Sheathless Size-Based Acoustic Particle Separation

Particle separation is of great interest in many biological and biomedical applications. Flow-based methods have been used to sort particles and cells. However, the main challenge with flow based particle separation systems is the need for a sheath flow for successful operation. Existence of the sheath liquid dilutes the analyte, necessitates precise flow control between sample and sheath flow, requires a complicated design to create sheath flow and separation efficiency depends on the sheath liquid composition. In this paper, we present a microfluidic platform for sheathless particle separation using standing surface acoustic waves. In this platform, particles are first lined up at the center of the channel without introducing any external sheath flow. The particles are then entered into the second stage where particles are driven towards the off-center pressure nodes for size based separation. The larger particles are exposed to more lateral displacement in the channel due to the acoustic force differences. Consequently, different-size particles are separated into multiple collection outlets. The prominent feature of the present microfluidic platform is that the device does not require the use of the sheath flow for positioning and aligning of particles. Instead, the sheathless flow focusing and separation are integrated within a single microfluidic device and accomplished simultaneously. In this paper, we demonstrated two different particle size-resolution separations; (1) 3 µm and 10 µm and (2) 3 µm and 5 µm. Also, the effects of the input power, the flow rate, and particle concentration on the separation efficiency were investigated. These technologies have potential to impact broadly various areas including the essential microfluidic components for lab-on-a-chip system and integrated biological and biomedical applications.Bankhead-Coley Florida Cancer Research Program (Grant # 1BN04-34183)National Science Foundation (U.S.) (Grant 0968736)National Science Foundation (U.S.) (Grant 1135419)National Science Foundation (U.S.) (Grant 1056475

Saltation under Martian Gravity and its Influence on the Global Dust Distribution

Dust and sand motion are a common sight on Mars. Understanding the interaction of atmosphere and Martian soil is fundamental to describe the planet's weather, climate and surface morphology. We set up a wind tunnel to study the lift of a mixture between very fine sand and dust in a Mars simulant soil. The experiments were carried out under Martian gravity in a parabolic flight. The reduced gravity was provided by a centrifuge under external microgravity. The onset of saltation was measured for a fluid threshold shear velocity of 0.82$\pm$0.04 m/s. This is considerably lower than found under Earth gravity. In addition to a reduction in weight, this low threshold can be attributed to gravity dependent cohesive forces within the sand bed, which drop by 2/3 under Martian gravity. The new threshold for saltation leads to a simulation of the annual dust cycle with a Mars GCM that is in agreement with observations

Drexel University

We present a 3D matching framework based on a many-to-many matching algorithm that works with skeletal representations of 3D volumetric objects. We demonstrate the performance of this approach on a large database of 3D objects containing more than 1000 exemplars. The method is especially suited to matching objects with distinct part structure and is invariant to part articulation. Skeletal matching has an intuitive quality that helps in defining the search and visualizing the results. In particular, the matching algorithm produces a direct correspondence between two skeletons and their parts, which can be used for registration and juxtaposition. 1

Comprehensive evaluation of the association of APOE genetic variation with plasma lipoprotein traits in U.S. Whites and African Blacks

Although common APOE genetic variation has a major influence on plasma LDL-cholesterol, its role in affecting HDL-cholesterol and triglycerides is not well established. Recent genome-wide association studies suggest that APOE also affects plasma variation in HDL-cholesterol and triglycerides. It is thus important to resequence the APOE gene to identify both common and uncommon variants that affect plasma lipid profile. Here, we have sequenced the APOE gene in 190 subjects with extreme HDL-cholesterol levels selected from two well-defined epidemiological samples of U.S. non-Hispanic Whites (NHWs) and African Blacks followed by genotyping of identified variants in the entire datasets (623 NHWs, 788 African Blacks) and association analyses with major lipid traits. We identified a total of 40 sequence variants, of which 10 are novel. A total of 32 variants, including common tagSNPs (≥5% frequency) and all uncommon variants (<5% frequency) were successfully genotyped and considered for genotype-phenotype associations. Other than the established associations of APOE∗2 and APOE∗4 with LDL-cholesterol, we have identified additional independent associations with LDL-cholesterol. We have also identified multiple associations of uncommon and common APOE variants with HDL-cholesterol and triglycerides. Our comprehensive sequencing and genotype-phenotype analyses indicate that APOE genetic variation impacts HDL-cholesterol and triglycerides in addition to affecting LDL-cholesterol

