Human cardiac and neuronal stem cell-derived spheroids and organoids are emerging models for drug discovery and drug safety studies. Their electrical properties are frequently investigated by means of multielectrode arrays (MEAs). However, it is difficult to establish adequate electrode contacts between planar MEAs and these round, 3D cell models. Contractions of cardiac 3D models and movement artefacts during the application of test solutions can also disrupt the recordings. As a solution, we present a microfluidics device (hereinafter referred to as SphereChip) that enables quick and stable attachment of free-floating spherical cell models such as cardiospheres, cardioids and neurospheres to conventional planar MEAs. The device reduces motion artifacts and enables complete solution exchange. It was successfully used with two different MEA designs for field potential measurements and simultaneous imaging using fluorescent probes on small cardio- and neurospheres (diameter 300 to 500 μm) and larger cardioids (800 to 900 μm). We observed concentration-dependent prolongation of action and field potentials of cardiospheres by the potassium channel (Kv1.11) inhibitors E4031 and dofetilide. In neurospheres, application of a potassium channel (Kv7.2/7.3) activator ML213 reduced spiking and bursting. We present these results as proof of concept for the microfluidics device as a means to enable organ-on-a-chip studies combining field potential measurements with simultaneous imaging on spherical cell models using planar MEAs. The method is applicable to different MEA formats and holds promise as a workable platform for drug testing and toxicity studies.
We report an integrated electrowetting-on-dielectric (EWOD) digital microfluidic (DMF) platform for automated gene assembly directly from oligonucleotide pools (OPs). The system is implemented on a glass chip with through-glass vias...
We report on a preliminary study to test the liquid flow and particle diffusion properties in a device developed to deliver a proof-of-principle for the so-called Brownian sieve-enforced hydrodynamic chromatography (BS-HDC). This is a recently proposed novel separation principle to enhance the selectivity and efficiency of conventional HDC by combining it with a size sieving step through a micro- or nano-perforated separating wall interfacing a central feed channel to a peripheral auxiliary channel, characterized by a different average velocity that can only accept the small particles in the sample. We demonstrate the feasibility to fabricate a proof-of-principle device with a 400 nm sieving gap, and report on the flow and diffusion tests that were carried out with a fluorescent marker. These tests demonstrate the magnitude of the velocity fields and the transport across the nano-gaps between the central and peripheral auxiliary channel, which perfectly match with theoretical expectations. Specifically, transport across the nano-gaps is dominated by molecular diffusion. Nanosieving experiments with 235 and 563 nm particles showed the ability to selectively transport the smaller particles through the nano-sieving gaps while the larger particles remained in the central feed channel with 100% selectivity. However, the observed fluxes were found to be strongly influenced by local convective flows opposing the diffusive transport near the inlet and outlet of the channels, a phenomenon we think can be owed to the presence of persistent air bubbles in the flow distributors creating undesirable pressure fluctuations.
Extramedullary hematopoiesis is increasingly recognized as an important mechanism by which peripheral tissues augment immune responses during inflammation and infection. However, the mechanisms governing recruitment, retention, and local differentiation of circulating hematopoietic stem and progenitor cells (HSPCs) within human tissues remain poorly understood due to the lack of physiologically relevant experimental models. Here, we developed a human skin-on-a-chip microphysiological platform to investigate the role of circulating hematopoietic stem and progenitor cells (HSPCs) in cutaneous immune responses and their potential contribution to extramedullary hematopoiesis. The device recapitulates key features of human skin, including a perfusable vascular endothelium, fibroblast-populated dermis, and keratinocyte epidermis. Upon stimulation with pro-inflammatory cytokines or a TLR2 agonist, endothelial activation significantly increased ICAM-1 and VCAM-1 expression and enhanced recruitment of both neutrophils (PMNs) and HSPCs. While PMNs readily underwent transendothelial migration into the dermal compartment, HSPCs remained localized to the vascular niche. Notably, HSPCs adhered robustly and persisted on inflamed endothelium independent of SDF-1/CXCR4 signaling. Under granulopoietic conditions, these retained HSPCs differentiated locally within the vascular compartment into PMN-like cells capable of phagocytosis and exhibiting pathogen-responsive gene expression profiles. These findings provide evidence in a human model that circulating HSPCs can contribute to host defense via localized granulopoiesis without tissue infiltration, and suggests that the vascular niche itself may serve as a site of immune cell production during infection. The platform further offers a foundation for developing HSPC-based therapeutic strategies to combat antibiotic-resistant skin infections.
