Toxic effect and mRNA mechanism of moon dust simulant induced pulmonary inflammation in rats.

Moon dust presents a significant hazard to manned moon exploration missions, yet our understanding of its toxicity remains limited. The objective of this study is to investigate the pattern and mechanism of lung inflammation induced by subacute exposure to moon dust simulants (MDS) in rats. SD rats were exposed to MDS and silica dioxide through oral and nasal inhalation for 6 hours per day continuously for 15 days. Pathological analysis indicated that the toxicity of MDS was lower than that of silica dioxide. MDS led to a notable recruitment and infiltration of macrophages in the rat lungs. Material characterization and biochemical analysis revealed that SiO2, Fe2O3, and TiO2 could be crucial sources of MDS toxicity. The study revealed that MDS-induced oxidative stress response can lead to pulmonary inflammation, which potentially may progress to lung fibrosis. Transcriptome sequencing revealed that MDS suppresses the PI3K-AKT signaling pathway, triggers the Tnfr2 non-classical NF-kB pathway and IL-17 signaling pathway, ultimately causing lung inflammation and activating predominantly antioxidant immune responses. Moreover, the study identified the involvement of upregulated genes IL1b, csf2, and Sod2 in regulating immune responses in rat lungs, making them potential key targets for preventing pulmonary toxicity related to moon dust exposure. These findings are expected to aid in safeguarding astronauts against the hazardous effects of moon dust and offer fresh insights into the implications and mechanisms of moon dust toxicity.

Numerical investigations of translocation characteristics of nano-silica lunar dust across pulmonary surfactant monolayer.

The interactions between nano-silica lunar dust (NSLD) on the moon surface and pulmonary surfactant (PS) monolayer will pose risks to astronaut health in future manned lunar exploration missions, but the specifics of these interactions are unknown. This study investigates them using the coarse-grained molecular dynamics method considering different sizes (5, 10, and 15 nm) and shapes (sphere, ellipsoid, and cube), with special focus on the unique morphology of NSLDs with bugles. The key findings are as follows: (1) The 10 nm and 15 nm NSLDs embed in the PS monolayer through the major sphere of spherical-type, major ellipsoid of ellipsoidal-type, or one edge of cubic-type NSLDs upon contact the PS monolayer. (2) Adsorbed NSLDs cause a higher Sz value (ASz > 0.84), while embedded NSLDs cause a lower Sz value (0.47 < ASz < 0.83) that decreases with an increase in the number of bulges. (3) The embedding process absorbs 50-342 dipalmitoylphosphatidylcholine (DPPC) molecules, reducing the PS monolayer area by 0.21%-6.05%. NSLDs with bulges absorb approximately 9-126 additional DPPC molecules and cause a 0.05%-3.22% reduction in the PS monolayer area compared to NSLDs without bulges. (4) NSLDs move obliquely or vertically within the PS monolayer, displaying two distinct stages with varying velocities. Their movement direction and speed are influenced by the increasing complexity of NSLD with more bulges on them. In general, larger NSLDs with sharper shapes and increasing complex morphology of more bulges cause more significant damages to the PS monolayer. These findings have implications for safeguarding astronaut health in future manned lunar exploration missions.

Human-airway surface mesh smoothing based on graph convolutional neural networks.

