Analysis of the airflow features and ventilation efficiency of an Ultra-Clean-Air operating theatre by qDNS simulations and experimental validation.

Ultra-Clean-Air (UCA) operating theatres aim to minimise surgical instrument contamination and wound infection through high flow rates of ultra-clean air, reducing the presence of Microbe Carrying Particles (MCPs). This study investigates the airflow patterns and ventilation characteristics of a UCA operating theatre (OT) under standard ventilation system operating conditions, considering both empty and partially occupied scenarios. Utilising a precise computational model, quasi-Direct Numerical Simulations (qDNS) were conducted to delineate flow velocity profiles, energy spectra, distributions of turbulent kinetic energy, energy dissipation rate, local Kolmogorov scales, and pressure-based coherent structures. These results were also complemented by a tracer gas decay analysis following ASHRAE standard guidelines. Simulations showed that contrary to the intended laminar regime, the OT's geometry inherently fosters a predominantly turbulent airflow, sustained until evacuation through the exhaust vents, and facilitating recirculation zones irrespective of occupancy level. Notably, the occupied scenario demonstrated superior ventilation efficiency, a phenomenon attributed to enhanced kinetic energy induced by the additional obstructions. The findings underscore the critical role of UCA-OT design in mitigating MCP dissemination, highlighting the potential to augment the design to optimise airflow across a broader theatre spectrum, thereby diminishing recirculation zones and consequently reducing the propensity for Surgical Site Infections (SSIs). The study advocates for design refinements to harness the turbulent dynamics beneficially, steering towards a safer surgical environment.

Platelet accumulation in an endothelium-coated elastic vein valve model of deep vein thrombosis is mediated by GPIbα-VWF interaction.

Deep vein thrombosis is a life-threatening disease that takes millions of people's lives worldwide. Given both technical and ethical issues of using animals in research, it is necessary to develop an appropriate in vitro model that would recapitulate the conditions of venous thrombus development. We present here a novel microfluidics vein-on-a-chip with moving valve leaflets to mimic the hydrodynamics in a vein, and Human Umbilical Vein Endothelial Cell (HUVEC) monolayer. A pulsatile flow pattern, typical for veins, was used in the experiments. Unstimulated human platelets, reconstituted with the whole blood, accumulated at the luminal side of the leaflet tips proportionally to the leaflet flexibility. Platelet activation by thrombin induced robust platelet accrual at the leaflet tips. Inhibition of glycoprotein (GP) IIb-IIIa did not decrease but, paradoxically, slightly increased platelet accumulation. In contrast, blockade of the interaction between platelet GPIbα and A1 domain of von Willebrand factor completely abolished platelet deposition. Stimulation of the endothelium with histamine, a known secretagogue of Weibel-Palade bodies, promoted platelet accrual at the basal side of the leaflets, where human thrombi are usually observed. Thus, platelet deposition depends on the leaflet flexibility, and accumulation of activated platelets at the valve leaflets is mediated by GPIbα-VWF interaction.

Correction: Schütt et al. Simulating the Hydrodynamic Conditions of the Human Ascending Colon: A Digital Twin of the Dynamic Colon Model. Pharmaceutics 2022, 14, 184.

In the original publication [...].

Simulating the Hydrodynamic Conditions of the Human Ascending Colon: A Digital Twin of the Dynamic Colon Model.

The performance of solid oral dosage forms targeting the colon is typically evaluated using standardised pharmacopeial dissolution apparatuses. However, these fail to replicate colonic hydrodynamics. This study develops a digital twin of the Dynamic Colon Model; a physiologically representative in vitro model of the human proximal colon. Magnetic resonance imaging of the Dynamic Colon Model verified that the digital twin robustly replicated flow patterns under different physiological conditions (media viscosity, volume, and peristaltic wave speed). During local contractile activity, antegrade flows of 0.06-0.78 cm s-1 and backflows of -2.16--0.21 cm s-1 were measured. Mean wall shear rates were strongly time and viscosity dependent although peaks were measured between 3.05-10.12 s-1 and 5.11-20.34 s-1 in the Dynamic Colon Model and its digital twin respectively, comparable to previous estimates of the USPII with paddle speeds of 25 and 50 rpm. It is recommended that viscosity and shear rates are considered when designing future dissolution test methodologies for colon-targeted formulations. In the USPII, paddle speeds >50 rpm may not recreate physiologically relevant shear rates. These findings demonstrate how the combination of biorelevant in vitro and in silico models can provide new insights for dissolution testing beyond established pharmacopeial methods.

