Bicuspid aortic valve (BAV) is the most common congenital cardiac disease and is a foremost risk factor for aortopathies. Despite the genetic basis of BAV and of the associated aortopathies, BAV-related alterations in aortic fluid-dynamics, and particularly in wall shear stresses (WSSs), likely play a role in the progression of aortopathy, and may contribute to its pathogenesis. To test whether WSS may trigger aortopathy, in this study we used 4D Flow sequences of phase-contrast cardiac magnetic resonance imaging (CMR) to quantitatively compare the in vivo fluid dynamics in the thoracic aorta of two groups of subjects: i) five prospectively enrolled young patients with normo-functional BAV and with no aortic dilation and ii) ten age-matched healthy volunteers. Through the semi-automated processing of 4D Flow data, the aortic bulk flow at peak systole was quantified, and WSSs acting on the endothelium of the ascending aorta were characterized throughout the systolic phase in terms of magnitude and time-dependency through a method recently developed by our group. Variables computed for each BAV patient were compared vs. the corresponding distribution of values obtained for healthy controls. In BAV patients, ascending aorta diameter was measured on cine-CMR images at baseline and at three-year follow-up. As compared to controls, normo-functional BAV patients were characterized by minor bulk flow disturbances at peak systole. However, they were characterized by evident alterations of WSS distribution and peak values in the ascending aorta. In particular, in four BAV patients, who were characterized by right-left leaflet fusion, WSS peak values exceeded by 27-46% the 90th percentile of the distribution obtained for healthy volunteers. Only in the BAV patient with right-non-coronary leaflet fusion the same threshold was exceeded by 132%. Also, evident alterations in the time-dependency of WSS magnitude and direction were observed. Despite these fluid-dynamic alterations, no clinically relevant anatomical remodeling was observed in the BAV patients at three-year follow-up. In light of previous evidence from the literature, our results suggest that WSS alterations may precede the onset of aortopathy and may contribute to its triggering, but WSS-driven anatomical remodeling, if any, is a very slow process.
The best swimmers have a streamlined shape that ensures an attached flow pattern and a laminar boundary layer at rather large values of the Reynolds number. Simple expressions may be obtained for the volumetric drag coefficient of an ideal body of revolution under laminar unseparated flow conditions together with estimations of a critical value of the Reynolds number. A measure, the capacity-efficiency factor, calculated for different organisms and underwater vehicles, shows that information about animal shapes and locomotion is of utmost biological interest and could be useful to improve robot fish and underwater vehicles as well.
Background: The epidemic outbreak cased by coronavirus 2019-nCoV is of great interest to researches because of the high rate of spread of the infection and the significant number of fatalities. A detailed scientific analysis of the phenomenon is yet to come, but the public is already interested in the questions of the duration of the epidemic, the expected number of patients and deaths. For long time predictions, the complicated mathematical models are necessary which need many efforts for unknown parameters identification and calculations. In this article, some preliminary estimates will be presented. Objective: Since the reliable long time data are available only for mainland China, we will try to predict the epidemic characteristics only in this area. We will estimate some of the epidemic characteristics and present the most reliable dependences for victim numbers, infected and removed persons versus time. Methods: In this study we use the known SIR model for the dynamics of an epidemic, the known exact solution of the linear equations and statistical approach developed before for investigation of the children disease, which occurred in Chernivtsi (Ukraine) in 1988-1989. Results: The optimal values of the SIR model parameters were identified with the use of statistical approach. The numbers of infected, susceptible and removed persons versus time were predicted. Conclusions: Simple mathematical model was used to predict the characteristics of the epidemic caused by coronavirus 2019-nCoV in mainland China. The further research should focus on updating the predictions with the use of fresh data and using more complicated mathematical models.
The fourth year of the COVID-19 pandemic without decreasing trends in the global numbers of new daily cases, high numbers of circulating SARS-CoV-2 variants and re-infections together with pessimistic predictions for the Omicron wave duration force studies about the endemic stage of the disease. The global trends were illustrated with the use the accumulated numbers of laboratory-confirmed COVID-19 cases and deaths, the percentages of fully vaccinated people and boosters (additional vaccinations), and the results of calculation of the effective reproduction number provided by Johns Hopkins University. A new modified SIR model with re-infections was proposed and analyzed. The estimated parameters of equilibrium show that the global numbers of new daily cases will range between 300 thousand and one million, daily deaths—between one and 3.3 thousand.