BACKGROUND AND OBJECTIVE: A detailed representation of the airway geometry in the respiratory system is critical for predicting precise airflow and pressure behaviors in computed tomography (CT)-image-based computational fluid dynamics (CFD). The CT-image-based geometry often contains artifacts, noise, and discontinuities due to the so-called stair step effect. Hence, an advanced surface smoothing is necessary. The existing smoothing methods based on the Laplacian operator drastically shrink airway geometries, resulting in the loss of information related to smaller branches. This study aims to introduce an unsupervised airway-mesh-smoothing learning (AMSL) method that preserves the original geometry of the three-dimensional (3D) airway for accurate CT-image-based CFD simulations. METHOD: The AMSL method jointly trains two graph convolutional neural networks (GCNNs) defined on airway meshes to filter vertex positions and face normal vectors. In addition, it regularizes a combination of loss functions such as reproducibility, smoothness and consistency of vertex positions, and normal vectors. The AMSL adopts the concept of a deep mesh prior model, and it determines the self-similarity for mesh restoration without using a large dataset for training. Images of the airways of 20 subjects were smoothed by the AMSL method, and among them, the data of two subjects were used for the CFD simulations to assess the effect of airway smoothing on flow properties. RESULTS: In 18 of 20 benchmark problems, the proposed smoothing method delivered better results compared with the conventional or state-of-the-art deep learning methods. Unlike the traditional smoothing, the AMSL successfully constructed 20 smoothed airways with airway diameters that were consistent with the original CT images. Besides, CFD simulations with the airways obtained by the AMSL method showed much smaller pressure drop and wall shear stress than the results obtained by the traditional method. CONCLUSIONS: The airway model constructed by the AMSL method reproduces branch diameters accurately without any shrinkage, especially in the case of smaller airways. The accurate estimation of airway geometry using a smoothing method is critical for estimating flow properties in CFD simulations.

Assessing airflow unsteadiness in the human respiratory tract under different expiration conditions.

To enhance the understanding of airflow characteristics in the human respiratory system, the expiratory airflow in a human respiratory tract model was simulated using large eddy simulation and dynamic mesh under different expiration conditions aligned with clinically measured data. The airflow unsteadiness was quantitatively assessed using power spectral density (PSD) and spectral entropy (SE). The following findings were obtained: (1) The airflow is highly turbulent in the mouth-pharynx region during expiration, with its dynamic characteristics being influenced by both the transient expiration flow pattern at mouth piece and the glottis motion. (2) PSD analysis reveals that the expiratory airflow is very unsteady, exhibiting a broad-band attenuation spectrum in the pharynx-trachea region. When only transient expiration or glottis motion is considered, the PSD spectrum changes slightly. When both are ignored, however, the change is significant, with the peak frequency reduced to 10% of the real expiration condition. (3) SE analysis indicates that the airflow transitions into turbulence in the trachea, and there may be multiple transitions in the region of soft palate. The transient expiration or glottis motion alone increases turbulence intensity by 2%-15%, while ignoring both reduces turbulence intensity by 10%-20%. This study implies that turbulence characteristics can be significantly different under different expiratory conditions, and therefore it is necessary to determine the expiratory flow characteristics using clinically measured expiratory data.

Numerical and Machine Learning Analysis of the Parameters Affecting the Regionally Delivered Nasal Dose of Nano- and Micro-Sized Aerosolized Drugs.

The nasal epithelium is an important target for drug delivery to the nose and secondary organs such as the brain via the olfactory bulb. For both topical and brain delivery, the targeting of specific nasal regions such as the olfactory epithelium (brain) is essential, yet challenging. In this study, a numerical model was developed to predict the regional dose as mass per surface area (for an inhaled mass of 2.5 mg), which is the biologically most relevant dose metric for drug delivery in the respiratory system. The role of aerosol diameter (particle diameter: 1 nm to 30 µm) and inhalation flow rate (4, 15 and 30 L/min) in optimal drug delivery to the vestibule, nasal valve, olfactory and nasopharynx is assessed. To obtain the highest doses in the olfactory region, we suggest aerosols with a diameter of 20 µm and a medium inlet air flow rate of 15 L/min. High deposition on the olfactory epithelium was also observed for nanoparticles below 1 nm, as was high residence time (slow flow rate of 4 L/min), but the very low mass of 1 nm nanoparticles is prohibitive for most therapeutic applications. Moreover, high flow rates (30 L/min) and larger micro-aerosols lead to highest doses in the vestibule and nasal valve regions. On the other hand, the highest drug doses in the nasopharynx are observed for nano-aerosol (1 nm) and fine microparticles (1-20 µm) with a relatively weak dependence on flow rate. Furthermore, using the 45 different inhalation scenarios generated by numerical models, different machine learning models with five-fold cross-validation are trained to predict the delivered dose and avoid partial differential equation solvers for future predictions. Random forest and gradient boosting models resulted in R2 scores of 0.89 and 0.96, respectively. The aerosol diameter and region of interest are the most important features affecting delivered dose, with an approximate importance of 42% and 47%, respectively.

