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Obstructive Sleep Apnea Syndrome (OSAS) disrupts millions of lives with its burden of airway obstruction during sleep. Continuous Positive Airway Pressure (CPAP) therapy has been scrutinized for its biomechanical impact on the respiratory tract. This study leverages computational fluid dynamics to investigate CPAP's effects at 9 cm H 2 O (882.6 Pa) on the computed-tomography-based nasal-to-14-generation full respiratory tract model compared to ambient conditions, focusing on static pressure, airflow velocity, and shear stress. Our findings reveal that CPAP significantly increases static pressure, enhancing airway patency without adverse changes in airflow velocity or harmful shear stress on lung tissue, challenging prior concerns about its safety. Notably, the larynx experiences the highest shear stress due to its narrow anatomy, yet CPAP therapy overall supports airway walls against collapse. This investigation highlights CPAP's critical role in OSAS treatment, offering reassurance about its safety and efficacy. By clarifying CPAP therapy's physiological impacts, our study contributes vital insights for optimizing OSAS management strategies, affirming CPAP's benefit in maintaining open airways with minimal tissue strain., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Microplastics have become omnipresent in the environment, including the air we inhale, the water we consume, and the food we eat. Despite limited research, the accumulation of microplastics within the human respiratory system has garnered considerable interest because of its potential implications for health. This review offers a comprehensive examination of the impacts stemming from the accumulation of microplastics on human lung airways and explores the computational benefits and challenges associated with studying this phenomenon. The existence of microplastics in the respiratory system can lead to a range of adverse effects. Research has indicated that microplastics can induce inflammation, oxidative stress, and impaired lung function. Furthermore, the small size of microplastics allows them to penetrate deep into the lungs, reaching the alveoli, where gas exchange takes place. This raises concerns about long-term health consequences, such as the development of respiratory diseases and the potential for translocation to other organs. Computational approaches have been instrumental in understanding the impact of microplastic deposition on human lung airways. Computational models and simulations enable the investigation of particle dynamics, deposition patterns, and interaction mechanisms at various levels of complexity. However, studying microplastics in the lung airways using computational methods presents several challenges. The complex anatomy and physiological processes of the respiratory system require accurate representation in computational models. Obtaining relevant data for model validation and parameterization remains a significant hurdle. Additionally, the diverse nature of microplastics, including variations in size, shape, and chemical composition, poses challenges in capturing their full range of behaviours and potential toxicological effects., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Understanding the adsorption mechanism of corticosteroids in the lung surfactant requires the knowledge of corticosteroid molecular interactions with lung surfactant monolayer (LSM). We employed coarse-grained molecular dynamics simulation to explore the action of hydrocortisone on an LSM comprised of a phospholipid, cholesterol and surfactant protein. The structural and dynamical morphology of the lung surfactant monolayer at different surface tensions were investigated to assess the monolayer compressibility. The simulations were also conducted at the two extreme ends of breathing cycles: exhalation (0 mN m -1 surface tension) and inhalation (20 mN m -1 surface tension). The impact of surface tension and hydrocortisone concentration on the monolayer compressibility and stability are significant, resulting the monolayer expansion at higher surface tension. However, at low surface tension, the highly compressed monolayer induces monolayer instability in the presence of the drug due to the accumulation of surfactant protein and drug. The constant area per lipid simulation results demonstrate that the surface pressure-area isotherms show a decrease in area-per-lipid with increased drug concentration. The drug-induced expansion causes considerable instability in the monolayer after a specific drug concentration is attained at inhalation breathing condition, whereas, for exhalation breathing, the monolayer gets more compressed, causing the LSM to collapse. The monolayer collapse occurs for inhalation due to the higher drug concentration, whereas for exhalation due to the accumulation of surfactant proteins and drugs. The findings from this study will aid in enhancing the knowledge of molecular interactions of corticosteroid drugs with lung surfactants to treat respiratory diseases., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Background: Computational fluid dynamics (CFD) simulations, in-vitro setups, and experimental ex-vivo approaches have been applied to numerous alveolar geometries over the past years. They aimed to study and examine airflow patterns, particle transport, particle propagation depth, particle residence times, and particle-alveolar wall deposition fractions. These studies are imperative to both pharmaceutical and toxicological studies, especially nowadays with the escalation of the menacing COVID-19 virus. However, most of these studies ignored the surfactant layer that covers the alveoli and the effect of the air-surfactant surface tension on flow dynamics and air-alveolar surface mechanics., Methods: The present study employs a realistic human breathing profile of 4.75s for one complete breathing cycle to emphasize the importance of the surfactant layer by numerically comparing airflow phenomena between a surfactant-enriched and surfactant-deficient model. The acinar model exhibits physiologically accurate alveolar and duct dimensions extending from lung generations 18 to 23. Airflow patterns in the surfactant-enriched model support previous findings that the recirculation of the flow is affected by its propagation depth. Proximal lung generations experience dominant recirculating flow while farther generations in the distal alveolar region exhibit dominant radial flows. In the surfactant-enriched model, surface tension values alternate during inhalation and exhalation, with values increasing to 25 mN/m at the inhalation and decreasing to 1 mN/m at the end of the exhalation. In the surfactant-deficient model, only water coats the alveolar walls with a high surface tension value of 70 mN/m., Results: Results showed that surfactant deficiency in the alveoli adversely alters airflow behavior and generates unsteady chaotic breathing through the production of vorticities, accompanied by higher vorticity magnitudes (100% increase at the end of exhalation) and higher velocity magnitudes (8.69% increase during inhalation and 11.9% increase during exhalation). In addition, high air-water surface tension in the surfactant-deficient case was found to induce higher shear stress values (by around a factor of 10) on the alveolar walls than that of the surfactant-enriched case., Conclusion: Overall, it was concluded that the presence of the surfactant improves respiratory mechanics and allows for smooth breathing and normal respiration., Competing Interests: The authors declare no conflict of interest., (© 2022 The Authors. Published by Elsevier Ltd.)

