Particle Sorting Research Articles

Light-controllable liquid crystal platform for microparticle oscillations and transport.

Liquid crystal colloids manifest complex motion caused by external stimuli, but tunable and addressable control of microsized objects remains a challenge. This study aims to demonstrate light-driven trapping, transport, and sustained periodic motions of microparticles by employing liquid crystal films as a light-controllable colloidal platform. The diverse motions of microscopic particles result from Marangoni convection coupled with elastic deformations in free-surface liquid crystal films subjected to light beam heating. The specific mode of particle motion, including damped and sustained oscillations, also combined with sustained rotation, is defined by the liquid crystal chirality, particle surface treatment, film thickness, and the power of the tightly focused light beam. The results reveal that free-surface liquid crystals provide a unique platform for the indirect optical manipulation of microscopic objects, paving the way for novel applications in microfluidic tools, particle sorting and transport, micropatterning, and various micromachines.

Study on the Particle Sorting Performance for Reactor Monte Carlo Neutron Transport on Apple Unified Memory GPUs

In simulation of nuclear reactor physics using the Monte Carlo neutron transport method on GPUs, the sorting of particles plays a significant role in performance of calculation. Traditionally, CPUs and GPUs are separated devices connected at low data transfer rate and high data transfer latency. Emerging computing chips tend to integrate CPUs and GPUs. One example is the Apple silicon chips with unified memory. Such unified memory chips have opened doors for new strategies of collaboration between CPUs and GPUs for Monte Carlo neutron transport. Sorting particles on CPU and transport on GPU is an example of such new strategy, which has been suffering the high CPU-GPU data transfer latency on the traditional devices with separated CPU and GPU. The finding is that for the Apple M2 max and M3 max chip, sorting on CPU leads to better performance per power than sorting on GPU for the ExaSMR whole core benchmark problems and the HTR-10 high temperature gas reactor fuel pebble problem. The partially sorted particle order has been identified to contribute to the higher performance with CPU sort than GPU. The in-house code using both CPU and GPU achieves 7.6 times (M3 max) power efficiency that of OpenMC on CPU for ExaSMR whole core benchmark with depleted fuel, and 130 times (M3 max) for HTR-10 fuel pebble benchmark with depleted fuel.

Method to Purify Phase-Separated p62 Bodies Using Fluorescence-Activated Particle Sorting.

p62 bodies are ubiquitin-positive cytoplasmic condensates formed by liquid-liquid phase separation. They are targeted by selective autophagy and play important roles in intracellular quality control and stress responses. However, little is known about their constituents. In this chapter, we describe a method for purifying p62 bodies using fluorescence-activated particle sorting. This method contributes to the identification of novel components of p62 bodies under various physiological and stress conditions.

Solute-particle separation in microfluidics enhanced by symmetrical convection.

The utilization of microfluidic technology for miniaturized and efficient particle sorting holds significant importance in fields such as biology, chemistry, and healthcare. Passive separation methods, achieved by modifying the geometric shapes of microchannels, enable gentle and straightforward enrichment and separation of particles. Building upon previous discussions regarding the effects of column arrays on fluid flow and particle separation within microchips, we introduced a column array structure into an H-shaped microfluidic chip. It was observed that this structure enhanced mass transfer between two fluids while simultaneously intercepting particles within one fluid, satisfying the requirements for particle interception. This enhancement was primarily achieved by transforming the originally single-mode diffusion-based mass transfer into dual-mode diffusion-convection mass transfer. By further optimizing the column array, it was possible to meet the basic requirements of mass transfer and particle interception with fewer microcolumns, thereby reducing device pressure drop and facilitating the realization of parallel and high-throughput microfluidic devices. These findings have enhanced the potential application of microfluidic systems in clinical and chemical engineering domains.

A centrifugal-driven spiral microchannel microfiltration chip for emulsion and deformable particle sorting.

