Search Results (252)

Digital PCR, as a nucleic acid absolute quantification method at the single-molecule level, has been widely applied in early cancer screening, single-cell analysis, and other biomedical fields. However, existing digital PCR methods still suffer from high costs, complex operations, and low detection dynamic range, which limit their applications. In the study, we developed a microfluidic chip-based digital PCR with a high-density vertical structure using PDMS (polydimethylsiloxane) flexible material. The chip features a three-layer structure of glass–PDMS–glass, with the PDMS structural layer containing 30,000 reaction chambers, each with a volume of 0.713 nL. This vertical-structured chip can increase the total volume and the total number of chambers by 50% without changing the chip area and chamber volume, thereby significantly enhancing dynamic range and sensitivity of the chip detection. This chip is theoretically capable of achieving a nucleic acid detection dynamic range close to 10⁵. Moreover, the digital PCR quantitative detection results of five different concentrations of serially diluted KRAS plasmid DNA templates using this chip also validated the accuracy and reliability of the nucleic acid quantitative detection results. The vertical-structured digital PCR chip, with its simple manufacturing process, uniform and stable sample partitioning, wide detection dynamic range, and low cost, will promote the widespread application of digital PCR. Full article

In recent years, a type of biochip known as a Digital Microfluidic Biochip (DMFB) has been actively researched in the field of life sciences. DMFBs perform dilution operations by mixing reagent solutions and buffer solutions at a 1:1 ratio to generate droplets with the desired concentration. One of the challenges of DMFBs is that droplets may not always be evenly split during the droplet division process. To address this issue, an error correction method utilizing error cancellation has been proposed. This method modifies the dilution graph to minimize the impact of division errors on the target node. However, this approach has a significant drawback: when large division errors occur in nodes close to the target node, they can introduce substantial concentration errors at the target node. In this paper, we propose a method that duplicates nodes near the target node and performs re-dilution to correct errors. Furthermore, we present an efficient and accurate error correction approach by modifying the dilution graph so that the output nodes of the dilution operation are at equal levels relative to the target node. Through simulations conducted 10,000 times, we demonstrate that our method effectively reduces the average concentration error at the target node. Full article

Micro Electrode Dot Array (MEDA) biochips have recently attracted considerable attention in the biochemical and medical industries. MEDA biochips manipulate micro droplets for biochemical experiments such as DNA analysis. Droplets on MEDA biochips are moved using the Electrowetting on Dielectric (EWOD) effect, but a portion of a droplet may remain on a cell after passing through, contaminating the cell. Other droplets cannot pass through a contaminated cell. In previous studies, contaminated cells were considered unavailable for droplet routing. As the number of contaminated cells increases, droplets may be prevented from moving to the desired position. Therefore, we propose a method for simultaneous routing of target functional and washing droplets based on a shape-dependent velocity model. In a simulation, the proposed method reduced the routing time by about 10% compared with an existing method. Full article

In recent years, digital microfluidic biochips (DMFBs), based on microfluidic technology, have attracted attention as compact and flexible experimental devices. DMFBs are widely applied in biochemistry and medical fields, including point-of-care clinical diagnostics and PCR testing. Among them, micro electrode dot array (MEDA) biochips, composed of numerous microelectrodes, have overcome the limitations of conventional chips by enabling finer droplet manipulation and real-time sensing, thus significantly improving experimental efficiency. While various studies have been conducted to enhance the utilization of MEDA biochips, few have considered the shape-dependent velocity characteristics of droplets in routing. Moreover, methods that do take such characteristics into account often face significant challenges in solving time. This study proposes a fast droplet routing method for MEDA biochips that incorporates shape-dependent velocity characteristics by utilizing the distance information to the target cell. The experimental results demonstrate that the proposed method achieves approximately a 67.5% reduction in solving time compared to existing methods, without compromising solution quality. Full article

Swine infectious diseases, often caused by multiple co-infecting agents, pose severe global threats to pig health and industry economics. Conventional single-plex testing assays, whether relying on pathogen antigens or nucleic acids, exhibit limited efficacy in the face of co-infection events. The modern nucleic acid-based multiplex testing (NAMT) methods demonstrate substantial strengths in the simultaneous detection of multiple pathogens involving co-infections owing to their remarkable sensitivity, exceptional specificity, high-throughput, and short turnaround time. The development, commercialization, and application of NAMT assays in swine infectious disease surveillance would be advantageous for early detection and control of pathogens at the onset of an epidemic, prior to community transmission. Such approaches not only contribute to saving the lives of pigs but also aid pig farmers in mitigating or preventing substantial economic losses resulting from infectious disease outbreaks, thereby alleviating unwanted pressure on animal and human health systems. The current literature review provides an overview of some modern NAMT methods, such as multiplex quantitative real-time PCR, multiplex digital PCR, microarrays, microfluidics, next-generation sequencing, and their applications in the diagnosis of swine infectious diseases. Furthermore, the strengths and weaknesses of these methods were discussed, as well as their future development and application trends in swine disease diagnosis. Full article

Real-time, high-resolution monitoring of chemically diverse water pollutants remains a critical challenge for smart water management. Here, we report a fully integrated, multi-modal nano-sensor array, combining graphene field-effect transistors, Ag/Au-nanostar surface-enhanced Raman spectroscopy substrates, and CdSe/ZnS quantum dot fluorescence, coupled to an edge-deployable CNN-LSTM architecture that fuses raw electrochemical, vibrational, and photoluminescent signals without manual feature engineering. The 45 mm × 20 mm microfluidic manifold enables continuous flow-through sampling, while 8-bit-quantised inference executes in 31 ms at <12 W. Laboratory calibration over 28,000 samples achieved limits of detection of 12 ppt (Pb²⁺), 17 pM (atrazine) and 87 ng L⁻¹ (nanoplastics), with R² ≥ 0.93 and a mean absolute percentage error <6%. A 24 h deployment in the Cherwell River reproduced natural concentration fluctuations with field R² ≥ 0.92. SHAP and Grad-CAM analyses reveal that the network bases its predictions on Dirac-point shifts, characteristic Raman bands, and early-time fluorescence-quenching kinetics, providing mechanistic interpretability. The platform therefore offers a scalable route to smart water grids, point-of-use drinking water sentinels, and rapid environmental incident response. Future work will address sensor drift through antifouling coatings, enhance cross-site generalisation via federated learning, and create physics-informed digital twins for self-calibrating global monitoring networks. Full article

Antithrombin (AT) plays a crucial role in the human anticoagulant system and has extensive clinical applications. However, traditional detection methods often require large sample volumes, complex procedures, and lengthy processing times. Methods: We integrated digital microfluidics technology with AT detection to develop a point-of-care testing (POCT) device that is user-friendly and fully automated for real-time AT testing. Results: This device allows for automation and enhanced adaptability to various settings, requiring only a minimal sample volume (whole capillary blood), thereby omitting steps such as plasma separation to save time and improve clinical testing efficiency. Comparisons with conventional AT activity detection methods demonstrate a high degree of consistency in the results obtained with this device. Conclusion: The AT detection system we developed exhibits significant effectiveness and holds substantial research potential, positioning it to evolve into a clinically impactful POCT solution for AT assessment. Full article

As three-dimensional (3D) printing becomes increasingly prevalent in microfluidic system fabrication, the demand for high precision has become critical. Among various 3D printing technologies, light-curing-based methods offer superior resolution and are particularly well suited for fabricating microfluidic channels and associated micron-scale components. Two-photon polymerization (TPP), one such method, can achieve ultra-high resolution at the submicron level. However, its severely limited printable volume and high operational costs significantly constrain its practicality for real-world applications. In contrast, digital light processing (DLP) 3D printing provides a more balanced alternative, offering operational convenience, lower cost, and print dimensions that are more compatible with practical microfluidic needs. Despite these advantages, most commercial DLP systems still struggle to fabricate intricate, high-resolution structures—particularly curve, thin-walled, or hollow ones—due to over-curing and interlayer adhesion issues. In this study, we developed a DLP-based projection micro-stereolithography (PμSL) system with a simple optical reconfiguration and fine-tuned its parameters to overcome limitations in printing precise and intricate structures. For demonstration, we selected an Archimedes microscrew as the target structure, as it serves as a key component in microfluidic micromixers. Based on our previous study, the most effective design was selected and fabricated in accordance with practical microfluidic dimensions. The PμSL system developed in this study, along with optimized parameters, provides a reference for applying DLP 3D printing in high-precision microfabrication and advancing microfluidic component development. Full article

Accurate and non-invasive optical metrology of transparent objects is essential in several commercial and research applications, from fluid dynamics to biomedical imaging. In this work, a digital holography approach for thickness measurement of glass plate and temperature mapping of candle flame is presented that leverages a double-field-of-view (FOV) configuration combined with high spatial bandwidth utilization (SBU). By capturing a multiplexed hologram from two distinct objects in a single shot, the system overcomes the limitations inherent to single-view holography, enabling more comprehensive object information of thickness measurement and temperature-induced refractive index variations. The method integrates double-FOV digital holography with high SBU, allowing for accurate surface profiling and mapping of complex optical path length changes caused by temperature gradients. The technique exhibits strong potential for applications in the glass industry and microfluidic thermometry, convection analysis, and combustion diagnostics, where precise thermal field measurements are crucial. This study introduces an efficient holographic framework that advances the capabilities of non-contact measurement applications by integrating double-FOV acquisition into a single shot with enhanced spatial bandwidth exploitation. The approach sets the groundwork for real-time, volumetric thermal imaging and expands the applicability of digital holography in both research and industrial settings. Full article

Newborn bloodspot screening for one or more lysosomal storage disorders (NBS-LSD) is currently performed by many public health NBS laboratories globally. The screening tests measure activities of selected lysosomal enzymes on dried blood spot (DBS) specimens collected from newborns by the heel stick method Because these assays measure enzyme activity, the quantitative results are dependent on the particular analytical method. DBS quality control (DBS QC) materials with assay-specific certified values that span the relevant range from typical to LSD-affected newborns are an important component of quality assurance in NBS laboratories. The Newborn Screening Quality Assurance Program (NSQAP) at the U.S. Centers for Disease Control and Prevention (CDC) provides public health NBS laboratories with DBS QC sets for NBS-LSD comprising four admixtures of pooled umbilical cord blood and a base pool made from leukodepleted peripheral blood and heat-inactivated serum. To evaluate the suitability of these materials for use with digital microfluidics fluorometry (DMF) assays which can currently measure the activity of four enzymes (acid α-galactosidase (GLA); acid β-glucocerebrosidase (GBA); acid α-glucosidase (GAA); and iduronidase (IDUA)), CDC collaborated with the Newborn Screening Unit at the Missouri State Public Health Laboratory (MSPHL). Using MSPHL criteria, we found that the certified results from each of two DBS QC lots collectively spanned the range from typical (screen negative) to enzyme deficient (screen positive) newborn DBS levels for each of the four lysosomal enzymes measured. The range included borderline results that would require repeat screening of the newborn under the MSPHL protocol. We conclude that these DBS QC preparations are suitable for use as external quality control materials for DMF assays used to detect LSDs in newborns. Full article

In recent years, emerging digital microfluidic technology has shown great application potential in fields such as biology and medicine due to its simple structure, sample-saving properties, ease of integration, and wide range of manipulation. Currently, due to potential faults in chips during production and usage, as well as high safety requirements in their application domains, thorough testing of chips is essential. This study records data using a machine vision-based digital microfluidic driving control system. As chip usage frequency rises, device degradation introduces seasonal and trend patterns in droplet motion time data, complicating predictive modeling. This paper first employs the density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm to analyze the droplet motion time data in digital microfluidic systems. Subsequently, principal component analysis (PCA) is applied for dimensionality reduction on the clustered data. Using the INFORMER model, we predict changes in droplet motion time and conduct correlation analysis, comparing results with traditional long short-term memory (LSTM), frequency-enhanced decomposed transformer (FEDformer), inverted transformer (iTransformer), INFORMER, and DBSCAN-INFORMER prediction models. Experimental results show that the DBSCAN-PCA-INFORMER model substantially outperforms LSTM and other benchmark models in prediction accuracy. It achieves an R² of 0.9864, an MSE of 3.1925, and an MAE of 1.3661, indicating an excellent fit between predicted and observed values.The results demonstrate that the DBSCAN-PCA-INFORMER model achieves higher prediction accuracy than traditional LSTM and other approaches, effectively identifying the health status of experimental devices and accurately predicting failure times, underscoring its efficacy and superiority. Full article

