperative cognitive dysfunction mechanism of potential targets and signaling pathways of Shenmai injection. These results provide an important reference for subsequent basic research on postoperative cognitive dysfunction. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Changing Trajectories of Alanine Aminotransferase and Risk of Antituberculosis Drug‐Induced Liver Injury in Chinese Patients: A Cohort Study.

Author

Chen, Xinyu, Pan, Hongqiu, Hao, Zhuolu, Yi, Honggang, and Tang, Shaowen

Subjects
DRUG therapy for tuberculosis, LIVER injuries, LIVER disease prevention, RISK assessment, RESEARCH funding, HOSPITAL care, LOGISTIC regression analysis, ANTITUBERCULAR agents, LIVER diseases, LONGITUDINAL method, ODDS ratio, ALANINE aminotransferase, CONFIDENCE intervals
Abstract

Antituberculosis drug‐induced liver injury (ATLI) is a major adverse effect during antituberculosis treatment. Early detection or prediction is essential to prevent ATLI in antituberculosis treatment patients. The purpose of this work is to explore the relationship between alanine aminotransferase (ALT) trajectories within 15 days of initial treatment and the risk of ATLI. Based on a historical cohort of patients hospitalized for antituberculosis treatment and group‐based trajectory modeling analysis, ALT trajectories within 15 days of initial treatment were determined. Conditional logistic regression model was used to estimate the association between different ALT trajectories and the risk of ATLI, and the corresponding odds ratios (ORs) and their 95% confidence intervals (CIs) were calculated with covariates. Based on the ALT levels within 15 days of initial treatment, a total of 853 patients were divided into four ALT trajectories. The incidence of ATLI significantly increased with the increase of ALT trajectories (2.33%, 4.38%, 5.90%, and 2.44%, respectively). Compared with trajectory 1, the adjusted OR for ATLI in trajectory 2, trajectory 3, and trajectory 4 were 2.448 (95% CI: 0.302–19.856, P = 0.402), 5.373 (95% CI: 0.636–45.411, P = 0.123), 11.010 (95% CI: 0.720–168.330, P = 0.085), respectively, and there was an increasing trend of ATLI risk (Ptrend = 0.015). Different ALT trajectories within 15 days of initial treatment were associated with different risk of ATLI, and it is necessary to pay attention to the ALT trajectory within 15 days of initial treatment to predict the occurrence of ATLI. [ABSTRACT FROM AUTHOR]

Published
2024
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8. Risk for stillbirth among pregnant individuals with SARS-CoV-2 infection varied by gestational age

Author

Wilcox, Adam B., Lee, Adam M., Graves, Alexis, Anzalone, Alfred (Jerrod), Manna, Amin, Saha, Amit, Olex, Amy, Zhou, Andrea, Williams, Andrew E., Southerland, Andrew, Girvin, Andrew T., Walden, Anita, Sharathkumar, Anjali A., Amor, Benjamin, Bates, Benjamin, Hendricks, Brian, Patel, Brijesh, Alexander, Caleb, Bramante, Carolyn, Ward-Caviness, Cavin, Madlock-Brown, Charisse, Suver, Christine, Chute, Christopher, Dillon, Christopher, Wu, Chunlei, Schmitt, Clare, Takemoto, Cliff, Housman, Dan, Gabriel, Davera, Eichmann, David A., Mazzotti, Diego, Brown, Don, Boudreau, Eilis, Hill, Elaine, Zampino, Elizabeth, Marti, Emily Carlson, Pfaff, Emily R., French, Evan, Koraishy, Farrukh M., Mariona, Federico, Prior, Fred, Sokos, George, Martin, Greg, Lehmann, Harold, Spratt, Heidi, Mehta, Hemalkumar, Liu, Hongfang, Sidky, Hythem, Hayanga, J.W. Awori, Pincavitch, Jami, Clark, Jaylyn, Harper, Jeremy Richard, Islam, Jessica, Ge, Jin, Gagnier, Joel, Saltz, Joel H., Saltz, Joel, Loomba, Johanna, Buse, John, Mathew, Jomol, Rutter, Joni L., McMurry, Julie A., Guinney, Justin, Starren, Justin, Crowley, Karen, Bradwell, Katie Rebecca, Walters, Kellie M., Wilkins, Ken, Gersing, Kenneth R., Cato, Kenrick Dwain, Murray, Kimberly, Kostka, Kristin, Northington, Lavance, Pyles, Lee Allan, Misquitta, Leonie, Cottrell, Lesley, Portilla, Lili, Deacy, Mariam, Bissell, Mark M., Clark, Marshall, Emmett, Mary, Saltz, Mary Morrison, Palchuk, Matvey B., Haendel, Melissa A., Adams, Meredith, Temple-O’Connor, Meredith, Kurilla, Michael G., Morris, Michele, Qureshi, Nabeel, Safdar, Nasia, Garbarini, Nicole, Sharafeldin, Noha, Sadan, Ofer, Francis, Patricia A., Burgoon, Penny Wung, Robinson, Peter, Payne, Philip R.O., Fuentes, Rafael, Jawa, Randeep, Erwin-Cohen, Rebecca, Patel, Rena, Moffitt, Richard A., Zhu, Richard L., Kamaleswaran, Rishi, Hurley, Robert, Miller, Robert T., Pyarajan, Saiju, Michael, Sam G., Bozzette, Samuel, Mallipattu, Sandeep, Vedula, Satyanarayana, Chapman, Scott, O’Neil, Shawn T., Setoguchi, Soko, Hong, Stephanie S., Johnson, Steve, Bennett, Tellen D., Callahan, Tiffany, Topaloglu, Umit, Sheikh, Usman, Gordon, Valery, Subbian, Vignesh, Kibbe, Warren A., Hernandez, Wenndy, Beasley, Will, Cooper, Will, Hillegass, William, Zhang, Xiaohan Tanner, Lyu, Tianchu, Liang, Chen, Liu, Jihong, Hung, Peiyin, Zhang, Jiajia, Campbell, Berry, Ghumman, Nadia, Olatosi, Bankole, Hikmet, Neset, Zhang, Manting, Yi, Honggang, and Li, Xiaoming

