- Email: [email protected]
Human nasal olfactory deposition of inhaled nanoparticles at low to moderate breathing rate
Author’s Accepted Manuscript Human Nasal Olfactory Deposition of Inhaled Nanoparticles at Low to Moderate Breathing Rate Lin Tian, Yidan Shang, Jingliang Dong, Kiao Inthavong, Jiyuan Tu www.elsevier.com/locate/jaerosci
PII: DOI: Reference:
S0021-8502(17)30224-0 http://dx.doi.org/10.1016/j.jaerosci.2017.08.006 AS5167
To appear in: Journal of Aerosol Science Received date: 20 June 2017 Revised date: 14 August 2017 Accepted date: 18 August 2017 Cite this article as: Lin Tian, Yidan Shang, Jingliang Dong, Kiao Inthavong and Jiyuan Tu, Human Nasal Olfactory Deposition of Inhaled Nanoparticles at Low to Moderate Breathing Rate, Journal of Aerosol Science, http://dx.doi.org/10.1016/j.jaerosci.2017.08.006 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Human Nasal Olfactory Deposition of Inhaled Nanoparticles at Low to Moderate Breathing Rate
Lin Tiana, Yidan Shanga, Jingliang Donga, Kiao Inthavonga, Kiao Inthavonga, Jiyuan Tua* a
School of Engineering – Mechanical and Automative, RMIT University, Bundoora, VIC, Australia b Key Laboratory of Ministry of Education for Advanced Reactor Engineering and Safety, Institute of Nuclear and New Energy Technology, Tsinghua University, PO Box 1021, Beijing, China *
Corresponding author. [email protected]
ABSTRACT Olfactory pathway, susceptible for direct translocation of inhaled nanoparticles into the brain, has been verified in a number of animal studies over past decades. In case of toxic substances, the extremely low dose strongly suggests a subclinical condition that prevents noticeable neurodegeneration until years after prolonged exposure. The exact mechanism, between elevated presence of toxic substances (e.g. heavy metals) and deteriorated neurofunction in human central nervous system, is still not clear; however, nasal olfactory, being portal of the entry for such a transport route, is undoubtedly a critical junction where hint to the time course and dose dependency might be inferred. Using a physiologically realistic nasal and upper airway replica, this study performed human inhalation simulations of nanoparticles (1 to 100 nm) under low to moderate breathing conditions (5 to 14 L/min). Emphasis is on olfactory deposition and the various factors contributing to the process. Details on airflow pattern and particle flux in nasal and olfactory were made visible through a 2D unwrapped surface mapping technique, and it was found out that airflow pattern, especially nasal wall shear had a remarkable correlation to particle movement and deposition at the ultrafine scale (< 1~2 nm). Olfactory deposition efficiency was found to be extremely low (< 3.5%), and showed distinctive variation in high diffusivity region when compared to that in the entire nasal cavity. The entrance profile of olfactory deposited particles was seen to be highly selective and unanimously originated from upper section of the nostril near nasal septum. Current study is of significant value to the understanding of human uptake of inhaled nanoparticles through olfactory pathway.
Keywords: Inhalation toxicity, neurotoxicity, nanoparticles, nasal olfactory, olfactory pathway, olfactory deposition
2
1. INTRODUCTION Olfactory pathway has been suspected to play a vital role in brain uptake of neuro toxics (such as heavy metals) which is linked to the chronic neurodegeneration in human central nervous system. This is supported by growing evidence of restricted admittance of such substances via blood-brain barrier, once considered as the primary uptaking route. Animal study of Zheng et al. (1991) in rats and rabbits demonstrated that the choroid plexus of the blood-brain barrier effectively sequester heavy metal toxicants (e.g. cadmium, lead, mercury, and arsenic) thus protecting the brain from accumulating such substances. Similar observation was reported by Ingersoll et al. (1995) where restricted penetration of manganese into rat cerebrospinal fluid (CSF) was rendered by effective sequestration through lateral choroid plexus of the blood–CSF barrier. These barriers act as highly selective filtration system to protect the microenvironment of the brain from foreign substances. Olfactory pathway, on the other hand, bypasses the protective blood-brain barrier and facilitates translocation of inhaled nanoparticles through olfactory nerve system leading to the accumulation of brain toxicants.
A landmark evidence of olfactory pathway as a viable transport route of inhaled nanoparticles into the brain was reported by De Lorenzo et al. (1970). In their experiment, intranasally instilled colloidal gold particles (50 nm) in squirrel monkeys were observed to translocate anterogradely in axons of the olfactory nerves and reach olfactory bulbs. A neuronal transport velocity of 2.5 mm/h was obtained based on the measurement. Clear evidence was also demonstrated by Gianutsos et al. (1997) that, following the unilateral intranasal instillation of manganese chloride in the right nostril of the rats, elevated levels of manganese were detected in the right olfactory bulb and olfactory tubercle while no changes were detected on the left side of the brain. The affected brain manganese levels were shown to be dose and time dependent. In addition, manganese content of the striatum, the targeted site for manganese neurotoxicity, was unchanged following acute administration; however was elevated when repeated injections were made during prolonged time course. These results not only suggested that air-borne manganese can be transported along olfactory neurons, but also implied that long term accumulation of neuron toxicants at targeted site might have profound implication towards chronic neurodegeneration in the central nervous system. Oberdorster et al. (2004) performed rats inhalation study by whole body exposure to carbon nanoparticles (36 nm) suspended in a confined compartment. 3
Translocation of inhaled nanoparticles to targeted sites (lung, cerebrum, Cerebellum and olfactory bulbs) via respiratory and various neuron routes were examined. The study found out that central nervous system can be targeted by airborne solid ultrafine particles, and the most likely mechanism is from deposits on olfactory mucosa (of nasopharyngeal region from respiratory tract) and subsequent translocation via the olfactory nerve. An estimated 20% of deposited ultrafine particles on olfactory mucosa can be translocated to the olfactory bulb. Uptake of manganese, cadmium, nickel, mercury and cobalt nanomaterial via rats olfactory pathways were also reported in the work of Tjälve et al. (1996), Henriksson et al. (1997, 1998), and Persson et al. (2003).
While limited data is available in human subject, olfactory pathway is considered a functional route for brain uptake of inhaled nanoparticles across different species. This is supported by assessment of Shiga et al. (2010) on healthy volunteer human subjects that, appreciable movement of thallium to the olfactory bulb was observed following nasal administration using single photon emission computed tomography (SPECT), X-ray computed tomography (CT), and MRI. The transport kinetic properties were shown to be consistent with delivery route via olfactory nerves, and agree with the observation in rodent studies (Kanayama et al., 2005). Similar conclusion was attained by Sen et al. (2011) where manganese accumulation (from welding fumes) in different brain regions was investigated by comparing the MRI and neuron functional tests between seasoned welders and controls. The findings support the hypothesis that olfactory nerve might be a viable transport route in human, and accumulation of the inhaled nanoparticles at olfactory bulb might lead to further translocation into the brain. Accumulation of inhaled submicron manganese particles in the olfactory bulb of nonhuman primates following aerosolized MnSO4 exposure was also reported in the work of Dorman et al. (2006ab). The exact mechanism, between elevated presence of toxic substances (e.g. heavy metals) and deteriorated neurofunction in human central nervous system, is still not clear; however, nasal olfactory, being portal of the entry for such a transport route, is undoubtedly a critical junction where hint to the time course and dose dependency might be inferred. Due to technical difficulty, quantitative measures of nanoparticle deposition onto nasal olfactory mucosa are not available in either animal or human studies, and quantitative assessments were only provided by very few 4
computational studies. Garcia and Kimbell (2009) were the first to propose a rat olfactory deposition equation based on computational investigation of inhaled nanoparticles (1 to 100 nm). According to the study, olfactory dose was predicted to be the highest for 3 to 4 nm particles, with approximately 6 to 9% deposited onto the olfactory epithelium. Similar approach was applied in human nasal cavity models (Garcia et al., 2015), and for breathing rates of 15 to 30 L/min, human olfactory deposition was shown to reach the maximum of 1% for 1-2 nm particles. Taking into account of the higher minute volume, olfactory dose per unit surface area was found to be greater in human than in rat (1-10 nm). Shang et al. (2015) and Dong et al. (2016) did comparative study of micron and nanoparticle deposition in human and rat nasal cavities, where deposition flux and intensity were obtained for various nasal sections including olfactory. It was found out that both the deposition pattern and flux onto the nasal olfactory varied significantly between human and rat models, and interspecies extrapolating schemes were proposed.
In this study, inhalation simulations of nanoparticles (1 to 100 nm) under low to moderate breathing conditions (5 to 14 L/min) were performed in a physiologically realistic human nasal and upper airway replica. The simulation emphasized on olfactory deposition and the various factors contributing to the process, which are lacking in current literature. Details on airflow pattern and particle flux in nasal and olfactory were made visible through a 2D unwrapped surface mapping technique (Inthavong et al., 2014), and it was found out that airflow pattern, especially nasal wall shear had a remarkable correlation to particle movement and deposition at the ultrafine scale (< 1~2 nm). Olfactory deposition efficiency was found to be extremely low (< 3.5%), and showed distinctive variation in high diffusivity region when compared to that in the entire nasal cavity. The entrance profile of olfactory deposited particles was seen to be highly selective and unanimously originated from upper section of the nostril near nasal septum. Current study is of significant value to the understanding of human uptake of inhaled nanoparticles through olfactory pathway.
2. METHOD 2.1 Human Nasal and Olfactory Airway Modeling A CFD model of the upper respiratory airway containing facial features, the nasal cavity, larynx, and the trachea was developed from CT scans (Shang et al. 2015) (Figure 1a). Each model of the 5
respiratory airway was connected to form a contiguous path via nostrils, from the external space to the end of the larynx region. The larynx region was extended to the trachea to allow sufficient flow recovery and improve numerical convergence in the CFD solution. The respiratory airway was added to a realistic human face exposed to the external surroundings containing airborne particles from the ambient environment. Details for model reconstruction and verification can be found in the work of Inthavong et al., 2012.
Human nasal olfactory was located at roof of the nasal cavity (Figure 1a), which has a surface area of 2097 mm2 and occupies 10.5% of the total nasal cavity (Shang el al., 2015). Olfactory channel (Figure 1b) was 1-2 mm wide, with inner layer covered by olfactory mucosa and connected to olfactory bulb through receptor neurons. As the interface between external airway and the brain, olfactory mucosa is considered the entry point for inhaled nanoparticles to get translocated into the brain. A 2D unwrapped nasal cavity model, showing details of the relative position and surface feature for human olfactory mucosa, was displayed in Figure 1c. The model was first sliced along the centerline of the nasal passage floor, where lateral and septal walls met. Then the 3D surface coordinates were transformed into a new set of 2D coordinates, mimicking the surfaces being unfurled. Layout of the top and bottom boundaries represents the initial centerline (sliced along the nasal floor), while left and the right boundaries represent the nostril and nasopharynx respectively. Details of surface-mapping technique to transform nasal cavity morphology from 3D onto a planar 2D domain can be found in the work of Inthavong et al., 2014.
2.2 Computational Mesh Fluent Meshing (ANSYS 18.0) was used to generate the computational mesh (Figure 2). A new polyhedron scheme was employed and shown to be computational efficient, numerical accurate, and generate solution with superior converging capabilities. Polyhedron elements with minimum cell dimension of 1 mm filled the main airway passage and maximum cell dimension of 10 mm filled the external domain, while a highly dense prism layer of hexahedron elements in normal direction of the wall was attached to resolve near wall features. The 5 prism layers evolved from the first grid point with cell dimension of 0.05 mm to the core region with a growing factor 1.2.
6
The resulting mesh consisted of 1,237,634 elements. Mesh independency was conducted and achieved at the specified size.
