模拟 HIV-1 的控制和缓解。

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Bharadwaj Vemparala, Shreya Chowdhury, Jérémie Guedj, Narendra M Dixit
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引用次数: 0

摘要

目前,在开发可使 HIV-1 感染长期缓解的干预措施方面取得了显著进展。这些干预措施的成功将使目前的治疗标准--终生抗逆转录病毒疗法--不再需要,并造福于当今数以百万计的 HIV-1 感染者。数学建模为这些努力做出了重大贡献。它帮助阐明了自然控制和治疗后控制的可能机理起源,推断了失去这种控制的潜在途径,量化了干预措施的效果,并开发了合理优化干预措施的框架。然而,一些重要的问题依然存在,给这些前景广阔的干预措施的转化带来了挑战。在此,我们将回顾 HIV-1 控制和缓解数学建模的最新进展,强调其贡献,并讨论未来发展的潜在途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Modelling HIV-1 control and remission.

Modelling HIV-1 control and remission.

Remarkable advances are being made in developing interventions for eliciting long-term remission of HIV-1 infection. The success of these interventions will obviate the need for lifelong antiretroviral therapy, the current standard-of-care, and benefit the millions living today with HIV-1. Mathematical modelling has made significant contributions to these efforts. It has helped elucidate the possible mechanistic origins of natural and post-treatment control, deduced potential pathways of the loss of such control, quantified the effects of interventions, and developed frameworks for their rational optimization. Yet, several important questions remain, posing challenges to the translation of these promising interventions. Here, we survey the recent advances in the mathematical modelling of HIV-1 control and remission, highlight their contributions, and discuss potential avenues for future developments.

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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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