One of the key events in the HIV-1 life cycle is reverse transcription, during which single-stranded viral RNA (ssRNA) is converted into double-stranded DNA (dsDNA). This process occurs inside the mature virus capsid and, once it reaches a critical threshold, drives capsid rupture. This uncoating is essential for infection because it releases viral genetic material into the host cell nucleus. Despite its importance, many mechanistic details of this process remain poorly understood. To address this gap, we develop a multiscale computational method for simulating reverse transcription inside the capsid, termed Coarse-Grained Kinetic Monte Carlo (CG-KMC). CG-KMC stochastically adds deoxynucleotide triphosphates (dNTPs) to the coarse-grained RNA model, enabling stepwise growth of DNA inside the HIV-1 capsid. We implement this method within an integrative coarse-grained framework that combines a "bottom-up" capsid model with a "top-down" representation of the viral RNA/DNA genome. Our simulations phenomenologically capture and predict diverse capsid rupture pathways during reverse transcription. The resulting ruptured structures closely match previously identified cryo-ET images. We further perform an extensive analysis of the rupture process, examining its mechanistic and kinetic aspects as well as the role of capsid-DNA interactions. Our findings illuminate how different capsid-DNA conditions give rise to distinct rupture pathways, which differ from ruptures due to simple outward pressure expansion models from within the capsid.
Measuring and reducing surgical staff stress in a realistic operating room setting using EDA monitoring and smart hearing protection
BackgroundStress is a critical factor in the operating room (OR) and affects both the performance and well-being of surgical staff. Measuring and mitigating this stress