2.3 Fluid Flow Simulation Current study employed a steady inhalation model with the assumption that particle deposition mainly occurs during the inhalation phase (Inthavong et al., 2010). It is worth to note that breathing pattern was shown to affect deposition for micron range particles between 1 and 5 µm (Häuβermann et al., 2002), however, the effect toward nanoparticle deposition was still not fully understood. Sedentary breathing (4 to 14 L/min) was assumed indicating laminar flow condition.
Airflow was simulated using ANSYS-FLUENT18.0. The surrounding walls were set to atmospheric pressure and inhalation was initiated by a negative pressure difference at the bronchial bifurcation outlet. This allowed the ambient flow field to be influenced only by the inhaled air. The continuity and momentum equation of the fluid flow are: ui 0 , xi
uj
ui p x j xi x j
(1)
ui . x j
(2)
where ρ, u and p are density, velocity and pressure of the air, respectively. A second order upwind scheme was used to approximate the momentum equation, while the pressure-velocity coupling was handled through the SIMPLE method. Further detail of the fluid flow modeling was given in Wen et al. (2008).
2.4 Particle Simulation Lagrangian particle tracking method is used where individual particle trajectory is computed. The particle equation is:
du p dt
g ( p ) 1 FD FL FB Cc p
(3)
here up is the particle velocity, t is the time, g is the gravitational constant, ρp is the particle density. In this study, both gravitational and buoyancy forces can be neglected. FD is the drag 7
force given by 18µ(up-u)/( d2ρp), with d being the particle diameter, and Cc the Cunningham correction given by: Cc 1
2 (1.257 0.4e( 1.1d d
/2 )
),
(4)
here λ is the molecular mean free path. FL in Equation (3) is the Saffman lift force, and FB is the Brownian diffusion force with amplitude of S0 / t /. ς is a zero mean, unit variance independent Gaussian random numbers. ∆t is the time-step for particle integration and So is a spectral intensity function (Li and Ahmadi, 1992): : So
216 kT 2 d 5 p Cc 2
.
(5)
ν is the fluid kinematic viscosity, k is the Boltzmann constant, and T is the absolute temperature of the inspiratory air in the nasal cavity. The simulation was carried out with ANSYSFLUENT18.0 discrete phase model (DPM).
Shang et al. (2015) showed that the airflow has negligible influence on particle trajectory outside the breathing zone. In this study, particles were uniformly released on a hemisphere (of radius 3 cm) with the center at the nose tip (Figure 2), resembling the release condition of Doorly et al. (2008). Statistically independent 100,000 uniform concentrated mono-dispersed ultrafine particles of 1, 1.1, 1.2, 1.3, 1.4, 1.5, 1.7, 2, 3, 5, 10, 15, 20, 30, 40, 50, 70 and 100 nm, were released. Deposition onto the respiratory walls occurred when the particle was within radius distance away from the surface.
2.5 Particle Flux To visualize particle spatial distribution across nasal airway passage, particle flux (f) is defined as the number of particles passing through per unit area of nasal cross sections along the transport route. f is normalized with the total number of particles entering nasal cavity, therefore, being 1.0 at the nostril. An evolving spatial distribution could shed light on particle bulk
8
movement and the consequence to olfactory deposition. Decreasing particle flux is anticipated as particles continue to be deposited along the transport route. Accordingly,
f(r)
# particles per unit cross sectional area # particles entering nasal cavity
f(r)dA 1.0 , and
f(r)dA 1.0
on subsequent cross sections.
(7)
(8)
Nostril
r is the position vector on cross sections with area element being dA in above equations.
2.6 Deposition Efficiency Particle deposition efficiency (DE) is defined as the ratio of the deposited particles in a region to the total number entering nasal cavity. That is:
DE
#deposited particles #particles entering the nasal cavity
(6)
It is an important parameter characterizing the regional filtering capacity and particle penetration rate. Deposition efficiency (DE) is closely related to the transport mechanisms and for nanoparticles, size, diffusivity and airflow rate are the governing parameters. Due to the geometric complexity of human airways, no analytical expression is available for deposition efficiency (DE). Frequently, empirical fitted equations are used to relate measured data (DE) to the governing parameters.
2.7 Model Validation The particle equation (3) was solved by stepwise integration over discrete time steps yielding a new particle velocity at each time step. Inthavong et al. (2016) identified the sensitivity of nanoparticle diffusion behavior (in Lagrangian tracking) to the integral time step factor, mesh size and flow condition. The evaluation was based on selecting the most appropriate time step factors to achieve optimal Lagrangian tracking outcome was proposed and verified in a pipe and a human pharynx model (Inthavong et al., 2016).
In ANSYS-FLUENT, the length scale factor of integration, Ls controls the integration time step size and Δt is a function of the particle velocity and the continuous airflow phase velocity: 9
t
Ls up u
(9)
This means that the length scale factor is proportional to the integration time step, which is the distance that the particle travels before its equations are solved again and its trajectory updated. A smaller value for the length scale increases the number of calculations per step length. Its selection must reproduce the diffusion dispersion mechanism for nanoparticles (Inthavong et al., 2016). A standard geometry in the form of a pipe (Figure 3a) with analytical solution by Ingham (1975) was used to validate the particle dispersion. A fully developed flow of 1 L/min and 5 L/min was used which has a corresponding Re = 312, and Re = 1560 respectively. The particles were introduced into the pipe with a mass flow rate distributed with a fully developed profile as:
r2 m(r ) m0 1 2 R
(10)
where m0 is the maximum mass flow rate at the pipe centerline, r is the radial position from the pipe centerline, and R is the pipe radius. Particle deposition in the pipe over a distance of 0.09m was compared with the deposition efficiency (DE) correlation by Ingham (1975).
DE 1 0.819e14.63 0.0976e89.22 0.0325e228 0.0509e125.9 2/3
(11)
where
DLpipe 4U inlet R
(12) 2
Particle deposition in a pipe length of 0.9 m was compared for length scale factors of 5e-5 m, 1e5 m, and 5e-6 m, which showed that the deposition was best described using a value of 1e-5 m. Applying the method to the current model in this study showed that an optimal value of 2e-5 m. Further detail of the methodology was given in (Inthavong et al., 2016).
3. RESULTS AND DISCUSSION 3.1 Breathing Airflow Pattern Low to moderate breathing at flow rates of 5 to 14 L/min was included in the simulation. Key features of the airflow pattern were similar, conforming to the geometric details of the airway. Figure 4 displayed the stream-wise and axial airflow pattern at breathing rate of 5 L/min in the 10
nasal and upper airways at selected locations. Ambient air entered the nostril in an upward direction, and turned 90o entering the middle and inferior nasal meatus before a second 90o at the posterior nasopharynx. High velocity was observed at the nostril entrance, downstream of the nasal valve and at the larynx. Bulk air passed through the middle and inferior meatus, whereas the superior meatus, where the olfactory region was located, had very low velocity air passing through.
The inhaled airborne particles were transported by the moving fluid and regions with higher velocity implied high particle concentrations. As implied, major air conducting sections (middle and inferior meatus) had significantly higher particle exposure than nasal olfactory. Compared to substantial airflow changes in major nasal channels induced by sharp turn, sudden shrink or expansion of the cross sectional area, airflow in olfactory region was sedentary and free of these changes. Also noted was the asymmetric cross section between left and right nasal passages which is common in human, with the right carrying larger volume of airflow owing to less resistance.
3.2 Wall Shear Stress Figure 5 displayed the wall shear stress on nasal and olfactory surface at the breathing rate of 5 L/min. Stress pattern on both the 3D and 2D unwrapped model were plotted for comparison. Strong localized high shear were observed on nasal anterior before the 90o turn, and in posterior nasal cavity following the second 90o turn. It was shown in Figure 5 that, nasal mucosa on the right passage experienced noticeable greater stress concentrated on vestibule and anterior of main nasal airway. On the other hand, a less prominent but more uniform stress pattern was shown on the left airway with friction appeared to be smeared out across the channel surface. Two sedentary airflow pockets with extremely low wall shear were observed near lateral border and in nasal olfactory in the right cavity. This was not observed in the left cavity. Averaged wall shear on the left nasal olfactory mucosa was about three times larger than that on the right, being 0.009 and 0.003 Pa respectively.
Wall shear distribution could well indicate the level of secondary flow and forming of local eddies contributing to enhancement of the particle deposition. Clearly shown in Figure 5ab, 2D 11
unwrapped surface mapping provided considerably more information than that of the 3D presentation, pushing forward our understanding of the particle transport process in nasal cavity.
3.3 Particle Flux and Spatial Distribution Figure 6 displayed the particle flux (1, 2 and 10 nm at 5 L/min) at cross sections of the nostril, nasal valve, main channel (anterior/posterior nasal olfactory), and posterior naris where the pair of nasal apertures merge into nasopharynx (Figure 4). A clear preferential particle distribution was observed at nostrils and nasal valves where significantly higher particle concentration was seen near nose tip and upper section of the openings. This is due to flow acceleration and momentum gain for both airflow and particles in vicinity of the nostril; however, concavely located floor of the opening are more likely to be shielded from impinging flow and particles by bottom of the facial features (Figure 4). This preferential particle distribution was seen to penetrate through nasal vestibule, and vanish when reaching mid channels where particle movement was more affected by local environment in the main nasal cavity (Figure 6). Midchannel particle concentration clearly conformed to the flow pattern (Figure 4) with middle and inferior meatus (septal side) saw significantly higher particle flux. For the same reason, particle concentration was significantly higher in the right channel than that in the left. Minimum particle flux was seen in nasal olfactory and the lateral scroll end of the channel floor. It was also noted a decreasing particle flux in the nasal passage as continuous deposition occurred along the transport route.
Particle size was clearly seen to affect particle flux and spatial distribution (Figure 6). Larger sized nanoparticles exhibited stronger preferential concentration when entering the nose while smaller sizes were relatively more uniformly distributed. This was consistently observed in mid and posterior nasal channels however with varying degrees. In addition, lower particle flux was seen with smaller sized particles. This is especially prominent in nasal olfactory where the number of 1 nm particles passing through the region was significantly lower than that of the 10 nm particles. These phenomena were largely related to molecular diffusivity, a fundamental mobility property inversely related to the particle size. That is, smaller size implies higher diffusivity and more likelihood to be dispersed uniformly, or travel a further distance to get lost
12
at the wall. Prior loss to airway surfaces might contribute to the extremely low level of particle flux observed in olfactory as seen for the 1 and 2 nm particles (Figure 6ab).
The evolving particle bulk movement in response to the combined transport mechanisms in nasal channel could very well shed light on olfactory deposition. It was clearly seen in Figure 6 that olfactory cavity was not in favor of hosting inhaled nanoparticles, and only a minimum succeeded arriving there. This is especially prominent for smaller sized particles such as 1 and 2 nm as shown in Figure 6ab. The phenomenon markedly correlated to olfactory sensory physiology where as few as one odor-biding molecule was probably sufficient to activate sensing (Neuhaus, 1953). Smelling through human olfactory mucosa, which was immersed in extreme sedentary flow with minimum shear, was clearly more related to the Brownian diffusional motion. Particle flux and spatial distribution in human nasal olfactory (Figure 6) may imply an extremely low deposition probability for all sizes onto the olfactory mucosa, as indicated by admission of particles either: 1) in low quantity with higher diffusivity (Figure 6ab); or 2) in higher quantity but low diffusivity (Figure 6c).
