On the role of aortic valve architecture for physiological haemodynamics and valve replacement. Part I: flow topology and vortex dynamics

Aortic valve replacement has become a growing concern due to the increasing prevalence of aortic stenosis in an ageing population. Existing replacement options have limitations, necessitating the development of improved prosthetic aortic valves. In this study, flow characteristics during systole in a stenotic aortic valve case are compared with those downstream of two newly designed surgical bioprosthetic aortic valves (BioAVs) using advanced simulations. Our findings reveal that the stenotic case maintains a high jet flow eccentricity due to a fixed orifice geometry, resulting in increased vortex stretching in the commissural low-flow regions. One BioAV design introduces non-axisymmetric leaflet motion, which reduces the maximum jet velocity and forms more vortical structures. The other BioAV design produces a fixed symmetric triangular jet shape due to non-moving leaflets and exhibits favourable vorticity attenuation and significantly reduced drag. Therefore, this study highlights the benefits of custom-designed aortic valves in the context of their replacement through comprehensive flow analyses. The results emphasise the importance of analysing jet flow, vortical structures, momentum balance and vorticity transport for evaluating aortic valve performance

On the role of aortic valve architecture for physiological haemodynamics and valve replacement. Part II: spectral analysis and anisotropy

Severe aortic valve stenosis can lead to heart failure and aortic valve replacement (AVR) is the primary treatment. However, increasing prevalence of aortic stenosis cases reveal limitations in current replacement options, necessitating improved prosthetic aortic valves. In this study, we investigate flow disturbances downstream of severe aortic stenosis and two bioprosthetic aortic valve (BioAV) designs using advanced energy-based analyses. Spectral analysis shows kinetic energy (KE) decay variations, with the stenotic case aligning with Kolmogorov's theory, while BioAVs differ. We explore the impact of flow helicity on KE transfer and decay in BioAVs. Probability distributions of modal KE anisotropy unveil flow asymmetries in the stenotic and one BioAV case. Moreover, an inverse correlation between modal KE anisotropy and normalised helicity intensity is noted, with the coefficient of determination varying among the valve configurations. Leaflet dynamics analysis highlights a stronger correlation between flow and biomechanical KE anisotropy in one BioAV due to higher leaflet displacement magnitude. These findings emphasise the role of valve architecture in aortic turbulence and its significance for BioAV performance and energy-based design optimisation

Modal analysis reveals imprint of snowflake shape on wake flow structures

This study investigates the complex interplay of wake flow structures, particle shape, and falling behavior of snowflakes through advanced flow analysis. We employ Proper Orthogonal Decomposition and Dynamic Mode Decomposition to analyze the wake flow patterns of three distinct snowflake geometries at Reynolds number of 1500: a dendrite crystal, a columnar crystal, and a rosette-like particle. Proper Orthogonal Decomposition reveals that spatial resolution significantly impacts the capture of flow structures, particularly for particles with with more intricate wake flow structure, corresponding to unstable falling motion. Dynamic Mode Decomposition demonstrates high sensitivity to temporal resolution, with data of the forces exerted on the snowflake incorporated in the matrix prior to the decomposition mitigating information loss at lower sampling rates. We establish a linear relationship between snowflake shape porosity and minimum and maximum Dynamic Mode Decomposition eigenfrequencies, absolute decay or growth rates, and wavenumbers of the most energetic mode, linking particle geometry to wake flow characteristics. Higher porosity corresponds to more stable, small-scale flow structures and steady falling motion, while lower porosity promotes larger, unstable structures and falling trajectories with random particle orientations. These findings reveal the interdependence of snowflake geometry, wake flow configuration, and falling behavior and highlight the importance of considering both spatial and temporal resolutions when dealing with modal analysis. This research contributes to improved predictions of snowflake falling behavior, with potential applications in meteorology and climate science

Drag coefficient prediction of complex-shaped snow particles falling in air beyond the Stokes regime

