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9. Full-Spectrum Surveillance of Pre-Treatment HIV Drug Resistance in Southeastern China.

Author

Zhang, Jiafeng, Sun, Baochang, Sheng, Zihang, Ding, Xiaobei, Fan, Qin, Huang, Gang, Guo, Zhihong, Zhong, Ping, Liao, Lingjie, Xing, Hui, Xia, Yan, Chai, Chengliang, and Jiang, Jianmin

Subjects
NUCLEOSIDE reverse transcriptase inhibitors, NON-nucleoside reverse transcriptase inhibitors, REVERSE transcriptase inhibitors, ANTI-HIV agents, ANTIRETROVIRAL agents, INTEGRASE inhibitors, REVERSE transcriptase
Abstract

HIV drug resistance compromises the ability of anti-retroviral therapy (ART) to suppress viral replication, resulting in treatment failure. This study investigates the prevalence of pre-treatment drug resistance (PDR) in newly diagnosed individuals in a prosperous city (Wenzhou) in Southeastern China. A cross-sectional investigation was carried out among 473 newly diagnosed ART-naive HIV-1-infected individuals between January and December 2022. The protease–reverse transcriptase (PR-RT) region and integrase (IN) region of HIV-1 were amplified by two separately nested PCRs, followed by sequencing. Drug resistance mutations (DRMs) and drug resistance to nucleoside reverse transcriptase inhibitors (NRTIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs), protease inhibitors (PIs) and integrase strand transfer inhibitors (INSTIs) were analyzed. The PDR prevalence was 6.5% [95% CI: 4.4–9.1] for any anti-retroviral drug, 0.9% [95% CI: 0.3–2.3] for NRTIs, 4.1% [95% CI: 2.5–6.5] for NNRTIs, 1.8% [95% CI: 0.8–3.6] for PIs and 0.5% [95% CI: 0.1–1.8] for INSTIs. According to the subtyping results of the PR-RT region, 11 different subtypes and 31 unique recombinant forms (URFs) were found. CRF07_BC was the dominant subtype (53.7%, 233/434), followed by CRF01_AE (25.3%, 110/434). V179D (1.6%) and K103N (1.4%) were the most predominant types of NNRTI DRMs. Q58E (1.2%) and M184V (0.7%) were the most frequent PI DRMs and NRTI DRMs, respectively. The INSTI-related DRMs Y143S (causes high-level resistance to RAL) and G163K (causes low-level resistance to EVG and RAL) were found in one patient each. Given the relatively high PDR prevalence of NNRTI (4.1%), non-NNRTI-based ART may be preferred in the future. It is recommended to include genotypic resistance testing before starting ART in regions where feasible. [ABSTRACT FROM AUTHOR]

Published
2024
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13. Pretreatment HIV Drug Resistance and the Molecular Transmission Network Among HIV-Positive Individuals in China in 2022: Multicenter Observational Study

Author

Chen, Hongli, primary, Hao, Jingjing, additional, Hu, Jing, additional, Song, Chang, additional, Zhou, Yesheng, additional, Li, Miaomiao, additional, Chen, Jin, additional, Liu, Xiu, additional, Wang, Dong, additional, Xu, Xiaoshan, additional, Xin, Peixian, additional, Zhang, Jiaxin, additional, Liao, Lingjie, additional, Feng, Yi, additional, Li, Dan, additional, Pan, Stephen W, additional, Shao, Yiming, additional, Ruan, Yuhua, additional, and Xing, Hui, additional

Published
2023
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18. Pretreatment HIV Drug Resistance and the Molecular Transmission Network Among HIV-Positive Individuals in China in 2022: Multicenter Observational Study (Preprint)

Author

Chen, Hongli, primary, Hao, Jingjing, additional, Hu, Jing, additional, Song, Chang, additional, Zhou, Yesheng, additional, Li, Miaomiao, additional, Chen, Jin, additional, Liu, Xiu, additional, Wang, Dong, additional, Xu, Xiaoshan, additional, Xin, Peixian, additional, Zhang, Jiaxin, additional, Liao, Lingjie, additional, Feng, Yi, additional, Li, Dan, additional, Pan, Stephen W, additional, Shao, Yiming, additional, Ruan, Yuhua, additional, and Xing, Hui, additional

Published
2023
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26. Modelling the impact of treatment adherence on the transmission of HIV drug resistance.