3.4 Particle Deposition Pattern Figure 7 showed sample deposition pattern of the inhaled nanoparticles (1, 2 and 10 nm) onto nasal cavity at a breathing rate of 5 L/min. Data mapping onto the unwrapped 2D surface were applied and presented for superior visualization throughout the highly overlapped nasal surface. Particles deposited onto nasal olfactory mucosa were marked in blue while the rest in red. Clearly shown in Figure 7, particle deposition pattern was highly affected by particle size, with high diffusivity particles (such as 1 and 2 nm in Figure 7ab) significantly more likely to be collected. Particles showed preferential deposition sites which were nasal vestibule, anterior septum, and posterior nasal cavity in the converging section of nasopharynx. In main nasal channels, majority of the deposition occurred in middle meatus, with a small fraction scattered across superior meatus (olfactory region) and the channel floor. High level of inhomogeneity was observed with smaller sized particles (1 and 2 nm, Figure 7ab). As the particle size increased, deposition tended to be more homogeneously distributed. The deposition patterns in left and right nasal cavities were not symmetric, with the right appeared to capture more (in middle meatus) and the left being more uniformly distributed. 13
Located at the ceiling, nasal olfactory mucosa was clearly an elusive spot where only a minimum of the inhaled nanoparticles found the way (blue in Figure 7). As seen in Figure 7, deposition pattern on olfactory mucosa were quite distinct among the three examined particle sizes (1, 2, and 10 nm at 5 L/min), with maximum deposition occurred for the 2 nm particles (Figure 7b) and noticeable fewer for the 1 and 10 nm ones. Large blank patches free from deposition were clearly shown at roof and olfactory for the 1 nm particles (Figure 7a), while this pattern was fading or completely vanished for the 2 and 10 nm ones (Figure 7bc). For the 1 nm particles, deposition was mostly concentrated surrounding a thin layer of the border on olfactory mucosa, while the 10 nm particle deposition penetrated through and uniformly spread all over the olfactory. Significantly more deposition was observed for the 2 nm particles; however, deposition did not penetrate through, with the inner most olfactory mucosa clearly less deposited. These phenomena implied a strong size dependency on olfactory deposition under coupled effect of varying deposition mechanisms. Similar to the olfactory region, visible void stripes lack of deposition were also observed at sites corresponding to the scroll end of the inferior meatus for 1 and 2 nm particles, with the latter at a lesser extent.
It should be noted that, human olfactory deposition pattern, with the inner most region hard to reach by inhaled nanoparticles, might imply a significant sensitivity to size of the olfactory mucosa. In case of the 1 nm particles as shown in Figure 7a, a slight shrink or increase of the olfactory mucosa area would lead to significant variation, non-proportional to the area alteration, in olfactory particle collection. The sensitivity was seen to decrease as particle size increased, and might be negligible at 10 nm diameter. In the current study, olfactory mucosa occupied 2097 mm2 of the surface area, or about 10.5% of the total nasal cavity.
Comparing Figure 7a with Figure 5, a remarkable correlation between nasal deposition pattern and the wall shear was recognized for the 1 nm sized particles. Nasal surface, with a strong shear (Figure 5a), was clearly linked to the deposition “hot spot” in the vicinity. Strong localized high shear on nasal anterior before the 90o turn, in posterior nasal cavity following the second 90o turn, and in middle meatus of the right main airway, all correlated to extreme depositions in nearby surfaces. A striking similarity of the sporadic and streak patterned wall shear and particle 14
deposition in the left nasal cavity (Figure 5a and 7a) clearly indicated an intrinsic physical connection. Effect of the shear on particle deposition appeared to propagate with the flow to a wider region, implying a time and spatial progression when up-taking this physical disturbance. Not surprisingly, low shear regions such as nasal roof, olfactory, lower meatus all had significant less deposition. When looking at the 2 nm particle deposition pattern (Figure 7b), strong correlation to the shear (Figure 5) was not observed. Rather than a highly concentrated deposition surrounding the high shear region, deposition appeared to be further dispersed to cover a wider area. For the 10 nm particles (Figure 7c), effect of the wall shear on particle deposition was further reduced. Particle deposition appeared to be uniformly scattered across all nasal cavity.
Correlation between nasal wall shear and the particle deposition pattern might very well have revealed the transport and deposition mechanism of nanoparticles in the nasal cavity. High shear implied higher friction and larger secondary flow in vicinity of the airway surface. Smaller particles of 1 nm were clearly more responsive to these changes due to the high intensity of Brownian motion. The delayed or negligible responses of the 2 and 10 nm particles toward the shear induced disturbances were more likely to be attributed to the reduced Brownian intensity, incapable of keeping pace of the flow disturbances in the coupled time and spatial domain.
3.5 Particle Deposition Efficiency Figure 8 displayed the deposition efficiency of the inhaled nanoparticles (1 to 100 nm) in nasal cavity. Simulation results were plotted against particle size for breathing rates of 5, 7, 10 and 14 L/min (Figure 8a). It was clearly shown that total deposition was inversely related to particle size and the breathing rate. Larger particles and higher breathing rate implied lower deposition efficiency. At 1 nm diameter, particle deposition efficiency at the examined flow rates was in the range from 58.3% to 75.2%. It quickly decreased to about 6% when particle size was increased to 10 nm. Beyond 15 nm, particle deposition efficiency was below 5% and approaching 1% at 100 nm diameter. Variation of particle deposition across different flow rates reached the maximum of 16.9% for the 1 nm particles, while a minimum difference of 0.07% was seen for the 100 nm particles, or a decrease of 241 folds.
15
Data correlation identified that the simulated deposition efficiency correlated most efficiently with D0.589/Q0.494, where the simulation data collapsed into a smooth single curve in Figure 8b. Here D is the particle diffusivity in m2/s, and Q is the breathing airflow rate in m3/s. The developed empirical equation was given as: D 17.87 0.494 Q 1 1.0013e 100 0.589
DE nasal
(13)
In Figure 8b, the measured deposition efficiencies from experiments of Kelly et al. (2004), Cheng et al. (1995), and Swift et al. (1992) were plotted for comparison. These experiments were performed on nanoparticles of 0.58 to 155 nm at low to moderate breathing conditions (4 to 12 L/min). It was shown in Figure 8b that simulation agreed reasonable well with the experimental results in trend and magnitude. Simulation most closely resembled the measurements from Cheng et al. (1995) for larger particles at low deposition side, while the simulated data matched well with the measured deposition efficiency of Swift et al. (1992) for high diffusivity particles. Simulation results generally followed the lower bound of measurements from Kelly et al. (2004). Data scattering were observed in all experiments, however within tolerance, due to noise and high sensitivity of the measurements. Prior simulation of Garcia et al. (2015) on human nasal nanoparticle deposition was also included in Figure 8b for comparison. It agreed well with current simulation and a slightly higher prediction was seen in high diffusivity region due to variation in testing subjects and simulation conditions.
Figure 9 displayed the human olfactory deposition efficiency of inhaled nanoparticles in the range from 1 to 100 nm at breathing rates of 5, 7, 10 and 14 L/min. As shown in Figure 9a, olfactory deposition had quite distinctive characteristics in high diffusivity region when compared to the nasal deposition (Figure 8a). Rather than negative impact, higher breathing rates were seen to enhance deposition for particles below 2.5 nm. Furthermore, deposition appeared to increase together with the particle size until a flow dependent peak value was reached. Particle sizes corresponding to the peak deposition were seen to shift toward the lower end as the breathing rate was increased. Based on the simulation, peak deposition occurred at 1.7, 1.5, 1.3 and 1.2 nm at breathing rates of 5, 7, 10 and 14 L/min respectively. Deposition characteristics in human olfactory were shown to be similar to that in the nasal cavity (Figure 8a) for particles 16
greater than 3 nm. Overall, human olfactory deposition was extremely low in all cases considered (< 3.5%).
Similar to Figure 8b, Figure 9 presented the human olfactory deposition efficiency against D0.589/Q0.494, which was shown to collapse nasal deposition data concisely. As expected, low diffusivity particles corresponded well with the correlation, however, large discrepancies were observed for high diffusivity particles. Clearly, more factors played the role and olfactory deposition cannot be efficiently described in a similar manner as that in the nasal cavity. Simulation result from Garcia et al. (2015) on human nasal olfactory deposition was plotted in Figure 8b for comparison, where similar trend and variation, however, noticeable difference for high diffusivity particles were observed. This was not surprising considering the high sensitivity of human olfactory deposition on olfactory surface area, particularly for high diffusivity particles as discussed in Figure 7. For the same reason, 3 models with varying olfactory sizes were considered in the work of Garcia et al. (2015), and fitting was provided on Model 1A (surface area of 11.2 cm2 or 5.5% of the nasal cavity) about half the size of the current olfactory model (Figure 1). Considering these variations, current simulation and the prediction of Garcia et al. (2015) showed excellent agreement. Due to complexity in experimental procedures, there has been no quantitative report on measurement of nanoparticle deposition onto human olfactory mucosa.
In summary, nanoparticle (1 to 100 nm) collection by human olfactory mucosa was extremely low, with the highest deposition (< 3.5%) seen for high diffusivity particles around 1.5 nm. As particles grew in size, human olfactory deposition was steadily decreasing to about 1% around 100 nm. Breathing rate might have a positive impact in the high diffusivity region; however, it was seen to negatively impact the deposition for low diffusivity particles. Human olfactory deposition efficiency cannot be characterized by Da/Qb with a and b being coefficients, an approach frequently used in nasal deposition study. More factors need to be included and further research is needed.
3.6 Entrance Profile of Olfactory Deposited Particles
17
Olfactory deposited particle profile at nostrils and nasal valves at the breathing rate of 5 L/min were given in Figure 10. Inhaled nanoparticles eventually deposited onto the olfactory region were plotted in blue while the rest in gray. It was clearly shown in the figure that olfactory deposition originated from the nose tip in septal side, and these particles were further pushed toward the ceiling when traveled to the nasal valves. Entrance profile of olfactory deposited particles appeared to be relatively scattered for the 1 nm size, while it was highly selective and concentrated in narrow bands for the 10 nm particles. None of the nanoparticles inhaled via lower half of the nostrils was collected by human olfactory mucosa. The information is of significant value to understand human olfactory uptake of inhaled nanoparticles.
4. CONCLUSIONS Inhalation simulations of nanoparticles (1 to 100 nm) under low to moderate breathing conditions (5 to 14 L/min) were performed in a physiologically realistic human nasal and upper airway replica. Emphasis was on olfactory deposition and the various factors contributing to the process and outcome. Details on the airflow pattern and particle flux in nasal and olfactory were revealed through 2D unwrapped surface mapping. Base on the study, following conclusions were drawn. A remarkable correlation between nasal wall shear and particle deposition pattern was identified at the ultrafine scale (< 1~2 nm). Nasal surface, with a strong shear (Figure 5a), was clearly linked to deposition “hot spot”, while low shear region, including nasal olfactory, had significant less deposition. Immersed in extreme sedentary flow with minimum shear, olfactory deposition was found to be extremely low (< 3.5%), and clearly more related to the Brownian diffusional motion. This phenomenon markedly correlated to olfactory sensory physiology where as few as one odor-biding molecule was probably sufficient to activate sensing. Olfactory deposition showed quite distinctive variation in the high diffusivity region (< ~2 nm) when compared to that in the entire nasal cavity; they are: 1) deposition increased with particle size; 2) higher breathing rate enhanced the deposition; 3) peak deposition was flow 18
rate dependent and peak particle size (~1.5 nm) was negatively impacted by the breathing rate. Beyond peak deposition, particle collection rate in nasal olfactory was steadily decreased as particle size increased, and reached about 1% at 100 nm. Breathing rate was seen to negatively impact the deposition efficiency. Human olfactory deposition efficiency was highly sensitive to olfactory size, especially for nanoparticles at the lower end. For smaller particles of 1-2 nm, deposition was mostly concentrated surrounding a thin layer of the border on olfactory mucosa, while for larger particles deposition was more uniformly spread over the entire region.
The entrance profile of olfactory deposited particles was seen to be highly selective and
unanimously originated from upper section of the nostril near nasal septum. None of the nanoparticles inhaled via lower half of the nostrils was collected by human olfactory mucosa. Human olfactory deposition efficiency cannot be characterized by Da/Qb (a and b being the coefficients), a parameter frequently used in the nasal deposition study. More factors need to be included and further research is needed.
5. ACKNOWLEDGEMENTS The financial supports provided by the National Natural Science Foundation of China (Grant No. 91643102) and the Australian Research Council (Grant No. DP160101953) are gratefully acknowledged.