Droplet sorting and enrichment, as a prominent field within microfluidic technology, represent a pivotal stage in the manipulation of droplets and particles. In recent times, droplet sorting methods based on lab-on-disk (LOD) have garnered significant interest among researchers for their inherent merits, including high throughput, ease of operation, seamless device integration, and independence from supplementary driving forces. This study introduces a centrifugal force-driven microfluidic chip comprising spiral microchannels. The chip incorporates microhole arrays along the sidewall of the spiral channels, enabling size-based sorting and enrichment of microdroplets under the influence of multiple forces. Firstly, a comparative analysis was performed to assess the influence of the separation port structure and rotational speed on efficiency, and a mechanical modeling approach was employed to conduct kinetic analyses of droplet behavior during instantaneous separation. Those findings demonstrated a good agreement with the experimental results at ω < 100 rpm. Subsequently, sorting experiments on homogeneous droplets indicated that repetitive sorting could increase the recovery ratios, RT(α), of high-concentration droplets (20.7%) from 35.3% to over 80%. We also conducted a sorting experiment on three-component homogeneous-phase emulsions using a serially connected chip array, and the sorting throughput was 0.58 mL min-1. As a result, the RT(α) for 60 and 160 μm droplets were 99.4% and 88.9%, respectively. Lastly, we conducted elution experiments and dual-sample sorting on a single chip, and the fluorescence results demonstrated that this study provided an efficient and non-cross-contaminating sorting method for non-homogenous phase multi-sample microreactor units.

Isolation of Phytochrome B Photobodies.

Phytochrome B (phyB), a plant photoreceptor, forms a membraneless organelle known as a photobody. Here, we present a protocol for the isolation of phyB photobodies through fluorescence-activated particle sorting from mature transgenic Arabidopsis leaves expressing phyB-GFP. This protocol involves the isolation of nuclei from frozen ground leaves using sucrose gradient centrifugation, the disruption of nuclear envelopes by sonication, and the subsequent isolation of phyB photobodies through fluorescence-activated particle sorting. We include experimental tips and notes for each step.

A novel electrophoretic assisted hydrophobic microdevice for enhancing blood cell sorting: design and numerical simulation.

Microfluidic technology has great advantages in the precise manipulation of micro-nano particles, and the hybrid microfluidic separation technology has attracted much attention due to the advantages of both active and passive separation technology at the same time. In this paper, the hydrophoresis sorting technique is combined with the dielectrophoresis technique, and a dielectrophoresis-assisted hydrophoresis microdevice is studied to separate blood cells. By using the dielectrophoresis force to change the suspension position of the cells in the channel, the scope of the hydrophoresis device for sorting particles is expanded. At the same time, the effects of microchannel width, fluid velocity, and electrode voltage on cell sorting were discussed, and the cell separation process was simulated. This work has laid a certain theoretical foundation for the rapid diagnosis of diseases in practical applications.

Machine learning-enhanced predictive modeling for arbitrary deterministic lateral displacement design and test.

The separation of biological particles like cells and macromolecules from liquid samples is vital in clinical medicine, supporting liquid biopsies and diagnostics. Deterministic Lateral Displacement (DLD) is prominent for sorting particles in microfluidics by size. However, the design, fabrication, and testing of DLDs are complex and time-consuming. Researchers typically rely on finite element analysis to predict particle trajectories, which are crucial in evaluating the performance of DLD. Traditional particle trajectory predictions through finite element analysis often inaccurately reflect experimental results due to manufacturing and experimental variabilities. To address this issue, we introduced a machine learning-enhanced approach, combining past experimental data and advanced modeling techniques. Our method, using a dataset of 132 experiments from 40 DLD chips and integrating finite element simulation with a microfluidic-optimized particle simulation algorithm (MOPSA) and a Random Forest model, improves trajectory prediction and critical size determination without physical tests. This enhanced accuracy in simulation across various DLD chips speeds up development. Our model, validated against three DLD chip designs, showed a high correlation between predicted and experimental particle trajectories, streamlining chip development for clinical applications.

Acoustic trapping in the undergraduate laboratory

Acoustic trapping is used in modern biophysics laboratories to study cell adhesion or aggregation, to sort particles, or to build model tissues. Here, we create an acoustic trapping setup in liquid for an undergraduate instructional laboratory that is low-cost, easy to build, and produces results in a 1-hour laboratory period. In this setup, we use a glass slide, cover slip, and double-sided tape to make the sample chamber. A piezo-electric transducer connected to a function generator serves as the acoustic source. We use this setup to measure the node spacing (millimeters) and the acoustic trap force (picoNewtons). We anticipate that the simplicity of the experimental setup, the tractability of the theoretical equations, and the richness of the research topics on the subject will lead to an undergraduate laboratory with many interesting student projects.

