The human immunodeficiency virus (HIV) is a type of retrovirus that infects humans and belongs to the Lentivirus group. Despite the availability of effective treatments, HIV infections are still increasing in some parts of the world, according to the World Health Organization (WHO). Another major challenge is the growing problem of HIV becoming resistant to drugs. This highlights the importance of ongoing research to better understand HIV and find new ways to stop the virus from spreading in the body. Scientists use a variety of methods to study HIV, including techniques from molecular and cellular biology. Many of these methods rely on fluorescent dyes to help visualize specific parts of the virus or infected cells. This article focuses on a technique called imaging flow cytometry, which is particularly useful for studying HIV. Imaging flow cytometry is unique because it not only measures fluorescence (light emitted by the dyes) but also captures images of each cell being analyzed. This allows researchers to see where the fluorescence is located within the cell and to study the cell’s shape and structure in detail. Additionally, this method can be combined with machine learning to analyze large amounts of data more efficiently.
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