Understanding nano-particle inhalation in human lung airways helps targeted drug delivery for treating lung diseases. A wide range of numerical models have been developed to analyse nano-particle transport and deposition (TD) in different parts of airways. However, a precise understanding of nano-particle TD in large-scale airways is still unavailable in the literature. This study developed an efficient one-path numerical model for simulating nano-particle TD in large-scale lung airway models. This first-ever one-path numerical approach simulates airflow and nano-particle TD in generations 0-11 of the human lung, accounting for 93% of the whole airway length. The one-path model enables the simulation of particle TD in many generations of airways with an affordable time. The particle TD of 5 nm, 10 nm and 20 nm particles is simulated at inhalation flow rates for two different physical activities: resting and moderate activity. It is found that particle deposition efficiency of 5 nm particles is 28.94% higher than 20 nm particles because of the higher dispersion capacity. It is further proved that the diffusion mechanism dominates the particle TD in generations 0-11. The deposition efficiency decreases with the increase of generation number irrespective of the flow rate and particle size. The effects of the particle size and flow rate on the escaping rate of each generation are opposite to the corresponding effects on the deposition rate. The quantified deposition and escaping rates at generations 0-11 provide valuable guidelines for drug delivery in human lungs., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

With the global burden of respiratory diseases, rapid identification of the best therapeutic measures to combat these diseases is essential. Animal models and 2D cell culture models do not replicate the findings observed in vivo. To gain deeper insight into lung pathology and physiology, 3D and advanced lung-on-a-chip models have been developed recently. Lung-on-a-chip models more accurately simulate the lung's microenvironment and functions in vivo, resulting in more-accurate assessments of drug safety and effectiveness. This review discusses the transition from 2D to 3D models and the recent advances in lung-on-a-chip platforms, their implementation and the numerous challenges faced. Finally, a general overview of this platform and its potential applications in respiratory disease research and drug discovery is highlighted., Competing Interests: Conflicts of Interest There are no conflicts of interest to declare., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Ligands like alkanethiol ( e.g. dodecanethiol, hexadecanethiol, etc. ) and polymers ( e.g. poly(vinyl pyrrolidone), polyethylene glycol-thiol) capped to the gold nanoparticles (AuNPs) are widely used in biomedical field as drug carriers and as promising materials for probing and manipulating cellular processes. Ligand functionalised AuNPs are known to interact with the pulmonary surfactant (PS) monolayer once reaching the alveolar region. Therefore, it is crucial to understand the interaction between AuNPs and PS monolayers. Using coarse-grained molecular dynamics simulations, the effect of ligand density, and ligand length have been studied for two classes of ligands on a PS model monolayer consisting of DPPC, POPG, cholesterol and SP-B (mini-peptide). The ligands considered in this study are alkanethiol and polyethylene glycol (PEG) thiol as examples of hydrophobic and hydrophilic ligands, respectively. It was observed that the interaction between AuNPs and PS changes the biophysical properties of PS monolayer in compressed and expanded states. The AuNPs with hydrophilic ligand, can penetrate through the monolayer more easily, while the AuNPs with hydrophobic ligand are embedded in the monolayer and participated in deforming the monolayer structure particularly the monolayer in the compressed state. The bare AuNPs hinder to lower the monolayer surface tension value at the interface, however introducing ligand to the bare AuNPs or increasing the ligand length and density have an impact of lowering of monolayer surface tension to a minor extent. The simulation results guide the design of ligand protected NPs as drug carriers and can identify the nanoparticles' potential side effects on lung surfactant., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