Cross-shelf processes of terrigenous organic matter drive mercury speciation on the east siberian shelf in the Arctic Ocean

The cross-shelf distributions of total mercury (THg), methylmercury (MeHg) and organic and inorganic matter, as well as the presence of the hgcA gene were investigated on the East Siberian Shelf (ESS) to understand the processes underlying the speciation of sedimentary Hg. Samples were collected from 12 stations grouped into four zones based on water depth: inner shelf (5 stations), mid-shelf (3 stations), outer shelf (2 stations), and slope (2 stations). The THg concentration in the surface sediment increased from the inner shelf (0.25 ± 0.023 nmol g−1) toward the slope (0.52 nmol g−1), and, when normalized to total organic carbon content, the THg showed a positive correlation with the clay-to-sand ratio (r2 = 0.48, p = 0.012) and degree of chemical weathering (r2 = 0.79, p = 0.0001). The highest MeHg concentrations (3.0 ± 1.8 pmol g−1), as well as peaks in the S/C ratio (0.012 ± 0.002) of sediment-leached organic matter, were found on the mid-shelf, suggesting that the activities of sulfate reducers control the net Hg(II) methylation rates in the sediment. This was supported by results from a principal component analysis (PCA) performed with Hg species concentrations and sediment-leached organic matter compositions. The site-specific variation in MeHg showed the highest similarity with that of CHONS compounds in the PCA, where Deltaproteobacteria were projected to be putative Hg(II) methylators in the gene analysis. In summary, the hydrodynamic sorting of lithogenic particles appears to govern the cross-shelf distribution of THg, and in situ methylation is considered a major source of MeHg in the ESS sediment.

Inertial migration of fine mineral particles in a curved microfluidic channel: Demystifying the role of non-neutrally buoyant particles

Fine mineral particles (FMPs) are ubiquitous in hazardous waste derived from metal mining, processing, and smelting. Inertial microfluidics has sparked tremendous attention due to its potential applications in separating neutral buoyant particles. However, it often fails when applied into non-neutral buoyant FMPs. The inertial migration and focusing tendencies of FMPs were still unknown. Herein, we present a modified microfluidic experiment platform to ensure the steady flow of FMPs in microfluidic systems. This platform avoids the deposition issue of FMPs by combined sample input and suspension system along with design of effective flow rate. FMPs of various particle diameter (2.2 μm, 6.8 μm and 10.2 μm, density of 6.29 g/cm3 or 3.2 g/cm3) were classified and compared to neutral buoyant particles (1.1 μm, 7 μm and 9.9 μm, density of 1.05 g/cm3) to investigate their differences in migration and focusing behaviors within a curved microfluidic channel (CR = 0.07). The migration dynamics of particles with multiple scale sizes may be divided into focusing, rough focusing, and non-focusing modes. Results revealed that a high density of FMPs had less effect on FMP migration and focusing behaviors in three modes. Nonetheless, the variability of FMP size and shape must be considered, as it will induce a shift in particle focusing position and, ultimately, might inhibit FMP separation in microfluidic channels. This work provides an experimental basis for the microfluidic behaviors of FMPs and might give advanced support for the possible application of microfluidic technology in mineral particle separation and sorting.

A minority of final stacks yields superior amplitude in single-particle cryo-EM

Cryogenic electron microscopy (cryo-EM) is widely used to determine near-atomic resolution structures of biological macromolecules. Due to the low signal-to-noise ratio, cryo-EM relies on averaging many images. However, a crucial question in the field of cryo-EM remains unanswered: how close can we get to the minimum number of particles required to reach a specific resolution in practice? The absence of an answer to this question has impeded progress in understanding sample behavior and the performance of sample preparation methods. To address this issue, we develop an iterative particle sorting and/or sieving method called CryoSieve. Extensive experiments demonstrate that CryoSieve outperforms other cryo-EM particle sorting algorithms, revealing that most particles are unnecessary in final stacks. The minority of particles remaining in the final stacks yield superior high-resolution amplitude in reconstructed density maps. For some datasets, the size of the finest subset approaches the theoretical limit.

The m6A reader ECT1 drives mRNA sequestration to dampen salicylic acid-dependent stress responses in Arabidopsis.