Droplet-based microfluidics have accelerated the discovery of rare variants in large combinatorial protein libraries by enabling high-throughput screening in miniaturized reaction systems. However, throughput limitations and assay compatibility constrain the...
Microfluidic diffusional sizing (MDS) has emerged as a versatile lab-on-a-chip technology for quantitative analysis of biomolecules in solution, particularly for determining particle sizes and characterizing biomolecular interactions. By measuring the diffusive behavior of molecules under laminar flow in a microfluidic chip, MDS enables the precise determination of hydrodynamic radii and binding affinities, even in complex biological samples, while requiring only minute sample volumes. As a result, MDS is establishing itself as a key tool in the life sciences. This review summarizes recent advances and applications of MDS in the context of bioanalysis and biosensing. We outline the fundamental principles of MDS and highlight its wide range of applications, including studies of protein aggregation, antibody affinity profiling, protein-lipid interactions, and nanoparticle sizing. We further discuss recent technological developments, such as single-molecule detection, label-free strategies, and multidimensional analysis, that have significantly expanded the scope, sensitivity, and utility of MDS. We conclude with an outlook on the anticipated impact of MDS on biomedical research, diagnostics, and therapeutic development.
Microfluidic platforms produce RNA-loaded lipid nanoparticles (RNA-LNPs) with superior uniformity, encapsulation efficiency, and control over size compared to bulk methods, and unlike bulk approaches, their throughput can be scaled over...
Antimicrobial resistance (AMR) complicates the treatment of diseases including lung and urinary tract infections (UTIs), which are among the most common bacterial infections worldwide. Motile pathogens can use rheotaxis to swim upstream against fluid flows, potentially promoting access to upper regions of anatomical tracts. However, it remains unclear how antibiotic exposure and resistance influence this transport process. Here, using single-cell tracking microscopy, we investigate how elongation induced by β-lactam antibiotics affects the rheotactic migration of E. coli in confined microfluidic channels. Remarkably, we find that rheotaxis can be inhibited 100-fold by antibiotics, even if the susceptible elongated cells remain fully motile. However, resistant bacteria remain short and retain upstream migration under the same conditions. Using genetically engineered bacteria with tunable cell length, we show that the underlying mechanism that governs rheotaxis is the coupling between cell morphology and flow vorticity, where elongated cells are rapidly rotated downstream. Finally, we exploit this length-dependent transport difference to separate short and elongated cells under flow and enrich ampicillin-resistant cells from mixed populations. Together, these results establish bacterial elongation as a key control parameter for rheotactic transport, and provide a proof-of-concept strategy for enriching β-lactam-resistant bacteria for potential use in rapid AMR detection.
Micro/nanostructures exhibit distinctive advantages in cell capture and spatial distribution analysis. Nonetheless, conventional cell research approaches face challenges including strong equipment dependence, complex operational procedures, and difficulties in achieving precise spatial confinement. In this study, three-dimensional microcage arrays are fabricated via FL-TPP, enabling the construction of structures with customizable inner diameters and achieving highly precise, three-dimensional biomimetic, and high-throughput cell capture. The fabrication of structures with controllable inner diameters is realized. Through the synergistic effects of gravity and hydrodynamic forces, the microcage arrays efficiently and selectively capture microspheres and fibroblasts of specific sizes. In addition, microcages with varying inner diameters significantly modulate cell behavior and effectively avoid cell damage. This work broadens the applicability of micro/nanostructures in tissue engineering, including cell capture and the construction of biomimetic microenvironments.
Microplastic pollution in groundwater has become one of the most challenging environmental issues. However, there is a lack of portable instruments for on-site detection of low-abundance microplastics. To address this, we developed a portable instrument for intelligent analysis of low-abundance microplastics in groundwater by integrating the dielectrophoretic (DEP) assembly of a four-phase rotating electric field with an object detection framework based on YOLO26. Firstly, a microfluidic chip was designed and fabricated to construct a portable instrument for rapid assembly, and an object detection model was developed to identify microplastics with diverse sizes, shapes, and colors. Secondly, a computational model was established to theoretically investigate the phase-dependent variation in the electric field and the microplastic assembly by analyzing particle velocities and trajectories. The feasibility of this portable instrument was demonstrated using polystyrene microplastics, which was consistent with the numerical simulations. Thirdly, the assembly performance of the chip was explored for microplastics of different polymer types, and the voltage-amplitude and solution-conductivity dependencies of microplastics assembly were systematically characterized. Depending on these, we used this portable instrument to achieve the intelligent analysis of spherical microplastics, including the size and abundance. Finally, the portable instrument was engineered for the detection of low-concentration microplastics in groundwater to rapidly acquire the size and abundance of microplastics with irregular shapes. This instrument can realize rapid assembly and intelligent analysis of low-concentration microplastics in groundwater and holds great potential in the guarantee of the drinking-water safety with advantages of intelligence, portability, and multiparametricity.
