This work was supported in part by the European Commission (FP7 Program) through a Career Integration Grant (PCIG09-GA-2011-293604), the Israel Science Foundation (Grant nr. 990/12) and the Technion Center of Excellence in Environmental Health and Exposure Science (TCEEH). Microfabrication of microfluidic chips was conducted at the Micro-Nano Fabrication Unit (MNFU) of the Technion and supported by a seed grant from the Russel Berrie Institute of Nanotechnology (RBNI) at Technion. The authors thank Avshalom Shai for assistance during deep reactive ion etching (DRIE) and Molly Mulligan and Philipp Hofemeier for helpful discussions.

1. Master Fabrication
<ol>
	<li>Use deep reactive ion etching (DRIE) of a silicon on insulator (SOI) wafer to fabricate a master silicon wafer as described in former works32, 33. 
	NOTE: DRIE is preferred to standard SU-8 micromachining due to the high aspect ratio features (40 &#181;m wide and 90 &#181;m deep trenches).</li>
</ol>
2. Casting and Sealing of the Microfluidic Device
<ol>
	<li>Mix PDMS and curing agent at a 10:1 weight ratio inside a clean small contain...

<ol>
	<li>Kleinstreuer, C., Zhang, Z. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Airflow+and+Particle+Transport+in+the+Human+Respiratory+System.">Airflow and Particle Transport in the Human Respiratory System.</a> Annu. Rev. Fluid Mech. 42 (1), 301-334 (2010).</li><li>Sznitman, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Respiratory+microflows+in+the+pulmonary+acinus.">Respiratory microflows in the pulmonary acinus.</a> J. Biomech. 46 (2), 284-298 (2013).</li><li>Tsuda, A., Henry, F. S., Butler, J. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gas+and+aerosol+mixing+in+the+acinus.">Gas and aerosol mixing in the acinus.</a> Respir. Physiol. Neurobiol. 163 (1-3), 139-149 (2008).</li><li>Kleinstreuer, C., Zhang, Z., Donohue, J. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Targeted+Drug-Aerosol+Delivery+in+the+Human+Respiratory+System.">Targeted Drug-Aerosol Delivery in the Human Respiratory System.</a> Annu. Rev. Biomed. Eng. 10 (1), 195-220 (2008).</li><li>Semmler-Behnke, M., Kreyling, W. G., Schulz, H., Takenaka, S., Butler, J. P., Henry, F. S., Tsuda, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nanoparticle+delivery+in+infant+lungs.">Nanoparticle delivery in infant lungs.</a> Proc. Natl. Acad. Sci. 109 (13), 5092-5097 (2012).</li><li>Sznitman, J., Heimsch, F., Heimsch, T., Rusch, D., Rosgen, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-Dimensional+Convective+Alveolar+Flow+Induced+by+Rhythmic+Breathing+Motion+of+the+Pulmonary+Acinus.">Three-Dimensional Convective Alveolar Flow Induced by Rhythmic Breathing Motion of the Pulmonary Acinus.</a> J. Biomech. Eng. 129 (5), 658-665 (2007).</li><li>Tsuda, A., Henry, F. S., Butler, J. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chaotic+mixing+of+alveolated+duct+flow+in+rhythmically+expanding+pulmonary+acinus.">Chaotic mixing of alveolated duct flow in rhythmically expanding pulmonary acinus.</a> J. Appl. Physiol. 79 (3), 1055-1063 (1995).</li><li>Henry, F. S., Butler, J. P., Tsuda, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Kinematically+irreversible+acinar+flow:+a+departure+from+classical+dispersive+aerosol+transport+theories.">Kinematically irreversible acinar flow: a departure from classical dispersive aerosol transport theories.</a> J. Appl. Physiol. 92 (2), 835-845 (2002).</li><li>Kumar, H., Tawhai, M. H., Hoffman, E. A., Lin, C. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effects+of+geometry+on+airflow+in+the+acinar+region+of+the+human+lung.">The effects of geometry on airflow in the acinar region of the human lung.</a> J. Biomech. 42 (11), 1635-1642 (2009).</li><li>Lee, D. Y., Lee, J. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characteristics+of+particle+transport+in+an+expanding+or+contracting+alveolated+tube.">Characteristics of particle transport in an expanding or contracting alveolated tube.</a> J. Aerosol Sci. 34 (9), 1193-1215 (2003).</li><li>Tsuda, A., Butler, J. P., Fredberg, J. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+alveolated+duct+structure+on+aerosol+kinetics.+I.+Diffusional+deposition+in+the+absence+of+gravity.">Effects of alveolated duct structure on aerosol kinetics. I. Diffusional deposition in the absence of gravity.</a> J. Appl. Physiol. 76 (6), 2497-2509 (1994).</li><li>Tsuda, A., Butler, J. P., Fredberg, J. 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The authors have nothing to disclose.

