ELECTROPHORESIS最新文献

There is abundant literature that deals with the electrophoresis of biocolloids and environmental entities. Most of these nanoparticles can be classified as soft particles, which are core–shell structured in nature. Most existing studies assume the inner core of the soft particles to be rigid in nature. However, there are various core–shell structured nanoparticles for which the inner core is semisoft in nature, which allows ion penetration but restricts fluid flow. In addition, the distribution of the peripheral layer of the soft (soft particle with rigid inner core) or semisoft (soft particle with semisoft inner core) particle is not necessarily uniform. In the present article, we consider the electrophoresis of soft and semisoft particles with the diffuse distribution of monomers across the peripheral shell layer. The mathematical model adopted here is based on the Poisson–Boltzmann equation for the electric double-layer potential and Darcy–Brinkman extended Stokes equation for fluid flow. The study is carried out considering a weak electric field assumption, which allows us to linearize the set of equations using perturbation analysis. A finite difference–based method is adopted to solve the perturbed set of equations and thus to calculate the electrophoretic mobility. The results are presented to indicate the difference in electrophoretic mobility of soft and semisoft particles under similar electrostatic conditions. We have further indicated the dependence of pertinent parameters on the electrophoretic mobility of soft or semisoft nanoparticles.

Flow velocity control is of great interest for passive microfluidic devices that are used in point-of-care diagnostics. Various methods have been developed for the flow velocity control of microfluidic paper-based analytical devices (µPADs), whereas fewer attempts have been made for microfluidic thread-based analytical devices (µTADs). In this research, we attempt to control the flow velocity in cotton thread-based µTADs with electroosmotic pumping. Utilizing electroosmotic pumps, the flow velocity in the cotton thread-based µTADs can be decreased or increased by 13% and 106%, respectively. Moreover, the dynamic control of the flow velocity in the cotton thread-based µTADs is achieved by adjusting the real-time magnitude and direction of the voltage. Furthermore, we demonstrate that electroosmotic pumps can be used to overcome the hydrophobic valves in the cotton thread-based µTADs. We show that the delivery sequence of different liquid samples for a three-branch µTAD can be controlled. Finally, we show the potential application in lithium detection with a colorimetric assay. This method for flow velocity control shows promise for customizing the flow velocity and reaction time of cotton thread-based µTADs, and this method can potentially increase the sensitivity of detection.

Identifying analyzable metaphase chromosomes is crucial for karyotyping, a common procedure used by clinicians to diagnose genetic disorders and some forms of cancer. This task is often laborious and time-consuming, making it essential to develop automated, efficient, and reliable methods to assist clinical technicians. In this work, an original label-free microfluidic approach to identify potential metaphases is developed that uses impedance-based detection of individual flowing nuclei and machine-learning-based processing of synchronized high-speed videos. Specifically, impedance signals are used to identify nucleus-containing frames, which are then processed to extract the contour of each nucleus. Feature extraction is then performed, and both unsupervised and supervised classification approaches are implemented to identify potential metaphases from those features. The proposed framework is tested on K562 cells, and the highest classification accuracy is obtained with the supervised approach coupled with a feature selection procedure and the Synthetic Minority Over-sampling Technique (SMOTE). Overall, this study encourages future developments aimed at integrating a sorting functionality in the device, thus achieving an effective microfluidic system for metaphase enrichment.

Fully characterizing subtle differences in biologically important particles—including peptides, proteins, protein complexes, exosomes, viruses, organelles, and cells—is essential, as any alteration can impact their function. Detailed bioparticle characterization has broad implications for biomedical engineering, health care, food science, astrobiology, environmental studies, and microbiology. Dielectrophoresis (DEP) generates distinct forces based on subtle structural differences between bioparticles and has the potential to enable full characterization by quantifying the DEP response of a particle. However, current DEP techniques primarily rely on particle trapping, which presents limitations, particularly for nanoparticles. In contrast, streaming-based DEP measurement techniques remain largely unexplored. Here, we introduce a streaming-based microfluidic method inspired by the (inverse) classical scattering problem in physics. Using a custom insulator-based DEP microchannel (iDEP), the DEP susceptibility of a particle is quantified based on its predictable deflection magnitude. We demonstrate the feasibility of this approach for negative DEP using finite element analysis to conduct numerical scattering experiments on representative nanoparticles. To fully capture diffusion effects, we solved the steady-state Smoluchowski advection–diffusion equation to obtain concentration fields in the microchannel and extract realistic scattering profiles. Additionally, deterministic particle trajectories, computed in the absence of diffusion, were analyzed using streamline analysis to support the advection–diffusion results. Our results indicate that, under optimal conditions, the prototype iDEP microchannel approaches the necessary sensitivity for protein DEP characterization, even when diffusion is included. Like existing iDEP devices, a real iDEP scattering instrument is expected to be easy and inexpensive to operate. Combined with the straightforward processing and interpretation of the scattering data, the iDEP scattering technique has the potential to enable high-throughput, accurate bioparticle characterization.

Solid-state nanopores (SSNPs) are progressively gaining importance in biomolecular sensing and ionic circuit applications. Unlocking their full potential, however, requires the development of fabrication techniques that enable precise control over their sizes and shapes. Electron-beam (EB) shrinking provides precise, real-time feedback and is ideally suited to address these requirements. However, it necessitates an initial pore diameter smaller than the membrane thickness for effective shrinking without material addition. Typical focused ion beam (FIB)-drilled pores in silicon nitride membranes often fail to meet these requirements. Alternative efforts towards mitigating these bottlenecks through deploying hydrocarbon-mediated EB shrinkage face challenges due to uncontrolled carbon contamination or a lack thereof in cleaner transmission electron microscope (TEM) chambers. To address these challenges, here we report an alternative approach of high-precision hydrocarbon-mediated EB shrinking with hydrocarbons sourced externally through controlled surface reactions on exposure to ethanol. This provides several decisive advantages, including the reduction of pore diameters much larger than the membrane thickness and controlled shrinking in cleaner environments without contaminations. These measures accelerate nanopore fabrication, improve its predictability by eliminating the dependence on variable carbon contamination in vacuum chambers, and provide high-resolution live feedback during dimension tuning. As a result, our method supports the large-scale production of nanopores with analyte-specific, tuneable dimensions. This capability is particularly imperative for low-noise biomolecular sequencing applications that leverage electrically-modulated transport and sensing over nanoscales. These features could pave the way for the broader application of SSNPs, addressing long-standing challenges in their fabrication and functionalisation that remained unresolved thus far.

The MC1R gene, which is responsible for most cases of red hair, affects other hair and skin colours and contributes to differences in pain sensitivity and consists of a single exon with a very high level of allelic heterogeneity. In this research, we show that the Oxford Nanopore Technology (ONT) offers a good alternative to study the MC1R sequence variation. MinION was used to sequence the 1590 bp MC1R exon and minimal promoter in a cohort of 126 subjects, including 65 red-haired individuals, using the FLO-MIN106 (R9.4) chemistry. Assigned DNA variants were validated using Ion Torrent technology provided with Ion Xpress Plus Fragment Library Kit and the Personal Genome Machine^TM (PGM^TM). We show that the use of the latest sequencing kit V14 together with the FLO-MIN114 (R10.4.1) flow cell has eliminated the systematic errors observed with the previous chemistry and allowed reliable detection of short indels important for phenotypic inference. Importantly, the use of the algorithm implemented in the EPI2ME software enabled convenient and accurate read-based phase determination which can be useful in data interpretation.