The lung surfactant monolayer (LSM) is the main barrier for particles entering the lung, including steroid drugs used to treat lung diseases. The present study combines Langmuir experiments and coarse-grained (CG) molecular dynamics simulations to investigate the concentration-dependent effect of steroid drug prednisolone on the structure and morphology of a model LSM. The surface pressure-area isotherms for the Langmuir monolayers reveal a concentration-dependent decrease in area per lipid (APL). Results from simulations at a fixed surface tension, representing inhalation and exhalation conditions, suggest that at high drug concentrations, prednisolone induces a collapse of the LSM, which is likely caused by the inability of the drug to diffuse into the bilayer. Overall, the monolayer is most susceptible to drug-induced collapse at surface tensions representing exhalation conditions. The presence of cholesterol also exacerbates the instability. The findings of this investigation might be helpful for better understanding the interaction between steroid drug prednisolone and lung surfactants in relation to off-target effects.

Genetic variants of severe acute respiratory syndrome coronavirus (SARS-CoV-2) have been globally surging and devastating many countries around the world. There are at least eleven reported variants dedicated with inevitably catastrophic consequences. In 2021, the most dominant Delta and Omicron variants were estimated to lead to more severity and deaths than other variants. Furthermore, these variants have some contagious characteristics involving high transmissibility, more severe illness, and an increased mortality rate. All outbreaks caused by the Delta variant have been rapidly skyrocketing in infection cases in communities despite tough restrictions in 2021. Apart from it, the United States, the United Kingdom and other high-rate vaccination rollout countries are still wrestling with this trend because the Delta variant can result in a significant number of breakthrough infections. However, the pandemic has changed since the latest SARS-CoV-2 variant in late 2021 in South Africa, Omicron. The preliminary data suggest that the Omicron variant possesses 100-fold greater than the Delta variant in transmissibility. Therefore, this paper aims to review these characteristics based on the available meta-data and information from the first emergence to recent days. Australia and the five most affected countries, including the United States, India, Brazil, France, as well as the United Kingdom, are selected in order to review the transmissibility, severity and fatality due to Delta and Omicron variants. Finally, the vaccination programs for each country are also reviewed as the main factor in prevention.

Mometasone is an investigational anti-inflammatory steroidal drug to treat inflammation via pulmonary administration. For steroid drugs to be effective they need to be adsorbed by lung surfactants, a thin monolayer at the air-water interface in alveoli that reduces surface tension. Information on the molecular-level interactions of the drug with lung surfactants is useful to understand the mechanism of adsorption. In this study, we use coarse-grained molecular dynamics simulation to understand the concentration-dependent effect of mometasone on a lung surfactant monolayer (LSM) composed of lipids and surfactant proteins, under two different breathing conditions (exhalation, at surface tension 0 mNm -1 and inhalation, surface tension 20-25 mNm -1 ). A series of fixed-APL and fixed-surface tension simulations were used to demonstrate that in the absence of drugs, the model LSM reproduces the surface tensions for the compressed and expanded states, as well as compressibility at different surface tensions. In-depth analysis of simulations of a LSM in the presence of five different drug concentrations shows that mometasone alters the structure and dynamics of the LSM in a concentration-dependent manner. Mometasone induces a collapse in the monolayer that is affected by the surfactant protein and surface tension. Overall, these findings suggest that the surfactant proteins, surface tension and drug concentration are all critical components affecting monolayer stability and drug adsorption. The outcomes of this study may be beneficial for a more in-depth understanding of how mometasone is adsorbed by lung surfactants., (Copyright © 2021 Elsevier Inc. All rights reserved.)

The lung surfactant monolayer (LSM) is a thin layer of lipids and proteins that forms the air/water interface of the alveoli. The primary function of the LSM is to reduce the surface tension at the air/water interface during breathing. The LSM also forms the main biological barrier for any inhaled particles, including drugs, to treat lung diseases. Elucidating the mechanism by which these drugs bind to and absorb into the LSM requires a molecular-level understanding of any drug-induced changes to the morphology, structure, and phase changes of the LSM.Molecular dynamics simulations have been used extensively to study the structure and dynamics of the LSM. The monolayer is usually simulated in at least two states: the compressed state, mimicking exhalation, and the expanded state, mimicking inhalation. In this chapter, we provide detailed instructions on how to set up, run, and analyze coarse-grained MD simulations to study the concentration-dependent effect of a sterol drug on the LSM, both in the expanded and compressed state., (© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

