Biomicrofluidics

Larval zebrafish are an appropriate animal and laboratory model for exploring the neural mechanisms underlying cognitive abilities, especially concerning their applicability to human cognition. To replicate the natural habitats of such organisms at the laboratory level, microfluidic platforms are employed as a valuable tool in mimicking the intricate spatiotemporal stimuli together with high-throughput screening. This work investigated the memory capabilities of zebrafish larvae across different developmental stages (5–9 days post-fertilization) by employing sound stimuli within the microfluidic environment. Notably, the sound signal with 1200 Hz frequency was observed to be significantly sensitive among all the considered developmental stages in stimulating the responses. In addition, the impact of the memory enhancer drug methylene blue (MB) was tested, revealing a significant enhancement in cognitive performance compared to controls. Specifically, learning (training) and memory (post-training) were observed to exhibit 2-fold and 20-fold increases, respectively, in MB-exposed larvae. In addition to sound stimuli and memory enhancer drugs, the impact of environmental complexity on cognitive abilities was examined by employing different designs of microchannels, such as series, parallel, and combined configurations. The presented experimental paradigm provides a robust framework for various zebrafish studies, including sensory processing mechanisms, learning capabilities, and potential therapeutic interventions.

With the transport of soft and multiphase systems such as droplets and vesicles, the controlled movement of these systems could be regulated in microfluidic channels using an external electrical field is a convenient method for further studying and even tuning micro-transport behaviors. The electric field induces complex electrohydrodynamic behaviors in such systems with considerable impact on their deformation, motion, and interaction with the surrounding fluid. Introducing an electric field exerts stresses at the interface of these fluids, which ensures precise control over their deformation and motion with the features of droplets or vesicles that are vital for their subsequent manipulation inside confined microchannels. Here, electrically modulated transport dynamics in soft multiphase systems, specifically droplets and vesicles, in microfluidic systems are studied meticulously. In this review work, we study how the electric field strength, fluid properties, and membrane characteristics, all of which are important to the directed motion of these systems, are coupled to one another. It also notes that vesicles, with their bilayer lipid membranes, have unique dynamics—such as the formation of membrane tensions and bending rigidity—that affect their electrohydrodynamic behaviors, unlike simple droplets. Studying the electrically driven dynamics of the soft matter, this review offers useful perspectives on the creation of next-generation microfluidics devices, ranging from drug delivery to synthetic biology and materials manufacturing. The effects of the field strength, frequency, and geometry on the transport properties of the droplets and vesicles and highlighting the rich interplay between the electrostatic forces and the inherent properties of soft matter are studied systematically. Recent advances in experimental methods (such as high-precision imaging, micro-manipulation, and sophisticated computational modeling) have also taken our understanding of these electrohydrodynamic processes to new heights. This review further explores potential applications of these technologies in lab-on-a-chip platforms, drug delivery systems, and bioanalytical tools and highlights challenges, including stability, scalability, and reproducibility. The conclusion includes proposed directions for future research aimed at enhancing the localization, control, and efficiency of electrokinetic manipulation in soft matter-based microfluidic systems.

Acoustofluidics, offering contact-free and precise manipulation of micro-objects, has emerged as a transformative tool for various biological and medical applications. In recent years, significant advancements have been made in droplet manipulation using acoustic waves. This review provides an in-depth exploration of acoustofluidic techniques for droplet manipulation, presenting a balanced perspective on the role of this versatile platform across diverse applications. The paper begins by introducing the underlying mechanism of acoustic forces acting on the droplets, followed by a comprehensive discussion of acoustofluidic techniques tailored for essential unit operations, such as droplet generation, separation, merging, splitting, steering, trapping, in-droplet sample manipulation, sample control within sessile droplets, and digital acoustofluidics. Finally, the prospects and limitations of acoustofluidics for droplet manipulations are also discussed, suggesting the future direction of droplet acoustofluidics research.