Author

Lai, Hao, Li, Rui, Li, Zengbin, Zhang, Baoming, Li, Chao, Song, Chang, Zhao, Quanbi, Huang, Jinghua, Zhu, Qiuying, Liang, Shujia, Chen, Huanhuan, Li, Jianjun, Liao, Lingjie, Shao, Yiming, Xing, Hui, Ruan, Yuhua, Lan, Guanghua, Zhang, Lei, and Shen, Mingwang

Subjects
HIV infection transmission, DRUG resistance, ANTI-HIV agents, PATIENT compliance, HIV, AIDS
Abstract

Introduction A lower adherence rate (percentage of individuals taking drugs as prescribed) to ART may increase the risk of emergence and transmission of HIV drug resistance, decrease treatment efficacy, and increase mortality rate. Exploring the impact of ART adherence on the transmission of drug resistance could provide insights in controlling the HIV epidemic. Methods We proposed a dynamic transmission model incorporating the CD4 cell count-dependent rates of diagnosis, treatment and adherence with transmitted drug resistance (TDR) and acquired drug resistance. This model was calibrated and validated by 2008–2018 HIV/AIDS surveillance data and prevalence of TDR among newly diagnosed treatment-naive individuals from Guangxi, China, respectively. We aimed to identify the impact of adherence on drug resistance and deaths during expanding ART. Results In the base case (ART at 90% adherence and 79% coverage), we projected the cumulative total new infections, new drug-resistant infections, and HIV-related deaths between 2022 and 2050 would be 420 539, 34 751 and 321 671. Increasing coverage to 95% would reduce the above total new infections (deaths) by 18.85% (15.75%). Reducing adherence to below 57.08% (40.84%) would offset these benefits of increasing coverage to 95% in reducing infections (deaths). Every 10% decrease in adherence would need 5.07% (3.62%) increase in coverage to avoid an increase in infections (deaths). Increasing coverage to 95% with 90% (80%) adherence would increase the above drug-resistant infections by 11.66% (32.98%). Conclusions A decrease in adherence might offset the benefits of ART expansion and exacerbate the transmission of drug resistance. Ensuring treated patients' adherence might be as important as expanding ART to untreated individuals. [ABSTRACT FROM AUTHOR]

Published
2023
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28. Molecular transmission network of pretreatment drug resistance among human immunodeficiency virus-positive individuals and the impact of virological failure on those who received antiretroviral therapy in China

Author

Chen, Hongli, primary, Hu, Jing, additional, Song, Chang, additional, Li, Miaomiao, additional, Zhou, Yesheng, additional, Dong, Aobo, additional, Kang, Ruihua, additional, Hao, Jingjing, additional, Zhang, Jiaxin, additional, Liu, Xiu, additional, Li, Dan, additional, Feng, Yi, additional, Liao, Lingjie, additional, Ruan, Yuhua, additional, Xing, Hui, additional, and Shao, Yiming, additional

Published
2022
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29. Genetic network analysis of human immunodeficiency virus sexual transmission in rural Southwest China after the expansion of antiretroviral therapy: A population-based study

Author

Chen, Jin, primary, Chen, Huanhuan, additional, Li, Jianjun, additional, Luo, Liuhong, additional, Kang, Ruihua, additional, Liang, Shujia, additional, Zhu, Qiuying, additional, Lu, Huaxiang, additional, Zhu, Jinhui, additional, Shen, Zhiyong, additional, Feng, Yi, additional, Liao, Lingjie, additional, Xing, Hui, additional, Shao, Yiming, additional, Ruan, Yuhua, additional, and Lan, Guanghua, additional

Published
2022
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30. Epidemic Characteristics of HIV Drug Resistance in Hefei, Anhui Province

Author

Zheng, Shan, primary, Wu, Jianjun, additional, Hao, Jingjing, additional, Wang, Dong, additional, Hu, Zhongwang, additional, Liu, Lei, additional, Song, Chang, additional, Hu, Jing, additional, Lei, Yanhua, additional, Wang, Hai, additional, Liao, Lingjie, additional, Feng, Yi, additional, Shao, Yiming, additional, Ruan, Yuhua, additional, and Xing, Hui, additional

Published
2022
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32. Iot Secured Disjunctive XOR Two Factor Mutual Authentication for Users

Author

Zhang Jiantao, A.M. Moklas Mohamad, Xing Hui, Ilkaeva Marina, A.B. Zakaria Zuki, Meek Bob, Ruan Yuhua, Saiano Filippo, Feng Yi, M. Mailafiya Maryam, Dong Aobo, B. Balamurugan, T. Rijkers Ger, Benko Zsigmond, M. Chiroma Samaila, Abubakar Kabeer, I. García-López Elisa, Natarajan Sampathkumar, Sun Jihong, B.A. Rahim Ezamin, Liao Lingjie, Thirupathi Anand, Liu Lei, M. Shanmugavadivelu Chandra, Marci Giuseppe, Shao Yiming, Palmisano Leonardo, Talwar Meenu, Y. Zhao Richard, Liang Shu, and Danmaigoro Abubakar