This study aims to understand the role of specific phenolic-lipid interactions in the membrane-altering properties of phenolic compounds. We combine tethered lipid bilayer (tBLM) electrical impedance spectroscopy (EIS) with all-atom molecular dynamics (MD) simulations to study the membrane interactions of six phenolic compounds: caffeic acid methyl ester, caffeic acid, 3,4 dihydroxybenzoic acid, chlorogenic acid, syringic acid and p -coumaric acid. tBLM/EIS experiments showed that caffeic acid methyl ester, caffeic acid and 3,4 dihydroxybenzoic acid significantly increase the permeability of phospholipid bilayers to Na + ions. In contrast, chlorogenic acid, syringic acid and p -coumaric acid showed no effect. Experiments with lipids lacking the phosphate group show a significant decrease in the membrane-altering effects indicating that specific phenolic-lipid interactions are critical in altering ion permeability. MD simulations confirm that compounds that alter ion permeability form stable interactions with the phosphate oxygen. In contrast, inactive phenolic compounds are superficially bound to the membrane surface and primarily interact with interfacial water. Our combined results show that compounds with similar structures can have very different effects on ion permeability in membranes. These effects are governed by specific interactions at the water-lipid interface and show no correlation with lipophilicity. Furthermore, none of the compounds alter the overall structure of the phospholipid bilayer as determined by area per lipid and order parameters. Based on data from this study and previous findings, we propose that phenolic compounds can alter membrane ion permeability by causing local changes in lipid packing that subsequently reduce the energy barrier for ion-induced pores.

The lung surfactant monolayer (LSM) forms the main biological barrier for any inhaled particles to enter our bloodstream, including gold nanoparticles (AuNPs) present as air pollutants and under investigation for use in biomedical applications. Understanding the interaction of AuNPs with lung surfactant can assist in understanding how AuNPs enter our lungs. In this study, we use coarse-grained molecular dynamics simulations to investigate the effect of four different shape D AuNPs (spherical, box, icosahedron and rod) on the structure and dynamics of a model LSM, with a particular focus on differences resulting from the shape of the AuNP. Monolayer-AuNP systems were simulated in two different states: the compressed state and the expanded state, representing inhalation and exhalation conditions, respectively. Our results indicate that the compressed state is more affected by the presence of the AuNPs than the expanded state. Our results show that in the compressed state, the AuNPs prevent the monolayer from reaching the close to zero surface tension required for normal exhalation. In the compressed state, all four nanoparticles (NPs) reduce the lipid order parameters and cause a thinning of the monolayer where the particles drag surfactant molecules into the water phase. Comparing the different properties shows no trend concerning which shape has the biggest effect on the monolayer, as shape-dependent effects vary among the different properties. Insights from this study might assist future work of how AuNP shapes affect the LSM during inhalation or exhalation conditions.

This paper is to design a new type of auxetic metamaterial-inspired structural architectures to innovate coronary stents under hemodynamics via a topological optimization method. The new architectures will low the occurrence of stent thrombosis (ST) and in-stent restenosis (ISR) associated with the mechanical factors and the adverse hemodynamics. A multiscale level-set approach with the numerical homogenization method and computational fluid dynamics is applied to implement auxetic microarchitectures and stenting structure. A homogenized effective modified fluid permeability (MFP) is proposed to efficiently connect design variables with motions of blood flow around the stent, and a Darcy-Stokes system is used to describe the coupling behavior of the stent structure and fluid. The optimization is formulated to include three objectives from different scales: MFP and auxetic property in the microscale and stenting stiffness in the macroscale. The design is numerically validated in the commercial software MATLAB and ANSYS, respectively. The simulation results show that the new design can not only supply desired auxetic behavior to benefit the deliverability and reduce incidence of the mechanical failure but also improve wall shear stress distribution to low the induced adverse hemodynamic changes. Hence, the proposed stenting architectures can help improve safety in stent implantation, to facilitate design of new generation of stents., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Xue, Saha, Beier, Jepson and Luo.)

The recent outbreak of the COVID-19 causes significant respirational health problems, including high mortality rates worldwide. The deadly corona virus-containing aerosol enters the atmospheric air through sneezing, exhalation, or talking, assembling with the particulate matter, and subsequently transferring to the respiratory system. This recent outbreak illustrates that the severe acute respiratory syndrome (SARS) coronavirus-2 is deadlier for aged people than for other age groups. It is evident that the airway diameter reduces with age, and an accurate understanding of SARS aerosol transport through different elderly people's airways could potentially help the overall respiratory health assessment, which is currently lacking in the literature. This first-ever study investigates SARS COVID-2 aerosol transport in age-specific airway systems. A highly asymmetric age-specific airway model and fluent solver (ANSYS 19.2) are used for the investigation. The computational fluid dynamics measurement predicts higher SARS COVID-2 aerosol concentration in the airway wall for older adults than for younger people. The numerical study reports that the smaller SARS coronavirus-2 aerosol deposition rate in the right lung is higher than that in the left lung, and the opposite scenario occurs for the larger SARS coronavirus-2 aerosol rate. The numerical results show a fluctuating trend of pressure at different generations of the age-specific model. The findings of this study would improve the knowledge of SARS coronavirus-2 aerosol transportation to the upper airways which would thus ameliorate the targeted aerosol drug delivery system., (© 2021 Author(s).)