Paper-based microfluidic devices are widely used in point-of-care diagnostics, yet the fundamental mechanisms governing analyte transport under partially saturated conditions remain insufficiently characterized. Here, we systematically investigate the concentration-dependent imbibition dynamics and particle trapping behavior of analyte/colloid-laden fluids in porous paper substrates. Using model food-dye colloids of varying particle sizes (∼0.3–4.5 μm) and concentrations (0.5–2 mg/ml), we quantify key saturation-dependent parameters and reveal their strong influence on wicking length and analyte retention. A semiempirical numerical model incorporating experimentally derived van Genuchten and Brooks–Corey parameters is developed to predict analyte flow under varying conditions. Our study demonstrates that particle size, concentration, and paper properties critically modulate transport behavior, with implications for reproducibility and sensitivity in lateral flow assays. Furthermore, through Damköhler number analysis, we propose practical design guidelines for optimal test line placement based on flow and reaction dynamics. This combined experimental and modeling framework offers new insights for the rational design and optimization of paper-based diagnostic platforms.

Microfluidic biochips (MBs) are transforming diagnostics, healthcare, and biomedical research. However, their rapid deployment has exposed them to diverse security threats, including structural tampering, material degradation, sample-level interference, and intellectual property (IP) theft, such as counterfeiting, overbuilding, and piracy. This perspective highlights emerging attack vectors and countermeasures aimed at mitigating these risks. Structural attacks, such as stealthy design code modifications, can result in faulty diagnostics. To address this, deep learning -based anomaly detection leverages microstructural changes, including optical changes such as shadows or reflections, to identify and resolve faults. Material-level countermeasures, including mechano-responsive dyes and spectrometric watermarking, safeguard against subtle chemical alterations during fabrication. Sample-level protections, such as molecular barcoding, ensure bio-sample integrity by embedding unique DNA sequences for authentication. At the IP level, techniques like watermarking, physically unclonable functions, fingerprinting, and obfuscation schemes provide robust defenses against reverse engineering and counterfeiting. Together, these approaches offer a multi-layered security framework to protect MBs, ensuring their reliability, safety, and trustworthiness in critical applications.

Microfluidic systems capable of generating uniform droplets are gaining attention in food, cosmetics, biochemical, and materials applications. While conventional shear- or interfacial tension-driven nozzle devices can generate highly monodisperse droplets (CV < 5%), their scalability is limited by complex flow designs and clogging. Post-array devices have recently emerged as a high-throughput alternative, producing quasi-monodisperse droplets (CV > 12%) by sequentially breaking larger droplets using micro-post structures. These devices offer shear-dependent tunability of droplet sizes, greater resistance to clogging, and scalability. Notably, droplet size is strongly influenced by the dispersed phase fraction, enabling potential decoupling of droplet size and dispersed phase fraction. This study reviews the principles and performance of post-array devices, compares them with other droplet generation methods, and examines their similarities to droplet splitting in T-junctions and premix membrane emulsification. Challenges such as improving droplet uniformity and miniaturization are also discussed to highlight the potential of post-array systems for practical emulsification applications.

Particle-wall interaction is important in various applications such as cell sorting, particle separation, the entire class of hydrodynamic filtration and its derivatives, etc. Yet, accurate implementation of interactions between the wall and finite-size particles is not trivial when working with the currently available particle tracking algorithms/packages as they typically work with point-wise particles. Herein, we report a particle tracking algorithm that takes into account interactions between particles of finite size and nearby solid objects. A particle is modeled as a set of circumferential points. While fluid–particle interactions are captured during the track of particle center, interactions between particles and nearby solid objects are modeled explicitly by examining circumferential points and applying a reflection scheme as needed to ensure impenetrability of solid objects. We also report a modified variant of auxiliary structured grid method to locate hosting cells, which in conjunction with a boundary condition scheme enables the capture of interactions between particles and solid objects. As a proof-of-concept, we numerically and experimentally study the particles’ motion within a deterministic lateral displacement microfluidic device. The results successfully demonstrate the zigzag and bump modes observed in our experiments. We also study a microfluidic device with pinched flow numerically and validate our results against experimental data from the literature. By demonstrating an almost 8 × speedup on a system with eight performance threads, our investigations suggest that the algorithm can benefit from parallel processing on multi-thread systems. We believe that the proposed framework can pave the way for designing related microfluidic chips precisely and conveniently.