Subjects
General Computer Science, business.industry, Computer science, Factor (programming language), Mutual authentication, business, Internet of Things, computer, computer.programming_language, Computer network
Abstract

Aims: The paper has introduced an algorithmic modification of M.L.Das's previous work done of " IoT Mutual Authentication". Background: IoT has proven that if there exists a thing on the earth then it is bound to be connected to the internet to tell its feature on its own. IoT plays a remarkable role in all aspects of our daily lives it covers entertainment, sports, healthcare, education, security, automobiles, industrial as well as home appliances and many more real time applications. To ease our everyday activities, it reinforcing the way people interact with their surroundings. This holistic view brings some major concerns in terms of security and privacy. Objective: The objective of the work is to increase security and protect the algorithm from various attackers so to use with real time application. Methods: In this we have used XoR (Exclusive OR) operation and because of this we can protect the algorithm from DoS attacks, bypass attack, intruder attack and allow user to change password. Conclusion: The proposed work has secured all the connected IoT devices to work inde-pendently and secured because every device has to verify at each step in the IoT system before initiating its operation.

Published
2021
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36. Spatiotemporal Patterns of CRF07_BC in China: A Population-Based Study of the HIV Strain With the Highest Infection Rates

Author

Gan, Mengze, Zheng, Shan, Hao, Jingjing, Ruan, Yuhua, Liao, Lingjie, Shao, Yiming, Feng, Yi, and Xing, Hui

Subjects
Male, China, Immunology, HIV, phylogeographic analysis, HIV Infections, molecular network, RC581-607, Sexual and Gender Minorities, diffusion trajectory, HIV-1, Immunology and Allergy, Humans, CRF07_BC, Immunologic diseases. Allergy, Homosexuality, Male, Phylogeny
Abstract

The prevalence of CRF07_BC is 39.7% and has become the most infectious HIV strain in China. To study the transmission and diffusion trajectory of CRF07_BC in China and to prevent further expansion of its transmission. A total of 16,635 sequences of the CRF07_BC pol gene were collected from 1997-2020. We characterized the gene subtypes according to a phylogenetic tree analysis. A 0.50% molecular network was constructed to analyze the transmission relationship among different provinces for CRF07_BC and its two epidemic clusters. Spatial and temporal propagation characteristics were analyzed according to phylogeographic analysis. Finally, we evaluated the differences in transmission of CRF07_BC-O, and CRF07_BC-N. Our dataset included 8,816 sequences of CRF07_BC-N and 7,819 sequences of CRF07_BC-O. There were 7,132 CRF07_BC sequences in the molecular network, and the rate of clustered was 42.9%. Compared to CRF07_BC-O, CRF07_BC-N showed significantly (P

Published
2021

41. Survey of Pretreatment HIV Drug Resistance and The Genetic Transmission Networks Among HIV-Infected Individuals in Southwestern China, 2014-2020

Author

Xu, Xiaoshan, primary, Luo, Liuhong, additional, Song, Chang, additional, Li, Jianjun, additional, Chen, Huanhuan, additional, Zhu, Qiuying, additional, Lan, Guanghua, additional, Liang, Shujia, additional, Shen, Zhiyong, additional, Cao, Zhiqiang, additional, Feng, Yi, additional, Liao, Lingjie, additional, Xing, Hui, additional, Shao, Yiming, additional, and Ruan, Yuhua, additional

Published
2021
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42. Additional file 2 of Survey of pretreatment HIV drug resistance and the genetic transmission networks among HIV-positive individuals in southwestern China, 2014���2020

Author

Xu, Xiaoshan, Luo, Liuhong, Song, Chang, Li, Jianjun, Chen, Huanhuan, Zhu, Qiuying, Lan, Guanghua, Liang, Shujia, Shen, Zhiyong, Cao, Zhiqiang, Feng, Yi, Liao, Lingjie, Xing, Hui, Shao, Yiming, and Ruan, Yuhua

Abstract

Additional file 2. Number of genetic transmission clusters and links, as a function of the TN93 distance threshold. (The epidemiologically plausible range of thresholds between 0.45% and 0.75% substitutions is highlighted in gray.)