This study considers complex ice particles falling in the atmosphere: predicting the drag of such particles is important for developing of climate models parameterizations. A Delayed-Detached Eddy Simulation model is developed to predict the drag coefficient of snowflakes falling at Reynolds number between 50 and 2200. We first consider the case where the orientation of the particle is known a posteriori, and evaluate our results against laboratory experiments using 3D-printed particles of the same shape, falling at the same Reynolds number. Close agreement is found in cases where the particles fall stably, while a more complex behavior is observed in cases where the flow is unsteady. The second objective of this study is to evaluate methods for estimating the drag coefficient when the orientation of the particles is not known a posteriori. We find that a suitable average of two orientations corresponding to the minimum and maximum eigenvalues of the inertia tensor provides a good estimate of the particle drag coefficient. Meanwhile, existing correlations for the drag on non-spherical particles produce large errors ( 50%). A new formula to estimate snow particles settling velocity is also proposed. Our approach provides a framework to investigate the aerodynamics of complex snowflakes and is relevant to other problems that involve the sedimentation of irregular particles in viscous fluids

Multiscale Multimodal Characterization and Simulation of Structural Alterations in Failed Bioprosthetic Heart Valves.

Calcific degeneration is the most frequent type of heart valve failure, with rising incidence due to the ageing population. The gold standard treatment to date is valve replacement. Unfortunately, calcification oftentimes re-occurs in bioprosthetic substitutes, with the governing processes remaining poorly understood. Here, we present a multiscale, multimodal analysis of disturbances and extensive mineralisation of the collagen network in failed bioprosthetic bovine pericardium valve explants with full histoanatomical context. In addition to highly abundant mineralized collagen fibres and fibrils, calcified micron-sized particles previously discovered in native valves were also prevalent on the aortic as well as the ventricular surface of bioprosthetic valves. The two mineral types (fibres and particles) were detectable even in early-stage mineralisation, prior to any macroscopic calcification. Based on multiscale multimodal characterisation and high-fidelity simulations, we demonstrate that mineral occurrence coincides with regions exposed to high haemodynamic and biomechanical indicators. These insights obtained by multiscale analysis of failed bioprosthetic valves may serve as groundwork for the evidence-based development of more durable alternatives. STATEMENT OF SIGNIFICANCE: Bioprosthetic valve calcification is a well-known clinically significant phenomenon, leading to valve failure. The nanoanalytical characterisation of bioprosthetic valves gives insights into the highly abundant, extensive calcification and disorganization of the collagen network and the presence of calcium phosphate particles previously reported in native cardiovascular tissues. While the collagen matrix mineralisation can be primarily attributed to a combination of chemical and mechanical alterations, the calcified particles are likely of host cellular origin. This work presents a straightforward route to mineral identification and characterization at high resolution and sensitivity, and with full histoanatomical context, hence providing design cues for improved bioprosthetic valve alternatives

Multiscale multimodal characterization and simulation of structural alterations in failed bioprosthetic heart valves

Calcific degeneration is the most frequent type of heart valve failure, with rising incidence due to the ageing population. The gold standard treatment to date is valve replacement. Unfortunately, calcification oftentimes re-occurs in bioprosthetic substitutes, with the governing processes remaining poorly understood. Here, we present a multiscale, multimodal analysis of disturbances and extensive mineralisation of the collagen network in failed bioprosthetic bovine pericardium valve explants with full histoanatomical context. In addition to highly abundant mineralized collagen fibres and fibrils, calcified micron-sized particles previously discovered in native valves were also prevalent on the aortic as well as the ventricular surface of bioprosthetic valves. The two mineral types (fibres and particles) were detectable even in early-stage mineralisation, prior to any macroscopic calcification. Based on multiscale multimodal characterisation and high-fidelity simulations, we demonstrate that mineral occurrence coincides with regions exposed to high haemodynamic and biomechanical indicators. These insights obtained by multiscale analysis of failed bioprosthetic valves may serve as groundwork for the evidence-based development of more durable alternatives. STATEMENT OF SIGNIFICANCE: Bioprosthetic valve calcification is a well-known clinically significant phenomenon, leading to valve failure. The nanoanalytical characterisation of bioprosthetic valves gives insights into the highly abundant, extensive calcification and disorganization of the collagen network and the presence of calcium phosphate particles previously reported in native cardiovascular tissues. While the collagen matrix mineralisation can be primarily attributed to a combination of chemical and mechanical alterations, the calcified particles are likely of host cellular origin. This work presents a straightforward route to mineral identification and characterization at high resolution and sensitivity, and with full histoanatomical context, hence providing design cues for improved bioprosthetic valve alternatives

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat