Lab on a Chip最新文献

Microfluidic impedance cytometry (MIC) is a label-free technique that characterizes individual flowing particles/cells based on their interaction with a multifrequency electric field. The technique has been successfully applied in different scenarios including life-science research, diagnostics, and environmental monitoring. The aim of this review is to illustrate the fascinating opportunities enabled by the integration of MIC with other microfluidic tools. Specifically, we identify five categories according to their synergistic advantage: (i) improving the multiparametric characterization capability, (ii) enabling on-chip sample preparation steps, (iii) stimulating the sample, (iv) sample carrying/confinement, and (v) impedance-activated sample sorting. We discuss examples from each category, highlighting integration challenges and promising perspectives for next-generation multifunctional systems.

Microfluidic technology, which involves the manipulation of fluids in microchannels, faces challenges in channel design and performance optimization due to its complex, multi-parameter nature. Traditional design and optimization approaches usually rely on time-consuming numerical simulations, or on trial-and-error methods, which entail high costs associated with experimental evaluations. Additionally, commonly used optimization methods require many numerical simulations, and to avoid excessive computation time, they approximate simulation results with faster surrogate models. Alternatively, machine learning (ML) is becoming increasingly significant in microfluidics and technology in general, enabling advancements in data analysis, automation, and system optimization. Among ML methods, Bayesian optimization (BO) stands out by systematically exploring the design space, usually using Gaussian processes (GP) to model the objective function and guide the search for optimal designs. In this paper, we demonstrate the application of BO in the design optimization of the microfluidic systems, by enhancing the mixing performance of a micromixer with parallelogram barriers and a Tesla micromixer modified with parallelogram barriers. Micromixer models were made using Comsol Multiphysics software® and their geometric parameters were optimized using BO. The presented approach minimizes the number of required simulations to reach the optimal design, thus eliminating the need for developing a separate surrogate model for approximation of the simulation results. The results showed the effectiveness of using BO for design optimization, both in terms of the execution speed and reaching the optimum of the objective function. The optimal geometries for efficient mixing were achieved at least an order of magnitude faster compared to state-of-the-art optimization methods for microfluidic design. In addition, the presented approach can be widely applied to other microfluidic devices, such as droplet generators, particle separators, etc.

Integrating microfluidic elements onto a single chip offers many advantages, including miniaturization, portability, and multifunctionality, making such systems highly useful for biomedical, healthcare, and sensing applications. However, these chips need redesigning for compatibility with microfluidic fabrication methods such as photolithography. To address this, we integrated microfluidics technology into our previously developed humidity-driven energy harvester to create a self-powered system and redesigned it so that it could be fabricated using photolithography and printing. The device comprises stacked electrodes, cation-exchange membranes, and microchannels. The multi-element version of the device generated ten times more voltage than the single-element version. Both versions produced stable patterns of voltage output with respect to the fluctuations in humidity in both controlled and real-world environments. Their potential as humidity sensors is supported by the correlations exhibited between humidity and voltage output. The capacity of the device to respond to changes in perspiration-induced changes in humidity suggests its usefulness as a power source for wearable sensors. This novel device element, which can be easily integrated into other microfluidic devices, is expected to provide a new approach to powering microfluidic-based wearable sensors.

The retina is a complex and highly metabolic tissue in the back of the eye essential for human vision. Retinal diseases can lead to loss of vision in early and late stages of life, significantly affecting patients' quality of life. Due to its accessibility for surgical interventions and its isolated nature, the retina is an attractive target for novel genetic therapies and stem cell-based regenerative medicine. Understanding disease mechanisms and evaluating new treatments require relevant and robust experimental models. Retina-on-chip models are microfluidic organ-on-chip systems based on human tissue that capture multi-cellular interactions and tissue-level functions in vitro. Various retina-on-chip models have been described in literature. Some of them capture basic retinal barrier functions while others replicate key events underlying vision. In addition, some of these cellular systems have also been used in studies to explore their added value in retinal disease modeling. Most existing retina-on-chip models capture limited aspects of the phenotypic complexity of human diseases. This limitation arises primarily from the challenges related to controlled recapitulation of retinal function, including the relevant multi-cellular interactions and functional read-outs. In this review, we provide an update on recent advancements in the field of retina-on-chip, and we discuss the biotechnical strategies to further enhance the physiological relevance of the models. We emphasize that developers and researchers should prioritize the incorporation of the full spectrum of retinal complexity to effectuate a direct impact of retina-on-chip models in disease modeling and development of therapeutic strategies.