Numerical investigations of the micro lunar dust particles deposition in the human oral respiratory airway.

Understanding the deposition of lunar dust (LD) particles in the human respiratory system is of great significance for protecting astronauts' health from the toxicity of lunar dust. A Euler-Lagrangian approach is adopted to track the LD particle motion in a human oral airway model. The investigations are conducted considering different inspiration rates and micro-particle sizes as well as different abnormal pressures and abnormal temperatures. It is found that 1) almost all the LD particles tend to enter the right lung rather than the left lung, especially in the upper right lobe; 2) at lower ambient pressure, fewer LD particles will deposit in the upper airway, while more particles will enter the lung; 3) at lower temperature, more LD particles are deposited in the upper airway, while fewer are deposited in the lung. In summary, the present work has shown that the LD particles have different depositing properties in the upper airway and the lung lobe regions up to the particle size, inspiration flow rate, temperature and pressure. It should pay more attentions on the upper airway and right upper lobe when it studies the toxicity of the lunar dust, and can't ignore the impact of the environmental temperature and pressure.

Effect of laryngeal jet on dry powder inhaler aerosol deposition: a numerical simulation.

Although pulmonary drug delivery has been deeply investigated, the effect of the laryngeal jet on particle deposition during drug delivery with dry powder inhalers (DPI) has not been evaluated profoundly. In this study, the flow structure and particle deposition pattern of a DPI in two airway models, one with mouth-throat region including the larynx and the other one without it, are numerically investigated. The results revealed that the laryngeal jet has a considerable effect on particle deposition. The presence of laryngeal jet leads to 4-fold and 2-fold higher deposition efficiencies for inlet flow rates of 30 and 90 L/min, respectively.

Effects of chlorine particle concentration on the human airway.

For COVID-19, chlorine has lately been utilised as a home disinfectant. Given that chlorine is hazardous to the human airway, the current research investigates the effects of chlorine mass fraction and droplet size on the human airway. The effects are investigated at chlorine mass ratios of 2% (24 ppm), 10% (120 ppm), 15% (180 ppm), and 20% (240 ppm), as well as chlorine particle diameters of 10 nm, 20 nm, 30 nm, and 50 nm, and three inhalation rates (15 l/min, 30 l/min, and 60 l/min). The results reveal that when the chlorine mass fraction is 2% and the inhalation rate is low, the chlorine volume fraction decreases. Furthermore, at 2% chlorine and a rapid breathing rate, chlorine particles are accelerated to escape into the lungs.

Effects of face shield on an emitter during a cough process: A large-eddy simulation study.

Face shield is a common personal protection equipment for pandemic. In the present work, three-dimensional computational fluid dynamic (CFD) method is used to simulate a cough jet from an emitter who wears a face shield. A realistic manikin model with a simplified mouth cavity is employed. A large eddy simulation with a dynamic structure subgrid scale model is applied to model the turbulence. An Eulerian-Lagrangian approach is adopted to model the two-phase flows, with which the droplets are represented by a cloud of particles. The droplet breakup, evaporation, dispersion, drag force, and wall impingement are considered in this model. An inlet velocity profile that is based on a variable mouth opening area is considered. Special attentions have been put the vortex structure and droplet re-distribution induced by the face shield. It is found that the multiple vortices are formed when the cough jet impinges on the face shield. Some droplets move backward and others move downward after the impinging. It is also found that a small modification of the face shield significantly modifies the flow field and droplet distribution. We conclude that face shield significantly reduces the risk factor in the front of the emitter, meanwhile the risk factor in the back of the emitter increases. When the receiver standing in front of the emitter is shorter than the emitter, the risk is still very high. More attentions should be paid on the design of the face field, clothes cleaning and floor cleaning of the emitters with face shields. Based on the predicted droplet trajectory, a conceptual model for droplet flux is proposed for the scenario with the face shield.