Frequent monitoring of prothrombin time and international normalized ratio (PT/INR) is essential for effective management of anticoagulation therapy, yet conventional laboratory-based testing remains costly, time-consuming, and difficult to access in decentralized settings. Addressing this challenge, a hybrid paper-based point-of-care (POC) platform is designed for rapid and affordable whole-blood PT/INR analysis. The assay is developed through systematic optimization of key parameters, including sample volume, blood-to-reagent ratio, reaction time, substrate type, assay geometry, and strip dimensions for both haematocrit (HCT) and PT/INR modules. The integrated system simultaneously estimates HCT using radial intensity-based detection on Whatman Grade 4 paper (R2 = 0.9788) and measures PT/INR on high-porosity MF1 glass-fibre strips (R2 ≈ 0.94), enabling correction of HCT-induced bias. Image-derived features were analyzed using AI/ML-based models, where support vector machine classifiers achieved diagnostic accuracies of 98.5% and 96.9% for non-anticoagulated and anticoagulated cohorts, respectively. Integrated with a custom desktop/web/smartphone application and an automated warfarin dosage calculator, the platform provides a low-cost, rapid, and user-friendly solution for accessible anticoagulation monitoring.
Timely and accurate nucleic acid extraction is a critical bottleneck in point-of-care (POC) molecular diagnostics, particularly for low-abundance cell-free nucleic acids (DNA, RNA, miRNA) in plasma. We present a fully finger-actuated microfluidic device for power-free, pipette-free, nucleic acid extraction. The prototype device integrates finger-actuated valves, pump and blister reagent storage, enabling a complete, intuitive, "sample-to-eluate" workflow, including lysis, binding, washing and elution via manual actuation in approximately 35 minutes. The device operation was benchmarked against a commercial magnetic bead-based manual benchtop and an automated robotic workflow. In DNA-spiked aqueous samples (5-20 ng mL-1), the device demonstrated recoveries of 84.6%, against 90.7% on the bench. Optimisation of magnetic bead volume identified 50 μL as the threshold for maximal recovery while minimising reagent consumption. Recovery from human pooled plasma samples were found to be on average 18, 62, and 552% higher than that obtained with the control bench extraction on initial sample volumes of 100, 75 and 50 μL, respectively. Coefficient of variation (CV%) for all techniques remained within reported laboratory ranges (20-80%). The device's clinical utility was piloted using patient samples positive for cytomegalovirus (CMV), monkeypox virus (MPXV) or chikungunya (CHIKV). The device achieved successful qPCR amplification for all targets, with viral DNA Cq values within as little as 0.3 cycles of the standard protocol. This instrument-free, manual circulating nucleic acid extraction tool could help bridge the gap between lateral flow based nucleic acid amplification technologies and real-world decentralised diagnostics, offering a scalable solution for infectious disease management in resource-limited settings.
Drug sensitivity profiling on patient-derived organoids mirrors patient response for gastrointestinal cancers and is currently being evaluated in clinical trials to guide treatment decisions. However, long expansion times are typically...
The integration of electrochemical sensing with microfluidic platforms is essential for advancing lab-on-a-chip technologies; however, many existing approaches rely on electrodes fabricated using costly and complex techniques such as thin-film deposition and photolithography. Laser-induced graphene (LIG) offers a rapid and low-cost alternative for electrode fabrication, yet it is most commonly produced on polyimide substrates, which are not readily compatible with permanent bonding to microfluidic channels and typically require adhesives or mechanical clamping. Here, we present a novel approach to integrating LIG electrodes with microchannels fabricated in polydimethyl siloxane (PDMS), a common material for microfluidics. Electrodes were formed on SU-8 photoresist-coated glass slides using a CO2 laser and then covalently bonded to PDMS via 3-aminopropyl triethoxysilane (APTES). Structural and spectroscopic characterization of the LIG on SU-8 demonstrate successful conversion into conductive turbostratic graphitic carbon, while mechanical studies demonstrate strong bond integrity between the electrode substrate and PDMS over 16 hours of continuous operation. Electrochemical validation of the electrodes both off- and on-chip demonstrate performance suitable for quantitative electroanalysis. Proof-of-principle application of the integrated device to the detection of acetaminophen (paracetamol) by differential pulse voltammetry under flow conditions reveals a clinically relevant limit of detection (0.08 mM) with high intra-device precision. The resulting platform enables seamless integration with microfluidic channels and exhibits robust electrochemical performance ideal for rapid prototyping.