Deterministic lateral displacement (DLD) is a popular technique for the size-based separation of particles. A key challenge in the design of DLD chips is to eliminate the fluid flow disturbance caused by channel sidewalls intersecting with pillar matrix. While there are numerous reports attempting to mitigate this issue by adjusting the gaps between pillars on the sidewalls and the closest ones residing on the bulk grid of DLD, there are only a few works that also configure the axial gap of pillars adjacent to the accumulation sidewall. Herein, we study various designs numerically to investigate the effects of geometrical configurations of sidewalls on the critical diameter and first stream flux fraction variations across the channel. Our results show that regardless of the model used for the boundary gap profile, applying a pressure balance scheme can improve the separation performance by reducing the critical diameter variations. In particular, we found that for a given boundary gap distribution, there can be two desired parameter sets with relatively low critical diameter variations. One is related to sufficiently low lateral resistance of interface unit cells next to the accumulation sidewall, while the other one emerges by reducing the axial resistance of the interface unit cells to an appropriate extent. This work should pave the way for designing DLD systems with improved performance, which can be critically important for applications such as the separation of rare cells, among others, wherein target species need to be concentrated into as narrow a stream as possible downstream of the device to enhance purity and the recovery rate simultaneously.

Manipulation of red blood cells (RBCs) in microscale has proven to play a pivotal role in various applications, such as disease diagnosis and drug delivery. Over the past decades, the capabilities of microscale manipulation techniques have evolved from simple particle manipulation to cells and organisms, with numerous microfluidic-based research tools being developed for RBC manipulation. This review first introduces the reported microscale manipulation techniques and their principles, including passive microfluidic methods based on microstructures and hydrodynamics, as well as active methods such as acoustic, optical, and electrical techniques. It then focuses on the application scenarios of these micro-scale manipulation methods for RBC manipulation, including the investigation of RBC mechanical properties, the preparation of RBC carriers, the control of RBC rotation, and RBC lysis. Finally, the future prospects of microscale techniques in RBC manipulation are discussed. This review offers a comprehensive comparison of various techniques, aiming to provide researchers from different fields with a broad perspective and to guide the continued development of microscale manipulation methods for RBC applications. It seeks to help researchers from diverse backgrounds stay informed about the latest trends and advancements in the field.

Silicon-based microfluidics enable the creation of highly complex, three-dimensional fluid networks. These comprise scalable channel sizes and monolithically integrated functionalities available from complementary–metal–oxide–semiconductor technology. On this versatile, solid-state platform, advanced manufacturing techniques exist that allow the channel walls to be directly electrified with one or multiple pairs of electrodes along the fluid-carrying channel. The electrodes have ideal electrostatic geometries, yielding homogeneous electric field distributions across the entire cross section of the microfluidic channel. As these are located directly at the channel, only low supply voltages are needed to achieve suitable field strengths. Furthermore, a controlled supply of charge carriers to the microfluidic channel is feasible. These configurations may serve numerous applications, including highly efficient mechanisms to manipulate droplets, cells, and molecular compounds, perform pico-injection or poration, trigger and control chemical reactions, or realize electrochemical and capacitive sensing modalities. In this perspective, we describe the generic design and fabrication of these electrodes and discuss their miniaturization and scaling properties. Furthermore, we forecast novel use cases and discuss challenges in the context of the most interesting applications.

