Redistribution of TPA Fluxes in the Presence of PAI-1 Regulates Spatial Thrombolysis

Abstract

The fibrin clot is gelatinous matter formed upon injury to stop blood loss and is later destroyed by fibrinolysis, an enzymatic cascade with feedback. Pharmacological fibrinolysis stimulation is also used to destroy pathological, life-threatening clots and thrombi (thrombolysis). The regulation of the nonlinear spatially nonuniform fibrinolytic process in thrombolysis is not currently well understood. We developed a reaction-diffusion-advection model of thrombolysis by tissue plasminogen activator (TPA) in an occluded vessel with a pressure gradient. Sensitivity-analysis-based model reduction was used to reveal the critical processes controlling different steps of thrombolysis. The propagation of thrombolysis in the system without flow was predominantly controlled by TPA diffusion, whereas transport of other active components was rendered nonessential either by their high fibrin-binding parameters and short lifetimes or their initial uniform distribution. The concentration of the main TPA inhibitor plasminogen activator inhibitor 1 (PAI-1) controlled both the extent of lysis propagation and the shape of fibrin spatial distribution during lysis. Interestingly, PAI-1 remained important even when its concentration was an order of magnitude below that of TPA because of its role at the edge of the diffusing TPA front. The system was robust to reaction rate constant perturbations. Using these data, a reduced model of thrombolysis was proposed. In the presence of flow, convection of TPA was the critical controlling process; although the role of PAI-1 concentration was much less in the presence of flow, its influence became greater in the presence of collateral bypassing vessels, which sufficiently reduced TPA flux through the thrombus. Flow bypass through the collateral vessel caused a decrease in TPA flux in the clotted vessel, which increased the PAI-1/TPA ratio, thus making PAI-1-induced inhibition relevant for the regulation of spatial lysis up to its arrest.

Investigating the two regimes of fibrin clot lysis: an experimental and computational approach

“…In their work, the authors directly used plasmin, whereas in our case, we used tPA and Pg. However, the diffusion constants of plasmin, Pg, and tPA are quite similar (16); thus, if plasmin can diffuse more easily (according to Feller et al), it might also be the case for tPA and Pg. Our hypothesis of dynamical change of binding sites accessibility may implement a coarse-grained version of the aforementioned phenomenological mechanism.…”

“…Even though it is recognized that computer simulations are an essential tool to deal with this complexity, mathematical modeling remains challenging. Compartmental models describing the biochemical processes of the coagulation and the lysis of the clot require dozens of differential equations ( 13 , 14 ), as well as advanced sensitivity analysis, to decipher the most relevant components of the reactions ( 15 , 16 ).…”

Investigating the two regimes of fibrin clot lysis: an experimental and computational approach

“…Then an excess of thrombin is added and the attenuation of a light beam through the test-tube is measured as a function of time, first indicating the clot formation and then the clot lysis. For this purpose, we designed a completely computerised semi-automated 8-channel measurement and determination of fibrin clot lysis (EREM, Belgium) (16). Biefly, a computer records every one minute the data from each channel.…”

“…Even though it is recognized that computer simulations is an essential tool to deal with this complexity, mathematical modeling remains challenging. Compartmental models describ-ing the biochemical processes of the coagulation and the lysis of the clot require dozens of differential equations [13,14] as well as advanced sensitivity analysis to decipher the most relevant components of the reactions [15,16]. In this work we combine in vitro experiments and computational modeling analysis of fibrin rich clot formation and lysis.…”

des-ist: A Simulation Framework to Streamline Event-Based In Silico Trials

“…The pipeline considers a containerised environment for each distinct event identified in the clinical trial, i.e. virtual patient generation, initial randomised clot placement, blood-flow and brain (re)perfusion analysis [7,12], chemical and mechanical treatments using thrombolysis [15] and thrombectomy [10], and finally the NIHSS scoring of each virtual patient [1].…”