Johnston, Barbara M Johnston, Peter R
Published in
Mathematical biosciences

Mathematical modelling is a useful technique to help elucidate the connection between non-transmural ischaemia and ST elevation and depression of the ECG. Generally, models represent non-transmural ischaemia using an ischaemic zone that extends from the endocardium partway to the epicardium. However, recent experimental work has suggested that isch...

Sellinger, Thibaut Müller, Johannes Hösel, Volker Tellier, Aurélien
Published in
Mathematical biosciences

Despite the wealth of empirical and theoretical studies, the origin and maintenance of cooperation is still an evolutionary riddle. In this context, ecological life-history traits which affect the efficiency of selection may play a role despite being often ignored. We consider here species such as bacteria, fungi, invertebrates and plants which exh...

Köhnke, M C Malchow, H
Published in
Mathematical biosciences

Biological invasions have impacts on diverse social, ecological, and economic issues. Among others, invasion success can be determined by epidemiological aspects, intraspecific dynamics as, e.g., Allee effects, and interspecific interactions as, e.g., competition. In this study, a process-based model describing competitive eco-epidemiological dynam...

Sigal, Daniel Przedborski, Michelle Sivaloganathan, Darshan Kohandel, Mohammad
Published in
Mathematical biosciences

The cancer stem cell hypothesis states that tumors are heterogeneous and comprised of several different cell types that have a range of reproductive potentials. Cancer stem cells (CSCs), represent one class of cells that has both reproductive potential and the ability to differentiate. These cells are thought to drive the progression of aggressive ...

Bichara, Derdei M Guiro, Aboudramane Iggidr, Abderrahman Ngom, Diene
Published in
Mathematical biosciences

We develop a general framework to estimate the proportion of infected snails and snail-human transmission parameter of a class of models that describes the evolution of schistosomiasis. To do so, we consider simultaneously the dynamics of schistosomiasis, captured by the homogeneous version of the classical MacDonald's model, and the measurable out...

Piretto, Elena Delitala, Marcello Kim, Peter S Frascoli, Federico
Published in
Mathematical biosciences

Cancer development is driven by mutations and selective forces, including the action of the immune system and interspecific competition. When administered to patients, anti-cancer therapies affect the development and dynamics of tumours, possibly with various degrees of resistance due to immunoediting and microenvironment. Tumours are able to expre...

Anderson, Daniel M Benson, James D Kearsley, Anthony J
Published in
Mathematical biosciences

Modeling a cell's response to encroaching ice has informed the development of cryopreservation protocols for four decades. It has been well documented that knowledge of the cellular state as a function of media and cooling rate faciliate informed cryopreservation protocol design and explain mechanisms of damage. However, previous efforts have negle...

Albers, David J Levine, Matthew E Mamykina, Lena Hripcsak, George
Published in
Mathematical biosciences

One way to interject knowledge into clinically impactful forecasting is to use data assimilation, a nonlinear regression that projects data onto a mechanistic physiologic model, instead of a set of functions, such as neural networks. Such regressions have an advantage of being useful with particularly sparse, non-stationary clinical data. However, ...

Nishikawa, S Takamatsu, A
Published in
Mathematical biosciences

Cell death-induced proliferation (CDIP) is a phenomenon in which cell death activates neighboring cells and promotes their proliferation. It was first reported as "compensatory proliferation" in injured tissues, which functions to maintain normal tissues. On the other hand, this phenomenon also affects potentially tumorigenic mutant cells and promo...

Reid, Brandon M Sidje, Roger B
Published in
Mathematical biosciences

When modeling a physical system using a Markov chain, it is often instructive to compute its probability distribution at statistical equilibrium, thereby gaining insight into the stationary, or long-term, behavior of the system. Computing such a distribution directly is problematic when the state space of the system is large. Here, we look at the c...