Search

Recently, microparticles have been used as nanoporous membranes in microfluidic devices, contributing to various bioassays on a chip. Here, we report a self-assembled particle membrane (SAPM) integrated microfluidic device that concentrates particles into an aimed microchamber array by using evaporation-driven capillary forces, and manipulates the chemical environment of the microchamber array by sequentially introducing different solutions. We demonstrate that the SAPM-integrated microchamber array can concentrate microparticles and microbial cells up to 120-fold for 2 h and 35-fold for 1 h, respectively, resulting in remarkably high concentration factors. Additionally, we demonstrate that the microchamber array has high potential as a chemostat-like bioreactor because it can actively manipulate the initial seeding number of bacterial cells and continuously supply and sequentially switch fresh nutrients to them. As an example of various applications, the chemostat-like bioreactor was used as a microbial biosensor platform that enabled microbial sensor cells to respond more efficiently and rapidly to external stimuli, such as heavy metal ions. This was made possible by almost eliminating the initial lag phase that dramatically shortened the whole assay time. Notably, the SAPM-integrated microchamber array not only facilitates various bioassays on a chip but also provides unprecedented experimental platforms to study microorganisms in a simple and convenient manner. [ABSTRACT FROM AUTHOR]

Surface-enhanced Raman scattering (SERS) spectroscopy is still considered poorly reproducible despite its numerous advantages and is not a sufficiently robust analytical technique for routine implementation outside of academia. In this article, we present a self-supervised deep learning-based information fusion technique to minimize the variance in the SERS measurements of multiple laboratories for the same target analyte. In particular, a variation minimization model, coined the minimum-variance network (MVNet), is designed. Moreover, a linear regression model is trained using the output of the proposed MVNet. The proposed model showed improved performance in predicting the concentration of the unseen target analyte. The linear regression model trained on the output of the proposed model was evaluated by several well-known metrics, such as root mean square error of prediction (RMSEP), BIAS, standard error of prediction (SEP), and coefficient of determination (R2). The leave-one-lab-out cross-validation (LOLABO-CV) results indicate that the MVNet also minimizes the variance of completely unseen laboratory datasets while improving the reproducibility and linear fit of the regression model. The Python implementation of MVNet and the code for the analysis can be found on the GitHub page https://github.com/psychemistz/MVNet. [ABSTRACT FROM AUTHOR]

This communication presents a microfluidic method for size-based cell sorting, which provides a simple and robust approach for cell cycle synchronization by manual and stand-alone operation. [ABSTRACT FROM AUTHOR]

The integration of nanoporous membranes into microfluidic devices allows a wide range of analytical and biochemical applications such as stable concentration gradient generation, sample pre-concentration, and ion and biomolecule filtration in a controllable manner. However, further applications of nanoporous membranes in microfluidic devices require rapid and controllable fabrication methods of various nanoporous precursor materials; currently, few such methods exist. Here, we describe simple and robust methods that can be used for microfabricating four different precursor materials as leakage-tight membranes in a microfluidic channel network. The methods consist of a common integration process and individual solidification processes such as solvent evaporation, UV-curing, and temperature treatment. We demonstrate that the fabricated membranes can be used for electrokinetic, nanofluidic pre-concentration of bio-samples such as proteins, cells, and microspheres on either the anodic or cathodic side of the membranes. In addition, we not only characterize the physicochemical properties of the membranes such as conductance of membrane-integrated microchannels, relative permselectivity, and pre-concentration ability, but also compare fabrication availability, membrane robustness, surface charge density tunability and biocompatibility with buffer solutions. The methods are versatile for many nanoporous precursor materials and easy to control the location and dimension of the membranes. Hence, the methods developed and the characterized properties of the membranes tested in this work could be widely employed for further applications of nanoporous membranes in microfluidic systems. [ABSTRACT FROM AUTHOR]