N 6-methyladenosine (m6A) is a common epitranscriptional mRNA modification in eukaryotes. Thirteen putative m6A readers, mostly annotated as EVOLUTIONARILY CONSERVED C-TERMINAL REGION (ECT) proteins, have been identified in Arabidopsis (Arabidopsis thaliana), but few have been characterized. Here, we show that the Arabidopsis m6A reader ECT1 modulates salicylic acid (SA)-mediated plant stress responses. ECT1 undergoes liquid-liquid phase separation in vitro, and its N-terminal prion-like domain is critical for forming in vivo cytosolic biomolecular condensates in response to SA or bacterial pathogens. Fluorescence-activated particle sorting coupled with quantitative PCR analyses unveiled that ECT1 sequesters SA-induced m6A modification-prone mRNAs through its conserved aromatic cage to facilitate their decay in cytosolic condensates, thereby dampening SA-mediated stress responses. Consistent with this finding, ECT1 overexpression promotes bacterial multiplication in plants. Collectively, our findings unequivocally link ECT1-associated cytosolic condensates to SA-dependent plant stress responses, advancing the current understanding of m6A readers and the SA signaling network.

Subcytoplasmic location of translation controls protein output

The cytoplasm is highly compartmentalized, but the extent and consequences of subcytoplasmic mRNA localization in non-polarized cells are largely unknown. We determined mRNA enrichment in TIS granules (TGs) and the rough endoplasmic reticulum (ER) through particle sorting and isolated cytosolic mRNAs by digitonin extraction. When focusing on genes that encode non-membrane proteins, we observed that 52% have transcripts enriched in specific compartments. Compartment enrichment correlates with a combinatorial code based on mRNA length, exon length, and 3' UTR-bound RNA-binding proteins. Compartment-biased mRNAs differ in the functional classes of their encoded proteins: TG-enriched mRNAs encode low-abundance proteins with strong enrichment of transcription factors, whereas ER-enriched mRNAs encode large and highly expressed proteins. Compartment localization is an important determinant of mRNA and protein abundance, which is supported by reporter experiments showing that redirecting cytosolic mRNAs to the ER increases their protein expression. In summary, the cytoplasm is functionally compartmentalized by local translation environments.

Sorting of large particles as a model for use in islet cryopreservation

Sorting of large particles as a model for use in islet cryopreservation

Fractal Characteristics of the Particle Size Distribution of Soil along an Urban–Suburban–Rural–Desert Gradient

In order to investigate the difference in particle size distribution of soil along an urban–suburban–rural–desert (USRD) gradient in an arid zone, surface soil (0–20 cm) samples were gathered at the urban, suburban, rural, and desert gradients in Urumqi, a northwestern Chinese city. Laser diffraction technology was adopted for determining the particle size distribution of the soil. Comparisons were made regarding the particle size distribution traits and soil properties in different gradient zones based on parameters such as the mean particle size (MG), fractal dimension (Dv), sorting coefficient (ơG), kurtosis (KG), and skewness (SKG). Results indicate that (1) particle size distribution in the urban, suburban, and rural soils was mainly sand particle sizes, whereas the desert soil was mainly composed of silt particle sizes. The average Dv value ranking for soil in each gradient is desert &gt; suburban &gt; urban &gt; rural. (2) The width and peak of the soil particle size frequency curve ranged within 0–500 μm, and the width and peak of the soil particle size frequency curve of each gradient were different. (3) The MG of rural soil was the highest, whereas the MG of desert soil was the lowest. The ơG values of the surface soil of each gradient were all greater than 4.0, and the sorting performance was extremely poor. The SKG of the desert and urban soil particle size showed extremely positive and negative skewness, respectively, while the SKG of the rural and suburban soil particle size showed extremely negative skewness. The KG values of the particle sizes of the rural and suburban soils exhibited narrow and medium peaks, whereas those of the urban and desert soils exhibited very broad and flat peaks. (4) The Dv of the soil in each gradient was strongly influenced by the soil particle size distribution, with the clay content of the soil playing a dominant role. Finally, the fractal dimension was identified as an indicator of the characteristics of the fine particle matter content in the soil structure. The novel contribution of this work is to clarify the fractal differences in the particle size distribution of soil along an urbanization gradient. The present research findings can offer fundamental information relating to the characteristics of soil particle size distribution along an urbanization gradient zone.

Synthesis and Characterization of Stimuli-Responsive Polymer Brushes in Nanofluidic Channels.