6. REFERENCES Cheng, KH, Cheng, YS, Yeh, HC, & Swift, D. (1995). Deposition of Ultrafine Aerosols in the Head Airways during Natural Breathing and during Simulated Breath Holding Using Replicate Human Upper Airway Casts, Aerosol Sci. Technol., 23, 465–474. De Lorenzo, A.J.D. (1970). The Olfactory Neuron And The Blood-Brain Barrier. In Taste and Smell in Vertebrates; Wolstenholme, GEW, Knight, J, Eds.; J. & A. Churchill: London, UK, 151–176. 19
Doorly, D.J., Taylor, D.J., & Schroter, R.C. (2008). Mechanics of Airflow in the Human Nasal Airways, Respiratory Physiology & Neurobiology, 163, 100–110. Dong, JL, Shang, YD, Inthavong, K., Tu, JY, Chen, R, Bai, R, Wang, DL, & Chen, CY (2016). Comparative Numerical Modeling of Inhaled Nanoparticle Deposition in Human and Rat Nasal, 152(2), 284-296. Dorman, D.C., Struve, M.F., Marshall, M.W., Parkinson, C.U., James, R.A., & Wong, B.A. (2006a). Tissue Manganese Concentrations in Young Male Rhesus Monkeys Following Subchronic Manganese Sulfate Inhalation, Toxicol Sci., 92(1), 201-210. Dorman, D.C., Struve, M.F., Wong B.A., Dye J.A., & Robertson I.D. (2006b). Correlation of Brain Magnetic Resonance Imaging Changes with Pallidal Manganese Concentrations in Rhesus Monkeys Following Subchronic Manganese Inhalation, Toxicol Sci., 92(1), 219227. Garcia, G.J.M., & Kimbell, J.S. (2009). Deposition of Inhaled Nanoparticles in the Rat Nasal Passages: Dose to the Olfactory Region, Inhalation Toxicology, 21(14), 1165-1175. Garcia, G.J.M., Schroeter, J.D., & Kimbell, J.S. (2015). Olfactory Deposition of Inhaled Nanoparticles in Humans, Inhalation Toxicology, 27(8), 394-403. Gianutsos, G., Morrow, G.R., & Morris, J.B. (1997). Accumulation of Manganese in Rat Brain Following Intranasal Administration, Toxicological Sciences, 37(2), 102-105. Häuβermann, S., Bailey, A.G., Bailey, M.R., Etherington, G., & Youngman, M. (2002). The Influence of Breathing Patterns on Particle Deposition in a Nasal Replica Cast. Journal of Aerosol Science, 33, 923-933. Henriksson, J., Tallkvist, J., & Tjälve, H. (1997). Uptake of Nickel Into the Brain via Olfactory Neurons in Rats, Toxicology Letters, 91, 153-162. Henriksson, J., & Tjälve, H. (1998). Uptake of Inorganic Mercury in the Olfactory Bulbs via Olfactory Pathways in Rats, Environmental Research, Section A, 77, 130-140. Ingersoll, R.T., Montgomery Jr, E.B., & Aposhian, H.V. (1995). Central Nervous System Toxicity Of Manganese. I. Inhibition Of Spontaneous Motor Activity In Rats After Intrathecal Administration Of Manganese Chloride. Toxicological Sciences, 27(1), 106113. Ingham, D.B. (1975). Diffusion of Aerosols from a Stream Flowing through a Cylindrical Tube. Journal of Aerosol Science, 6(2), 125-132. 20
Inthavong, K, Choi, L., Tu, JY, Ding, S., & Thien, F. (2010). Micron Particle Deposition in a Tracheobronchial Airway Model under Different Breathing Conditions. Medical Engineering & Physics, 32(10), 1198-1212. Inthavong, K., Ge, Q. J., Li, X. D., & Tu, J. Y. (2012). Detailed predictions of particle aspiration affected by respiratory inhalation and airflow. Atmospheric Environment, 62(0), 107117. Inthavong, K, Shang, YD, & Tu, JY. (2014). Surface Mapping for Visualization of Wall Stresses during Inhalation in a Human Nasal Cavity. Respiratory physiology & neurobiology, 190, 54-61. Inthavong, K, Tian, L., & Tu, JY (2016). Lagrangian Particle Modelling of Spherical Nanoparticle Dispersion and Deposition in Confined Flows, Journal of Aerosol Science, 96, 56-68. Kanayama, Y., Enomoto, S., Irie, T., & Amano, R. (2005). Axonal Transport of Rubidium and Thallium in the Olfactory Nerve of Mice, Nucl Med Biol., 32(5), 505-512. Kelly, J.T., Asgharian, B., Kimbell, J.S., & Wong, B. (2004). Particle Deposition in Human Nasal Airway Replicas Manufactured by Different Methods. Part II: Ultrafine Particles, Aerosol Sci. Technol., 38, 1072–1079. Li, A., & Ahmadi, G. (1992). Dispersion and Deposition of Spherical Particles from Point Sources in a Turbulent Channel Flow, Aerosol Science and Technology, 16(4), 209-226. Oberdörster, G., Sharp, Z., Atudorei, V., Elder, A., Gelein, R., Kreyling, W., & Cox, C. (2004). Translocation of Inhaled Ultrafine Particles to the Brain, Inhalation Toxicology, 16(6-7), 437-445. Persson, E., Henriksson, J., & Tjälve, H. (2003). Uptake of Cobalt from the Nasal Mucosa into the Brain via Olfactory Pathways in Rats, Toxicology Letters, 145, 19-27. Sen, S., Flynn, M.R., Du, GW, Troster, A.I., An, HY, & Huang, XM (2011). Manganese Accumulation in the Olfactory Bulbs and Other Brain Regions of "Asymptomatic" Welders, Toxicological Sciences, 121(1), 160-167. Shang, YD, Dong, JL, Inthavong, Kiao, & Tu, Jiyuan (2015). Comparative Numerical Modeling of Inhaled Micron-Sized Particle Deposition in Human and Rat Nasal Cavities, Inhalation Toxicology, 27(13), 694-705.
21
Shiga, H., Taki, J., Yamada, M., Washiyama, K., Amano, R., Matsuura, Y., Matsui, O., Tatsutomi, S., Yagi, S., Tsuchida, A., Yoshizaki, T., Furukawa, M., Kinuya, S., & Miwa, T. (2011). Evaluation of the Olfactory Nerve Transport Function by SPECT-MRI Fusion Image with Nasal Thallium-201 Administration, Mol Imaging Biol, 13(6), 1262-1266. Swift, D.L., Montassier,N., Hopke, P.K., Karpen-Hayes, K, Cheng, YS, Su, YF, Yeh, HC, & Strong, J.C. (1992). Inspiratory Deposition of Ultrafine Particles in Human Nasal Replicate Cast, Journal of Aerosol Science, 23(1), 65–72. Tjälve, H., Henriksson, J., Tallkvist, J., Larsson, B.S., & Lindquist, N.G. (1996). Uptake of
Manganese and Cadmium from the Nasal Mucosa into the Central Nervous System via Olfactory Pathways in Rats, Phurmacology & Toxicology, 79, 347-356. University of Calgary. (2006). Psychology Instruction Project (PIP) - Psyc 369 (Sensation & Perception).
[ONLINE]
Available
at:
http://www.ucalgary.ca/pip369/mod8/smell/pathways. [Accessed 19 June 2017]. Wen, J., Inthavong, K., Tu, JY, & Wang S. (2008). Numerical Simulations for Detailed Airflow Dynamics in Human Nasal Cavity, Respiratory Physiology & Neurobiology, 161, 125135. Zheng, W., Perry, D.F., Nelson, D.L., & Aposhian, H.V. (1991). Choroid Plexus Protects Cerebrospinal Fluid Against Toxic Metals. FASEB J., 5(8), 2188-2193.
22
FIGURE LIST Figure 1 Human nasal and olfactory model: (a) upper respiratory airways, olfactory brain pathways, and particle release profile; (b) sample cross section of nasal and olfactory channel; (c) 2D unwrapped nasal cavity surface model. (Brain image: University of Calgary, 2006). Figure 2 Computational mesh with polyhedron meshing scheme. Figure 3 Brownian diffusion validation testing in a pipe geometry. Figure 4 Stream-wise and axial air flow pattern in the nasal and olfactory airways at selected locations. Figure 5 Wall shear stress on nasal and olfactory surface at breathing rate of 5 L/min: (a) 3D model; (b) 2D unwrapped surface model. Figure 6 Particle flux at cross sections of the nostril, nasal valve, main channel (incorporating anterior/posterior nasal olfactory), and posterior naris at the breathing rate of 5L/min. Particle diameters are: (a) 1 nm; (b) 2 nm; (c) 10 nm. Figure 7 Particle deposition pattern in nasal cavity and olfactory at 5L/min. Particle diameters are: (a) 1nm; (b) 2 nm; (c) 10 nm. Figure 8 Particle deposition efficiency in the nasal cavity: (a) against particle size; (b) against D0.589/Q0.494. Figure 9 Particle deposition efficiency in human olfactory mucosa: (a) against particle size; (b) against D0.589/Q0.494. Figure 10 Evolution of olfactory deposited particle profile at nostrils and nasal valves at breathing rate of 5 L/min: (a) 1 nm at nostrils; (b) 2 nm at nostrils; (c) 10 nm at nostrils; (d) 1 nm at nasal valves; (e) 2 nm at nasal vales; (f) 10 nm at nasal valves.
23
Highlights
Human olfactory deposition of inhaled nanoparticles is computational simulated. Airflow and particle flux to olfactory deposition was visualized and discussed. Distinctive deposition variations were identified in olfactory and nasal cavity. Unique entrance profile for olfactory deposited particles was revealed.
b
a
olfactory
meatus
septum
c
vestibule
olfactory lateral side (right)
septal side
nasopharynx
lateral side (left)
Figure 1. Human nasal and olfactory model: (a) upper respiratory airways, olfactory brain pathways, and particle release profile; (b) sample cross section of nasal and olfactory channel; (c) 2D unwrapped nasal cavity surface model. (Brain image: University of Calgary, 2006).
24
Figure 2. Computational mesh with polyhedron meshing scheme.
c
b a
Figure 3. Brownian diffusion validation testing in a pipe geometry.
25
a
b nasal lateral side (right)
Wall shear stress (Pa) 0.10
0
2D
3D
0.05
nasal olfactory
vestibule
septal side
nasopharynx
5 L/min nasal lateral side (left)
Figure 5. Wall shear stress on nasal and olfactory surface at breathing rate of 5 L/min: (a) 3D model; (b) 2D unwrapped surface model. a Particle flux 0.04
b
c
5 L/min 1 nm
5 L/min 10 nm
5 L/min 2 nm
0.02
0
Figure 6. Particle flux at cross sections of the nostril, nasal valve, main channel (incorporating anterior/posterior nasal olfactory), and posterior naris at the breathing rate of 5L/min. Particle diameters are: (a) 1 nm; (b) 2 nm; (c) 10 nm. a
b
c
right
5 L/min 1 nm
5 L/min 2 nm
left
26
5 L/min 10 nm
Figure 7. Particle deposition pattern in nasal cavity and olfactory at 5L/min. Particle diameters are: (a) 1nm; (b) 2 nm; (c) 10 nm.
Figure 8. Particle deposition efficiency in the nasal cavity: (a) against particle size; (b) against D0.589/Q0.494.
Figure 9. Particle deposition efficiency in human olfactory mucosa: (a) against particle size; (b) against D0.589/Q0.494.
27
a
b 5 L/min 1 nm
c 5 L/min 2 nm
5 L/min 10 nm
Nostrils
right
left f
e
d 5 L/min 1 nm
5 L/min 2 nm
5 L/min 10 nm
Nasal Valves
Figure 10. Evolution of olfactory deposited particle profile at nostrils and nasal valves at breathing rate of 5 L/min: (a) 1 nm at nostrils; (b) 2 nm at nostrils; (c) 10 nm at nostrils; (d) 1 nm at nasal valves; (e) 2 nm at nasal vales; (f) 10 nm at nasal valves.
