Journal of Theoretical Biology最新文献

Colorectal cancer (CRC) poses a major public health challenge due to its increasing prevalence, particularly among younger populations. Microsatellite instability-high (MSI-H) CRC and deficient mismatch repair (dMMR) CRC constitute 15 % of all CRC and exhibit remarkable responsiveness to immunotherapy, especially with PD-1 inhibitors. Despite this, there is a significant need to optimise immunotherapeutic regimens to maximise clinical efficacy and patient quality of life. To address this, we employ a novel framework driven by delay integro-differential equations to model the interactions among cancer cells, immune cells, and immune checkpoints in locally advanced MSI-H/dMMR CRC (laMCRC). Several of these components are being modelled deterministically for the first time in cancer, paving the way for a deeper understanding of the complex underlying immune dynamics. We consider two compartments: the tumour site and the tumour-draining lymph node, incorporating phenomena such as dendritic cell (DC) migration, T cell proliferation, and CD8+ T cell exhaustion and reinvigoration. Parameter values and initial conditions are derived from experimental data, integrating various pharmacokinetic, bioanalytical, and radiographic studies, along with deconvolution of bulk RNA-sequencing data from the TCGA COADREAD and GSE26571 datasets. We finally optimised neoadjuvant treatment with pembrolizumab, a widely used PD-1 inhibitor, to balance efficacy, efficiency, and toxicity in laMCRC patients. We mechanistically analysed factors influencing treatment success and improved upon currently FDA-approved therapeutic regimens for metastatic MSI-H/dMMR CRC, demonstrating that a single medium-to-high dose of pembrolizumab may be sufficient for effective tumour eradication while being efficient, safe and practical.

The link between the virus and antibody dynamics of an infected host to the transmission of the virus to a susceptible population remains a central problem in science as it involves several complex and dynamic processes at different scales. In this study, we integrate deterministic and stochastic within-host models to explore multiscale transmission dynamics. Our methodology accounts for encounter frequency, within-host variability, and reinfection dynamics to assess their impact on epidemic progression. Our results show that within-host stochasticity disrupts synchronized viral peaks, leading to a more uniform transmission pattern and reducing the effectiveness of interventions targeting peak viral load. Considering the half-life of antibodies is 25 days, cycles of reinfections cannot be maintained in small populations, but reinfections become self-sustaining when a circular network exceeds 21 nodes, allowing indefinite circulation. These findings emphasize the need for integrating within-host dynamics in epidemic research.

The HIV epidemic in sub-Saharan Africa is historically characterised by high levels of prevalence and incidence. With the global effort to reach UNAIDS 95-95-95 targets, the scaling-up of HIV treatment, and focused preventive interventions, incidence has been declining over the past decade, albeit non-consistently across different sex and age groups. Two questions remain to be addressed to help tailor setting-specific interventions and allocate resources optimally. Firstly, are there unidentified demographic groups that are sources of transmission? Secondly, what are the patterns of decline in incidence across different groups? Model-based assessment is a valuable tool for the design of focused interventions and to answer these questions. PopART-IBM, an individual-based model calibrated to (anonymised) age-and-sex stratified data, was developed in the context of the HPTN-071 (PopART) trial, and it offers a unique opportunity to explore such questions in the context of high-burden HIV communities in Zambia and South Africa. The outputs of the model include the full HIV transmission and partnership networks. In this work, we explore these and show that the sexual partnership network exhibits a large connected component, usually comprising over 40 % of the population, in each of the studied communities. An analysis of the large connected component reveals that it is formed by young people (20-40 years old) and is centered around the most sexually active individuals of the community. At the same time, many individuals in the large connected component only have one partner, highlighting the complex dynamics of risk correlations in a population. Inspecting the transmission network reveals that, on average, more than 80% of transmissions occur among individuals belonging to the large connected component. These findings indicate that populations consisting of young and highly sexually active individuals should be given high priority when designing or deploying interventions.