Modelling and Simulation of the Drug Release from a Solid Dosage Form in the Human Ascending Colon: The Influence of Different Motility Patterns and Fluid Viscosities.

For colonic drug delivery, the ascending part of the colon is the most favourable site as it offers the most suitable environmental conditions for drug dissolution. Commonly, the performance of a drug formulation is assessed using standardised dissolution apparatus, which does not replicate the hydrodynamics and shear stress evoked by wall motion in the colon. In this work, computer simulations are used to analyse and understand the influence of different biorelevant motility patterns on the disintegration/drug release of a solid dosage form (tablet) under different fluid conditions (viscosities) to mimic the ascending colonic environment. Furthermore, the ability of the motility pattern to distribute the drug in the ascending colon luminal environment is analysed to provide data for a spatiotemporal concentration profile. The motility patterns used are derived from in vivo data representing different motility patterns in the human ascending colon. The applied motility patterns show considerable differences in the drug release rate from the tablet, as well as in the ability to distribute the drug along the colon. The drug dissolution/disintegration process from a solid dosage form is primarily influenced by the hydrodynamic and shear stress it experiences, i.e., a combination of motility pattern and fluid viscosity. Reduced fluid motion leads to a more pronounced influence of diffusion in the tablet dissolution process. The motility pattern that provoked frequent single shear stress peaks seemed to be more effective in achieving a higher drug release rate. The ability to simulate drug release profiles under biorelevant colonic environmental conditions provides valuable feedback to better understand the drug formulation and how this can be optimised to ensure that the drug is present in the desired concentration within the ascending colon.

Combined Peridynamics and Discrete Multiphysics to Study the Effects of Air Voids and Freeze-Thaw on the Mechanical Properties of Asphalt.

This paper demonstrates the use of peridynamics and discrete multiphysics to assess micro crack formation and propagation in asphalt at low temperatures and under freezing conditions. Three scenarios are investigated: (a) asphalt without air voids under compressive load, (b) asphalt with air voids and (c) voids filled with freezing water. The first two are computed with Peridynamics, the third with peridynamics combined with discrete multiphysics. The results show that the presence of voids changes the way cracks propagate in the material. In asphalt without voids, cracks tend to propagate at the interface between the mastic and the aggregate. In the presence of voids, they 'jump' from one void to the closest void. Water expansion is modelled by coupling Peridynamics with repulsive forces in the context of Discrete Multiphysics. Freezing water expands against the voids' internal surface, building tension in the material. A network of cracks forms in the asphalt, weakening its mechanical properties. The proposed methodology provides a computational tool for generating samples of 'digital asphalt' that can be tested to assess the asphalt properties under different operating conditions.

The role of valve stiffness in the insurgence of deep vein thrombosis.

Deep vein thrombosis is a life-threatening development of blood clots in deep veins. Immobility and blood flow stagnancy are typical risk factors indicating that fluid dynamics play an important role in the initiation of venous clots. However, the roles of physical parameters of the valves and flow conditions in deep vein thrombosis initiation have not been fully understood. Here, we describe a microfluidics in vitro method that enabled us to explore the role of valve elasticity using in situ fabrication and characterisation. In our experimental model the stiffness of each valve leaflet can be controlled independently, and various flow conditions were tested. The resulting complex flow patterns were detected using ghost particle velocimetry and linked to localised thrombus formation using whole blood and an aqueous suspension of polystyrene particles. In particular, valves with leaflets of similar stiffness had clot formation on the valve tips whereas valves with leaflets of different stiffness had clot formation in the valve pocket.

A smoothed particle hydrodynamics study of the collapse for a cylindrical cavity.

In this study, we propose a mesh-free (particle-based) Smoothed Particle Hydrodynamics model for simulating a Rayleigh collapse. Both empty and gas cavities are investigates and the role of heat diffusion is also accounted for. The system behaves very differently according to the ratio between the characteristic time of collapse and the characteristic time of thermal diffusion. This study identifies five different possible behaviours that range from isothermal to adiabatic.

Deep multiphysics: Coupling discrete multiphysics with machine learning to attain self-learning in-silico models replicating human physiology.