A comprehensive understanding of airflow characteristics and particle transport in the human lung can be useful in modelling to inform clinical diagnosis, treatment, and management, including prescription medication and risk assessment for rehabilitation. One of the difficulties in clinical treatment of lung disorders lies in the patients' variable physical lung characteristics caused by age, amongst other factors, such as different lung sizes. A precise understanding of the comparison between different age groups with various flow rates is missing in the literature, and this study aims to analyse the airflow and aerosol transport within the age-specific lung. ANSYS Fluent solver and the large-eddy simulation (LES) model were employed for the numerical simulation. The numerical model was validated with the available literature and the computational results showed airway size-reduction significantly affected airflow and particle transport in the upper airways. This study reports higher deposition at the mouth-throat region for larger diameter particles. The overall deposition efficiency (DE) increased with airway size reduction and flow rate. Lung aging effected the pressure distribution and a higher pressure drop was reported for the aged lung as compared to the younger lung. These findings could inform medical management through individualised simulation of drug-aerosol delivery processes for the patient-specific lung.

The recent outbreak of the SARS CoV-2 virus has had a significant effect on human respiratory health around the world. The contagious disease infected a large proportion of the world population, resulting in long-term health issues and an excessive mortality rate. The SARS CoV-2 virus can spread as small aerosols and enters the respiratory systems through the oral (nose or mouth) airway. The SARS CoV-2 particle transport to the mouth-throat and upper airways is analyzed by the available literature. Due to the tiny size, the virus can travel to the terminal airways of the respiratory system and form a severe health hazard. There is a gap in the understanding of the SARS CoV-2 particle transport to the terminal airways. The present study investigated the SARS CoV-2 virus particle transport and deposition to the terminal airways in a complex 17-generation lung model. This first-ever study demonstrates how far SARS CoV-2 particles can travel in the respiratory system. ANSYS Fluent solver was used to simulate the virus particle transport during sleep and light and heavy activity conditions. Numerical results demonstrate that a higher percentage of the virus particles are trapped at the upper airways when sleeping and in a light activity condition. More virus particles have lung contact in the right lung than the left lung. A comprehensive lobe specific deposition and deposition concentration study was performed. The results of this study provide a precise knowledge of the SARs CoV-2 particle transport to the lower branches and could help the lung health risk assessment system., (© 2021 Author(s).)

Colloidal nanoparticles, such as gold nanoparticles (AuNPs), are promising materials for the delivery of hydrophilic drugs via the pulmonary route. The inhaled nanoparticle drug carriers primarily deposit in lung alveoli and interact with the alveolar surface known as lung surfactants. Therefore, it is vital to understand the interactions of nanocarriers with the surfactant layer. To understand the interactions at the molecular level, here we simulated model lung surfactant monolayers with phospholipid (PL)-wrapped AuNPs at the vacuum-water interface using coarse-grained molecular dynamics simulations. The PL-wrapped AuNPs quickly adsorbed into the surfactant layer, altered the structural properties of the monolayer, and at high concentrations initiated the compressed monolayer to collapse/buckle. Among the surfactant monolayer lipid components, cholesterol adsorbed to the AuNPs preferentially over PL species. The position of the adsorbed PL-AuNPs within the monolayer, and subsequent monolayer perturbation, vary depending on the monolayer phase, monolayer composition, and species of PL used as a ligand. Information provided by these molecular dynamic simulations helps to rationalize why some colloidal nanoparticles work better as nanocarriers than others and aid the design of new ones, to avoid biological toxicity and improve efficacy for pulmonary drug delivery.

Lung surfactant (LS) monolayers that continuously expand and compress during breathing cycles, act as the first line barrier for inhaled nanoparticles. It is known that nanoparticles which adsorb to the surface of the surfactant layer facilitate the rearrangement of lipids and peptides at various stages of the breathing cycle. However, the structural mechanisms for this ability of the lipid rearrangement are not yet fully understood. Coarse-grained molecular dynamics simulations are performed to investigate the role of surfactant protein B (SP-B) segments (SP-B 1-25 ) in modulating the biophysical properties of the surfactant monolayer in the presence of polydisperse gold nanoparticles (AuNPs) at different concentrations. Herein, we observe that the AuNPs significantly alter the inherent structural and dynamical properties of the monolayer and its components in three different breathing states. When adsorbed into the monolayer, the AuNPs inhibit the ability of the monolayer to recover its surface tension and other properties. The presence of SP-B 1-25 in the monolayer accelerates the diffusion of the monolayer phospholipids, contrarily to the role of AuNPs on phospholipid diffusion. Also, the AuNPs and the peptides in the monolayer significantly increase their agglomeration in the presence of one another. Overall, the simulations predict that the presence of polydisperse AuNPs hampers the stability and biophysical functions of the LS in contrast to the role of the peptide. This study provides a clear view of the hydrophobic peptide role in the LS monolayer at the interface along with the interactions and the translocation of AuNPs that could have a significant impact to assess the NPs inhalation.

