Microfluidic Chip for Site-Specific Neuropharmacological Treatment and Activity Probing of 3D Neuronal "Optonet" Cultures

The study introduces a "brain-on-a-chip" microfluidic platform that hosts brain-like 3D cultures ("optonets") whose activity and responses to flowing drugs are recorded optically. Optonets are viable, optically accessible 3D neural networks whose characteristics approximate cortical networks. The results demonstrate the ability to monitor complex 3D activity patterns during extended site-specific, reversible neuropharmacogical exposure, suggesting an interesting potential in drug screening.

Model-independent phenotyping of C. elegans locomotion using scale-invariant feature transform

To uncover the genetic basis of behavioral traits in the model organism C. elegans, a common strategy is to study locomotion defects in mutants. Despite efforts to introduce (semi-)automated phenotyping strategies, current methods overwhelmingly depend on worm-specific features that must be hand-crafted and as such are not generalizable for phenotyping motility in other animal models. Hence, there is an ongoing need for robust algorithms that can automatically analyze and classify motility phenotypes quantitatively. To this end, we have developed a fully-automated approach to characterize C. elegans’ phenotypes that does not require the definition of nematode-specific features. Rather, we make use of the popular computer vision Scale-Invariant Feature Transform (SIFT) from which we construct histograms of commonly-observed SIFT features to represent nematode motility. We first evaluated our method on a synthetic dataset simulating a range of nematode crawling gaits. Next, we evaluated our algorithm on two distinct datasets of crawling C. elegans with mutants affecting neuromuscular structure and function. Not only is our algorithm able to detect differences between strains, results capture similarities in locomotory phenotypes that lead to clustering that is consistent with expectations based on genetic relationships. Our proposed approach generalizes directly and should be applicable to other animal models. Such applicability holds promise for computational ethology as more groups collect high-resolution image data of animal behavior.

Biomimetics of fetal alveolar flow phenomena using microfluidics

At the onset of life in utero, the respiratory system begins as a liquid-filled tubular organ and undergoes significant morphological changes during fetal development towards establishing a respiratory organ optimized for gas exchange. As airspace morphology evolves, respiratory alveolar flows have been hypothesized to exhibit evolving flow patterns. In the present study, we have investigated flow topologies during increasing phases of embryonic life within an anatomically inspired microfluidic device, reproducing real-scale features of fetal airways representative of three distinct phases of in utero gestation. Micro-particle image velocimetry measurements, supported by computational fluid dynamics simulations, reveal distinct respiratory alveolar flow patterns throughout different stages of fetal life. While attached, streamlined flows characterize the shallow structures of premature alveoli indicative of the onset of saccular stage, separated recirculating vortex flows become the signature of developed and extruded alveoli characteristic of the advanced stages of fetal development. To further mimic physiological aspects of the cellular environment of developing airways, our biomimetic devices integrate an alveolar epithelium using the A549 cell line, recreating a confluent monolayer that produces pulmonary surfactant. Overall, our in vitro biomimetic fetal airways model delivers a robust and reliable platform combining key features of alveolar morphology, flow patterns, and physiological aspects of fetal lungs developing in utero.

Dendritic tree extraction from noisy maximum intensity projection images in C. elegans

BACKGROUND

Maximum Intensity Projections (MIP) of neuronal dendritic trees obtained from confocal microscopy are frequently used to study the relationship between tree morphology and mechanosensory function in the model organism C. elegans. Extracting dendritic trees from noisy images remains however a strenuous process that has traditionally relied on manual approaches. Here, we focus on automated and reliable 2D segmentations of dendritic trees following a statistical learning framework.

METHODS

Our dendritic tree extraction (DTE) method uses small amounts of labelled training data on MIPs to learn noise models of texture-based features from the responses of tree structures and image background. Our strategy lies in evaluating statistical models of noise that account for both the variability generated from the imaging process and from the aggregation of information in the MIP images. These noisy models are then used within a probabilistic, or Bayesian framework to provide a coarse 2D dendritic tree segmentation. Finally, some post-processing is applied to refine the segmentations and provide skeletonized trees using a morphological thinning process.