A critical feature of the microfluidic acinar platform presented here is its ability to reproduce physiologically-realistic breathing motions that give rise to physiological flow profiles and velocities within acinar ducts and within alveoli. Since the microfluidic channels are produced with a relatively low aspect ratio (i.e., wd/h &#8776; 3.9, where wd is the duct width and h is the duct height), the measured flows show more plug-like ...

A detailed quantification of respiratory flow dynamics in the distal, alveolated regions of the lungs is paramount towards understanding airflow mixing in the pulmonary acinus and predicting the fate of inhaled aerosols in the deepest airways1&#8211;3. This latter aspect is of particular concern when addressing on the one hand the hazards of inhaled pollutant particles or conversely in seeking novel strategies for improved and targeted drug delivery of inhaled therapeutics to localized lung sites4, 5&#160;as well as for systemic delivery.
To date, respiratory flows in the deep pulmonary acinar regions have been typically investigated in silico using computational fluid dynamics (CFD) or alternatively in vitro with scaled-up experimental models following hydrodynamic similarity matching. In the past few decades, CFD methods have been increasingly applied to study acinar flow phenomena, from single alveolar models6, 7&#160;and alveolated ducts8&#8211;12&#160;to more elaborate in silico models that capture anatomically-realistic acinar tree structures with multiple generations of alveolated ducts and up to several hundreds of individual alveoli13&#8211;15.
Together, numerical efforts have been pivotal in shedding light on the role and influence of wall motion during breathing movements on ensuing acinar airflow patterns. In the absence of breathing motion, static alveoli feature recirculating flows within their cavities that exhibit no convective exchange of air between the acinar duct and the alveolus6, 7; in other words, alveolar flows would be entirely isolated from flows within the acinar trees and exchange of air would result uniquely from diffusive mechanisms. With the existence of cyclic expansions of the alveolar domain, however, alveolar flow topologies are drastically modified and the resulting flow patterns inside alveoli are intimately tied to the location of an alveolus along the acinar tree (e.g., proximal vs. distal generations).
In particular, it has been hypothesized in simulations that alveolar flow patterns are strongly influenced by the ratio of alveolar to ductal flow rates such that proximal generations of the pulmonary acinar tree, where this ratio is relatively large following mass conservation across a tree structure, feature complex recirculating flows inside the alveolar cavities with irreversible fluid pathlines. With each deeper acinar generation, the ratio of alveolar to ductal flow rates gradually decreases such that distal acinar generations exhibit more radial-like streamlines that are reminiscent of simple inflations and deflations of a balloon. With advances in modern imaging modalities, lung imaging data16, 17&#160;of rodents, including rat and mouse, have given rise to some of the first CFD simulations of anatomically-reconstructed acinar flows in reconstructed alveoli. Despite such promising progress, these recent studies are still limited to addressing airflow phenomena in terminal alveolar sacs only18, 19&#160;or a few alveoli surrounding a single duct20. As a result, state-of-the-art investigations of respiratory flow phenomena in the acinus remain dominated by studies focusing on generic anatomically-inspired geometries of the acinar environment2.
On the experimental side, various setups featuring an airway with one or several alveoli have been developed over the years21&#8211;24. Yet, there exists no experimental models of bifurcating alveolated airways that are capable of mimicking physiological respiration by expanding and contracting in a breathing-like fashion. Given a lack of attractive experimental platforms at hand, the study of acinar transport phenomena remains limited with regards to validating computational studies and critically, there remains a dearth of experimental data available. In recent years, Ma et al. (2009) have constructed a scaled-up rigid-wall model of an acinus consisting of three acinar generations; however, the lack of wall motion in this model limited its capability to capture realistic alveolar flow patterns under breathing conditions.
Other scaled-up experiments including a moving wall model based on anatomical data from cast replica were recently introduced25; however, since the model only captured the last two acinar generations (i.e., terminal sacs), it failed to capture the complex recirculating flows that characterize more proximal acinar generations. These latter examples of scaled-up experiments further underline the ongoing limitations with such approaches. Specifically, no existing experiment has thus far demonstrated the hypothesized transition from recirculating to radial flows along the acinus and thereby confirm numerical predictions of flow topologies hypothesized to exist in real pulmonary acinar trees7, 15. Perhaps most critically, scaled-up experiments are extremely limited in investigating inhaled particle transport and deposition dynamics26&#160;due to difficulties in matching all relevant non-dimensional parameters (e.g., particle diffusion, a critical transport mechanism for sub-micron particles, is completely neglected).
With ongoing experimental challenges, new experimental platforms that permit investigations of respiratory air flows and particle dynamics in complex moving walls acinar networks are sought. Here, an anatomically-inspired in vitro acinar model is introduced. This microfluidic platform mimics pulmonary acinar flows directly at the representative acinar scale, and broadens the growing range of pulmonary microfluidic models27, including bronchial liquid plug-flows28&#8211;30&#160;and the alveolar-capillary barrier31.
Namely, the present design features a simplified five generation alveolated airway tree with cyclically expanding and contracting walls, where cyclic motions are achieved by controlling pressure inside a water chamber which surrounds the thin PDMS lateral walls and where the top wall is deformed by an additional water chamber sitting directly above the acinar structure. Unlike common multilayer microfluidic devices, this chamber is simply formed by embedding the barrel section of a syringe inside the PDMS Device, and does not require preparation of an additional PDMS mold.
The miniaturized approach presented here offers a simple and versatile means for reproducing complicated acinar structures with moving walls as compared to scaled-up models while capturing the underlying characteristics of the acinar flow environment. This platform can be used for flow visualization using fluid-suspended particles inside the airways (see Representative Results below). In the near future, the model will be used with airborne particles for studying inhaled acinar particle dynamics.