Nanochannels with controllable gating behavior are attractive features in a wide range of nanofluidic applications including viral detection, particle sorting, and flow regulation. Here, we use selective sidewall functionalization of nanochannels with a polyelectrolyte brush to investigate the channel gating response to variations in solution pH and ionic strength. The conformational and structural changes of the interfacial brush layer within the channels are interrogated by specular and off-specular neutron reflectometry. Simultaneous fits of the specular and off-specular signals, using a dynamical theory model and a fitting optimization protocol, enable detailed characterization of the brush conformations and corresponding channel geometry under different solution conditions. Our results indicate a collapsed brush state under basic pH, equivalent to an open gate, and an expanded brush state representing a partially closed gate upon decreasing the pH and salt concentration. These findings open new possibilities in noninvasive in situ characterization of tunable nanofluidics and lab-on-chip devices with advanced designs and improved functionality.

Particle sorting method based on swirl induction.

Fluid-based methods for particle sorting demonstrate increasing appeal in many areas of biosciences due to their biocompatibility and cost-effectiveness. Herein, we construct a microfluidic sorting system based on a swirl microchip. The impact of microchannel velocity on the swirl stagnation point as well as particle movement is analyzed through simulation and experiment. Moreover, the quantitative mapping relationship between flow velocity and particle position distribution is established. With this foundation established, a particle sorting method based on swirl induction is proposed. Initially, the particle is captured by a swirl. Then, the Sorting Region into which the particle aims to enter is determined according to the sorting condition and particle characteristic. Subsequently, the velocities of the microchannels are adjusted to control the swirl, which will induce the particle to enter its corresponding Induction Region. Thereafter, the velocities are adjusted again to change the fluid field and drive the particle into a predetermined Sorting Region, hence the sorting is accomplished. We have extensively conducted experiments taking particle size or color as a sorting condition. An outstanding sorting success rate of 98.75% is achieved when dealing with particles within the size range of tens to hundreds of micrometers in radius, which certifies the effectiveness of the proposed sorting method. Compared to the existing sorting techniques, the proposed method offers greater flexibility. The adjustment of sorting conditions or particle parameters no longer requires complex chip redesign, because such sorting tasks can be successfully realized through simple microchannel velocities control.

Automated design of a 3D passive microfluidic particle sorter.

Microfluidic chips that can sort mixtures of cells and other particles have important applications in research and healthcare. However, designing a sorter chip for a given application is a slow and difficult process, especially when we extend the design space from 2D into a 3D scenario. Compared to the 2D scenario, we need to explore more geometries to derive the appropriate design due to the extra dimension. To evaluate sorting performance, the simulation of the particle trajectory is needed. The 3D scenario brings particle trajectory simulation more challenges of runtime and collision handling with irregular obstacle shapes. In this paper, we propose a framework to design a 3D microfluidic particle sorter for a given application with an efficient 3D particle trajectory simulator. The efficient simulator enables us to simulate more samples to ensure the robustness of the sorting performance. Our experimental result shows that the sorter designed by our framework successfully separates the particles with the targeted size.

Engineering a tunable micropattern-array assay to sort single extracellular vesicles and particles to detect RNA and protein in situ.

The molecular heterogeneity of extracellular vesicles (EVs) and the co-isolation of physically similar particles, such as lipoproteins (LPs), confounds and limits the sensitivity of EV bulk biomarker characterization. Herein, we present a single-EV and particle (siEVP) protein and RNA assay (siEVP PRA) to simultaneously detect mRNAs, miRNAs, and proteins in subpopulations of EVs and LPs. The siEVP PRA immobilizes and sorts particles via positive immunoselection onto micropatterns and focuses biomolecular signals in situ. By detecting EVPs at a single-particle resolution, the siEVP PRA outperformed the sensitivities of bulk-analysis benchmark assays for RNA and protein. To assess the specificity of RNA detection in complex biofluids, EVs from various glioma cell lines were processed with small RNA sequencing, whereby two mRNAs and two miRNAs associated with glioblastoma multiforme (GBM) were chosen for cross-validation. Despite the presence of single-EV-LP co-isolates in serum, the siEVP PRA detected GBM-associated vesicular RNA profiles in GBM patient siEVPs. The siEVP PRA effectively examines intravesicular, intervesicular, and interparticle heterogeneity with diagnostic promise.