A biophysical detailed multiscale model of the myocardium is presented. The model was used to study the contribution of interrelated cellular mechanisms to global myocardial function. The multiscale model integrates cellular electrophysiology, excitation propagation dynamics and force development models into a geometrical fiber based model of the ventricle. The description of the cellular electrophysiology in this study was based on the Ten Tusscher-Noble-Noble-Panfilov heterogeneous model for human ventricular myocytes. A four-state model of the sarcomeric control of contraction developed by Negroni and Lascano was employed to model the intracellular mechanism of force generation. The propagation of electrical excitation was described by a reaction-diffusion equation. The 3D geometrical model of the ventricle, based on single fiber contraction was used as a platform for the evaluation of proposed models. The model represents the myocardium as an anatomically oriented array of contracting fibers with individual fiber parameters such as size, spatial location, orientation and mechanical properties. Moreover, the contracting ventricle model interacts with intraventricular blood elements linking the contractile elements to the heart's preload and afterload, thereby producing the corresponding pressure-volume loop. The results show that the multiscale ventricle model is capable of simulating mechanical contraction, pressure generation and load interactions as well as demonstrating the individual contribution of each ion current.

Mechano-electric feedback affects the electrophysiological and mechanical function of the heart and the cellular, tissue, and organ properties. To determine the main factors that contribute to this effect, this study investigated the changes in the action potential characteristics of the ventricle during contraction. A model of stretch-activated channels was incorporated into a three-dimensional multiscale model of the contracting ventricle to assess the effect of different preload lengths on the electrophysiological behavior. The model describes the initiation and propagation of the electrical impulse, as well as the passive (stretch) and active (contraction) changes in the cardiac mechanics. Simulations were performed to quantify the relationship between the cellular activation and recovery patterns as well as the action potential durations at different preload lengths in normal and heart failure pathological conditions. The simulation results showed that heart failure significantly affected the excitation propagation parameters compared to normal condition. The results showed that the mechano-electrical feedback effects appear to be most important in failing hearts with low ejection fraction.

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Funding Acknowledgements Type of funding sources: Public hospital(s). Main funding source(s): Al-mouwasat University Hospital, University Heart Surgery Center in Damascus, Syrian Arab Republic. Background left ventricular (LV) diastolic function and filling pressure assessment is a challenge. ESC 2016 diastolic guidelines handles with this issue. Validation of and comparing the correlation between this guidelines and invasively measured different waves may add a step forward in the assessment, prognosis and treatment of LV diastolic function by echo. Purpose this study validates of the correlation of ESC 2016 left ventricular filling pressure echo guidelines with invasively measured left ventricular end-diastolic pressure and left ventricular pre-a. Methods 124 patients who accepted to participate for this study underwent transthoracic echocardiography immediately before left heart catheterization. This study obtained echo parameters to assess LV filling pressure according to ESC 2016 algorithms. It also obtained left ventricular end-diastolic pressure (LVEDP) and LV pre-a waves during catheterization. It analyzed the data and compared the results. Results Correlations of grading system (normal, abnormal parameters 1,2 and 3 present) with LV pre-a and LVEDP waves were (P= < 0.0001 r = 0.47, P = 0.0027 r = 0.41), respectively. After excluding group of patients with only one abnormal parameter as indeterminate group, pressure assessment guidelines correlations with the presence of LV pre-a and LVEDP waves were (P = 0.0009 OR = 31.76, p= 0.0170 OR = 36.00), respectively. Means difference of LV pre-a and LVEDP waves between pressure guidelines presence and absence two groups were (LV pre-a: 12.72, 7.52, P < 0.0001and LVEDP: 21.03 10.36, P = 0.0043), respectively. All results are summarized in (Table:1 + 2+3 + 4+5). Conclusion ESC 2016 guidelines pressure assessment correlated strongly with both LV pre-a and LVEDP waves which means that the higher the number of abnormal echo parameters is resulted by echo guidelines, the higher the LV pre-a or LVEDP is presented invasively. Different approaches had different diagnostic accuracy, the best specific was cutoff≥ 2 abnormal echo parameters and the best sensitive and overall accuracy was still cutoff≥2 but after excluding only one abnormal echo parameter group as indeterminate group. The difference between means between echo guidelines pressure assessment was more significant statistically in LV pre-a wave than in LVEDP. Abstract Figure. Abstract Figure.

Computational methods and tools are a powerful complementary approach to experimental work for studying regulatory interactions in living cells and systems. We demonstrate the use of formal reasoning methods as applied to the Caenorhabditis elegans germ line, which is an accessible model system for stem cell research. The dynamics of the underlying genetic networks and their potential regulatory interactions are key for understanding mechanisms that control cellular decision making between stem cells and differentiation.We model the 'stem cell fate' versus entry into the 'meiotic development' pathway decision circuit in the young adult germ line based on an extensive study of published experimental data and known/hypothesized genetic interactions. We apply a formal reasoning framework to derive predictive networks for control of differentiation. Using this approach we simultaneously specify many possible scenarios and experiments together with potential genetic interactions, and synthesize genetic networks consistent with all encoded experimental observations. In silico analysis of knock-down and overexpression experiments within our model recapitulate published phenotypes of mutant animals and can be applied to make predictions on cellular decision-making. This work lays a foundation for developing realistic whole tissue models of the C. elegans germ line where each cell in the model will execute a synthesized genetic network.