Microfluidic flow cytometry (MFCM) is considered to be an effective substitute for traditional flow cytometry, because of its advantages in terms of higher integration, smaller device size, lower cost, and higher cell sorting activity. However, MFCM still faces challenges in balancing parameters such as sorting throughput, viability, sorting efficiency, and cost. Here, we demonstrate a cost-effective and high-performance microfluidic cytometry cell sorting system, along with a customized microfluidic chip that integrates hydrodynamic focusing, droplet encapsulation, and sorting for precise cell manipulation. An innovative photon incremental counting-based fluorescence detection method is proposed, which requires only one-fiftieth of the data compared to traditional methods. This significantly simplifies the structure of the system and substantially reduces costs. The system exhibits detection recoveries exceeding 95% across sample solution flow rates ranging from 10 to 80 μL min⁻¹. Moreover, it accurately achieves individual droplet deflections at a droplet generation frequency of 1600 Hz. Ultimately, our cell sorting system offers an impressive sorting efficiency of 90.7% and a high cell viability of 94.3% when operating at a droplet generation frequency of 1316 Hz, highlighting its accuracy and gentleness throughout the entire process. Our work will enhance advances in the life sciences, thereby creating a boom in great applications in single-cell cloning, single-cell analysis, drug screening, etc.

Wearable microfluidic sweat sensors could play a major role in the future of monitoring health and wellbeing. Sweat contains biomarkers to monitor health and hydration status, and it can provide information on drug intake, making it an interesting non-invasive alternative to blood. However, sweat is not created in excess, and this requires smart sweat collection strategies to handle small volumes. Microfluidic solutions are commonly employed which use capillary action or evaporation to drive flow. In current literature about sweat analytics, the emphasis lies predominantly on developing the sensors for measuring the composition of sweat. Yet, solely measuring sweat composition does not suffice, because the composition varies due to inter- and intra-individual differences in sweat rate. The measurement of sweat rate is thus crucial for enabling a reliable interpretation and standardisation of this data. Recently, more wearable sweat sensors, also integrating a means of measuring flow, have been developed. This manuscript reviews state-of-the-art sweat collection strategies and flow rate measuring techniques. Generally, flow rate measurements are performed by impedimetric or capacitive methods. However, these techniques can be impaired due to limited lifetime and signal interference from changing ionic contents in sweat. Discrete measurement techniques, such as impedance measurements of an advancing fluid front with interdigitated electrodes, calorimetric and colorimetric techniques can be very reliable, because they selectively measure flow. However, one should take the available size, intended application and compatibility with other sensors into account. Overall, accurate flow rate sensors integrated in reliable microfluidic sweat sensor platforms will enable the standardisation of sweat measurements to unlock the potential of sweat analytics in advancing physiological research, personalized diagnostics and treatment of diseases.