28
PII: DOI: Reference:
S0021-8502(17)30224-0 http://dx.doi.org/10.1016/j.jaerosci.2017.08.006 AS5167
To appear in: Journal of Aerosol Science Received date: 20 June 2017 Revised date: 14 August 2017 Accepted date: 18 August 2017 Cite this article as: Lin Tian, Yidan Shang, Jingliang Dong, Kiao Inthavong and Jiyuan Tu, Human Nasal Olfactory Deposition of Inhaled Nanoparticles at Low to Moderate Breathing Rate, Journal of Aerosol Science, http://dx.doi.org/10.1016/j.jaerosci.2017.08.006 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Human Nasal Olfactory Deposition of Inhaled Nanoparticles at Low to Moderate Breathing Rate
Lin Tiana, Yidan Shanga, Jingliang Donga, Kiao Inthavonga, Kiao Inthavonga, Jiyuan Tua* a
School of Engineering – Mechanical and Automative, RMIT University, Bundoora, VIC, Australia b Key Laboratory of Ministry of Education for Advanced Reactor Engineering and Safety, Institute of Nuclear and New Energy Technology, Tsinghua University, PO Box 1021, Beijing, China *
Corresponding author. [email protected]
ABSTRACT Olfactory pathway, susceptible for direct translocation of inhaled nanoparticles into the brain, has been verified in a number of animal studies over past decades. In case of toxic substances, the extremely low dose strongly suggests a subclinical condition that prevents noticeable neurodegeneration until years after prolonged exposure. The exact mechanism, between elevated presence of toxic substances (e.g. heavy metals) and deteriorated neurofunction in human central nervous system, is still not clear; however, nasal olfactory, being portal of the entry for such a transport route, is undoubtedly a critical junction where hint to the time course and dose dependency might be inferred. Using a physiologically realistic nasal and upper airway replica, this study performed human inhalation simulations of nanoparticles (1 to 100 nm) under low to moderate breathing conditions (5 to 14 L/min). Emphasis is on olfactory deposition and the various factors contributing to the process. Details on airflow pattern and particle flux in nasal and olfactory were made visible through a 2D unwrapped surface mapping technique, and it was found out that airflow pattern, especially nasal wall shear had a remarkable correlation to particle movement and deposition at the ultrafine scale (< 1~2 nm). Olfactory deposition efficiency was found to be extremely low (< 3.5%), and showed distinctive variation in high diffusivity region when compared to that in the entire nasal cavity. The entrance profile of olfactory deposited particles was seen to be highly selective and unanimously originated from upper section of the nostril near nasal septum. Current study is of significant value to the understanding of human uptake of inhaled nanoparticles through olfactory pathway.
Keywords: Inhalation toxicity, neurotoxicity, nanoparticles, nasal olfactory, olfactory pathway, olfactory deposition
2
1. INTRODUCTION Olfactory pathway has been suspected to play a vital role in brain uptake of neuro toxics (such as heavy metals) which is linked to the chronic neurodegeneration in human central nervous system. This is supported by growing evidence of restricted admittance of such substances via blood-brain barrier, once considered as the primary uptaking route. Animal study of Zheng et al. (1991) in rats and rabbits demonstrated that the choroid plexus of the blood-brain barrier effectively sequester heavy metal toxicants (e.g. cadmium, lead, mercury, and arsenic) thus protecting the brain from accumulating such substances. Similar observation was reported by Ingersoll et al. (1995) where restricted penetration of manganese into rat cerebrospinal fluid (CSF) was rendered by effective sequestration through lateral choroid plexus of the blood–CSF barrier. These barriers act as highly selective filtration system to protect the microenvironment of the brain from foreign substances. Olfactory pathway, on the other hand, bypasses the protective blood-brain barrier and facilitates translocation of inhaled nanoparticles through olfactory nerve system leading to the accumulation of brain toxicants.
A landmark evidence of olfactory pathway as a viable transport route of inhaled nanoparticles into the brain was reported by De Lorenzo et al. (1970). In their experiment, intranasally instilled colloidal gold particles (50 nm) in squirrel monkeys were observed to translocate anterogradely in axons of the olfactory nerves and reach olfactory bulbs. A neuronal transport velocity of 2.5 mm/h was obtained based on the measurement. Clear evidence was also demonstrated by Gianutsos et al. (1997) that, following the unilateral intranasal instillation of manganese chloride in the right nostril of the rats, elevated levels of manganese were detected in the right olfactory bulb and olfactory tubercle while no changes were detected on the left side of the brain. The affected brain manganese levels were shown to be dose and time dependent. In addition, manganese content of the striatum, the targeted site for manganese neurotoxicity, was unchanged following acute administration; however was elevated when repeated injections were made during prolonged time course. These results not only suggested that air-borne manganese can be transported along olfactory neurons, but also implied that long term accumulation of neuron toxicants at targeted site might have profound implication towards chronic neurodegeneration in the central nervous system. Oberdorster et al. (2004) performed rats inhalation study by whole body exposure to carbon nanoparticles (36 nm) suspended in a confined compartment. 3
Translocation of inhaled nanoparticles to targeted sites (lung, cerebrum, Cerebellum and olfactory bulbs) via respiratory and various neuron routes were examined. The study found out that central nervous system can be targeted by airborne solid ultrafine particles, and the most likely mechanism is from deposits on olfactory mucosa (of nasopharyngeal region from respiratory tract) and subsequent translocation via the olfactory nerve. An estimated 20% of deposited ultrafine particles on olfactory mucosa can be translocated to the olfactory bulb. Uptake of manganese, cadmium, nickel, mercury and cobalt nanomaterial via rats olfactory pathways were also reported in the work of Tjälve et al. (1996), Henriksson et al. (1997, 1998), and Persson et al. (2003).
While limited data is available in human subject, olfactory pathway is considered a functional route for brain uptake of inhaled nanoparticles across different species. This is supported by assessment of Shiga et al. (2010) on healthy volunteer human subjects that, appreciable movement of thallium to the olfactory bulb was observed following nasal administration using single photon emission computed tomography (SPECT), X-ray computed tomography (CT), and MRI. The transport kinetic properties were shown to be consistent with delivery route via olfactory nerves, and agree with the observation in rodent studies (Kanayama et al., 2005). Similar conclusion was attained by Sen et al. (2011) where manganese accumulation (from welding fumes) in different brain regions was investigated by comparing the MRI and neuron functional tests between seasoned welders and controls. The findings support the hypothesis that olfactory nerve might be a viable transport route in human, and accumulation of the inhaled nanoparticles at olfactory bulb might lead to further translocation into the brain. Accumulation of inhaled submicron manganese particles in the olfactory bulb of nonhuman primates following aerosolized MnSO4 exposure was also reported in the work of Dorman et al. (2006ab). The exact mechanism, between elevated presence of toxic substances (e.g. heavy metals) and deteriorated neurofunction in human central nervous system, is still not clear; however, nasal olfactory, being portal of the entry for such a transport route, is undoubtedly a critical junction where hint to the time course and dose dependency might be inferred. Due to technical difficulty, quantitative measures of nanoparticle deposition onto nasal olfactory mucosa are not available in either animal or human studies, and quantitative assessments were only provided by very few 4
computational studies. Garcia and Kimbell (2009) were the first to propose a rat olfactory deposition equation based on computational investigation of inhaled nanoparticles (1 to 100 nm). According to the study, olfactory dose was predicted to be the highest for 3 to 4 nm particles, with approximately 6 to 9% deposited onto the olfactory epithelium. Similar approach was applied in human nasal cavity models (Garcia et al., 2015), and for breathing rates of 15 to 30 L/min, human olfactory deposition was shown to reach the maximum of 1% for 1-2 nm particles. Taking into account of the higher minute volume, olfactory dose per unit surface area was found to be greater in human than in rat (1-10 nm). Shang et al. (2015) and Dong et al. (2016) did comparative study of micron and nanoparticle deposition in human and rat nasal cavities, where deposition flux and intensity were obtained for various nasal sections including olfactory. It was found out that both the deposition pattern and flux onto the nasal olfactory varied significantly between human and rat models, and interspecies extrapolating schemes were proposed.
In this study, inhalation simulations of nanoparticles (1 to 100 nm) under low to moderate breathing conditions (5 to 14 L/min) were performed in a physiologically realistic human nasal and upper airway replica. The simulation emphasized on olfactory deposition and the various factors contributing to the process, which are lacking in current literature. Details on airflow pattern and particle flux in nasal and olfactory were made visible through a 2D unwrapped surface mapping technique (Inthavong et al., 2014), and it was found out that airflow pattern, especially nasal wall shear had a remarkable correlation to particle movement and deposition at the ultrafine scale (< 1~2 nm). Olfactory deposition efficiency was found to be extremely low (< 3.5%), and showed distinctive variation in high diffusivity region when compared to that in the entire nasal cavity. The entrance profile of olfactory deposited particles was seen to be highly selective and unanimously originated from upper section of the nostril near nasal septum. Current study is of significant value to the understanding of human uptake of inhaled nanoparticles through olfactory pathway.
2. METHOD 2.1 Human Nasal and Olfactory Airway Modeling A CFD model of the upper respiratory airway containing facial features, the nasal cavity, larynx, and the trachea was developed from CT scans (Shang et al. 2015) (Figure 1a). Each model of the 5
respiratory airway was connected to form a contiguous path via nostrils, from the external space to the end of the larynx region. The larynx region was extended to the trachea to allow sufficient flow recovery and improve numerical convergence in the CFD solution. The respiratory airway was added to a realistic human face exposed to the external surroundings containing airborne particles from the ambient environment. Details for model reconstruction and verification can be found in the work of Inthavong et al., 2012.
Human nasal olfactory was located at roof of the nasal cavity (Figure 1a), which has a surface area of 2097 mm2 and occupies 10.5% of the total nasal cavity (Shang el al., 2015). Olfactory channel (Figure 1b) was 1-2 mm wide, with inner layer covered by olfactory mucosa and connected to olfactory bulb through receptor neurons. As the interface between external airway and the brain, olfactory mucosa is considered the entry point for inhaled nanoparticles to get translocated into the brain. A 2D unwrapped nasal cavity model, showing details of the relative position and surface feature for human olfactory mucosa, was displayed in Figure 1c. The model was first sliced along the centerline of the nasal passage floor, where lateral and septal walls met. Then the 3D surface coordinates were transformed into a new set of 2D coordinates, mimicking the surfaces being unfurled. Layout of the top and bottom boundaries represents the initial centerline (sliced along the nasal floor), while left and the right boundaries represent the nostril and nasopharynx respectively. Details of surface-mapping technique to transform nasal cavity morphology from 3D onto a planar 2D domain can be found in the work of Inthavong et al., 2014.
2.2 Computational Mesh Fluent Meshing (ANSYS 18.0) was used to generate the computational mesh (Figure 2). A new polyhedron scheme was employed and shown to be computational efficient, numerical accurate, and generate solution with superior converging capabilities. Polyhedron elements with minimum cell dimension of 1 mm filled the main airway passage and maximum cell dimension of 10 mm filled the external domain, while a highly dense prism layer of hexahedron elements in normal direction of the wall was attached to resolve near wall features. The 5 prism layers evolved from the first grid point with cell dimension of 0.05 mm to the core region with a growing factor 1.2.
6
The resulting mesh consisted of 1,237,634 elements. Mesh independency was conducted and achieved at the specified size.
2.3 Fluid Flow Simulation Current study employed a steady inhalation model with the assumption that particle deposition mainly occurs during the inhalation phase (Inthavong et al., 2010). It is worth to note that breathing pattern was shown to affect deposition for micron range particles between 1 and 5 µm (Häuβermann et al., 2002), however, the effect toward nanoparticle deposition was still not fully understood. Sedentary breathing (4 to 14 L/min) was assumed indicating laminar flow condition.