The knowledge of respiratory particle transport in the extra-thoracic pathways is essential for the estimation of lung health-risk and optimization of targeted drug delivery. The published literature reports that a significant fraction of the inhaled aerosol particles are deposited in the upper airways, and available inhalers can deliver only a small amount of drug particles to the deeper airways. To improve the targeted drug delivery efficiency to the lungs, it is important to reduce the drug particle deposition in the upper airways. This study aims to minimize the unwanted aerosol particle deposition in the upper airways by employing a gas mixture model for the aerosol particle transport within the upper airways. A helium-oxygen (heliox) mixture (80% helium and 20% oxygen) model is developed for the airflow and particle transport as the heliox mixture is less dense than air. The mouth-throat and upper airway geometry are extracted from CT-scan images. Finite volume based ANSYS Fluent (19.2) solver is used to simulate the airflow and particle transport in the upper airways. Tecplot software and MATLAB code are employed for the airflow and particle post-processing. The simulation results show that turbulence intensity for heliox breathing is lower than in the case of air-breathing. The less turbulent heliox breathing eventually reduces the deposition efficiency (DE) at the upper airways than the air-breathing. The present study, along with additional patient-specific investigation, could improve the understanding of particle transport in upper airways, which may also increase the efficiency of aerosol drug delivery.

Airflow and particle transport in the human lung system is influenced by biological and other factors such as breathing pattern, particle properties, and deposition mechanisms. Most of the studies to date have analyzed airflow characterization and aerosol transport in idealized and realistic models. Precise airflow characterization for airway stenosis in a digital reference model is lacking in the literature. This study presents a numerical simulation of airflow and particle transport through a stenosis section of the airway. A realistic CT-scan-based mouth-throat and upper airway model was used for the numerical calculations. Three different models of a healthy lung and of airway stenosis of the left and right lung were used for the calculations. The ANSYS FLUENT solver, based on the finite volume discretization technique, was used as a numerical tool. Proper grid refinement and validation were performed. The numerical results show a complex-velocity flow field for airway stenosis, where airflow velocity magnitude at the stenosis section was found to be higher than that in healthy airways. Pressure drops at the mouth-throat and in the upper airways show a nonlinear trend. Comprehensive pressure analysis of stenosis airways would increase our knowledge of the safe mechanical ventilation of the lung. The turbulence intensities at the stenosis sections of the right and left lung were found to be different. Deposition efficiency (DE) increased with flow rate and particle size. The findings of the present study increase our understanding of airflow patterns in airway stenosis under various disease conditions. More comprehensive stenosis analysis is required to further improve knowledge of the field.

The airways of the human respiratory system are covered by a protective layer, which is known as airway surface liquid (ASL). This layer consists of two relatively distinct sub-layers; a mucus layer (ML), and a periciliary liquid layer (PCL). In addition, the airways are lined with a dense mat of hair-like structures, called cilia, which beat back and forth in a co-ordinated manner and mainly propel the mucus layer. Such interaction between the cilia and mucus is called 'muco-ciliary clearance' (MCC) which is essential to clear the respiratory airways from the inhaled toxic particles deposited on the mucus. The complex nature of lung clearance mechanisms limit the ability to conduct experiments to investigate micro-scale physiological phenomena. As such, modelling techniques are commonly implemented to investigate the effects of biological parameters on the lung muco-ciliary clearance. In the present work, modelling techniques of cilia-ASL interactions - including continuum cilia modelling and discrete cilia modelling - are reviewed and the numerical procedures and level of complexity related to each technique are explained. This is followed by a detailed analysis of the airway surface liquid modelling approaches. In addition, findings of numerical investigations related to the effects of various parameters such as ciliary beat frequency (CBF), mucus rheology, metachronal waves of cilia, surface tension at the PCL-mucus interface, ciliary length, ciliary density, and airway surface liquid depth on the bronchial and tracheal ASL transport are reviewed. This review also explains how these biological parameters can alter the internal power required to perform ciliary beating. Lastly, the main limitations of current numerical works are discussed and significant research directions are brought forward that may be considered in future models to better understand this complex human biological system and its vital clearance mechanism., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