RESULTS

Following a Leave-One-Out Cross Validation (LOOCV) method for an MIP databse with available "ground truth" images, we demonstrate that our approach provides significant improvements in tree-structure segmentations over traditional intensity-based methods. Improvements for MIPs under various imaging conditions are both qualitative and quantitative, as measured from Receiver Operator Characteristic (ROC) curves and the yield and error rates in the final segmentations. In a final step, we demonstrate our DTE approach on previously unseen MIP samples including the extraction of skeletonized structures, and compare our method to a state-of-the art dendritic tree tracing software.

CONCLUSIONS

Overall, our DTE method allows for robust dendritic tree segmentations in noisy MIPs, outperforming traditional intensity-based methods. Such approach provides a useable segmentation framework, ultimately delivering a speed-up for dendritic tree identification on the user end and a reliable first step towards further morphological characterizations of tree arborization.

Role of Alveolar Topology on Acinar Flows and Convective Mixing

Due to experimental challenges, computational simulations are often sought to quantify inhaled aerosol transport in the pulmonary acinus. Commonly, these are performed using generic alveolar topologies, including spheres, toroids, and polyhedra, to mimic the complex acinar morphology. Yet, local acinar flows and ensuing particle transport are anticipated to be influenced by the specific morphological structures. We have assessed a range of acinar models under self-similar breathing conditions with respect to alveolar flow patterns, convective flow mixing, and deposition of fine particles (1.3 μm diameter). By tracking passive tracers over cumulative breathing cycles, we find that irreversible flow mixing correlates with the location and strength of the recirculating vortex inside the cavity. Such effects are strongest in proximal acinar generations where the ratio of alveolar to ductal flow rates is low and interalveolar disparities are most apparent. Our results for multi-alveolated acinar ducts highlight that fine 1 μm inhaled particles subject to alveolar flows are sensitive to the alveolar topology, underlining interalveolar disparities in particle deposition patterns. Despite the simplicity of the acinar models investigated, our findings suggest that alveolar topologies influence more significantly local flow patterns and deposition sites of fine particles for upper generations emphasizing the importance of the selected acinar model. In distal acinar generations, however, the alveolar geometry primarily needs to mimic the space-filling alveolar arrangement dictated by lung morphology.

Microfluidic shear stress-regulated surfactant secretion in alveolar epithelial type II cells in vitro

We investigated the role of flow-induced shear stress on the mechanisms regulating surfactant secretion in type II alveolar epithelial cells (ATII) using microfluidic models. Following flow stimulation spanning a range of wall shear stress (WSS) magnitudes, monolayers of ATII (MLE-12 and A549) cells were examined for surfactant secretion by evaluating essential steps of the process, including relative changes in the number of fusion events of lamellar bodies (LBs) with the plasma membrane (PM) and intracellular redistribution of LBs. F-actin cytoskeleton and calcium levels were analyzed in A549 cells subjected to WSS spanning 4-20 dyn/cm(2). Results reveal an enhancement in LB fusion events with the PM in MLE-12 cells upon flow stimulation, whereas A549 cells exhibit no foreseeable changes in the monitored number of fusion events for WSS levels ranging up to a threshold of ∼8 dyn/cm(2); above this threshold, we witness instead a decrease in LB fusion events in A549 cells. However, patterns of LB redistribution suggest that WSS can potentially serve as a stimulus for A549 cells to trigger the intracellular transport of LBs toward the cell periphery. This observation is accompanied by a fragmentation of F-actin, indicating that disorganization of the F-actin cytoskeleton might act as a limiting factor for LB fusion events. Moreover, we note a rise in cytosolic calcium ([Ca(2+)]c) levels following stimulation of A549 cells with WSS magnitudes ranging near or above the experimental threshold. Overall, WSS stimulation can influence key components of molecular machinery for regulated surfactant secretion in ATII cells in vitro.

