Mathematical Models of Early Hepatitis B Virus Dynamics in Humanized Mice.
Stanca M CiupeHarel DahariAlexander PlossPublished in: Bulletin of mathematical biology (2024)
Analyzing the impact of the adaptive immune response during acute hepatitis B virus (HBV) infection is essential for understanding disease progression and control. Here we developed mathematical models of HBV infection which either lack terms for adaptive immune responses, or assume adaptive immune responses in the form of cytolytic immune killing, non-cytolytic immune cure, or non-cytolytic-mediated block of viral production. We validated the model that does not include immune responses against temporal serum hepatitis B DNA (sHBV) and temporal serum hepatitis B surface-antigen (HBsAg) experimental data from mice engrafted with human hepatocytes (HEP). Moreover, we validated the immune models against sHBV and HBsAg experimental data from mice engrafted with HEP and human immune system (HEP/HIS). As expected, the model that does not include adaptive immune responses matches the observed high sHBV and HBsAg concentrations in all HEP mice. By contrast, while all immune response models predict reduction in sHBV and HBsAg concentrations in HEP/HIS mice, the Akaike Information Criterion cannot discriminate between non-cytolytic cure (resulting in a class of cells refractory to reinfection) and antiviral block functions (of up to 99 % viral production 1-3 weeks following peak viral load). We can, however, reject cytolytic killing, as it can only match the sHBV and HBsAg data when we predict unrealistic levels of hepatocyte loss.
Keyphrases
- hepatitis b virus
- immune response
- liver failure
- high fat diet induced
- dendritic cells
- toll like receptor
- endothelial cells
- electronic health record
- big data
- magnetic resonance
- sars cov
- healthcare
- intensive care unit
- induced apoptosis
- type diabetes
- induced pluripotent stem cells
- cell proliferation
- endoplasmic reticulum stress
- pi k akt
- aortic dissection
- deep learning
- circulating tumor