<table>
	<tbody>
		<tr>
			<td>Polydimethylsiloxane (PDMS) and curing agent</td>
			<td>Dow Corning</td>
			<td>(240)4019862</td>
			<td>SYLGARD&#174; 184 SILICONE ELASTOMER KIT</td>
		</tr>
		<tr>
			<td>Plastipak 2 ml syringe</td>
			<td>BD</td>
			<td>300185</td>
			<td></td>
		</tr>
		<tr>
			<td>Norm-Ject Luer slip 1 ml syringe</td>
			<td>Henke Sass Wolf </td>
			<td>4010-200V0</td>
			<td></td>
		</tr>
		<tr>
			<td>1mm Biopsy punch</td>
			<td>Kai Medical</td>
			<td>BP-10F</td>
			<td></td>
		</tr>
		<tr>
			<td>Laboratory Corona Treater</td>
			<td>Electro-Technic Products</td>
			<td>BD-20AC</td>
			<td></td>
		</tr>
		<tr>
			<td>PHD Ultra Syringe pump</td>
			<td>Harvard apparatus</td>
			<td>703006</td>
			<td></td>
		</tr>
		<tr>
			<td>Dyed red rqueous fluorescent particles</td>
			<td >Thermo-Scientific</td>
			<td ></td>
			<td >Uncatalloged 0.86 &#181;m beads were used</td>
		</tr>
		<tr>
			<td>Glycerin AR</td>
			<td>Gadot</td>
			<td>830131320</td>
			<td></td>
		</tr>
		<tr>
			<td>FlowMaster MITAS micro-particle image velocimetry (&#181;PIV) system </td>
			<td>LaVision</td>
			<td>1108630</td>
			<td ></td>
		</tr>
	</tbody>
</table>