Numerical study of the impact of glottis properties on the airflow field in the human trachea using V-LES.

The influences of the profiles and cross-sectional areas of glottal aperture on the upper respiratory airway are investigated using an idealized cast-based mouth-throat model and three dimensional computational fluid dynamics (CFD). The open source CFD code OpenFOAM is employed. The transient flows are modeled using the very-large eddy simulation with the Smagorinsky sub-grid scale (SGS) model. Five different shapes of glottis are considered, including circular glottis with 100 %, 75 % and 50 % cross-sectional area and elliptic glottis with 75 % and 50 % cross-sectional area. Both instantaneous and averaged flow fields are analyzed. It is found that the variations of glottis have great impacts on the properties of downstream flow fields such as the secondary flow, laryngeal jet, recirculation zone, turbulent kinetic energy, and vortex. Evident impacts are observed in the region within 6 tracheal diameters downstream of the glottis. The profile of the glottis has more impacts on the laryngeal shape, while the cross-sectional area has more impacts on velocity of the laryngeal jet and turbulent intensity. It is concluded that both the glottal areas and profiles are critical for an idealized geometrical mouth-throat model.

Effect of swirling flow and particle-release pattern on drug delivery to human tracheobronchial airways.

The present study aims to investigate the effect of swirling flow on particle deposition in a realistic human airway. A computational fluid dynamic (CFD) model was utilized for the simulation of oral inhalation and particle transport patterns, considering the k-ω turbulence model. Lagrangian particle tracking was used to track the particles' trajectories. A normal breathing condition (30 L/min) was applied, and two-micron particles were injected into the mouth, considering swirling flow to the oral inhalation airflow. Different cases were considered for releasing the particles, which evaluated the impacts of various parameters on the deposition efficiency (DE), including the swirl intensity, injection location and pattern of the particle. The work's novelty is applying several injection locations and diameters simultaneously. The results show that the swirling flow enhances the particle deposition efficiency (20-40%) versus no-swirl flow, especially in the mouth. However, releasing particles inside the mouth, or injecting them randomly with a smaller injection diameter (dinj) reduced DE in swirling flow condition, about 50 to 80%. Injecting particles inside the mouth can decrease DE by about 20%, and releasing particles with smaller dinj leads to 50% less DE in swirling flow. In conclusion, it is indicated that the airflow condition is an important parameter for a reliable drug delivery, and it is more beneficial to keep the inflow uniform and avoid swirling flow.

Investigation of airflow field in the upper airway under unsteady respiration pattern using large eddy simulation method.

In this paper, the airflow field in the upper airway under unsteady respiration process is predicted using large eddy simulation. The geometrical model is created by combining a popular cast-based mouth-throat model with tracheo-bronchial airways modeled with a trumpet-shaped conduit. The respiration process is simulated by sinusoidal displacing the bottom surface of the geometrical model. Large eddy simulation with dynamic sub-grid scale model is adopted for modeling the turbulent flow via a commercial CFD software, Converge. This study has found that (1) the secondary vortices in the mouth cavity are much more complex considering the lung expansion than setting the quasi-steady inspiration flow at the mouth-inlet; (2) the properties of secondary vortices in the trachea are not evidently different at the same Reynolds number at the accelerating and decelerating inspiration phases; (3) the reversed pharynx jet as well as recirculation zone is much unsteadier at the accelerating expiration phase than decelerating expiration phase for the same Reynolds number. We conclude that the properties of airflow structures are highly impacted by the respiration pattern and more investigations should be conducted, particularly, on the airflow structures during expiration phase for further understanding the properties of flow field.

Atmospheric observation-based estimation of fossil fuel CO2 emissions from regions of central and southern California.