Respiratory physiology on a chip

Our current understanding of respiratory physiology and pathophysiological mechanisms of lung diseases is often limited by challenges in developing in vitro models faithful to the respiratory environment, both in cellular structure and physiological function. The recent establishment and adaptation of microfluidic-based in vitro devices (μFIVDs) of lung airways have enabled a wide range of developments in modern respiratory physiology. In this paper, we address recent efforts over the past decade aimed at advancing in vitro models of lung structure and airways using microfluidic technology and discuss their applications. We specifically focus on μFIVDs covering four major areas of respiratory physiology, namely, artificial lungs (AL), the air-liquid interface (ALI), liquid plugs and cellular injury, and the alveolar-capillary barrier (ACB).

Undulatory locomotion of Caenorhabditis elegans on wet surfaces

The physical and biomechanical principles that govern undulatory movement on wet surfaces have important applications in physiology, physics, and engineering. The nematode Caenorhabditis elegans, with its highly stereotypical and functionally distinct sinusoidal locomotory gaits, is an excellent system in which to dissect these properties. Measurements of the main forces governing the C. elegans crawling gait on lubricated surfaces have been scarce, primarily due to difficulties in estimating the physical features at the nematode-gel interface. Using kinematic data and a hydrodynamic model based on lubrication theory, we calculate both the surface drag forces and the nematode's bending force while crawling on the surface of agar gels within a preexisting groove. We find that the normal and tangential surface drag coefficients during crawling are ∼222 and 22, respectively, and the drag coefficient ratio is ∼10. During crawling, the calculated internal bending force is time-periodic and spatially complex, exhibiting a phase lag with respect to the nematode's body bending curvature. This phase lag is largely due to viscous drag forces, which are higher during crawling as compared to swimming in an aqueous buffer solution. The spatial patterns of bending force generated during either swimming or crawling correlate well with previously described gait-specific features of calcium signals in muscle. Further, our analysis indicates that one may be able to control the motility gait of C. elegans by judiciously adjusting the magnitude of the surface drag coefficients.

Multi-environment model estimation for motility analysis of Caenorhabditis elegans

The nematode Caenorhabditis elegans is a well-known model organism used to investigate fundamental questions in biology. Motility assays of this small roundworm are designed to study the relationships between genes and behavior. Commonly, motility analysis is used to classify nematode movements and characterize them quantitatively. Over the past years, C. elegans' motility has been studied across a wide range of environments, including crawling on substrates, swimming in fluids, and locomoting through microfluidic substrates. However, each environment often requires customized image processing tools relying on heuristic parameter tuning. In the present study, we propose a novel Multi-Environment Model Estimation (MEME) framework for automated image segmentation that is versatile across various environments. The MEME platform is constructed around the concept of Mixture of Gaussian (MOG) models, where statistical models for both the background environment and the nematode appearance are explicitly learned and used to accurately segment a target nematode. Our method is designed to simplify the burden often imposed on users; here, only a single image which includes a nematode in its environment must be provided for model learning. In addition, our platform enables the extraction of nematode ‘skeletons’ for straightforward motility quantification. We test our algorithm on various locomotive environments and compare performances with an intensity-based thresholding method. Overall, MEME outperforms the threshold-based approach for the overwhelming majority of cases examined. Ultimately, MEME provides researchers with an attractive platform for C. elegans' segmentation and ‘skeletonizing’ across a wide range of motility assays.

Material properties of Caenorhabditis elegans swimming at low Reynolds number

Undulatory locomotion, as seen in the nematode Caenorhabditis elegans, is a common swimming gait of organisms in the low Reynolds number regime, where viscous forces are dominant. Although the nematode's motility is expected to be a strong function of its material properties, measurements remain scarce. Here, the swimming behavior of C. elegans is investigated in experiments and in a simple model. Experiments reveal that nematodes swim in a periodic fashion and generate traveling waves that decay from head to tail. The model is able to capture the experiments' main features and is used to estimate the nematode's Young's modulus E and tissue viscosity eta. For wild-type C. elegans, we find E approximately 3.77 kPa and eta approximately -860 Pa.s; values of eta for live C. elegans are negative because the tissue is generating rather than dissipating energy. Results show that material properties are sensitive to changes in muscle functional properties, and are useful quantitative tools with which to more accurately describe new and existing muscle mutants.

