WG Seminars: Garira, Disease Dynamics and Shenoy, Fibroblasts and Macrophages, April 15, 2021

Описание: A Theory for Multiscale Modeling of Disease Dynamics
Winston Garira
University of Venda
South Africa

Most scientific fields have been made over with a revolutionary theory at least once in recent centuries. Such paradigm shifts reorder old knowledge into a new framework. Revolutionary theories succeed when the new framework they introduce makes it possible to solve problems that challenged the previous intellectual regime. In this talk, I will discuss about a theory for multiscale dynamics of infectious diseases. This theory reorders old scientific knowledge of disease dynamics based on transmission mechanism theory into a new framework based on the multiscale dynamics of infectious disease called the replication-transmission relativity theory. The replication-transmission relativity theory states that at every level of organization of an infectious disease system, there is no privileged or absolute scale which would determine disease dynamics, only interactions between the microscale and macroscale. It identifies an infectious disease system as a complex system which is organized into seven main hierarchical levels at which host-pathogen interactions can play out. Describing the multiscale dynamics of an infectious in its entirety as a complex system is a mammoth task. The replication-transmission relativity theory enables us to bring down the complexity of an infectious disease system to manageable levels by discretizing or decomposing the infectious disease system into hierarchical levels of organization, each of which, can analyzed independently using multiscale modelling methods. This theory ripped the entire fabric of classical transmission mechanism theory which has been in existence at least since Daniel Bernoulli developed a dynamic model of smallpox transmission and control in 1760, which was later unified by Kermack and McKendrick in their seminal work, into an idea now more widely known as mathematical epidemiology. It demolished the notion that transmission is the only main dynamic process in infectious disease dynamics. I anticipate that the replication-transmission relativity theory will remain firmly established as the fundamental theory on which multiscale modelling of infectious disease dynamics is based on from the cell level to the macro ecosystem level. Therefore, with a theory in place, we expect that multiscale modelling of infectious disease systems will evolve and expand in scope.

Dynamic Fibroblast Contractions Attract Remote Macrophages in Fibrillar Collagen Matrix
Vivek Shenoy
University of Pennsylvania

Macrophage (Mϕ)-fibroblast interactions coordinate tissue repair after injury whereas miscommunications can result in pathological healing and fibrosis. We show that contracting fibroblasts generate deformation fields in fibrillar collagen matrix that provide far-reaching physical cues for Mϕ. Within collagen deformation fields created by fibroblasts or actuated microneedles, Mϕ migrate towards the force source from several hundreds of micrometers away. The presence of a dynamic force source in the matrix is critical to initiate and direct Mϕ migration. In contrast, collagen condensation and fiber alignment resulting from fibroblast remodeling activities or chemotactic signals are neither required nor sufficient to guide Mϕ migration. Binding of α2β1 integrin and stretch-activated channels mediate Mϕ migration and mechanosensing in fibrillar collagen ECM. We propose that Mϕ mechanosense the velocity of local displacements of their substrate, allowing contractile fibroblasts to attract Mϕ over distances that exceed the range of chemotactic gradients.

If you found this video useful, please check out our other videos on computational modeling, infection and immunology:    • IMAG/MSM WG and GLIMPRINT Seminars on Mult...  

Please consider joining our IMAG/MSM WG on Multiscale Modeling and Viral Pandemics: https://www.imagwiki.nibib.nih.gov/co...

Please also consider joining the Global Alliance for Immune Prediction and Intervention: http://glimprint.org/