BackgroundApoptosis is an essential property of all higher organisms that involves extremely complex signaling pathways. Mathematical modeling provides a rigorous integrative approach for analyzing and understanding such intricate biological systems.ResultsHere, we constructed a large-scale, literature-based model of apoptosis pathways responding to an external stimulus, cisplatin. Our model includes the key elements of three apoptotic pathways induced by cisplatin: death receptor-mediated, mitochondrial, and endoplasmic reticulum-stress pathways. We showed that cisplatin-induced apoptosis had dose- and time-dependent characteristics, and the level of apoptosis was saturated at higher concentrations of cisplatin. Simulated results demonstrated that the effect of the mitochondrial pathway on apoptosis was the strongest of the three pathways. The cross-talk effect among pathways accounted for approximately 25% of the total apoptosis level.ConclusionsUsing this model, we revealed a novel mechanism by which cisplatin induces dose-dependent cell death. Our finding that the level of apoptosis was affected by not only cisplatin concentration, but also by cross talk among pathways provides in silico evidence for a functional impact of system-level characteristics of signaling pathways on apoptosis.

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Flow resistances exerted in the coronary arteries are the key parameters for the image-based computer simulation of coronary hemodynamics. The resistances depend on the anatomical characteristics of the coronary system. A simple and reliable estimation of the resistances is a compulsory procedure to compute the fractional flow reserve (FFR) of stenosed coronary arteries, an important clinical index of coronary artery disease. The cardiac muscle volume reconstructed from computed tomography (CT) images has been used to assess the resistance of the feeding coronary artery (muscle volume-based method). In this study, we estimate the flow resistances exerted in coronary arteries by using a novel method. Based on a physiological observation that longer coronary arteries have more daughter branches feeding a larger mass of cardiac muscle, the method measures the vessel lengths from coronary angiogram or CT images (vessel length-based method) and predicts the coronary flow resistances. The underlying equations are derived from the physiological relation among flow rate, resistance, and vessel length. To validate the present estimation method, we calculate the coronary flow division over coronary major arteries for 50 patients using the vessel length-based method as well as the muscle volume-based one. These results are compared with the direct measurements in a clinical study. Further proving the usefulness of the present method, we compute the coronary FFR from the images of optical coherence tomography.

The purpose of this study was to propose a patient-specific model of atrial fibrillation (AF) and apply it to virtual radiofrequency ablation (RFA). We obtained patient-specific geometries of the left atrium (LA) from CT data and constructed three-dimensional (3D) simulation models. A bidomain Courtemanche model was used to simulate the 3D electric waves on the LA surface, and an S1-S2 protocol was applied to induce AF in the model. To identify scar areas in the models, we converted clinically measured voltage data on the LA surface to the scar maps of the simulation model. Then, after initiation of AF, we applied the virtual ablation scheme to the model and investigated whether the AF was terminated by the scheme. The computed results of AF and ablation were similar to those of clinical observation, providing a clinically important simulation method for preclinical virtual trials of AF treatment.