Recent advances in microfluidic technology have shown the importance of precise temperature control in a wide range of biological applications. This perspective review presents a comprehensive overview of state-of-the-art microfluidic platforms that utilize thermal modulation for various applications, such as rapid nucleic acid amplification, targeted hyperthermia for cancer therapy, and efficient cellular lysis. We detail various heating mechanisms—including nanoparticle–driven induction, photothermal conversion, and electrothermal approaches (both external and on-chip)—and discuss how they are integrated within lab-on-a-chip systems. In parallel, advanced multi-modal sensing methods within microfluidics, ranging from conventional integrated sensors to cutting-edge quantum-based techniques using nanodiamond nitrogen-vacancy centers and suspended microchannel resonators, are highlighted. By integrating advanced multi-modal sensing capabilities into these microfluidic platforms, a broader range of applications are enabled, including single-cell analysis, metabolic profiling, and scalable diagnostics. Looking ahead, overcoming challenges in system integration, scalability, and cost-effectiveness will be essential to harnessing their full potential. Future developments in this field are expected to drive the evolution of lab-on-a-chip technologies, ultimately enabling breakthroughs in precision medicine and high-throughput biomedical applications.

Remote health monitoring has the potential to enable individuals to take control of their own health and well-being and to facilitate a transition toward preventative and personalized healthcare. Sweat can be sampled non-invasively and contains a wealth of information about the metabolic state of an individual, making it an excellent candidate for remote health monitoring. An accurate, rapid, and low-cost biofluid characterization technique is required to enable the widespread use of remote health monitoring. We previously introduced microfluidic impedance spectroscopy for the detection of electrolyte concentration in fluids, whereby a novel device architecture, measurement method, and analysis technique were presented for the characterization of cationic species. The purely electrical nature of this measurement technique removes the intermediate steps inherent in common rival technologies such as optical and electrochemical sensing, offering a range of advantages. In this work, we investigate the effect of temperature on microfluidic impedance spectroscopy of ionic species commonly present in biofluids. We find that the impedance spectra and concentration determination are temperature-dependent; remote health monitoring devices must be calibrated appropriately as they are likely to experience temperature fluctuations. Importantly, we demonstrate the ability of the method to measure the concentration of anionic species alongside that of cationic species, enabling the detection of chloride and lactate, which are useful biomarkers for hydration, cystic fibrosis, fatigue, sepsis, and hypoperfusion. We show that the presence of neutral species does not impair accurate determination of ionic concentration, thus, demonstrating the suitability of microfluidic impedance spectroscopy for non-invasive biofluid characterization.

Acoustic holography offers the ability to generate designed acoustic fields, enhancing the versatility of acoustic micromanipulation. However, the quality of the generated holograms depends on the nature of the iterative algorithm that is utilized, where the iterative angular spectrum approach (IASA) has been the standard method to date. Here, we introduce a novel approach that categorically improves IASA performance, where we apply the principles of simulated annealing for the generation of high-quality acoustic holograms. We utilize this to realize significant improvements in hologram quality via simulations, fabricated holograms, experimental particle patterning, and high-resolution 2D hydrophone scans. Comparing holograms produced from IASA and/or simulated annealing, we demonstrate that the use of simulated annealing in acoustic holography results in sharper reconstructions and improved hologram outputs across a range of evaluation metrics.

Thanks to their softness, biocompatibility, porosity, and ready availability, hydrogels are commonly used in microfluidic assays and organ-on-chip devices as a matrix for cells. They not only provide a supporting scaffold for the differentiating cells and the developing organoids, but also serve as the medium for transmitting oxygen, nutrients, various chemical factors, and mechanical stimuli to the cells. From a bioengineering viewpoint, the transmission of forces from fluid perfusion to the cells through the hydrogel is critical to the proper function and development of the cell colony. In this paper, we develop a poroelastic model to represent the fluid flow through a hydrogel containing a biological cell modeled as a hyperelastic inclusion. In geometries representing shear and normal flows that occur frequently in microfluidic experiments, we use finite-element simulations to examine how the perfusion engenders interstitial flow in the gel and displaces and deforms the embedded cell. The results show that pressure is the most important stress component in moving and deforming the cell, and the model predicts the velocity in the gel and stress transmitted to the cell that is comparable to in vitro and in vivo data. This work provides a computational tool to design the geometry and flow conditions to achieve optimal flow and stress fields inside the hydrogels and around the cell.