Published
2023
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17. Relationship between common telomere length‐related genetic variations, telomere length, and risk of antituberculosis drug‐induced hepatotoxicity in Chinese Han population: As assessed for causality using the updated Roussel Uclaf Causality Assessment Method

Author

Chen, Xinyu, primary, Hao, Zhuolu, additional, Pan, Hongqiu, additional, Liu, Wenpei, additional, Lu, Lihuan, additional, Zhang, Meiling, additional, He, Xiaomin, additional, Yi, Honggang, additional, and Tang, Shaowen, additional

Published
2023
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38. IPRS: Leveraging Gene-Environment Interaction to Reconstruct Polygenic Risk Score

Author

Tang, Yingdan, You, Dongfang, Yi, Honggang, Yang, Sheng, and Zhao, Yang

Subjects
Genetics, Molecular Medicine, Genetics (clinical)
Abstract

Background: Polygenic risk score (PRS) is widely regarded as a predictor of genetic susceptibility to disease, applied to individuals to predict the risk of disease occurrence. When the gene-environment (G×E) interaction is considered, the traditional PRS prediction model directly uses PRS to interact with the environment without considering the interactions between each variant and environment, which may lead to prediction performance and risk stratification of complex diseases are not promising.Methods: We developed a method called interaction PRS (iPRS), reconstructing PRS by leveraging G×E interactions. Two extensive simulations evaluated prediction performance, risk stratification, and calibration performance of the iPRS prediction model, and compared it with the traditional PRS prediction model. Real data analysis was performed using existing data from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial study to predict genetic susceptibility, pack-years of smoking history, and G×E interactions in patients with lung cancer.Results: Two extensive simulations indicated iPRS prediction model could improve the prediction performance of disease risk, the accuracy of risk stratification, and clinical calibration performance compared with the traditional PRS prediction model, especially when antagonism accounted for the majority of the interaction. PLCO real data analysis also suggested that the iPRS prediction model was superior to the PRS prediction model in predictive effect (p = 0.0205).Conclusion: IPRS prediction model could have a good application prospect in predicting disease risk, optimizing the screening of high-risk populations, and improving the clinical benefits of preventive interventions among populations.

Published
2021

44. Clinical characteristics of re-positive COVID-19 patients in Huangshi, China: A retrospective cohort study

Author

Zhou, Ji, primary, Zhang, Jingying, additional, Zhou, Juan, additional, Yi, Honggang, additional, Lin, Zichen, additional, Liu, Yu, additional, Zhu, Min, additional, Wang, Hongyu, additional, Zhang, Wei, additional, Xu, Hai, additional, Jiang, Hangping, additional, Xiang, Zhengzhong, additional, Qu, Ze, additional, Yang, Yuemei, additional, Lu, Linjuan, additional, Guo, Shuai, additional, Fu, Heng, additional, Adcock, Ian M., additional, Wei, Yu, additional, and Yao, Xin, additional

Published
2020
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45. Association between early treatment with Qingfei Paidu decoction and favorable clinical outcomes in patients with COVID-19: A retrospective multicenter cohort study