OBJECTIVES: The objective of this study is to devise a modelling strategy for attaining in-silico models replicating human physiology and, in particular, the activity of the autonomic nervous system. METHOD: Discrete Multiphysics (a multiphysics modelling technique) and Reinforcement Learning (a Machine Learning algorithm) are combined to achieve an in-silico model with the ability of self-learning and replicating feedback loops occurring in human physiology. Computational particles, used in Discrete Multiphysics to model biological systems, are associated to (computational) neurons: Reinforcement Learning trains these neurons to behave like they would in real biological systems. RESULTS: As benchmark/validation, we use the case of peristalsis in the oesophagus. Results show that the in-silico model effectively learns by itself how to propel the bolus in the oesophagus. CONCLUSIONS: The combination of first principles modelling (e.g. multiphysics) and machine learning (e.g. Reinforcement Learning) represents a new powerful tool for in-silico modelling of human physiology. Biological feedback loops occurring, for instance, in peristaltic or metachronal motion, which until now could not be accounted for in in-silico models, can be tackled by the proposed technique.

Temperature dependence of the Young's modulus of polymers calculated using a hybrid molecular mechanics-molecular dynamics method.

A hybrid molecular mechanics-molecular dynamics (MM-MD) method is proposed to calculate the Young's modulus of polymers at various temperature. It overcomes the limitation that MD is restricted to extremely high strain rates. A case study based on poly-methyl-methacrylate demonstrates that, contrary to previous MD studies, the method is able to accurately reproduce the effect of temperature on the Young's modulus in close agreement with experimental data. The method can also predict a more clear transition between the glassy and rubbery states than previous MD studies.

Discrete multi-physics simulations of diffusive and convective mass transfer in boundary layers containing motile cilia in lungs.

In this paper, the mass transfer coefficient (permeability) of boundary layers containing motile cilia is investigated by means of discrete multi-physics. The idea is to understand the main mechanisms of mass transport occurring in a ciliated-layer; one specific application being inhaled drugs in the respiratory epithelium. The effect of drug diffusivity, cilia beat frequency and cilia flexibility is studied. Our results show the existence of three mass transfer regimes. A low frequency regime, which we called shielding regime, where the presence of the cilia hinders mass transport; an intermediate frequency regime, which we have called diffusive regime, where diffusion is the controlling mechanism; and a high frequency regime, which we have called convective regime, where the degree of bending of the cilia seems to be the most important factor controlling mass transfer in the ciliated-layer. Since the flexibility of the cilia and the frequency of the beat changes with age and health conditions, the knowledge of these three regimes allows prediction of how mass transfer varies with these factors.

Discrete multi-physics: A mesh-free model of blood flow in flexible biological valve including solid aggregate formation.

We propose a mesh-free and discrete (particle-based) multi-physics approach for modelling the hydrodynamics in flexible biological valves. In the first part of this study, the method is successfully validated against both traditional modelling techniques and experimental data. In the second part, it is further developed to account for the formation of solid aggregates in the flow and at the membrane surface. Simulations of various types of aggregates highlight the main benefits of discrete multi-physics and indicate the potential of this approach for coupling the hydrodynamics with phenomena such as clotting and calcification in biological valves.

The discrete multi-hybrid system for the simulation of solid-liquid flows.

This study proposes a model based on the combination of Smoothed Particle Hydrodynamics, Coarse Grained Molecular Dynamics and the Discrete Element Method for the simulation of dispersed solid-liquid flows. The model can deal with a large variety of particle types (non-spherical, elastic, breakable, melting, solidifying, swelling), flow conditions (confined, free-surface, microscopic), and scales (from microns to meters). Various examples, ranging from biological fluids to lava flows, are simulated and discussed. In all cases, the model captures the most important features of the flow.

Extension of the method of moments for population balances involving fractional moments and application to a typical agglomeration problem.

The method of moment (MOM) is a powerful tool for solving population balance. Nevertheless it cannot be used in every circumstance. Sometimes, in fact, it is not possible to write the governing equations in closed form. Higher moments, for instance, could appear in the evolution of the lower ones. This obstacle has often been resolved by prescribing some functional form for the particle size distribution. Another example is the occurrence of fractional moment, usually connected with the presence of fractal aggregates. For this case we propose a procedure that does not need any assumption on the form of the distribution but it is based on the "moments generating function" (that is the Laplace transform of the distribution). An important result of probability theory is that the kth derivative of the moments generating function represents the kth moment of the original distribution. This result concerns integer moments but, taking in account the Weyl fractional derivative, could be extended to fractional orders. Approximating fractional derivative makes it possible to express the fractional moments in terms of the integer ones and so to use regularly the method of moments.