Despite the widespread application of microfluidic chips in research fields, such as cell biology, molecular biology, chemistry, and life sciences, the process of designing new chips for specific applications remains complex and time-consuming, often relying on experts. To accelerate the development of high-performance and high-throughput microfluidic chips, this paper proposes an automated Deterministic Lateral Displacement (DLD) chip design algorithm based on reinforcement learning. The design algorithm proposed in this paper treats the throughput and sorting efficiency of DLD chips as key optimization objectives, achieving multi-objective optimization. The algorithm integrates existing research results from our team, enabling rapid evaluation and scoring of DLD chip design parameters. Using this comprehensive performance evaluation system and deep Q-network technology, our algorithm can balance optimal separation efficiency and high throughput in the automated design process of DLD chips. Additionally, the quick execution capability of this algorithm effectively guides engineers in developing high-performance and high-throughput chips during the design phase.

To address the growing need for accurate lung models, particularly in light of respiratory diseases, lung cancer, and the COVID-19 pandemic, lung-on-a-chip technology is emerging as a powerful alternative. Lung-on-a-chip devices utilize microfluidics to create three-dimensional models that closely mimic key physiological features of the human lung, such as the air–liquid interface, mechanical forces associated with respiration, and fluid dynamics. This review provides a comprehensive overview of the fundamental components of lung-on-a-chip systems, the diverse fabrication methods used to construct these complex models, and a summary of their wide range of applications in disease modeling and aerosol deposition studies. Despite existing challenges, lung-on-a-chip models hold immense potential for advancing personalized medicine, drug development, and disease prevention, offering a transformative approach to respiratory health research.

The gut–brain axis (GBA) connects the gastrointestinal tract and the central nervous system (CNS) via the peripheral nervous system and humoral (e.g., circulatory and lymphatic system) routes. The GBA comprises a sophisticated interaction between various mammalian cells, gut microbiota, and systemic factors. This interaction shapes homeostatic and pathophysiological processes and plays an important role in the etiology of many disorders including neuropsychiatric conditions. However, studying the underlying processes of GBA in vivo, where numerous confounding factors exist, is challenging. Furthermore, conventional in vitro models fall short of capturing the GBA anatomy and physiology. Microfluidic platforms with integrated sensors and actuators are uniquely positioned to enhance in vitro models by representing the anatomical layout of cells and allowing to monitor and modulate the biological processes with high spatiotemporal resolution. Here, we first briefly describe microfluidic technologies and their utility in modeling the CNS, vagus nerve, gut epithelial barrier, blood–brain barrier, and their interactions. We then discuss the challenges and opportunities for each model, including the use of induced pluripotent stem cells and incorporation of sensors and actuator modalities to enhance the capabilities of these models. We conclude by envisioning research directions that can help in making the microfluidics-based GBA models better-suited to provide mechanistic insight into pathophysiological processes and screening therapeutics.

The micromechanical measurement field has struggled to establish repeatable techniques because the deforming stresses can be difficult to model. A recent numerical study [Lu et al., J. Fluid Mech. 962, A26 (2023)] showed that viscoelastic capsules flowing through a cross-slot can achieve a quasi-steady strain near the extensional flow stagnation point that is equal to the equilibrium static strain, thereby implying that the capsule's elastic behavior can be captured in continuous device operation. However, no experimental microfluidic cross-slot studies have reported quasi-steady strains for suspended cells or particles to our knowledge. Here, we demonstrate experimentally the conditions necessary for the cross-slot microfluidic device to replicate a uniaxial creep test at the microscale and at relatively high throughput. By using large dimension cross-slots relative to the microparticle diameter, our cross-slot implementation creates an extensional flow region that is large enough for agarose hydrogel microparticles to achieve a strain plateau while dwelling near the stagnation point. This strain plateau will be key for accurately and precisely measuring viscoelastic properties of small microscale biological objects. We propose an analytical mechanical model to extract linear viscoelastic mechanical properties from observed particle strain histories. Particle image velocimetry measurements of the unperturbed velocity field is used to estimate where in the device particles experienced extensional flow and where the mechanical model might be applied to extract mechanical property measurements. Finally, we provide recommendations for applying the cross-slot microscale creep experiment to other biomaterials and criteria to identify particles that likely achieved a quasi-steady strain state.