Airflow was simulated using ANSYS-FLUENT18.0. The surrounding walls were set to atmospheric pressure and inhalation was initiated by a negative pressure difference at the bronchial bifurcation outlet. This allowed the ambient flow field to be influenced only by the inhaled air. The continuity and momentum equation of the fluid flow are: ui 0 , xi
uj
ui p x j xi x j
(1)
ui . x j
(2)
where ρ, u and p are density, velocity and pressure of the air, respectively. A second order upwind scheme was used to approximate the momentum equation, while the pressure-velocity coupling was handled through the SIMPLE method. Further detail of the fluid flow modeling was given in Wen et al. (2008).
2.4 Particle Simulation Lagrangian particle tracking method is used where individual particle trajectory is computed. The particle equation is:
du p dt
g ( p ) 1 FD FL FB Cc p
(3)
here up is the particle velocity, t is the time, g is the gravitational constant, ρp is the particle density. In this study, both gravitational and buoyancy forces can be neglected. FD is the drag 7
force given by 18µ(up-u)/( d2ρp), with d being the particle diameter, and Cc the Cunningham correction given by: Cc 1
2 (1.257 0.4e( 1.1d d
/2 )
),
(4)
here λ is the molecular mean free path. FL in Equation (3) is the Saffman lift force, and FB is the Brownian diffusion force with amplitude of S0 / t /. ς is a zero mean, unit variance independent Gaussian random numbers. ∆t is the time-step for particle integration and So is a spectral intensity function (Li and Ahmadi, 1992): : So
216 kT 2 d 5 p Cc 2
.
(5)
ν is the fluid kinematic viscosity, k is the Boltzmann constant, and T is the absolute temperature of the inspiratory air in the nasal cavity. The simulation was carried out with ANSYSFLUENT18.0 discrete phase model (DPM).
Shang et al. (2015) showed that the airflow has negligible influence on particle trajectory outside the breathing zone. In this study, particles were uniformly released on a hemisphere (of radius 3 cm) with the center at the nose tip (Figure 2), resembling the release condition of Doorly et al. (2008). Statistically independent 100,000 uniform concentrated mono-dispersed ultrafine particles of 1, 1.1, 1.2, 1.3, 1.4, 1.5, 1.7, 2, 3, 5, 10, 15, 20, 30, 40, 50, 70 and 100 nm, were released. Deposition onto the respiratory walls occurred when the particle was within radius distance away from the surface.
2.5 Particle Flux To visualize particle spatial distribution across nasal airway passage, particle flux (f) is defined as the number of particles passing through per unit area of nasal cross sections along the transport route. f is normalized with the total number of particles entering nasal cavity, therefore, being 1.0 at the nostril. An evolving spatial distribution could shed light on particle bulk
8
movement and the consequence to olfactory deposition. Decreasing particle flux is anticipated as particles continue to be deposited along the transport route. Accordingly,
f(r)
# particles per unit cross sectional area # particles entering nasal cavity
f(r)dA 1.0 , and
f(r)dA 1.0
on subsequent cross sections.
(7)
(8)
Nostril
r is the position vector on cross sections with area element being dA in above equations.
2.6 Deposition Efficiency Particle deposition efficiency (DE) is defined as the ratio of the deposited particles in a region to the total number entering nasal cavity. That is:
DE
#deposited particles #particles entering the nasal cavity
(6)
It is an important parameter characterizing the regional filtering capacity and particle penetration rate. Deposition efficiency (DE) is closely related to the transport mechanisms and for nanoparticles, size, diffusivity and airflow rate are the governing parameters. Due to the geometric complexity of human airways, no analytical expression is available for deposition efficiency (DE). Frequently, empirical fitted equations are used to relate measured data (DE) to the governing parameters.
2.7 Model Validation The particle equation (3) was solved by stepwise integration over discrete time steps yielding a new particle velocity at each time step. Inthavong et al. (2016) identified the sensitivity of nanoparticle diffusion behavior (in Lagrangian tracking) to the integral time step factor, mesh size and flow condition. The evaluation was based on selecting the most appropriate time step factors to achieve optimal Lagrangian tracking outcome was proposed and verified in a pipe and a human pharynx model (Inthavong et al., 2016).
In ANSYS-FLUENT, the length scale factor of integration, Ls controls the integration time step size and Δt is a function of the particle velocity and the continuous airflow phase velocity: 9
t
Ls up u
(9)
This means that the length scale factor is proportional to the integration time step, which is the distance that the particle travels before its equations are solved again and its trajectory updated. A smaller value for the length scale increases the number of calculations per step length. Its selection must reproduce the diffusion dispersion mechanism for nanoparticles (Inthavong et al., 2016). A standard geometry in the form of a pipe (Figure 3a) with analytical solution by Ingham (1975) was used to validate the particle dispersion. A fully developed flow of 1 L/min and 5 L/min was used which has a corresponding Re = 312, and Re = 1560 respectively. The particles were introduced into the pipe with a mass flow rate distributed with a fully developed profile as:
r2 m(r ) m0 1 2 R
(10)
where m0 is the maximum mass flow rate at the pipe centerline, r is the radial position from the pipe centerline, and R is the pipe radius. Particle deposition in the pipe over a distance of 0.09m was compared with the deposition efficiency (DE) correlation by Ingham (1975).
DE 1 0.819e14.63 0.0976e89.22 0.0325e228 0.0509e125.9 2/3
(11)
where
DLpipe 4U inlet R
(12) 2
Particle deposition in a pipe length of 0.9 m was compared for length scale factors of 5e-5 m, 1e5 m, and 5e-6 m, which showed that the deposition was best described using a value of 1e-5 m. Applying the method to the current model in this study showed that an optimal value of 2e-5 m. Further detail of the methodology was given in (Inthavong et al., 2016).
3. RESULTS AND DISCUSSION 3.1 Breathing Airflow Pattern Low to moderate breathing at flow rates of 5 to 14 L/min was included in the simulation. Key features of the airflow pattern were similar, conforming to the geometric details of the airway. Figure 4 displayed the stream-wise and axial airflow pattern at breathing rate of 5 L/min in the 10
nasal and upper airways at selected locations. Ambient air entered the nostril in an upward direction, and turned 90o entering the middle and inferior nasal meatus before a second 90o at the posterior nasopharynx. High velocity was observed at the nostril entrance, downstream of the nasal valve and at the larynx. Bulk air passed through the middle and inferior meatus, whereas the superior meatus, where the olfactory region was located, had very low velocity air passing through.
The inhaled airborne particles were transported by the moving fluid and regions with higher velocity implied high particle concentrations. As implied, major air conducting sections (middle and inferior meatus) had significantly higher particle exposure than nasal olfactory. Compared to substantial airflow changes in major nasal channels induced by sharp turn, sudden shrink or expansion of the cross sectional area, airflow in olfactory region was sedentary and free of these changes. Also noted was the asymmetric cross section between left and right nasal passages which is common in human, with the right carrying larger volume of airflow owing to less resistance.
3.2 Wall Shear Stress Figure 5 displayed the wall shear stress on nasal and olfactory surface at the breathing rate of 5 L/min. Stress pattern on both the 3D and 2D unwrapped model were plotted for comparison. Strong localized high shear were observed on nasal anterior before the 90o turn, and in posterior nasal cavity following the second 90o turn. It was shown in Figure 5 that, nasal mucosa on the right passage experienced noticeable greater stress concentrated on vestibule and anterior of main nasal airway. On the other hand, a less prominent but more uniform stress pattern was shown on the left airway with friction appeared to be smeared out across the channel surface. Two sedentary airflow pockets with extremely low wall shear were observed near lateral border and in nasal olfactory in the right cavity. This was not observed in the left cavity. Averaged wall shear on the left nasal olfactory mucosa was about three times larger than that on the right, being 0.009 and 0.003 Pa respectively.
Wall shear distribution could well indicate the level of secondary flow and forming of local eddies contributing to enhancement of the particle deposition. Clearly shown in Figure 5ab, 2D 11
unwrapped surface mapping provided considerably more information than that of the 3D presentation, pushing forward our understanding of the particle transport process in nasal cavity.
3.3 Particle Flux and Spatial Distribution Figure 6 displayed the particle flux (1, 2 and 10 nm at 5 L/min) at cross sections of the nostril, nasal valve, main channel (anterior/posterior nasal olfactory), and posterior naris where the pair of nasal apertures merge into nasopharynx (Figure 4). A clear preferential particle distribution was observed at nostrils and nasal valves where significantly higher particle concentration was seen near nose tip and upper section of the openings. This is due to flow acceleration and momentum gain for both airflow and particles in vicinity of the nostril; however, concavely located floor of the opening are more likely to be shielded from impinging flow and particles by bottom of the facial features (Figure 4). This preferential particle distribution was seen to penetrate through nasal vestibule, and vanish when reaching mid channels where particle movement was more affected by local environment in the main nasal cavity (Figure 6). Midchannel particle concentration clearly conformed to the flow pattern (Figure 4) with middle and inferior meatus (septal side) saw significantly higher particle flux. For the same reason, particle concentration was significantly higher in the right channel than that in the left. Minimum particle flux was seen in nasal olfactory and the lateral scroll end of the channel floor. It was also noted a decreasing particle flux in the nasal passage as continuous deposition occurred along the transport route.
Particle size was clearly seen to affect particle flux and spatial distribution (Figure 6). Larger sized nanoparticles exhibited stronger preferential concentration when entering the nose while smaller sizes were relatively more uniformly distributed. This was consistently observed in mid and posterior nasal channels however with varying degrees. In addition, lower particle flux was seen with smaller sized particles. This is especially prominent in nasal olfactory where the number of 1 nm particles passing through the region was significantly lower than that of the 10 nm particles. These phenomena were largely related to molecular diffusivity, a fundamental mobility property inversely related to the particle size. That is, smaller size implies higher diffusivity and more likelihood to be dispersed uniformly, or travel a further distance to get lost
12
at the wall. Prior loss to airway surfaces might contribute to the extremely low level of particle flux observed in olfactory as seen for the 1 and 2 nm particles (Figure 6ab).
The evolving particle bulk movement in response to the combined transport mechanisms in nasal channel could very well shed light on olfactory deposition. It was clearly seen in Figure 6 that olfactory cavity was not in favor of hosting inhaled nanoparticles, and only a minimum succeeded arriving there. This is especially prominent for smaller sized particles such as 1 and 2 nm as shown in Figure 6ab. The phenomenon markedly correlated to olfactory sensory physiology where as few as one odor-biding molecule was probably sufficient to activate sensing (Neuhaus, 1953). Smelling through human olfactory mucosa, which was immersed in extreme sedentary flow with minimum shear, was clearly more related to the Brownian diffusional motion. Particle flux and spatial distribution in human nasal olfactory (Figure 6) may imply an extremely low deposition probability for all sizes onto the olfactory mucosa, as indicated by admission of particles either: 1) in low quantity with higher diffusivity (Figure 6ab); or 2) in higher quantity but low diffusivity (Figure 6c).