We describe a novel and simple mechanism for inducing ion concentration polarization (ICP) using a surface-patterned perm-selective nanoporous film like Nafion in single, open microchannels. Such a surface-patterned Nafion film can rapidly transport only cations from the anodic side to the cathodic side through the nanopore clusters so that it is possible to generate an ICP phenomenon near the Nafion film. In this work, we characterize transport phenomena and distributions of ion concentration under various electric fields near the Nafion film and show that single-channel based ICP (SC-ICP) is affected by Nafion film thicknesses, strengths of applied electric fields, and ionic strengths of buffer solutions. We also emphasize that SC-ICP devices have several advantages over previous dual-channel ICP (DC-ICP) devices: easy and simple fabrication processes, inherently leak-tight, simple experimental setup requiring only one pair of electrodes, stable and robust ICP induced rapidly, and low electrical resistances helping to avoid Joule heating, and membrane perm-selectivity breakdown but allowing as high bulk flow as an open, plain microchannel. As an example of applications, we demonstrate that SC-ICP devices not only have high potential in pre-concentrating proteins in massively parallel microchannels but also enable the concentration and lysis of bacterial cells simultaneously and continuously on a chip; therefore, proteins within the cells are extracted, separated from the concentrated cells and then pre-concentrated at a different location that is closer to the Nafion film. Hence, we believe that the SC-ICP devices have higher possibilities of being easily integrated with traditional microfluidic systems for analytical and biotechnological applications. [ABSTRACT FROM AUTHOR]

Progress in neurological research has experienced bottlenecks owing to the limited availability of purified primary neurons. Since neuronal cells are non-proliferative, it is necessary to obtain purified neurons from animal models or human patients for experimental work. However, currently available methods for purifying primary neurons are time-consuming (taking approximately 1 week), and suffer from insufficient viability and purity. Here, we report a method for rapid enrichment of neurons from the mouse embryonic dorsal root ganglion (DRG), using a fully-automated continuous centrifugal microfluidics (CCM) based neuron purification disc (NPD). Non-neuronal cells were removed via negative depletion by combining density gradient centrifugation and immunomagnetic separation. The CCM-NPD platform enables effective isolation of intact neurons within 13 min, which is approximately 800 times faster than the conventional chemical purification method. Furthermore, the neurons purified using the CCM-NPD platform showed better neurite growth, along with higher viability (93.5%) and purity (97.0%) after 1 week of culture, compared to the chemical purification method. Therefore, the proposed automated and rapid system yields purified DRG neurons with high viability and purity, while avoiding the use of harsh chemicals. We believe this system will significantly mitigate the shortage of purified primary neurons and advance neurological research. [ABSTRACT FROM AUTHOR]

Nanoparticle separation techniques are of significant importance in nanoscience and nanotechnological applications and different concentration gradients, electric/dielectric forces, flow/pressure fields, and acoustic waves have been intensively investigated. However, precise separation of nanoparticles has many technical challenges in terms of sizes, shapes, and material properties, limiting the separation resolution, capability, applicability, throughput and so on. In this study, we present a microfluidic device for continuous separation of nanoparticles by combining diffusiophoresis (DP) and electrophoresis (EP) to achieve high separation performance. Concentration gradients formed from sodium chloride (NaCl) and potassium acetate (K-acetate) passively drive the diffusiophoretic migration of nanoparticles. Simultaneously, a low electric potential is additionally applied to impose a synergistic effect on nanoparticle migration by size and surface charge, which is called low-electric-potential-assisted DP (LEPDP). Using a LEPDP-based separation device, we demonstrate the separation of nanoparticles having different sizes (diameters of 500, 200, and 50 nm) and under different surface-charge conditions (carboxylated polystyrene, silica, and polylactide). The resulting separation performance exceeded 95%, in terms of size uniformity, which is about two times better than that obtained using DP alone. We also emphasize that the enhancement of separation performance only needs a small voltage (<1 V), thereby demonstrating that our multiphysical approach could be utilized for high-resolution and portable nanoparticle separation on a chip without the side effects associated with high electric fields. Lastly, we ensure that rapid and precise bio/chemical sensing and analysis of various nanosized particles would be envisioned by strategically combining two nonlinear but synergistic migration effects. [ABSTRACT FROM AUTHOR]