Respiratory flow phenomena and gravitational deposition in a three-dimensional space-filling model of the pulmonary acinar tree

The inhalation of micron-sized aerosols into the lung's acinar region may be recognized as a possible health risk or a therapeutic tool. In an effort to develop a deeper understanding of the mechanisms responsible for acinar deposition, we have numerically simulated the transport of nondiffusing fine inhaled particles (1 mum and 3 microm in diameter) in two acinar models of varying complexity: (i) a simple alveolated duct and (ii) a space-filling asymmetrical acinar branching tree following the description of lung structure by Fung (1988, "A Model of the Lung Structure and Its Validation," J. Appl. Physiol., 64, pp. 2132-2141). Detailed particle trajectories and deposition efficiencies, as well as acinar flow structures, were investigated under different orientations of gravity, for tidal breathing motion in an average human adult. Trajectories and deposition efficiencies inside the alveolated duct are strongly related to gravity orientation. While the motion of larger particles (3 microm) is relatively insensitive to convective flows compared with the role of gravitational sedimentation, finer 1 microm aerosols may exhibit, in contrast, complex kinematics influenced by the coupling between (i) flow reversal due to oscillatory breathing, (ii) local alveolar flow structure, and (iii) streamline crossing due to gravity. These combined mechanisms may lead to twisting and undulating trajectories in the alveolus over multiple breathing cycles. The extension of our study to a space-filling acinar tree was well suited to investigate the influence of bulk kinematic interaction on aerosol transport between ductal and alveolar flows. We found the existence of intricate trajectories of fine 1 microm aerosols spanning over the entire acinar airway network, which cannot be captured by simple alveolar models. In contrast, heavier 3 microm aerosols yield trajectories characteristic of gravitational sedimentation, analogous to those observed in the simple alveolated duct. For both particle sizes, however, particle inhalation yields highly nonuniform deposition. While larger particles deposit within a single inhalation phase, finer 1 microm particles exhibit much longer residence times spanning multiple breathing cycles. With the ongoing development of more realistic models of the pulmonary acinus, we aim to capture some of the complex mechanisms leading to deposition of inhaled aerosols. Such models may lead to a better understanding toward the optimization of pulmonary drug delivery to target specific regions of the lung.

Convective gas transport in the pulmonary acinus: comparing roles of convective and diffusive lengths

To investigate the relative importance of convection and diffusion in the transport of oxygen in the pulmonary acinus, it is often useful to locate the transition from convection-dominated to diffusion-dominated transport. Traditionally, this is done by estimating the values of a Peclet number. This dimensionless number compares the bulk ductal flow velocity at an acinar generation with a diffusion velocity over a characteristic length scale. Here, we revisit the convection-diffusion transition by comparing the relative importance of convective and diffusive lengths. We introduce the ratio of such lengths (L(conv)/L(diff)) to quantify the extent of convective transport in the acinus over an inhalation phase. We distinguish between convection along the acinar airways and within alveoli, respectively. Results for L(conv)/L(diff) suggest that convection in acinar ducts may play a potential role in more peripheral airways compared with values obtained for a Peclet number. Within alveoli, however, independent of acinar depth, oxygen transport is governed by diffusion as soon as molecules enter within alveolar cavities.

Three-dimensional convective alveolar flow induced by rhythmic breathing motion of the pulmonary acinus

Low Reynolds number flows (Re<1) in the human pulmonary acinus are often difficult to assess due to the submillimeter dimensions and accessibility of the region. In the present computational study, we simulated three-dimensional alveolar flows in an alveolated duct at each generation of the pulmonary acinar tree using recent morphometric data. Rhythmic lung expansion and contraction motion was modeled using moving wall boundary conditions to simulate realistic sedentary tidal breathing. The resulting alveolar flow patterns are largely time independent and governed by the ratio of the alveolar to ductal flow rates, Qa/Qd. This ratio depends uniquely on geometrical configuration such that alveolar flow patterns may be entirely determined by the location of the alveoli along the acinar tree. Although flows within alveoli travel very slowly relative to those in acinar ducts, 0.021%<or=Ua/Ud<or=9.1%, they may exhibit complex patterns linked to the three-dimensional nature of the flow and confirm findings from earlier three-dimensional simulations. Such patterns are largely determined by the interplay between recirculation in the cavity induced by ductal shear flow over the alveolar opening and radial flows induced by wall displacement. Furthermore, alveolar flow patterns under rhythmic wall motion contrast sharply with results obtained in a rigid alveolus, further confirming the importance of including inherent wall motion to understand realistic acinar flow phenomena. The present findings may give further insight into the role of convective alveolar flows in determining aerosol kinematics and deposition in the pulmonary acinus.