a microfluidic model of biomimetically breathing pulmonary acinar airways

Quantifying respiratory flow characteristics in the pulmonary acinar depths and how they influence inhaled aerosol transport is critical towards optimizing drug inhalation techniques as well as predicting deposition patterns of potentially toxic airborne particles in the pulmonary alveoli. Here, soft-lithography techniques are used to fabricate complex acinar-like airway structures at the truthful anatomical length-scales that reproduce physiological acinar flow phenomena in an optically accessible system. The microfluidic device features 5 generations of bifurcating alveolated ducts with periodically expanding and contracting walls. Wall actuation is achieved by altering the pressure inside water-filled chambers surrounding the thin PDMS acinar channel walls both from the sides and the top of the device. In contrast to common multilayer microfluidic devices, where the stacking of several PDMS molds is required, a simple method is presented to fabricate the top chamber by embedding the barrel section of a syringe into the PDMS mold. This novel microfluidic setup delivers physiological breathing motions which in turn give rise to characteristic acinar air-flows. In the current study, micro particle image velocimetry (&#181;PIV) with liquid suspended particles was used to quantify such air flows based on hydrodynamic similarity matching. The good agreement between &#181;PIV results and expected acinar flow phenomena suggest that the microfluidic platform may serve in the near future as an attractive in vitro tool to investigate directly airborne representative particle transport and deposition in the acinar regions of the lungs.

Computer-aided design (CAD) and microscope images of the in vitro acinar platform are presented in Fig. 1. The biomimetic acinar model features five generations of branching rectangular channels lined with alveolar-like cylindrical cavities (Fig. 1). Here, the model generations are numbered from generation 1 (for the most proximal generation) to generation 5 (for the most distal generation). Note that only the channel inlet leading to generation 1 is open to the outer environmen...

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A Microfluidic Model of Biomimetically Breathing Pulmonary Acinar Airways

Soft-lithography was utilized to produce a representative true-scale model of pulmonary alveolated airways that expand and contract periodically, mimicking physiological breathing motion. This platform recreates respiratory acinar flows on a chip, and is anticipated to facilitate experimental investigation of inhaled aerosol dynamics and deposition in the pulmonary acinus.

Quantifying respiratory flow characteristics in the pulmonary acinar depths and how they influence inhaled aerosol transport is critical towards ...