3.4 Particle Deposition Pattern Figure 7 showed sample deposition pattern of the inhaled nanoparticles (1, 2 and 10 nm) onto nasal cavity at a breathing rate of 5 L/min. Data mapping onto the unwrapped 2D surface were applied and presented for superior visualization throughout the highly overlapped nasal surface. Particles deposited onto nasal olfactory mucosa were marked in blue while the rest in red. Clearly shown in Figure 7, particle deposition pattern was highly affected by particle size, with high diffusivity particles (such as 1 and 2 nm in Figure 7ab) significantly more likely to be collected. Particles showed preferential deposition sites which were nasal vestibule, anterior septum, and posterior nasal cavity in the converging section of nasopharynx. In main nasal channels, majority of the deposition occurred in middle meatus, with a small fraction scattered across superior meatus (olfactory region) and the channel floor. High level of inhomogeneity was observed with smaller sized particles (1 and 2 nm, Figure 7ab). As the particle size increased, deposition tended to be more homogeneously distributed. The deposition patterns in left and right nasal cavities were not symmetric, with the right appeared to capture more (in middle meatus) and the left being more uniformly distributed. 13
Located at the ceiling, nasal olfactory mucosa was clearly an elusive spot where only a minimum of the inhaled nanoparticles found the way (blue in Figure 7). As seen in Figure 7, deposition pattern on olfactory mucosa were quite distinct among the three examined particle sizes (1, 2, and 10 nm at 5 L/min), with maximum deposition occurred for the 2 nm particles (Figure 7b) and noticeable fewer for the 1 and 10 nm ones. Large blank patches free from deposition were clearly shown at roof and olfactory for the 1 nm particles (Figure 7a), while this pattern was fading or completely vanished for the 2 and 10 nm ones (Figure 7bc). For the 1 nm particles, deposition was mostly concentrated surrounding a thin layer of the border on olfactory mucosa, while the 10 nm particle deposition penetrated through and uniformly spread all over the olfactory. Significantly more deposition was observed for the 2 nm particles; however, deposition did not penetrate through, with the inner most olfactory mucosa clearly less deposited. These phenomena implied a strong size dependency on olfactory deposition under coupled effect of varying deposition mechanisms. Similar to the olfactory region, visible void stripes lack of deposition were also observed at sites corresponding to the scroll end of the inferior meatus for 1 and 2 nm particles, with the latter at a lesser extent.
It should be noted that, human olfactory deposition pattern, with the inner most region hard to reach by inhaled nanoparticles, might imply a significant sensitivity to size of the olfactory mucosa. In case of the 1 nm particles as shown in Figure 7a, a slight shrink or increase of the olfactory mucosa area would lead to significant variation, non-proportional to the area alteration, in olfactory particle collection. The sensitivity was seen to decrease as particle size increased, and might be negligible at 10 nm diameter. In the current study, olfactory mucosa occupied 2097 mm2 of the surface area, or about 10.5% of the total nasal cavity.
Comparing Figure 7a with Figure 5, a remarkable correlation between nasal deposition pattern and the wall shear was recognized for the 1 nm sized particles. Nasal surface, with a strong shear (Figure 5a), was clearly linked to the deposition “hot spot” in the vicinity. Strong localized high shear on nasal anterior before the 90o turn, in posterior nasal cavity following the second 90o turn, and in middle meatus of the right main airway, all correlated to extreme depositions in nearby surfaces. A striking similarity of the sporadic and streak patterned wall shear and particle 14
deposition in the left nasal cavity (Figure 5a and 7a) clearly indicated an intrinsic physical connection. Effect of the shear on particle deposition appeared to propagate with the flow to a wider region, implying a time and spatial progression when up-taking this physical disturbance. Not surprisingly, low shear regions such as nasal roof, olfactory, lower meatus all had significant less deposition. When looking at the 2 nm particle deposition pattern (Figure 7b), strong correlation to the shear (Figure 5) was not observed. Rather than a highly concentrated deposition surrounding the high shear region, deposition appeared to be further dispersed to cover a wider area. For the 10 nm particles (Figure 7c), effect of the wall shear on particle deposition was further reduced. Particle deposition appeared to be uniformly scattered across all nasal cavity.
Correlation between nasal wall shear and the particle deposition pattern might very well have revealed the transport and deposition mechanism of nanoparticles in the nasal cavity. High shear implied higher friction and larger secondary flow in vicinity of the airway surface. Smaller particles of 1 nm were clearly more responsive to these changes due to the high intensity of Brownian motion. The delayed or negligible responses of the 2 and 10 nm particles toward the shear induced disturbances were more likely to be attributed to the reduced Brownian intensity, incapable of keeping pace of the flow disturbances in the coupled time and spatial domain.
3.5 Particle Deposition Efficiency Figure 8 displayed the deposition efficiency of the inhaled nanoparticles (1 to 100 nm) in nasal cavity. Simulation results were plotted against particle size for breathing rates of 5, 7, 10 and 14 L/min (Figure 8a). It was clearly shown that total deposition was inversely related to particle size and the breathing rate. Larger particles and higher breathing rate implied lower deposition efficiency. At 1 nm diameter, particle deposition efficiency at the examined flow rates was in the range from 58.3% to 75.2%. It quickly decreased to about 6% when particle size was increased to 10 nm. Beyond 15 nm, particle deposition efficiency was below 5% and approaching 1% at 100 nm diameter. Variation of particle deposition across different flow rates reached the maximum of 16.9% for the 1 nm particles, while a minimum difference of 0.07% was seen for the 100 nm particles, or a decrease of 241 folds.
15
Data correlation identified that the simulated deposition efficiency correlated most efficiently with D0.589/Q0.494, where the simulation data collapsed into a smooth single curve in Figure 8b. Here D is the particle diffusivity in m2/s, and Q is the breathing airflow rate in m3/s. The developed empirical equation was given as: D 17.87 0.494 Q 1 1.0013e 100 0.589
DE nasal
(13)
In Figure 8b, the measured deposition efficiencies from experiments of Kelly et al. (2004), Cheng et al. (1995), and Swift et al. (1992) were plotted for comparison. These experiments were performed on nanoparticles of 0.58 to 155 nm at low to moderate breathing conditions (4 to 12 L/min). It was shown in Figure 8b that simulation agreed reasonable well with the experimental results in trend and magnitude. Simulation most closely resembled the measurements from Cheng et al. (1995) for larger particles at low deposition side, while the simulated data matched well with the measured deposition efficiency of Swift et al. (1992) for high diffusivity particles. Simulation results generally followed the lower bound of measurements from Kelly et al. (2004). Data scattering were observed in all experiments, however within tolerance, due to noise and high sensitivity of the measurements. Prior simulation of Garcia et al. (2015) on human nasal nanoparticle deposition was also included in Figure 8b for comparison. It agreed well with current simulation and a slightly higher prediction was seen in high diffusivity region due to variation in testing subjects and simulation conditions.
Figure 9 displayed the human olfactory deposition efficiency of inhaled nanoparticles in the range from 1 to 100 nm at breathing rates of 5, 7, 10 and 14 L/min. As shown in Figure 9a, olfactory deposition had quite distinctive characteristics in high diffusivity region when compared to the nasal deposition (Figure 8a). Rather than negative impact, higher breathing rates were seen to enhance deposition for particles below 2.5 nm. Furthermore, deposition appeared to increase together with the particle size until a flow dependent peak value was reached. Particle sizes corresponding to the peak deposition were seen to shift toward the lower end as the breathing rate was increased. Based on the simulation, peak deposition occurred at 1.7, 1.5, 1.3 and 1.2 nm at breathing rates of 5, 7, 10 and 14 L/min respectively. Deposition characteristics in human olfactory were shown to be similar to that in the nasal cavity (Figure 8a) for particles 16
greater than 3 nm. Overall, human olfactory deposition was extremely low in all cases considered (< 3.5%).
Similar to Figure 8b, Figure 9 presented the human olfactory deposition efficiency against D0.589/Q0.494, which was shown to collapse nasal deposition data concisely. As expected, low diffusivity particles corresponded well with the correlation, however, large discrepancies were observed for high diffusivity particles. Clearly, more factors played the role and olfactory deposition cannot be efficiently described in a similar manner as that in the nasal cavity. Simulation result from Garcia et al. (2015) on human nasal olfactory deposition was plotted in Figure 8b for comparison, where similar trend and variation, however, noticeable difference for high diffusivity particles were observed. This was not surprising considering the high sensitivity of human olfactory deposition on olfactory surface area, particularly for high diffusivity particles as discussed in Figure 7. For the same reason, 3 models with varying olfactory sizes were considered in the work of Garcia et al. (2015), and fitting was provided on Model 1A (surface area of 11.2 cm2 or 5.5% of the nasal cavity) about half the size of the current olfactory model (Figure 1). Considering these variations, current simulation and the prediction of Garcia et al. (2015) showed excellent agreement. Due to complexity in experimental procedures, there has been no quantitative report on measurement of nanoparticle deposition onto human olfactory mucosa.
In summary, nanoparticle (1 to 100 nm) collection by human olfactory mucosa was extremely low, with the highest deposition (< 3.5%) seen for high diffusivity particles around 1.5 nm. As particles grew in size, human olfactory deposition was steadily decreasing to about 1% around 100 nm. Breathing rate might have a positive impact in the high diffusivity region; however, it was seen to negatively impact the deposition for low diffusivity particles. Human olfactory deposition efficiency cannot be characterized by Da/Qb with a and b being coefficients, an approach frequently used in nasal deposition study. More factors need to be included and further research is needed.
3.6 Entrance Profile of Olfactory Deposited Particles
17
Olfactory deposited particle profile at nostrils and nasal valves at the breathing rate of 5 L/min were given in Figure 10. Inhaled nanoparticles eventually deposited onto the olfactory region were plotted in blue while the rest in gray. It was clearly shown in the figure that olfactory deposition originated from the nose tip in septal side, and these particles were further pushed toward the ceiling when traveled to the nasal valves. Entrance profile of olfactory deposited particles appeared to be relatively scattered for the 1 nm size, while it was highly selective and concentrated in narrow bands for the 10 nm particles. None of the nanoparticles inhaled via lower half of the nostrils was collected by human olfactory mucosa. The information is of significant value to understand human olfactory uptake of inhaled nanoparticles.
4. CONCLUSIONS Inhalation simulations of nanoparticles (1 to 100 nm) under low to moderate breathing conditions (5 to 14 L/min) were performed in a physiologically realistic human nasal and upper airway replica. Emphasis was on olfactory deposition and the various factors contributing to the process and outcome. Details on the airflow pattern and particle flux in nasal and olfactory were revealed through 2D unwrapped surface mapping. Base on the study, following conclusions were drawn. A remarkable correlation between nasal wall shear and particle deposition pattern was identified at the ultrafine scale (< 1~2 nm). Nasal surface, with a strong shear (Figure 5a), was clearly linked to deposition “hot spot”, while low shear region, including nasal olfactory, had significant less deposition. Immersed in extreme sedentary flow with minimum shear, olfactory deposition was found to be extremely low (< 3.5%), and clearly more related to the Brownian diffusional motion. This phenomenon markedly correlated to olfactory sensory physiology where as few as one odor-biding molecule was probably sufficient to activate sensing. Olfactory deposition showed quite distinctive variation in the high diffusivity region (< ~2 nm) when compared to that in the entire nasal cavity; they are: 1) deposition increased with particle size; 2) higher breathing rate enhanced the deposition; 3) peak deposition was flow 18
rate dependent and peak particle size (~1.5 nm) was negatively impacted by the breathing rate. Beyond peak deposition, particle collection rate in nasal olfactory was steadily decreased as particle size increased, and reached about 1% at 100 nm. Breathing rate was seen to negatively impact the deposition efficiency. Human olfactory deposition efficiency was highly sensitive to olfactory size, especially for nanoparticles at the lower end. For smaller particles of 1-2 nm, deposition was mostly concentrated surrounding a thin layer of the border on olfactory mucosa, while for larger particles deposition was more uniformly spread over the entire region.
The entrance profile of olfactory deposited particles was seen to be highly selective and
unanimously originated from upper section of the nostril near nasal septum. None of the nanoparticles inhaled via lower half of the nostrils was collected by human olfactory mucosa. Human olfactory deposition efficiency cannot be characterized by Da/Qb (a and b being the coefficients), a parameter frequently used in the nasal deposition study. More factors need to be included and further research is needed.
5. ACKNOWLEDGEMENTS The financial supports provided by the National Natural Science Foundation of China (Grant No. 91643102) and the Australian Research Council (Grant No. DP160101953) are gratefully acknowledged.