The liver and kidneys are essential for drug metabolism and clearance and are highly sensitive to toxicity. Most in vitro models assess these organs in isolation, limiting the study of inter-organ interactions. Here, an induced pluripotent stem cell (iPSC)-derived kidney-liver organ-on-a-chip model was developed that co-cultured hepatocyte-like cell (HLC) organobodies and proximal tubular-like cells (PTL) under microfluidic flow. In parallel, a PTL-HepaRG spheroid co-culture model was established to investigate bioactivation of the prodrug ifosfamide. Co-culture induced distinct transcriptional responses in PTL and HLC, as revealed by gene set enrichment analysis. In PTL, co-culture with HepaRG enriched signaling and cell polarity pathways, while co-culture with HLC enhanced metabolic and transport-related programs. In HLC, co-culture with PTL affected intermediary metabolism, lipid processing, redox regulation, and plasma protein synthesis. The PTL-HepaRG model demonstrated bioactivation of ifosfamide into metabolite chloroacetaldehyde, highlighting the utility of these systems for studying human-relevant kidney-liver interactions and drug metabolism in vitro. However, the concentration of chloroacetaldehyde was too low to cause adverse effects in the renal tissue in the current setup.
Organ- and organoid-on-a-chip technologies provide critical human-relevant models for drug screening. Despite their promise, translating their complex biological outputs into reproducible, quantifiable, and pharmacologically interpretable readouts remains a significant challenge. To address this, artificial intelligence (AI) is increasingly employed to process the high-content imaging, sensor, and molecular data derived from these platforms. Crucially, this integration elevates AI from a conventional post-experimental analytical tool into a comprehensive framework that actively drives quality control, response quantification, model integration, and critical screening decisions. This review examines AI-augmented microphysiological systems across the entire drug screening pipeline by connecting biological readouts with specific computational strategies and pharmacological endpoints. We evaluate representative platforms, analytical methodologies, and specific applications where computational frameworks enable model standardization, robust phenotype interpretation, mechanism-informed evaluation, and compound prioritization. Furthermore, we outline primary barriers to clinical translation, including inherent biological and engineering variability, model generalizability, the need for external validation, and clinical dose relevance. Ultimately, these insights establish a comprehensive framework for evaluating the reproducibility, pharmacological applicability, interpretability, and translational potential of AI-driven microphysiological screening.
In this study, we present and analyze a deep learning framework designed to achieve real-time particle localization from successive electrical impedance measurements with a limited training dataset. The goal is to provide the research community with a comprehensive analysis of the role of the different constituent elements of a network and a way to optimize their parameters. All the code is made available (see SI). The proposed algorithm combines a temporal convolutional network (TCN), a bidirectional long short-term memory (BiLSTM), a fully connected network (FCN), and an automated parameter tuning engine. Although vision-based systems could be used to track the position of micrometer-sized particles, this modality has practical limitations due to the size of the equipment, its complexity, and the narrow field of view. Thus, an emerging approach for localization is to exploit the correlation between electrical impedance measurements and the position of the successive particles. While physics-based algorithms have been proposed for localizing particles from impedance measurements, they rely on analytical assumptions on feature correlation. Learning-based approaches remove this bias by directly mapping patterns from raw data. However, state-of-the-art models typically require massive training datasets and offer minimal transparency regarding parameter selection. To contribute to the deployment of such algorithms in the lab-on-a-chip community, we introduce a framework that unifies feature extraction with a data-driven architectural tuning engine, designed to maintain predictive capacity under data-scarcity constraints. This paper analyzes the role of each element of the algorithm with respect to the particularities of particle localization, with the data made available alongside the code. The methodological robustness of the framework is validated via a micrometer-scale particle localization case study. Using a small training dataset of only 53 polystyrene beads of 8 μm and 5 μm, the optimized model establishes a localization accuracy of 3.34 μm ± 1.24 μm, while demonstrating real-time prediction times as low as 0.58 ms to support its potential for closed-loop control applications. While this work validates the methodology using uniform beads to evaluate network behavior independently of biological variability, the underlying optimization framework is inherently generic and so, applicable to more complex, heterogeneous biological samples, and will contribute to the deployment of data-driven approaches in the community.
