English

Andrei Garzon Dasgupta

Cellular automaton modelling of platelet aggregation

Platelet aggregation plays an important role in hemostasis, as it prevents blood loss upon vessel wall disruption. Computational modelling is one of the useful approaches to study this system.  The use of a cellular automaton as a model makes it possible both to study the dynamics of individual aggregates and to investigate the behaviour of the system as a whole. The aim of this research is to study platelet aggregation using a model based on a cellular automaton. As a result, a model of platelet aggregation in the basic approximation and with flow condition was constructed. It was shown that under flow conditions, the most number of the aggregates are dimers and trimers, whereas aggregates of large sizes are much less presented.

null
419
0
#platelet aggregation#mathematical modeling#cellular automaton

STIM1-ORAI1 direct interaction cannot govern store-operated calcium entry (SOCE) in platelets

Store-operated calcium entry (SOCE) plays an important role in platelet function. It is generally assumed that the mechanism of SOCE relies on the direct interaction of STIM1 and ORAI1 proteins with specific STIM1:ORAI1 stoichiometry. However, in platelets, other pathways may take place. Here we aim to investigate the mechanisms of SOCE in platelets. We developed a lattice-based mathematical model that represented STIM1-ORAI1 interactions and applied it to both HEK cells, where SOCE mechanism is well established, and platelets. The model was able to describe STIM1-ORAI1 behavior in HEK cells successfully. We used the same parameters for protein interaction and applied them to platelets. As a result, we demonstrated that the number of STIM1 proteins on ER membrane could not assure the needed stoichiometry to proper SOCE in platelets.

(A) STIM1-ORAI1 interaction for HEK cells. Bound proteins are presented by brown, STIM1 in cluster – green, free proteins - red. (B) STIM1-ORAI1 puncta formation dependance on clustering probability. Dashed lines represent same process for D=0.01 〖μm〗^2/s (C) Typical system state at t=100ms for different clustering probabilities
6 935
0
#platelets#mathematical modeling#store-operated calcium entry#platelet intracellular signaling