Combustion of fossil fuel is the dominant source of greenhouse gas emissions to the atmosphere in California. Here, we describe radiocarbon (14CO2) measurements and atmospheric inverse modeling to estimate fossil fuel CO2 (ffCO2) emissions for 2009-2012 from a site in central California, and for June 2013-May 2014 from two sites in southern California. A priori predicted ffCO2 mixing ratios are computed based on regional atmospheric transport model (WRF-STILT) footprints and an hourly ffCO2 prior emission map (Vulcan 2.2). Regional inversions using observations from the central California site suggest that emissions from the San Francisco Bay Area (SFBA) are higher in winter and lower in summer. Taking all years together, the average of a total of fifteen 3-month inversions from 2009 to 2012 suggests ffCO2 emissions from SFBA were within 6 ±â€¯35% of the a priori estimate for that region, where posterior emission uncertainties are reported as 95% confidence intervals. Results for four 3-month inversions using measurements in Los Angeles South Coast Air Basin (SoCAB) during June 2013-May 2014 suggest that emissions in SoCAB are within 13 ±â€¯28% of the a priori estimate for that region, with marginal detection of any seasonality. While emissions from the SFBA and SoCAB urban regions (containing ~50% of prior emissions from California) are constrained by the observations, emissions from the remaining regions are less constrained, suggesting that additional observations will be valuable to more accurately estimate total ffCO2 emissions from California as a whole.

Large eddy simulation of the flow pattern in an idealized mouth-throat under unsteady inspiration flow conditions.

An excellent understanding of the airflow properties is critical to improve the drug delivery efficiency via the extrathoracic airway. The present numerical study focuses on the investigation the characteristics of important airflow structures such as the secondary vortices, the impinging jet and the recirculation zone under unsteady inspiration flow conditions in a circular idealized mouth-throat model using large eddy simulation (LES). Five inhalation cycles are simulated, the last one of which is analyzed in detail at five different times. Two times are chosen during the accelerating branch, one at the peak and two within the decelerating inhalation wave. The flow exhibits an extinct process of the flow transiting from laminar to turbulent during the accelerating phase and transiting back from turbulent to laminar in the decelerating phase. It is found that the flow is much more turbulent during the decelerating phase compared to the accelerating phase of the inspiration wave, which is associated with more smaller secondary vortices, a shorter and more unsteady laryngeal jet, a smaller and more unsteady recirculation zone, as well as an enlarged mixing zone. These differences during the unsteady inspiration require more attention in particular if particle transport and deposition in the upper airway are to be investigated.

Numerical study of the airflow structures in an idealized mouth-throat under light and heavy breathing intensities using large eddy simulation.

An excellent understanding of the airflow structures is critical to enhance the efficiency of drug delivery via the human oral airway. The present paper investigates the characteristics of both steady and unsteady airflow structures in an idealized mouth-throat using large eddy simulation (LES). Representative inhalation flow rates of 15L/min at rest and 60L/min in exercise are considered. The study shows that there are more secondary vortices in the pharynx and the laryngeal jet is much longer and more concave in the steady flow field at 15L/min compared to the higher inspiration rate, which decreases the possibility of drug impinging on the wall. In contrast, the laryngeal jet is much more unsteady at heavy breathing and its strong interaction with the recirculation zone in the trachea leads to a enlarged mixing zone, increasing the possibility for carrying the particles from the laryngeal jet into the recirculation zone, which will lead to a longer residence time of the particles in the trachea and this increases the possibility of drug deposition in this area. In addition, the recirculation zone size is larger, the separation region is far away from glottis, and the reversed flow is slower at light compared to heavy breathing. In conclusion, these airflow structures show distinct properties at light and heavy breathing conditions, particularly in the unsteady flow field. The study provides evidence about the physical processes leading to both enlarged mixing zones and recirculation zones. It is known that stronger secondary vortices, a stronger laryngeal jet and enlarged recirculation zones definitely increase the particle deposition in the upper airway. The present paper aims to uncover the physical properties of the airflow for different breathing conditions, and their detailed effect on particle deposition will be studied in future.