Centrifugation is crucial for size and density-based sample separation, but low-volume or delicate samples suffer from loss and impurity issues during repeated spins. We introduce the "Spinochip", a novel microfluidic system utilizing centrifugal forces for efficient filling of dead-end microfluidic channels. The Spinochip enables versatile fluid manipulation with a single reservoir for both inlet and outlet functions. It expels compressed air, facilitating fluid flow, and offers programmable filling mechanisms based on the hydraulic resistance of microfluidic channels. Compatible with a basic centrifuge, it allows sequential filling, internal mixing, and collection in straight microfluidic channels by simply adjusting the spinning speed, eliminating the need for complex valving. We demonstrated the Spinochip's efficacy in blood testing, where it successfully separated blood components, such as plasma, buffy coat, and red blood cells, from a single drop using centrifugation alone. This system enabled simultaneous hematocrit (R² >0.99) and total white blood cell (R² >0.93) quantification within a single microfluidic channel without the need for staining or special reagents. Remarkably, the Spinochip can perform hematocrit measurements on as little as 100 nL of blood, potentially paving the way for less invasive blood analysis. This innovative approach unlocks new possibilities in microfluidics, providing precise fluidic control and centrifugation for sample volumes as small as a few nanoliters.

Creative designs, precise fluidic manipulation, and automation have supported the development of microfluidics for single-cell applications. Together with the advancements in detection technologies and artificial intelligence (AI), microfluidic-assisted platforms have been increasingly used for new modalities of single-cell investigations and in spatial omics applications. This review explores the use of microfluidic technologies for morpholomics and spatial omics with a focus on single-cell and tissue characterization. We emphasize how various fluid dynamic principles and unique design integrations enable highly precise fluid manipulation, enhancing sample handling in morpholomics. Additionally, we examine the use of microfluidics-assisted spatial barcoding with micrometer resolutions for the spatial profiling of tissue specimens. Finally, we discuss how microfluidics can serve as a bridge for integrating multiple unique fields in omics research and outline key challenges that these technologies may face in practical translation.

Bacterial infections remain a global threat, particularly in low-resource settings, where access to accurate and timely diagnosis is limited. Point-of-care nucleic acid amplification tests have shown great promise in addressing this challenge. However, their dependence on complex traditional sample preparation methods remains a major challenge. To address this limitation, we present a paper-based sample preparation device that integrates bacterial cell lysis, DNA purification, and concentration using an electrokinetic technique called isotachophoresis (ITP). This is the first device that (i) integrates electrochemical bacterial lysis with ITP and (ii) demonstrates the focusing of whole bacterial genomic DNA (gDNA) in paper. Characterization with buffers showed that the paper-based ITP sample preparation module (p-ITPrep) concentrated bacterial gDNA with an average concentration factor of 12×, and DNA could be extracted from a sample containing as few as 10² CFU mL⁻¹Mycobacterium smegmatis (Msm). From complex biological matrices – human saliva, human blood serum, and artificial urine – p-ITPrep extracted DNA from samples containing 10² CFU Msm per mL saliva or artificial urine and 10³ CFU Msm per mL serum within 20 min. The extraction procedure involved only 3 user steps, in contrast to conventional solid phase extraction kits that require more than 10 user steps. p-ITPrep may provide a simple, inexpensive, and versatile alternative to conventional multi-step nucleic acid extraction protocols for point-of-care diagnostics.

Zoonotic outbreaks present with unpredictable threats to human health, food production, biodiversity, national security and disrupt the global economy. The COVID-19 pandemic-caused by zoonotic coronavirus, SARS-CoV2- is the most recent upsurge of an increasing trend in outbreaks for the past 100 years. This year, emergence of avian influenza (H5N1) is a stark reminder of the need for national and international pandemic preparedness. Tools for threat reduction include consistent practices in reporting pandemics, and widespread availability of accurate detection technologies. Wars and extreme climate events redouble the need for fast, adaptable and affordable diagnostics at the point of need. During the recent pandemic, rapid home tests for SARS-CoV-2 proved to be a viable functional model that leverages simplicity. In this perspective, we introduce the concept of syndemnicity in the context of infectious diseases and point-of-need healthcare diagnostics. We also provide a brief state-of-the-art for paper-based microfluidics. We illustrate our arguments with a case study for detecting brucellosis in cows. Finally, we conclude with lessons learned, challenges and opportunities for paper-based microfluidics to serve point-of-need healthcare diagnostics during syndemics.