The overall goal of this model system, is to mimic the geometry and breathing motion of the Pulmonary Acinus for studying Acinar airflow patterns and airborne micro-particle trajectories. This method can help answer key questions in the field of Acinar Transport Phenomena. Such as, the effects of gravity, drug, and diffusion on particle deposition outcomes.The main advantage of this technique is that experiments are done inside a one-to-one scale model rather than a scaled up model. This allows for accurate observation of particle Brownian motion. The implications of this technique extend towards inhalation therapy, because a better understanding of aerosolized drug deposition can be achieved.To begin, use deep reactive ion etching of a silicon on insulator wafer to fabricate a master silicon wafer as described previously. Next, mix the PDMS and curing agent at a ten-to-one weight ratio inside a clean small container. Degas the mixture in a desiccator under vacuum until all of the air bubbles are removed.Place the master wafer into a petri dish, and pour the degassed PDMS mixture to a height of approximately one millimeter above the master wafer. Degas the poured PDMS once again for at least 40 minutes, until all air bubbles are removed above the wafer, and bubbles below the wafer are minimized. Make sure that the wafer is as close as possible to the bottom of the plate.If necessary, press the wafer gently to the bottom using two stirring sticks and degas once again. Then, bake the PDMS at 65 degrees Celsius for 20 minutes in a natural convection oven. While the PDMS is baking, file the barrel section of a plastic two milliliter syringe, using a fine grit sand paper to improve its adherence to PDMS.In addition, use the sand paper to flatten the base of the syringe barrel by placing the sand paper on a flat surface and sliding the base of the syringe barrel on top of it. Clean off any debris from the syringe using pressurized air. Then place the barrel section of the syringe on top of the first PDMS layer with the large opening facing the surface of the PDMS.Pour a second layer of PDMS on top of the first one, to a height of about five millimeters, while ensuring that the PDMS does not enter the barrel of the syringe. Then, degas the PDMS once again. Bake the entire set-up at 65 degrees Celsius for at least two hours in a natural convection oven to harden the PDMS.Cut through the PDMS mold around the patterned region of the master wafer using a scalpel. While cutting, the scalpel should weakly touch the surface of the wafer. Then, gently insert a thin tool, such as wafer forceps, in the notch created by the scalpel, and peel off the PDMS cast from the master wafer.Place the cast on a soft surface covered with aluminum foil, so that the patterned side faces up and punch a hole in the PDMS at the chamber inlet and channel inlet, using a one millimeter biopsy punch. Next, add some of the PDMS with curing agent to a clean glass slide and spin coat a thin layer at 3, 000 RPM's for 30 seconds. Then, bake the slide at 65 degrees Celsius for at least one hour.Clean the slide and PDMS cast using scotch tape. Treat the surfaces of the coated glass slide and the molded PDMS with oxygen plasma using a corona treater. Note that each surface should be treated for at least one minute.Then, gently press the surfaces together and bake them overnight at 65 degrees Celsius. Mix water suspended fluorescent polystyrene particles with water and glycerol in a glass vile to obtain a 64-to-36 volume to volume ratio of glycerol to water containing 0.25%particles by weight. Next, place a drop of the glycerol solution on top of the channel inlet and a drop of DI water on the chamber inlet.Then, set the apparatus inside a desiccator and pull a vacuum for about five minutes. Before releasing the vacuum, wait for the bubbles that form in the drops of glycerol solution and DI water to pop. Upon vacuum release, the liquids are drawn into the voids inside the device.If residual air remains inside the channels, eliminate it by applying external pressure on the fluids using a syringe and allowing the air to diffuse into the PDMS. Next, inject about two millimeters of deionized water into the top chamber until it is fully filled with water. Then, cover the chamber with a 19 gauge blunt syringe tip.Cut the tip of another blunt 19 gauge syringe tip and insert this tip into the side chamber inlet. Connect both syringe tips to a one milliliter syringe using thin, Teflon tubing and a t-shaped connector. Make sure that the one milliliter syringe, Teflon tubing, t-shaped connector, and top chamber are all filled with water, without any bubbles.Then, connect the one milliliter syringe to a syringe pump and program it to mimic a quiet title breathing cycle as described in the accompanying text protocol. In order to obtain micro-particle vilo symmetry images, place the device on to the stage of an inverted microscope. Then, turn on the double pulsed Nd:YAG laser and load the image analysis software on the computer.While the device is being actuated, obtain a series of nine-to-twelve phase locked double frame images of the particle seeded flow, using a micro-particle image vilo symmetry system in accordance with the manufacturers'specifications. To achieve phase locked double frame images, acquire a double frame series at 10 hertz. Then, reorganize the data so that all framed pairs that are separated by a full cycle time form a new time series.Use the sum of correlation algorithm to compute phase locked velocity vector map so the resulting flow field from the image series. Repeat this process several times with varying lag times between the first and second frames of each frame pair for resolving different flow regions inside the alveolar cavity. Next, use a data analysis program to stitch together the individual flow maps into a complete and high detailed map of flow patterns by averaging overlapping data points.A critical feature of the micro-fluidic acinar platform presented here, is its ability to reproduce physiologically realistic breathing motions that give rise to physiological flow profiles and velocities within acinar ducts and within alveoli. Flow velocity profiles across the width of the channels show a steady drop of flow rates towards deeper acinar generations. Flow profiles near and within alveolar cavities show that flow magnitudes drop steeply along the opening of alveoli.Resulting in flow velocity that are two to three orders of magnitudes slower inside alveoli compared to the ducts. In addition, flow patterns change considerably with increasing acinar generation. While generation one features a re-circulation zone, which roughly coincides with the center of the alveolas, generation three's characterized by a re-circulation zone which is shifted toward the proximal side of alveolas with a more open stream line pattern.Finally, radial stream lines with no re-circulation zone are observed in device generation five. Once mastered, this technique can be done in a few hours if it is performed properly. Following this procedure, which enables flow visualization in acinar geometries, the platform can be used to track single airborne particles in order to explore the dynamics and the position of inhaled particles.

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7.9K Görüntüleme.  Technion - Israel Institute of Technology. The overall goal of this model system, is to mimic the geometry and breathing motion of the Pulmonary Acinus for studying Acinar airflow patterns and airborne micro-particle trajectories. This method can help answer key questions in the field of Acinar Transport Phenomena. Such as, the effects of gravity, drug, and diffusion on particle deposition outcomes.The main advantage of this technique is that experiments are done inside a one-to-one scale model rather than a scaled up model. Th...