The understanding of complex inhalation and transport processes of pollutant particles through the human respiratory system is important for investigations into dosimetry and respiratory health effects in various settings, such as environmental or occupational health. The studies over the last few decades for micro- and nanoparticle transport and deposition have advanced the understanding of drug-aerosol impacts in the mouth-throat and the upper airways. However, most of the Lagrangian and Eulerian studies have utilized the non-realistic symmetric anatomical model for airflow and particle deposition predictions. Recent improvements to visualization techniques using high-resolution computed tomography (CT) data and the resultant development of three dimensional (3-D) anatomical models support the realistic representation of lung geometry. Yet, the selection of different modelling approaches to analyze the transitional flow behavior and the use of different inlet and outlet conditions provide a dissimilar prediction of particle deposition in the human lung. Moreover, incorporation of relevant physical and appropriate boundary conditions are important factors to consider for the more accurate prediction of transitional flow and particle transport in human lung. This review critically appraises currently available literature on airflow and particle transport mechanism in the lungs, as well as numerical simulations with the aim to explore processes involved. Numerical studies found that both the Euler-Lagrange (E-L) and Euler-Euler methods do not influence nanoparticle (particle diameter ≤50 nm) deposition patterns at a flow rate ≤25 L/min. Furthermore, numerical studies demonstrated that turbulence dispersion does not significantly affect nanoparticle deposition patterns. This critical review aims to develop the field and increase the state-of-the-art in human lung modelling.

Background: Pulmonary lobectomy has been a well-established curative treatment method for localized lung cancer. After left upper pulmonary lobectomy, the upward displacement of remaining lower lobe causes the distortion or kink of bronchus, which is associated with intractable cough and breathless. However, the quantitative study on structural and functional alterations of the tracheobronchial tree after lobectomy has not been reported. We sought to investigate these alterations using CT imaging analysis and computational fluid dynamics (CFD) method., Methods: Both preoperative and postoperative CT images of 18 patients who underwent left upper pulmonary lobectomy are collected. After the tracheobronchial tree models are extracted, the angles between trachea and bronchi, the surface area and volume of the tree, and the cross-sectional area of left lower lobar bronchus are investigated. CFD method is further used to describe the airflow characteristics by the wall pressure, airflow velocity, lobar flow rate, etc. RESULTS: It is found that the angle between the trachea and the right main bronchus increases after operation, but the angle with the left main bronchus decreases. No significant alteration is observed for the surface area or volume of the tree between pre-operation and post-operation. After left upper pulmonary lobectomy, the cross-sectional area of left lower lobar bronchus is reduced for most of the patients (15/18) by 15-75%, especially for 4 patients by more than 50%. The wall pressure, airflow velocity and pressure drop significantly increase after the operation. The flow rate to the right lung increases significantly by 2-30% (but there is no significant difference between each lobe), and the flow rate to the left lung drops accordingly. Many vortices are found in various places with severe distortions., Conclusions: The favorable and unfavorable adaptive alterations of tracheobronchial tree will occur after left upper pulmonary lobectomy, and these alterations can be clarified through CT imaging and CFD analysis. The severe distortions at left lower lobar bronchus might exacerbate postoperative shortness of breath.

In clinical assessments, the correlation between atmospheric air pollution and respiratory damage is highly complicated. Epidemiological studies show that atmospheric air pollution is largely responsible for the global proliferation of pulmonary disease. This is particularly significant, since most Computational Fluid Dynamics (CFD) studies to date have used monodisperse particles, which may not accurately reflect realistic inhalation patterns, since atmospheric aerosols are mostly polydisperse. The aim of this study is to investigate the anatomy and turbulent effects on polydisperse particle transport and deposition (TD) in the upper airways. The Euler-Lagrange approach is used for polydisperse particle TD prediction in both laminar and turbulent conditions. Various anatomical models are adopted to investigate the polydisperse particle TD under different flow conditions. Rossin-Rammler diameter distribution is used for the distribution of the initial particle diameter. The numerical results illustrate that airflow rate distribution at the right lung of a realistic model is higher than a non-realistic model. The CFD study also shows that turbulence effects on deposition are higher for larger diameter particles than with particles of smaller diameter. A significant amount of polydisperse particles are also shown to be deposited at the tracheal wall for CT-based model, whereas particles are mostly deposited at the carinal angle for the non-realistic model. A comprehensive, polydisperse particle TD analysis would enhance understanding of the realistic deposition pattern and decrease unwanted therapeutic aerosol deposition at the extrathoracic airways.

Inhaled nanoparticles (NPs) are experienced by the first biological barrier inside the alveolus known as lung surfactant (LS), a surface tension reducing agent, consisting of phospholipids and proteins in the form of the monolayer at the air-water interface. The monolayer surface tension is continuously regulated by the alveolus compression and expansion and protects the alveoli from collapsing. Inhaled NPs can reach deep into the lungs and interfere with the biophysical properties of the lung components. The interaction mechanisms of bare gold nanoparticles (AuNPs) with the LS monolayer and the consequences of the interactions on lung function are not well understood. Coarse-grained molecular dynamics simulations were carried out to elucidate the interactions of AuNPs with simplified LS monolayers at the nanoscale. It was observed that the interactions of AuNPs and LS components deform the monolayer structure, change the biophysical properties of LS and create pores in the monolayer, which all interfere with the normal lungs function. The results also indicate that AuNP concentrations >0.1 mol% (of AuNPs/lipids) hinder the lowering of the LS surface tension, a prerequisite of the normal breathing process. Overall, these findings could help to identify the possible consequences of airborne NPs inhalation and their contribution to the potential development of various lung diseases., (Copyright © 2019 Elsevier B.V. All rights reserved.)