Author

Shi, Nannan, primary, Liu, Bin, additional, Liang, Ning, additional, Ma, Yan, additional, Ge, Youwen, additional, Yi, Honggang, additional, Wo, Hongmei, additional, Gu, Heng, additional, Kuang, Yuan, additional, Tang, Shaowen, additional, Zhao, Yang, additional, Tong, Lin, additional, Liu, Sihong, additional, Zhao, Chen, additional, Chen, Renbo, additional, Bai, Weiguo, additional, Fan, Yipin, additional, Shi, Zhan, additional, Li, Li, additional, Liu, Jia, additional, Gu, Hao, additional, Zhi, Yingjie, additional, Wang, Zhifei, additional, Li, Yuanyuan, additional, Li, Huizhen, additional, Wang, Jingya, additional, Jiao, Liwen, additional, Tian, Yaxin, additional, Xiong, Yibai, additional, Huo, Ruili, additional, Zhang, Xiaohui, additional, Bai, Jiangfeng, additional, Chen, Hong, additional, Chen, Liying, additional, Feng, Qiao, additional, Guo, Tuanmao, additional, Hou, Yong, additional, Hu, Guifen, additional, Hu, Xiaomei, additional, Hu, Yunhong, additional, Huang, Jin, additional, Huang, Qiuhua, additional, Huang, Shaozhen, additional, Ji, Liang, additional, Jin, Haihao, additional, Lei, Xiao, additional, Li, Chunyan, additional, Wu, Guihui, additional, Li, Jike, additional, Li, Minqing, additional, Li, Quntang, additional, Li, Xianyong, additional, Liu, Hongde, additional, Liu, Jinping, additional, Liu, Zhang, additional, Ma, Yuting, additional, Mao, Ya, additional, Mo, Liufen, additional, Na, Hui, additional, Wang, Jingwei, additional, Song, Fangli, additional, Sun, Sheng, additional, Wang, Dongting, additional, Wang, Mingxuan, additional, Wang, Xiaoyan, additional, Wang, Yinzhen, additional, Wang, Yudong, additional, Wu, Wei, additional, Wu, Lanping, additional, Xiao, Yanhua, additional, Xie, Haijun, additional, Xu, Hongming, additional, Xu, Shoufang, additional, Xue, Ruixia, additional, Yang, Chun, additional, Yang, Kaijun, additional, Yang, Puye, additional, Yuan, Shengli, additional, Zhang, Gongqi, additional, Zhang, Jinbo, additional, Zhang, Linsong, additional, Zhao, Shusen, additional, Zhao, Wanying, additional, Zheng, Kai, additional, Zhou, Yingchun, additional, Zhu, Junteng, additional, Zhu, Tianqing, additional, Li, Guangxi, additional, Wang, Wei, additional, Zhang, Huamin, additional, Wang, Yanping, additional, and Wang, Yongyan, additional

Published
2020
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50. Association between Early Treatment and Favorable Clinical Outcomes of COVID-19: Evidence from Nine Provinces in China

Author

Shi, Nannan, primary, Liu, Bin, additional, Liang, Ning, additional, Ma, Yan, additional, Ge, Youwen, additional, Wo, Hongmei, additional, Yi, Honggang, additional, Gu, Heng, additional, Kuang, Yuan, additional, Tang, Shaowen, additional, Zhao, Yang, additional, Tong, Lin, additional, Liu, Sihong, additional, Zhao, Chen, additional, Chen, Renbo, additional, Bai, Weiguo, additional, Fan, Yipin, additional, Shi, Zhan, additional, Li, Li, additional, Liu, Jia, additional, Gu, Hao, additional, Zhi, Yingjie, additional, Wang, Zhifei, additional, Li, Yuanyuan, additional, Li, Huizhen, additional, Jiao, Liwen, additional, Tian, Yaxin, additional, Xiong, Yibai, additional, Huo, Ruili, additional, Bai, Jiangfeng, additional, Chen, Hong, additional, Chen, Liying, additional, Feng, Qiao, additional, Guo, Tuanmao, additional, Hou, Yong, additional, Hu, Guifen, additional, Hu, Xiaomei, additional, Hu, Yunhong, additional, Huang, Jin, additional, Huang, Qiuhua, additional, Huang, Shaozhen, additional, Ji, Liang, additional, Jin, Haihao, additional, Lei, Xiao, additional, Li, Chunyan, additional, Wu, Guihui, additional, Li, Jike, additional, Li, Minqing, additional, Li, Quntang, additional, Li, Xianyong, additional, Liu, Hongde, additional, Liu, Jinping, additional, Liu, Zhang, additional, Ma, Yuting, additional, Mao, Ya, additional, Mo, Liufen, additional, Na, Hui, additional, Wang, Jingwei, additional, Song, Fangli, additional, Sun, Sheng, additional, Wang, Dongting, additional, Wang, Mingxuan, additional, Wang, Xiaoyan, additional, Wang, Yinzhen, additional, Wang, Yudong, additional, Wu, Wei, additional, Wu, Lanping, additional, Xiao, Yanhua, additional, Xie, Haijun, additional, Xu, Hongming, additional, Xu, Shoufang, additional, Xue, Ruixia, additional, Yang, Chun, additional, Yang, Kaijun, additional, Yang, Puye, additional, Yuan, Shengli, additional, Zhang, Gongqi, additional, Zhang, Jinbo, additional, Zhang, Linsong, additional, Zhao, Shusen, additional, Zhao, Wanying, additional, Zheng, Kai, additional, Zhou, Yingchun, additional, Zhu, Junteng, additional, Li, Guangxi, additional, Zhu, Tianqing, additional, Wang, Wei, additional, Zhang, Huamin, additional, Wang, Yanping, additional, and Wang, Yongyan, additional

Published
2020
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