Genetic contribution of SCARB1 variants to lipid traits in African Blacks: A candidate gene association study

Background: High-density lipoprotein cholesterol (HDL-C) exerts many anti-atherogenic properties including its role in reverse cholesterol transport (RCT). Scavenger receptor class B member 1 (SCARB1) plays a key role in RCT by selective uptake of HDL cholesteryl esters. We aimed to explore the genetic contribution of SCARB1 to affecting lipid levels in African Blacks from Nigeria. Methods: We resequenced 13 exons and exon-intron boundaries of SCARB1 in 95 individuals with extreme HDL-C levels using Sanger method. Then, we genotyped 147 selected variants (78 sequence variants, 69 HapMap tagSNPs, and 2 previously reported relevant variants) in the entire sample of 788 African Blacks using either the iPLEX Gold or TaqMan methods. A total of 137 successfully genotyped variants were further evaluated for association with major lipid traits. Results: The initial gene-based analysis demonstrated evidence of association with HDL-C and apolipoprotein A-I (ApoA-I). The follow-up single-site analysis revealed nominal evidence of novel associations of nine common variants with HDL-C and/or ApoA-I (P < 0.05). The strongest association was between rs11057851 and HDL-C (P = 0.0043), which remained significant after controlling for multiple testing using false discovery rate. Rare variant association testing revealed a group of 23 rare variants (frequencies ≤1 %) associated with HDL-C (P = 0.0478). Haplotype analysis identified four SCARB1 regions associated with HDL-C (global P < 0.05). Conclusions: To our knowledge, this is the first report of a comprehensive association study of SCARB1 variations with lipid traits in an African Black population. Our results showed the consistent association of SCARB1 variants with HDL-C across various association analyses, supporting the role of SCARB1 in lipoprotein-lipid regulatory mechanism

Statistical Modeling of Single Target Cell Encapsulation

High throughput drop-on-demand systems for separation and encapsulation of individual target cells from heterogeneous mixtures of multiple cell types is an emerging method in biotechnology that has broad applications in tissue engineering and regenerative medicine, genomics, and cryobiology. However, cell encapsulation in droplets is a random process that is hard to control. Statistical models can provide an understanding of the underlying processes and estimation of the relevant parameters, and enable reliable and repeatable control over the encapsulation of cells in droplets during the isolation process with high confidence level. We have modeled and experimentally verified a microdroplet-based cell encapsulation process for various combinations of cell loading and target cell concentrations. Here, we explain theoretically and validate experimentally a model to isolate and pattern single target cells from heterogeneous mixtures without using complex peripheral systems.Wallace H. Coulter Foundation (Young Investigator in Bioengineering Award)National Institutes of Health (U.S.) (Grant R01AI081534)National Institutes of Health (U.S.) (Grant R21AI087107

Interaction of Colloidal Particles with Surfaces of Biological Significance

The adhesion of colloidal gold on membranes was examined with an electron microscope with protein on the membrane, on the colloidal particles and present on both membrane and particles. The conditions for best adhesion were determined. Quantitative measurements were caNied out using adhesion to the membrane to monitor diffusion, centrifugation and electrophoresis of colloidal particles. Electrophoresis in a centrifugal field was used as a nul method to determine the charge on the colloidal particle

Unsupervised system to classify SO2 pollutant concentrations in Salamanca, Mexico

Salamanca is cataloged as one of the most polluted cities in Mexico. In order to observe the behavior and clarify the influence of wind parameters on the Sulphur Dioxide (SO2) concentrations a Self-Organizing Maps (SOM) Neural Network have been implemented at three monitoring locations for the period from January 1 to December 31, 2006. The maximum and minimum daily values of SO2 concentrations measured during the year of 2006 were correlated with the wind parameters of the same period. The main advantages of the SOM Neural Network is that it allows to integrate data from different sensors and provide readily interpretation results. Especially, it is powerful mapping and classification tool, which others information in an easier way and facilitates the task of establishing an order of priority between the distinguished groups of concentrations depending on their need for further research or remediation actions in subsequent management steps. For each monitoring location, SOM classifications were evaluated with respect to pollution levels established by Health Authorities. The classification system can help to establish a better air quality monitoring methodology that is essential for assessing the effectiveness of imposed pollution controls, strategies, and facilitate the pollutants reduction