Droplet microfluidics has emerged as a versatile and powerful tool for various analytical applications, including single-cell studies, synthetic biology, directed evolution, and diagnostics. Initially, access to droplet microfluidics was predominantly limited to specialized technology labs. However, the landscape is shifting with the increasing availability of commercialized droplet manipulation technologies, thereby expanding its use to non-specialized labs. Although these commercial solutions offer robust platforms, their adaptability is often constrained compared to in-house developed devices. Consequently, both within the industry and academia, significant efforts are being made to further enhance the robustness and automation of droplet-based platforms, not only to facilitate technology transfer to non-expert laboratories but also to reduce experimental failures. This Perspective article provides an overview of recent advancements aimed at increasing the robustness and accessibility of systems enabling complex droplet manipulations. The discussion encompasses diverse aspects such as droplet generation, reagent addition, splitting, washing, incubation, sorting, and dispensing. Moreover, alternative techniques like double emulsions and hydrogel capsules, minimizing or eliminating the need for microfluidic operations by the end user, are explored. These developments are foreseen to facilitate the integration of intricate droplet manipulations by non-expert users in their workflows, thereby fostering broader and faster adoption across scientific domains.

Atmospheric ice-nucleating particles (INPs) make up a vanishingly small proportion of atmospheric aerosol but are key to triggering the freezing of supercooled liquid water droplets, altering the lifetime and radiative properties of clouds and having a substantial impact on weather and climate. However, INPs are notoriously difficult to model due to a lack of information on their global sources, sinks, concentrations, and activity, necessitating the development of new instrumentation for quantifying and characterizing INPs in a rapid and automated manner. Microfluidic technology has been increasingly adopted by ice nucleation research groups in recent years as a means of performing droplet freezing analysis of INPs, enabling the measurement of hundreds or thousands of droplets per experiment at temperatures down to the homogeneous freezing of water. The potential for microfluidics extends far beyond this, with an entire toolbox of bioanalytical separation and detection techniques developed over 30 years for medical applications. Such methods could easily be adapted to biological and biogenic INP analysis to revolutionize the field, for example, in the identification and quantification of ice-nucleating bacteria and fungi. Combined with miniaturized sampling techniques, we can envisage the development and deployment of microfluidic sample-to-answer platforms for automated, user-friendly sampling and analysis of biological INPs in the field that would enable a greater understanding of their global and seasonal activity. Here, we review the various components that such a platform would incorporate to highlight the feasibility, and the challenges, of such an endeavor, from sampling and droplet freezing assays to separations and bioanalysis.

Circulating tumor cells are central to metastasis, a particularly malign spread of cancer beyond its original location. While rare, there is growing evidence that the clusters of circulating tumor cells are significantly more harmful than individual cells. Microfluidic platforms constitute the core of circulating tumor cell cluster research, allowing cluster detection, analysis, and treatment. In this work, we propose a new mathematical model of circulating tumor cell clusters and apply it to simulate the dynamics of the aggregates inside a microfluidic channel with the external flow of a fluid. We leverage our previous model of the interactions of circulating tumor cells with varying clustering affinities and introduce explicit bonds between the cells that makeup a cluster. We show that the bonds have a visible impact on the cluster dynamics and that they enable the reproduction of known cluster flow and deformation patterns. Furthermore, we demonstrate that the dynamics of these aggregates are sensitive to bond properties, as well as initialization and flow conditions. We believe that our modeling framework represents a valuable mesoscopic formulation with an impact beyond circulating tumor cell clusters, as cell aggregates are common in both nature and applications.

