CD8⁺ “cytotoxic” T cells are important for the immune control of HIV and the closely related simian models SIV and chimeric simian–human immunodeficiency virus (SHIV), although the mechanisms of this control are unclear. One effect of CD8⁺ T cell-mediated recognition of virus-infected cells is the rapid selection of escape mutant (EM) virus that is not recognized. To investigate the mechanisms of virus-specific CD8⁺ T cell control during immune escape in vivo, we used a real-time PCR assay to study the dynamics of immune escape in early SHIV infection of pigtail macaques. For immune escape mediated by cytolysis, we would expect that the death rate of wild type (WT) infected cells should be faster than that of EM-infected cells. In addition, escape should be fastest during periods when the total viral load is declining. However, we find that there is no significant difference in the rate of decay of WT virus compared with EM virus. Further, immune escape is often fastest during periods of viral growth, rather than viral decline. These dynamics are consistent with an epitope-specific, MHC class I-restricted, noncytolytic mechanism of CD8⁺ T cell control of SHIV that specifically inhibits the growth of WT virus in vivo.

Triple negative breast cancer (TNBC) is the most aggressive subtype of breast cancer in women. It has the poorest prognosis along with limited therapeutic options. Smart nano-based carriers are emerging as promising approaches in treating TNBC due to their favourable characteristics such as specifically delivering different cargos to cancer cells. However, nanoparticles’ tumour cell uptake, and subsequent drug release, are essential factors considered during the drug development process. Contemporary qualitative analyses based on imaging are cumbersome and prone to human biases. Deep learning-based algorithms have been well-established in various healthcare settings with promising scope in drug discovery and development. In this study, the performance of five different convolutional neural network models was evaluated. In this research, we investigated two sequential models from scratch and three pre-trained models, VGG16, ResNet50, and Inception V3. These models were trained using confocal images of nanoparticle-treated cells loaded with a fluorescent anticancer agent. Comparative and cross-validation analyses were further conducted across all models to obtain more meaningful results. Our models showed high accuracy in predicting either high or low drug uptake and release into TNBC cells, indicating great translational potential into practice to aid in determining cellular uptake at the early stages of drug development in any area of research.

Persistence of HIV DNA presents a major barrier to the complete control of HIV infection under current therapies. Most studies suggest that cells with latently integrated HIV decay very slowly under therapy. However, it is much more difficult to study the turnover and persistence of HIV DNA during active infection. We have developed an “escape clock” approach for measuring the turnover of HIV DNA in resting CD4+ T cells. This approach studies the replacement of wild-type (WT) SIV DNA present in early infection by CTL escape mutant (EM) strains during later infection. Using a strain-specific real time PCR assay, we quantified the relative amounts of WT and EM strains in plasma SIV RNA and cellular SIV DNA. Thus we can track the formation and turnover of SIV DNA in sorted resting CD4+ T cells. We studied serial plasma and PBMC samples from 20 SIV-infected Mane-A*10 positive pigtail macaques that have a signature Gag CTL escape mutation. In animals with low viral load, WT virus laid down early in infection is extremely stable, and the decay of this WT species is very slow, consistent with findings in subjects on anti-retroviral medications. However, during active, high level infection, most SIV DNA in resting cells was turning over rapidly, suggesting a large pool of short-lived DNA produced by recent infection events. Our results suggest that, in order to reduce the formation of a stable population of SIV DNA, it will be important either to intervene very early or intervene during active replication. New treatments for HIV have proved very successful at controlling viral replication and preventing the onset of AIDS. However, these treatments must be continued for life, because if they are stopped the virus rapidly ‘rebounds’ to its original levels. The reason for this rebound is the existence of a population of viruses that lie dormant inside cells during treatment, and reactivate as soon as treatment is stopped. This ‘latent virus’ is extremely long-lived under drug therapy conditions, and therefore presents a major barrier to viral eradication. However, very little is known about the survival and reactivation of latently infected cells during ongoing infection, because virus is being formed and destroyed all the time. We have developed a novel ‘escape clock’ approach to measure how long viral DNA lasts in monkeys. We find that, in the setting of low viral load, the lifespan of infected cells is very long, whereas during active infection there is a surprisingly high turnover of viral DNA within resting CD4 T cells. We believe this is due to high level of immune activation when there is a high level of replicating virus. This result may have important implications for the optimal timing of drug treatment.