The atmospheric particles from different sources, and the therapeutic particles from various drug delivery devices, exhibit a complex size distribution, and the particles are mostly polydisperse. The limited available in vitro, and the wide range of in silico models have improved understanding of the relationship between monodisperse particle deposition and therapeutic aerosol transport. However, comprehensive polydisperse transport and deposition (TD) data for the terminal airways is still unavailable. Therefore, to benefit future drug therapeutics, the present numerical model illustrates detailed polydisperse particle TD in the terminal bronchioles for the first time. Euler-Lagrange approach and Rosin-Rammler diameter distribution is used for polydisperse particles. The numerical results show higher deposition efficiency (DE) in the right lung. Specifically, the larger the particle diameter (d p  > 5 μm), the higher the DE at the bifurcation area of the upper airways is, whereas for the smaller particle (d p  < 5 μm), the DE is higher at the bifurcation wall. The overall deposition pattern shows a different deposition hot spot for different diameter particle. These comprehensive lobe-specific polydisperse particle deposition studies will increase understanding of actual inhalation for particle TD, which could potentially increase the efficiency of pharmaceutical aerosol delivery at the targeted position of the terminal airways.

To understand how to assess optimally the risks of inhaled particles on respiratory health, it is necessary to comprehend the uptake of ultrafine particulate matter by inhalation during the complex transport process through a non-dichotomously bifurcating network of conduit airways. It is evident that the highly toxic ultrafine particles damage the respiratory epithelium in the terminal bronchioles. The wide range of in silico available and the limited realistic model for the extrathoracic region of the lung have improved understanding of the ultrafine particle transport and deposition (TD) in the upper airways. However, comprehensive ultrafine particle TD data for the real and entire lung model are still unavailable in the literature. Therefore, this study is aimed to provide an understanding of the ultrafine particle TD in the terminal bronchioles for the development of future therapeutics. The Euler-Lagrange (E-L) approach and ANSYS fluent (17.2) solver were used to investigate ultrafine particle TD. The physical conditions of sleeping, resting, and light activity were considered in this modelling study. A comprehensive pressure-drop along five selected path lines in different lobes was calculated. The non-linear behaviour of pressure-drops is observed, which could aid the health risk assessment system for patients with respiratory diseases. Numerical results also showed that ultrafine particle-deposition efficiency (DE) in different lobes is different for various physical activities. Moreover, the numerical results showed hot spots in various locations among the different lobes for different flow rates, which could be helpful for targeted therapeutical aerosol transport to terminal bronchioles and the alveolar region., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Background: Blood continuously flows through the blood vessels in the human body. When blood flows through the smallest blood vessels, red blood cells (RBCs) in the blood exhibit various types of motion and deformed shapes. Computational modelling techniques can be used to successfully predict the behaviour of the RBCs in capillaries. In this study, we report the application of a meshfree particle approach to model and predict the motion and deformation of three-dimensional RBCs in capillaries., Methods: An elastic spring network based on the discrete element method (DEM) is employed to model the three-dimensional RBC membrane. The haemoglobin in the RBC and the plasma in the blood are modelled as smoothed particle hydrodynamics (SPH) particles. For validation purposes, the behaviour of a single RBC in a simple shear flow is examined and compared against experimental results. Then simulations are carried out to predict the behaviour of RBCs in a capillary; (i) the motion of five identical RBCs in a uniform capillary, (ii) the motion of five identical RBCs with different bending stiffness (K b ) values in a stenosed capillary, (iii) the motion of three RBCs in a narrow capillary. Finally five identical RBCs are employed to determine the critical diameter of a stenosed capillary., Results: Validation results showed a good agreement with less than 10% difference. From the above simulations, the following results are obtained; (i) RBCs exhibit different deformation behaviours due to the hydrodynamic interaction between them. (ii) Asymmetrical deformation behaviours of the RBCs are clearly observed when the bending stiffness (K b ) of the RBCs is changed. (iii) The model predicts the ability of the RBCs to squeeze through smaller blood vessels. Finally, from the simulations, the critical diameter of the stenosed section to stop the motion of blood flow is predicted., Conclusions: A three-dimensional spring network model based on DEM in combination with the SPH method is successfully used to model the motion and deformation of RBCs in capillaries. Simulation results reveal that the condition of blood flow stopping depends on the pressure gradient of the capillary and the severity of stenosis of the capillary. In addition, this model is capable of predicting the critical diameter which prevents motion of RBCs for different blood pressures.