To address the challenges of excessive control pins and inefficient high-throughput droplet manipulation in conventional digital microfluidic chips, this study developed a parallel-motion digital microfluidic system integrated with an image acquisition device. The system employs an enhanced YOLOv8 object detection model for droplet recognition. By enabling parallel droplet transportation and processing, it significantly improves operational efficiency and detection accuracy. For droplet recognition, the YOLOv8 model was optimized through the integration of GAM_Attention and EMA mechanisms, which strengthen feature extraction capabilities and detection performance. Experimental results demonstrated that the optimized model achieves remarkable accuracy and robustness in droplet detection tasks, with mAP50 increasing from 96.5% to 98.7% and mAP50–90 improving from 65.8% to 68.5%. The system exhibits enhanced detection precision and real-time responsiveness, maintaining an error rate below 0.53%. Furthermore, a host computer interface was implemented for multi-droplet path planning and feedback, establishing a closed-loop control system. This work provides an efficient and reliable solution for high-throughput operations in microfluidic chip applications. Full article

We propose a pulsed modulated digital holographic microscopy (PM-DHM) technique for the dynamic measurement of flowing microparticles in microfluidic systems. By digitally tuning the pulse width and the repetition rate of a laser source within a single-frame exposure, this method enables the recording of multiple images of flowing microparticles at different time points within a single hologram, allowing the quantification of velocity and acceleration. We demonstrate the feasibility of PM-DHM by measuring the velocity, acceleration, and forces exerted on PMMA microspheres and red blood cells flowing in microfluidic chips. Compared to traditional frame-sampling-based imaging methods, this technique has a much higher time resolution (in a range of microseconds) that is limited only by the pulse duration. This method demonstrates significant potential for high-throughput label-free flow cytometry detection and offers promising applications in drug development and cell analysis. Full article

Heavy metal ion (HMI) contamination poses significant threats to public health and environmental safety, necessitating advanced detection technologies that are rapid, sensitive, and field-deployable. While conventional methods like atomic absorption spectroscopy (AAS) and inductively coupled plasma mass spectrometry (ICP-MS) remain prevalent, their limitations—including high costs, complex workflows, and lack of portability—underscore the urgent need for innovative alternatives. This review consolidates advancements in the last five years in microfluidic technologies for HMI detection, emphasizing their transformative potential through miniaturization, integration, and automation. We critically evaluate the synergy of microfluidics with cutting-edge materials (e.g., graphene and quantum dots) and detection mechanisms (electrochemical, optical, and colorimetric), enabling ultra-trace detection at parts-per-billion (ppb) levels. We highlight novel device architectures, such as polydimethylsiloxane (PDMS)-based labs-on-chip (LOCs), paper-based microfluidics, 3D-printed systems, and digital microfluidics (DMF), which offer unparalleled portability, cost-effectiveness, and multiplexing capabilities. Additionally, we address persistent challenges (e.g., selectivity and scalability) and propose future directions, including AI integration and sustainable fabrication. By bridging gaps between laboratory research and practical deployment, this review provides a roadmap for next-generation microfluidic solutions, positioning them as indispensable tools for global HMI monitoring. Full article

Polymerase chain reaction (PCR) chips are advanced, microfluidic platforms that have revolutionized biomarker discovery and validation because of their high sensitivity, specificity, and throughput levels. These chips miniaturize traditional PCR processes for the speed and precision of nucleic acid biomarker detection relevant to advancing drug development. Biomarkers, which are useful in helping to explain disease mechanisms, patient stratification, and therapeutic monitoring, are hard to identify and validate due to the complexity of biological systems and the limitations of traditional techniques. The challenges to which PCR chips respond include high-throughput capabilities coupled with real-time quantitative analysis, enabling researchers to identify novel biomarkers with greater accuracy and reproducibility. More recent design improvements of PCR chips have further expanded their functionality to also include digital and multiplex PCR technologies. Digital PCR chips are ideal for quantifying rare biomarkers, which is essential in oncology and infectious disease research. In contrast, multiplex PCR chips enable simultaneous analysis of multiple targets, therefore simplifying biomarker validation. Furthermore, single-cell PCR chips have made it possible to detect biomarkers at unprecedented resolution, hence revealing heterogeneity within cell populations. PCR chips are transforming drug development, enabling target identification, patient stratification, and therapeutic efficacy assessment. They play a major role in the development of companion diagnostics and, therefore, pave the way for personalized medicine, ensuring that the right patient receives the right treatment. While this tremendously promising technology has exhibited many challenges regarding its scalability, integration with other omics technologies, and conformity with regulatory requirements, many still prevail. Future breakthroughs in chip manufacturing, the integration of artificial intelligence, and multi-omics applications will further expand PCR chip capabilities. PCR chips will not only be important for the acceleration of drug discovery and development but also in raising the bar in improving patient outcomes and, hence, global health care as these technologies continue to mature. Full article