Published
2021
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43. The prevalence of CRF55_01B among HIV-1 strain and its connection with traffic development in China

Author

Gan, Mengze, Zheng, Shan, Hao, Jingjing, Ruan, Yuhua, Liao, Lingjie, Shao, Yiming, Feng, Yi, and Xing, Hui

Abstract

CRF55_01B is a relatively “young” HIV strain. At present, we do not know much about its transmission characteristics in China. So, to describe the transmission characteristics of CRF55_01B strain among provinces and HIV infected people, and to analyze the reasons for its rapid epidemic in China, a total of 1237 subjects infected with CRF55_01B from 31 provinces spanning a period of 12 years from 2007 to 2018 were enrolled in this study. By constructing a molecular network and Bayesian correlation analysis, we found that CRF55_01B increased exponentially from 2005 to 2009 after its origin in Shenzhen, and increased rapidly after 2010. CRF55_01B began to spread to other provinces in 2007. After 2010, the strain showed a trend of rapid spread and epidemic from Guangdong-Shenzhen to other provinces in China. Guangdong, Shenzhen, Hunan, Beijing, Guangxi, Hubei, Jiangxi, Guizhou, Hebei, Anhui, Shanghai, Shandong, Henan, and Yunnan were the key provinces of CRF55_01B transmission. CRF55_01B, although originating from men who sex with men (MSM), was transmitted among heterosexuals in 2010. Males in heterosexuals played a crucial role in the transmission and diffusion of this strain. We also revealed that CRF55_01B might spread rapidly along with the rapid development of the Beijing-Guangzhou and Beijing-Kowloon railways. This study suggests that if we detect the spread of MSMs in time through molecular monitoring in the early stage of the epidemic, it can help us control the epidemic early and prevent its spread, which is of great significance to China's national prevention and control of HIV-1.

Published
2021
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44. Additional file 1 of Survey of pretreatment HIV drug resistance and the genetic transmission networks among HIV-positive individuals in southwestern China, 2014���2020

Author

Xu, Xiaoshan, Luo, Liuhong, Song, Chang, Li, Jianjun, Chen, Huanhuan, Zhu, Qiuying, Lan, Guanghua, Liang, Shujia, Shen, Zhiyong, Cao, Zhiqiang, Feng, Yi, Liao, Lingjie, Xing, Hui, Shao, Yiming, and Ruan, Yuhua

Subjects
virus diseases, sense organs, skin and connective tissue diseases
Abstract

Additional file 1. Changes in pretreatment HIV drug resistance among HIV-positive individuals in southwestern China, 2014���2020.

Published
2021
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45. Additional file 4 of Survey of pretreatment HIV drug resistance and the genetic transmission networks among HIV-positive individuals in southwestern China, 2014���2020

Author

Xu, Xiaoshan, Luo, Liuhong, Song, Chang, Li, Jianjun, Chen, Huanhuan, Zhu, Qiuying, Lan, Guanghua, Liang, Shujia, Shen, Zhiyong, Cao, Zhiqiang, Feng, Yi, Liao, Lingjie, Xing, Hui, Shao, Yiming, and Ruan, Yuhua

Subjects
endocrine system diseases, mental disorders, sense organs, eye diseases
Abstract

Additional file 4. Links difference between HIV-positive individuals with and without PDR in the genetic transmission networks.

Published
2021
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46. Additional file 3 of Survey of pretreatment HIV drug resistance and the genetic transmission networks among HIV-positive individuals in southwestern China, 2014���2020

Author

Xu, Xiaoshan, Luo, Liuhong, Song, Chang, Li, Jianjun, Chen, Huanhuan, Zhu, Qiuying, Lan, Guanghua, Liang, Shujia, Shen, Zhiyong, Cao, Zhiqiang, Feng, Yi, Liao, Lingjie, Xing, Hui, Shao, Yiming, and Ruan, Yuhua

Subjects
endocrine system diseases, mental disorders, sense organs, eye diseases
Abstract

Additional file 3. Difference in proportion of HIV-positive individuals belonging to genetic transmission networks who did and did not harbor PDR.

Published
2021
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49. HIV Drug Resistance Mutations Detection by Next-Generation Sequencing during Antiretroviral Therapy Interruption in China

Author

Li, Miaomiao, primary, Liang, Shujia, additional, Zhou, Chao, additional, Chen, Min, additional, Liang, Shu, additional, Liu, Chunhua, additional, Zuo, Zhongbao, additional, Liu, Lei, additional, Feng, Yi, additional, Song, Chang, additional, Xing, Hui, additional, Ruan, Yuhua, additional, Shao, Yiming, additional, and Liao, Lingjie, additional

Published
2021
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