Correlation of spirometry and symptom scores in childhood asthma and the usefulness of curvature assessment in expiratory flow-volume curves

BACKGROUND

Spirometry, and in particular forced expiratory volume in the first second (FEV(1)), are standard tools for objective evaluation of asthma. However, FEV(1) does not correlate with symptom scores, and hence its value in the assessment of childhood asthma may be limited. Therefore, some clinicians subjectively assess the presence of curvature in the maximum expiratory flow-volume (MEFV) curves obtained from spirometry, where concave patterns are observable despite normal FEV(1) values.

OBJECTIVE

To evaluate the usefulness of subjective and objective measures of the curvature in the descending phase of the MEFV curve for the assessment of asthma.

METHODS

We obtained symptom scores and performed spirometry in 48 patients with asthma (21 females, mean +/- SD age 10.8 +/- 2.4 y). We measured FEV(1), the ratio of FEV(1) to forced vital capacity (FEV(1)/FVC), maximum expiratory flow at one quarter of the way, and at halfway, through the forced expiratory maneuver (MEF(25) and MEF(50), respectively), and maximum expiratory flow in the middle half of the forced expiratory maneuver (MEF(25-75)). Expiratory obstruction was ranked independently by 3 pediatric pulmonologists, by subjective assessment of the MEFV curve. In addition, the curvature of the descending limb of the MEFV curve was quantitatively estimated by introducing an "average curvature index."

RESULTS

No significant correlations were found between FEV(1), MEF(50), MEF(25), and MEF(25-75,) respectively, and symptom score (r = -0.22, p = 0.14; r = -0.23, p = 0.11; r = -0.28, p = 0.057; r = -0.27, p = 0.06). A weak correlation was found for FEV(1)/FVC and symptom score (r = -0.33, p = 0.021). However, quantitatively determined average curvature index (ACI) correlated significantly better with measured symptom scores (r = 0.53, p < 0.001) and were in good agreement with the assessment of expiratory obstruction from subjective curvature assessment.

CONCLUSIONS

Our general findings show that individual lung function variables do not correlate well with symptoms, whereas subjective curvature assessment is thought to be helpful. With the average curvature index we have illustrated a potential clinical usefulness of quantifying the curvatures of MEFV curves.

Heat transfer variations of bicycle helmets

Bicycle helmets exhibit complex structures so as to combine impact protection with ventilation. A quantitative experimental measure of the state of the art and variations therein is a first step towards establishing principles of bicycle helmet ventilation. A thermal headform mounted in a climate-regulated wind tunnel was used to study the ventilation efficiency of 24 bicycle helmets at two wind speeds. Flow visualization in a water tunnel with a second headform demonstrated the flow patterns involved. The influence of design details such as channel length and vent placement was studied, as well as the impact of hair. Differences in heat transfer among the helmets of up to 30% (scalp) and 10% (face) were observed, with the nude headform showing the highest values. On occasion, a negative role of some vents for forced convection was demonstrated. A weak correlation was found between the projected vent cross-section and heat transfer variations when changing the head tilt angle. A simple analytical model is introduced that facilitates the understanding of forced convection phenomena. A weak correlation between exposed scalp area and heat transfer was deduced. Adding a wig reduces the heat transfer by approximately a factor of 8 in the scalp region and up to one-third for the rest of the head for a selection of the best ventilated helmets. The results suggest that there is significant optimization potential within the basic helmet structure represented in modern bicycle helmets.