Diabetic nephropathy (DN) is driven by progressive dysfunction of the glomerular filtration barrier (GFB), yet current in vitro models inadequately capture its multicellular architecture and dynamic microenvironment. Herein, we present a glomerular spheroid-on-a-chip that integrates organoid-like cellular organization with microfluidic perfusion to mimic the pathophysiology of DN. The strategic integration of human mesangial cells (HMCs), a critical component often neglected in existing platforms, into triculture spheroids alongside conditionally immortalized human podocytes and human umbilical vein endothelial cells (HUVECs) significantly augments the structural integrity and functional recapitulation of the engineered GFB. A streamlined, cost-effective micro-3D printing strategy generates bowl-shaped PDMS microdevices that anchor spheroids for controlled lateral expansion under dynamic perfusion, establishing a biomimetic GFB with distinct vascular and urinary compartments. Under diabetic conditions, the platform faithfully recapitulates key pathological features of DN, including HMC expansion, podocyte injury and increased barrier permeability, while directly revealing the critical contribution of HMCs to filtration barrier dysfunction. Moreover, the system supports small-molecule therapeutic evaluation, underscoring its potential for mechanistic studies and preclinical drug screening. This work establishes a versatile and manufacturable platform that bridges static glomerulus spheroid cultures and dynamic, disease-relevant modeling of DN.
Organ-on-chip (OoC) platforms are increasingly used to replicate structural, functional and molecular features of native tissue within controlled microenvironments. While most current brain-on-chip (BoC) systems rely on 2D cultures or 3D stem cell-derived constructs, the integration of intact brain tissue slices-particularly organotypic explants of the central nervous system-offers distinct advantages by preserving native cytoarchitecture, synaptic connectivity, and regional specificity. This systematic review aimed to identify and critically assess OoC platforms that incorporate ex vivo brain tissue slices maintained under dynamic perfusion for extended periods (≥10 days in vitro). A structured PubMed search conducted in accordance with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines identified 2796 records, of which 7 studies met the predefined inclusion criteria. All included studies employed organotypic brain slices derived from early postnatal rodents and integrated them into perfused microfluidic systems. Most platforms combined air-liquid interface culture with low-volume perfusion to support prolonged tissue viability and partial functional maintenance, including electrophysiological activity, preserved structural integrity, and molecular homeostasis. Notably, none of the identified studies reported the successful long-term cultivation of adult rodent or human brain tissue in a comparable perfused OoC configuration, underscoring a major limitation of current approaches. Moreover, assessment of tissue viability and function was heterogeneous and frequently relied on descriptive or insufficiently sensitive readouts, limiting cross-platform comparisons and translational relevance. Future development of BoC technologies should prioritize improved microenvironmental control, the integration of suitable biomaterials, and embedded monitoring strategies capable of assessing metabolic state and circuit-level function. Addressing these challenges will be essential for advancing OoC platforms towards physiologically meaningful and translationally relevant applications in neuroscience.
Precise spatial organization of cells and microparticles is essential for engineering physiologically relevant tissues and in vitro disease models, yet current bioink-based bioprinting approaches still face limitations regarding cell density dilution and crosslinking-induced cellular stress. Here we introduce the FUS-pen system, a template-free, focused ultrasound platform that enables non-contact, flexible and cross-scale manipulation of microparticles and cells with demonstrated biocompatibility. Mechanistic investigations reveal a cooperative interaction where acoustic streaming drives long-range transport and localized acoustic radiation forces achieve near-focus confinement of microparticles, while boundary reflections establish standing-wave-like fields that yield distinct, frequency-dependent swarm dimensions. By optimizing GelMA hydrogel substrates for reliable cell pattern retention and integrating poly-D-lysine (PDL) modification to facilitate electrostatically driven cell interface interactions, we achieved a quantified sub-millimeter feature resolution (∼293 μm line width), consistent geometric spot reproducibility and high cell viability (>94%). As a proof of concept, a compartmentalized tumor-endothelial co-culture layout was successfully established using breast cancer (MCF-7) cells and endothelial (EA.hy926) cells, where endothelial cells exhibited active proliferation and morphological remodeling into capillary-like networks, demonstrating the platform's utility for constructing complex multicellular models. Together, these results establish the FUS-pen as an agile tool for constructing organized in vitro microenvironments with broad implications for disease modeling and drug screening.
