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   https://doi.org/10.1016/j.jtbi.2020.110502  

   Guo, Ting; Qiu, Zhipeng; Kitagawa, Kosaku; Iwami, Shingo; Rong, Libin (January 2021, Journal of Theoretical Biology)

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2. Modeling the Effect of HIV/AIDS Stigma on HIV Infection Dynamics in Kenya

   https://doi.org/10.1007/s11538-021-00891-7  

   Levy, Ben; Correia, Hannah E.; Chirove, Faraimunashe; Ronoh, Marilyn; Abebe, Ash; Kgosimore, Moatlhodi; Chimbola, Obias; Machingauta, M. Hellen; Lenhart, Suzanne; White, K. A. (May 2021, Bulletin of Mathematical Biology)

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   Abstract Stigma toward people living with HIV/AIDS (PLWHA) has impeded the response to the disease across the world. Widespread stigma leads to poor adherence of preventative measures while also causing PLWHA to avoid testing and care, delaying important treatment. Stigma is clearly a hugely complex construct. However, it can be broken down into components which include internalized stigma (how people with the trait feel about themselves) and enacted stigma (how a community reacts to an individual with the trait). Levels of HIV/AIDS-related stigma are particularly high in sub-Saharan Africa, which contributed to a surge in cases in Kenya during the late twentieth century. Since the early twenty-first century, the United Nations and governments around the world have worked to eliminate stigma from society and resulting public health education campaigns have improved the perception of PLWHA over time, but HIV/AIDS remains a significant problem, particularly in Kenya. We take a data-driven approach to create a time-dependent stigma function that captures both the level of internalized and enacted stigma in the population. We embed this within a compartmental model for HIV dynamics. Since 2000, the population in Kenya has been growing almost exponentially and so we rescale our model system to create a coupled system for HIV prevalence and fraction of individuals that are infected that seek treatment. This allows us to estimate model parameters from published data. We use the model to explore a range of scenarios in which either internalized or enacted stigma levels vary from those predicted by the data. This analysis allows us to understand the potential impact of different public health interventions on key HIV metrics such as prevalence and disease-related death and to see how close Kenya will get to achieving UN goals for these HIV and stigma metrics by 2030. 

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3. A Network Immuno-Epidemiological HIV Model

   https://doi.org/10.1007/s11538-020-00855-3  

   Gupta, Churni; Tuncer, Necibe; Martcheva, Maia (March 2021, Bulletin of Mathematical Biology)

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4. HSF1 Activation Can Restrict HIV Replication

   https://doi.org/10.1021/acsinfecdis.0c00166  

   Nekongo, Emmanuel E.; Ponomarenko, Anna I.; Dewal, Mahender B.; Butty, Vincent L.; Browne, Edward P.; Shoulders, Matthew D. (July 2020, ACS Infectious Diseases)

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5. The role of tunneling nanotubes during early stages of HIV infection and reactivation: implications in HIV cure

   https://doi.org/10.1515/nipt-2022-0015  

   Valdebenito, Silvana; Ono, Akira; Rong, Libin; Eugenin, Eliseo A. (August 2022, NeuroImmune Pharmacology and Therapeutics)

   Abstract Tunneling nanotubes (TNTs), also called cytonemes or tumor microtubes, correspond to cellular processes that enable long-range communication. TNTs are plasma membrane extensions that form tubular processes that connect the cytoplasm of two or more cells. TNTs are mostly expressed during the early stages of development and poorly expressed in adulthood. However, in disease conditions such as stroke, cancer, and viral infections such as HIV, TNTs proliferate, but their role is poorly understood. TNTs function has been associated with signaling coordination, organelle sharing, and the transfer of infectious agents such as HIV. Here, we describe the critical role and function of TNTs during HIV infection and reactivation, as well as the use of TNTs for cure strategies. 

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