Gap junction connectivity is crucial to intercellular communication and plays a key role in many critical processes in developmental biology. However, direct analysis of gap junction connectivity in populations of developing cells has proven difficult due to the limitations of patch clamp and dye diffusion based technologies. We re-examine a microfluidic technique based on the principle of laminar flow, which aims to electrically measure gap junction connectivity. In the device, the trilaminar flow of a saline sheathed sucrose solution establishes distinct regions of electrical conductivity in the extracellular fluid spanning an NRK-49F cell monolayer. In theory, the sucrose gap created by laminar flow provides sufficient electrical isolation to detect electrical current flows through the gap junctional network. A novel calibration approach is introduced to account for stream width variation in the device, and elastomeric valves are integrated to improve the performance of gap junction blocker assays. Ultimately, however, this approach is shown to be ineffective in detecting changes in gap junction impedance due to the gap junction blocker, 2-APB. A number of challenges associated with the technique are identified and analyzed in depth and important improvements are described for future iterations.

In the field of microfluidics, high-pressure microfluidics technology, which utilizes high driving pressure for microfluidic analysis, is an evolving technology. This technology combines microfluidics and pressurization, where the flow of fluid is controlled by means of high-pressure-driven devices greater than 10 MPa. This paper first reviews the existing high-pressure microfluidics systems and describes their components and applications. Then, it summarizes several materials used in the microfabrication of high-pressure microfluidics chips, reviewing their properties, processing methods, and bonding methods. In addition, advanced laser processing techniques for the microfabrication of high-pressure microfluidics chips are described. Last, the paper examines the analytical detection methods employed in high-pressure microfluidics systems, encompassing optical and electrochemical detection methods. The review of analytical detection methods shows the different functions and application scenarios of high-pressure microfluidics systems. In summary, this study provides an efficient and advanced microfluidics system, which can be widely used in chemical engineering, food industry, and environmental engineering under high pressure conditions.

Monitoring platelet aggregation is crucial for predicting thrombotic diseases and identifying the risk of bleeding or resistance to antiplatelet drugs. This study developed a microfluidic device to measure platelet activation with high sensitivity. By controlling exposure time through repeated reinjections, the device enables the detection of subtle changes in platelet activity influenced by lifestyle factors, such as alcohol consumption. Using computational fluid dynamics simulations, the design was optimized to achieve moderate shear stresses and fabricated with 3D printing. Experimental results revealed that pillars biased to one side partially accelerate the flow and inhibit platelet adhesion. A distinct difference in platelet adhesion was clearly observed before and after alcohol consumption. Despite the high standard deviations in platelet adhesion area, hematocrit, and viscosity after alcohol consumption, the area covered by adhered platelets increased by 3.12 times compared to that before alcohol consumption. This microfluidic chip offers potential for personalized health monitoring by distinguishing platelet variations caused by lifestyle or dietary habits. However, challenges such as reinjection procedures and large sample volumes require further investigation.

Glioblastoma multiforme, the most common type of highly aggressive primary brain tumor, is influenced by complex molecular signaling pathways, where microRNAs (miRNAs) play a critical regulatory role. Originating from glial cells, glioblastoma cells are affected by the physiological direct current electric field (dcEF) in the central nervous system. While dcEF has been shown to affect glioblastoma migration (electrotaxis), the specific impact on glioblastoma intercellular communication and miRNA expression in glioblastoma cells and their exosomes remains unclear. This study aims to fill this gap by investigating the differential expression of microRNAs in glioblastoma cells and exosomes under dcEF stimulation. We have developed a novel, reversibly sealed dcEF stimulation bioreactor that ensures uniform dcEF stimulation across a large cell culture area, specifically targeting glioblastoma cells and primary human astrocytes. Using microarray analysis, we examined differential miRNA profiles in both cellular and exosomal RNAs. Our study identified shared molecular targets and pathways affected by dcEF stimulation. Our findings reveal significant changes in miRNA expression due to dcEF stimulation, with specific miRNAs, such as hsa-miR-4440 being up-regulated and hsa-miR-3201 and hsa-mir-548g being down-regulated. Future research will focus on elucidating the molecular mechanisms of these miRNAs and their potential as diagnostic biomarkers. The developed platform offers high-quality dcEF stimulation and rapid sample recovery, with potential applications in tissue engineering and multi-omics molecular analysis.