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A mechanical mock of the cardiovascular system was used to simulate different conditions of ventricular-arterial mechanical matching. Four ventricles and four aortas with different elastances were set up, and all possible connection combinations tested by sampling ventricular and aortic pressures and flows. The mechanical energy produced by the simulated ventricles and the amount transferred to the aorta in the different connection conditions were calculated. The results demonstrate a clear dependence between the mechanical work production of the ventricles and the ventricular elastance (slope of the end-systolic pressure–volume relation) (from 20.42 ± 0.02 mJ/beat to 12.10 ± 0.02 mJ/beat), and an efficiency of energy transfer to the aorta strongly dependent on ventricular-aortic mechanical matching (from 56% to 20.7%). These results show that, even in optimal simulated conditions, only 56% of the energy produced is transferred to the load; and highlight the important role of mechanical aspects in conditions of very limited cardiovascular performance (i.e. final stages of heart failure), where energy transfer efficiency may be as low as 20.7%. This evidence emphasizes that the mechanical aspects must also be entertained in the evolution of complex cardiovascular pathologies, evaluating the possibility of combining mechanical and pharmaceutical interventions.

The thrombus is the inappropriate activation of hemostasis in vascular system. In this paper, biomechanical factors affecting the behaviors of artery with intraluminal thrombus were studies. Results indicated that heart rate and blood viscosity had strong impact on the compliance of the stenosis artery and flow pattern. The alteration in blood viscosity had stronger influence than cardiac cycle on the volume change of the fluid region surrounded by thrombus. von Mises stress measured at the thinnest region of the plaque had the largest time-averaged value. The alteration of these parameters could potentially lead to stress redistribution at intraluminal thrombus.

Understanding alveolar mechanics is important for preventing the possible lung injuries during mechanical ventilation. Alveolar clusters with smaller size are found having lower compliance in two-dimensional studies. But the influence of alveolar shape on compliance is unclear. In order to investigate how alveolar morphology affects their behavior, we tracked subpleural alveoli of isolated mouse lungs during quasi-static ventilation using two- and three-dimensional imaging techniques. Results showed that alveolar clusters with smaller size and more spherical shape had lower compliance. There was a better correlation of sphericity rather than circularity with alveolar compliance. The compliance of clusters with great shape change was larger than that with relatively slight shape change. These findings suggest the contribution of lung heterogeneous expansion to lung injuries associated with mechanical ventilation.

Cardiovascular diseases like atherosclerosis, peripheral arterial disease, coronary heart disease, etc. are dangerous and hence early detection of such diseases is important in the field of medical sciences. The existing methods used for diagnosing diseases are time-consuming and highly expensive. On the other hand, experimentation with Cardiovascular System (CVS) for the analysis and decision making for treatment is unsafe and hence it is important to develop an accurate CVS model. It is observed from the existing integer order cardiovascular models that the viscoelastic property of four chambers is not taken into consideration. To accommodate these properties, this paper proposes a fractional order model by introducing fractionality to the dynamical equation of CVS. Further, an optimization method is presented to obtain the fractionality of different chambers by minimizing the integral square error between clinical data of healthy human and model output using Cuckoo search, Firefly and Accelerated particle swarm algorithms. The results indicate that fractional models are better than integer order CVS models and specifically, the Firefly algorithm provides a better fractional model than the models obtained from other algorithms. Further, the best model obtained using firefly algorithm is considered for simulating the diseases (i) increased arterial stiffness and (ii) atherosclerosis.