6. REFERENCES Cheng, KH, Cheng, YS, Yeh, HC, & Swift, D. (1995). Deposition of Ultrafine Aerosols in the Head Airways during Natural Breathing and during Simulated Breath Holding Using Replicate Human Upper Airway Casts, Aerosol Sci. Technol., 23, 465–474. De Lorenzo, A.J.D. (1970). The Olfactory Neuron And The Blood-Brain Barrier. In Taste and Smell in Vertebrates; Wolstenholme, GEW, Knight, J, Eds.; J. & A. Churchill: London, UK, 151–176. 19
Doorly, D.J., Taylor, D.J., & Schroter, R.C. (2008). Mechanics of Airflow in the Human Nasal Airways, Respiratory Physiology & Neurobiology, 163, 100–110. Dong, JL, Shang, YD, Inthavong, K., Tu, JY, Chen, R, Bai, R, Wang, DL, & Chen, CY (2016). Comparative Numerical Modeling of Inhaled Nanoparticle Deposition in Human and Rat Nasal, 152(2), 284-296. Dorman, D.C., Struve, M.F., Marshall, M.W., Parkinson, C.U., James, R.A., & Wong, B.A. (2006a). Tissue Manganese Concentrations in Young Male Rhesus Monkeys Following Subchronic Manganese Sulfate Inhalation, Toxicol Sci., 92(1), 201-210. Dorman, D.C., Struve, M.F., Wong B.A., Dye J.A., & Robertson I.D. (2006b). Correlation of Brain Magnetic Resonance Imaging Changes with Pallidal Manganese Concentrations in Rhesus Monkeys Following Subchronic Manganese Inhalation, Toxicol Sci., 92(1), 219227. Garcia, G.J.M., & Kimbell, J.S. (2009). Deposition of Inhaled Nanoparticles in the Rat Nasal Passages: Dose to the Olfactory Region, Inhalation Toxicology, 21(14), 1165-1175. Garcia, G.J.M., Schroeter, J.D., & Kimbell, J.S. (2015). Olfactory Deposition of Inhaled Nanoparticles in Humans, Inhalation Toxicology, 27(8), 394-403. Gianutsos, G., Morrow, G.R., & Morris, J.B. (1997). Accumulation of Manganese in Rat Brain Following Intranasal Administration, Toxicological Sciences, 37(2), 102-105. Häuβermann, S., Bailey, A.G., Bailey, M.R., Etherington, G., & Youngman, M. (2002). The Influence of Breathing Patterns on Particle Deposition in a Nasal Replica Cast. Journal of Aerosol Science, 33, 923-933. Henriksson, J., Tallkvist, J., & Tjälve, H. (1997). Uptake of Nickel Into the Brain via Olfactory Neurons in Rats, Toxicology Letters, 91, 153-162. Henriksson, J., & Tjälve, H. (1998). Uptake of Inorganic Mercury in the Olfactory Bulbs via Olfactory Pathways in Rats, Environmental Research, Section A, 77, 130-140. Ingersoll, R.T., Montgomery Jr, E.B., & Aposhian, H.V. (1995). Central Nervous System Toxicity Of Manganese. I. Inhibition Of Spontaneous Motor Activity In Rats After Intrathecal Administration Of Manganese Chloride. Toxicological Sciences, 27(1), 106113. Ingham, D.B. (1975). Diffusion of Aerosols from a Stream Flowing through a Cylindrical Tube. Journal of Aerosol Science, 6(2), 125-132. 20
Inthavong, K, Choi, L., Tu, JY, Ding, S., & Thien, F. (2010). Micron Particle Deposition in a Tracheobronchial Airway Model under Different Breathing Conditions. Medical Engineering & Physics, 32(10), 1198-1212. Inthavong, K., Ge, Q. J., Li, X. D., & Tu, J. Y. (2012). Detailed predictions of particle aspiration affected by respiratory inhalation and airflow. Atmospheric Environment, 62(0), 107117. Inthavong, K, Shang, YD, & Tu, JY. (2014). Surface Mapping for Visualization of Wall Stresses during Inhalation in a Human Nasal Cavity. Respiratory physiology & neurobiology, 190, 54-61. Inthavong, K, Tian, L., & Tu, JY (2016). Lagrangian Particle Modelling of Spherical Nanoparticle Dispersion and Deposition in Confined Flows, Journal of Aerosol Science, 96, 56-68. Kanayama, Y., Enomoto, S., Irie, T., & Amano, R. (2005). Axonal Transport of Rubidium and Thallium in the Olfactory Nerve of Mice, Nucl Med Biol., 32(5), 505-512. Kelly, J.T., Asgharian, B., Kimbell, J.S., & Wong, B. (2004). Particle Deposition in Human Nasal Airway Replicas Manufactured by Different Methods. Part II: Ultrafine Particles, Aerosol Sci. Technol., 38, 1072–1079. Li, A., & Ahmadi, G. (1992). Dispersion and Deposition of Spherical Particles from Point Sources in a Turbulent Channel Flow, Aerosol Science and Technology, 16(4), 209-226. Oberdörster, G., Sharp, Z., Atudorei, V., Elder, A., Gelein, R., Kreyling, W., & Cox, C. (2004). Translocation of Inhaled Ultrafine Particles to the Brain, Inhalation Toxicology, 16(6-7), 437-445. Persson, E., Henriksson, J., & Tjälve, H. (2003). Uptake of Cobalt from the Nasal Mucosa into the Brain via Olfactory Pathways in Rats, Toxicology Letters, 145, 19-27. Sen, S., Flynn, M.R., Du, GW, Troster, A.I., An, HY, & Huang, XM (2011). Manganese Accumulation in the Olfactory Bulbs and Other Brain Regions of "Asymptomatic" Welders, Toxicological Sciences, 121(1), 160-167. Shang, YD, Dong, JL, Inthavong, Kiao, & Tu, Jiyuan (2015). Comparative Numerical Modeling of Inhaled Micron-Sized Particle Deposition in Human and Rat Nasal Cavities, Inhalation Toxicology, 27(13), 694-705.
21
Shiga, H., Taki, J., Yamada, M., Washiyama, K., Amano, R., Matsuura, Y., Matsui, O., Tatsutomi, S., Yagi, S., Tsuchida, A., Yoshizaki, T., Furukawa, M., Kinuya, S., & Miwa, T. (2011). Evaluation of the Olfactory Nerve Transport Function by SPECT-MRI Fusion Image with Nasal Thallium-201 Administration, Mol Imaging Biol, 13(6), 1262-1266. Swift, D.L., Montassier,N., Hopke, P.K., Karpen-Hayes, K, Cheng, YS, Su, YF, Yeh, HC, & Strong, J.C. (1992). Inspiratory Deposition of Ultrafine Particles in Human Nasal Replicate Cast, Journal of Aerosol Science, 23(1), 65–72. Tjälve, H., Henriksson, J., Tallkvist, J., Larsson, B.S., & Lindquist, N.G. (1996). Uptake of
Manganese and Cadmium from the Nasal Mucosa into the Central Nervous System via Olfactory Pathways in Rats, Phurmacology & Toxicology, 79, 347-356. University of Calgary. (2006). Psychology Instruction Project (PIP) - Psyc 369 (Sensation & Perception).
[ONLINE]
Available
at:
http://www.ucalgary.ca/pip369/mod8/smell/pathways. [Accessed 19 June 2017]. Wen, J., Inthavong, K., Tu, JY, & Wang S. (2008). Numerical Simulations for Detailed Airflow Dynamics in Human Nasal Cavity, Respiratory Physiology & Neurobiology, 161, 125135. Zheng, W., Perry, D.F., Nelson, D.L., & Aposhian, H.V. (1991). Choroid Plexus Protects Cerebrospinal Fluid Against Toxic Metals. FASEB J., 5(8), 2188-2193.
22
FIGURE LIST Figure 1 Human nasal and olfactory model: (a) upper respiratory airways, olfactory brain pathways, and particle release profile; (b) sample cross section of nasal and olfactory channel; (c) 2D unwrapped nasal cavity surface model. (Brain image: University of Calgary, 2006). Figure 2 Computational mesh with polyhedron meshing scheme. Figure 3 Brownian diffusion validation testing in a pipe geometry. Figure 4 Stream-wise and axial air flow pattern in the nasal and olfactory airways at selected locations. Figure 5 Wall shear stress on nasal and olfactory surface at breathing rate of 5 L/min: (a) 3D model; (b) 2D unwrapped surface model. Figure 6 Particle flux at cross sections of the nostril, nasal valve, main channel (incorporating anterior/posterior nasal olfactory), and posterior naris at the breathing rate of 5L/min. Particle diameters are: (a) 1 nm; (b) 2 nm; (c) 10 nm. Figure 7 Particle deposition pattern in nasal cavity and olfactory at 5L/min. Particle diameters are: (a) 1nm; (b) 2 nm; (c) 10 nm. Figure 8 Particle deposition efficiency in the nasal cavity: (a) against particle size; (b) against D0.589/Q0.494. Figure 9 Particle deposition efficiency in human olfactory mucosa: (a) against particle size; (b) against D0.589/Q0.494. Figure 10 Evolution of olfactory deposited particle profile at nostrils and nasal valves at breathing rate of 5 L/min: (a) 1 nm at nostrils; (b) 2 nm at nostrils; (c) 10 nm at nostrils; (d) 1 nm at nasal valves; (e) 2 nm at nasal vales; (f) 10 nm at nasal valves.
23
Highlights
Human olfactory deposition of inhaled nanoparticles is computational simulated. Airflow and particle flux to olfactory deposition was visualized and discussed. Distinctive deposition variations were identified in olfactory and nasal cavity. Unique entrance profile for olfactory deposited particles was revealed.
b
a
olfactory
meatus
septum
c
vestibule
olfactory lateral side (right)
septal side
nasopharynx
lateral side (left)
Figure 1. Human nasal and olfactory model: (a) upper respiratory airways, olfactory brain pathways, and particle release profile; (b) sample cross section of nasal and olfactory channel; (c) 2D unwrapped nasal cavity surface model. (Brain image: University of Calgary, 2006).
24
Figure 2. Computational mesh with polyhedron meshing scheme.
c
b a
Figure 3. Brownian diffusion validation testing in a pipe geometry.
25
a
b nasal lateral side (right)
Wall shear stress (Pa) 0.10
0
2D
3D
0.05
nasal olfactory
vestibule
septal side
nasopharynx
5 L/min nasal lateral side (left)
Figure 5. Wall shear stress on nasal and olfactory surface at breathing rate of 5 L/min: (a) 3D model; (b) 2D unwrapped surface model. a Particle flux 0.04
b
c
5 L/min 1 nm
5 L/min 10 nm
5 L/min 2 nm
0.02
0
Figure 6. Particle flux at cross sections of the nostril, nasal valve, main channel (incorporating anterior/posterior nasal olfactory), and posterior naris at the breathing rate of 5L/min. Particle diameters are: (a) 1 nm; (b) 2 nm; (c) 10 nm. a
b
c
right
5 L/min 1 nm
5 L/min 2 nm
left
26
5 L/min 10 nm
Figure 7. Particle deposition pattern in nasal cavity and olfactory at 5L/min. Particle diameters are: (a) 1nm; (b) 2 nm; (c) 10 nm.
Figure 8. Particle deposition efficiency in the nasal cavity: (a) against particle size; (b) against D0.589/Q0.494.
Figure 9. Particle deposition efficiency in human olfactory mucosa: (a) against particle size; (b) against D0.589/Q0.494.
27
a
b 5 L/min 1 nm
c 5 L/min 2 nm
5 L/min 10 nm
Nostrils
right
left f
e
d 5 L/min 1 nm
5 L/min 2 nm
5 L/min 10 nm
Nasal Valves
Figure 10. Evolution of olfactory deposited particle profile at nostrils and nasal valves at breathing rate of 5 L/min: (a) 1 nm at nostrils; (b) 2 nm at nostrils; (c) 10 nm at nostrils; (d) 1 nm at nasal valves; (e) 2 nm at nasal vales; (f) 10 nm at nasal valves.
28