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Droplet-based dPCR offers many advantages over chip-based dPCR, such as lower processing cost, higher droplet density, higher throughput, while requiring less sample. However, the stochastic nature of droplet locations, uneven illuminations, and unclear droplet boundaries make automatic image analysis challenging. Most methods currently used to count a large amount of microdroplets rely on flow detection. Conventional machine vision algorithms cannot extract all information of the targets from complex backgrounds. Some two-stage methods, which first locate and then classify droplets according to their grayscale values, require high-quality imaging. In this study, we addressed these limitations by improving a one-stage deep learning algorithm named YOLOv5 and applying it to the detection task to realize one-stage detection. We introduced an attention mechanism module to increase the detection rate of small targets and used a new loss function to speed up the training process. Furthermore, we employed a network pruning method to facilitate the deployment of the model on mobile devices while preserving its performance. We validated the model with captured droplet-based dPCR images and found that the improved model accurately identified negative and positive droplets in complex backgrounds with an error rate of 0.65%. This method is characterized by its fast detection speed, high accuracy, and ability to be used on mobile devices or cloud platforms. Overall, the study presents a novel approach for detecting droplets in large-scale microdroplet images and provides a promising solution for accurate and efficient droplet counting in droplet-based dPCR. [ABSTRACT FROM AUTHOR]

As the gold standard for nucleic acid detection, full-process polymerase chain reaction (PCR) analysis often falls into the dilemma of complex workflow, time-consuming, and high equipment costs. Therefore, we designed and optimized a DNA quantification microfluidic system by strategically integrating sample pretreatment and a smartphone-readable gradient plasmonic photothermal (GPPT) continuous-flow PCR (CF-PCR). Through preloading and sequential injection of immiscible extraction reagents, combined with magnetic bead (MB) manipulation, the microfluidic chip successfully purified and concentrated 100 μL of HBV-DNA spiked plasma into a 20-μL purified sample within 14 minutes. With a digital PCR platform, the optimized experiments showed that the DNA extraction efficiency can reach 69% at an immiscible reagent configuration ratio of 10 : 10 : 1 : 12 : 2 (sample : lysis/binding buffer : MB : silicone oil : eluent) and a flow rate of 25 μL min−1. For the first time, we used gold nanorod (AuNR)-doped PDMS to prepare a CF-PCR submodule for the amplification of a 40 μL PCR mixture. Due to the plasmonic photothermal effect of AuNRs and the gradient intensity of an expanded laser spot, the PCR thermal gradient was formed on a coin-sized area. The compact annular thermal-microfluidic layout, optimized DNA dye concentration, and chip transmittance synergistically enable a rarely reported smartphone-based fluorescence CF-PCR, greatly simplifying thermal control and detection setup. Prototype construction and validation experiments show that the microsystem can complete the sample-to-answer quantification of HBV-DNA with a dynamic linear range from 1.2 × 101 to 1.2 × 106 copies per μL in ∼37 minutes. This novel microfluidic solution effectively bridges the technical gap between the CF-PCR, sample pretreatment and result characterization, making the workflow standardized and rapid and requiring <15% of the commercial instrument cost. The simplicity, rapidity and low cost of this work make it promising for applications in decentralized laboratories and low-resource settings. [ABSTRACT FROM AUTHOR]

Step emulsification (SE) devices coupled with parallel generation nozzles are widely used in the production of large-scale monodisperse droplets, especially for droplet-based digital polymerase chain reaction (ddPCR) analysis. Although current ddPCR systems based on the SE method can provide a fully enclosed ddPCR scheme, high demands on chip fabrication and system control will increase testing costs and reduce its flexibility in ddPCR analysis. In this study, a compact SE device, integrating a smart SE chip into a reaction tube, was developed to prepare large-scale water-in-fluorinated-oil droplets for ddPCR analysis. The SE chip contained dozens of droplet-generation nozzles. By adjusting the nozzle height of the SE chip, monodisperse droplets in a picolitre to nanolitre vloume could be prepared at a production rate of tens to hundreds of microlitres per minute. Subsequently, we utilized such an integrated SE device to prepare monodisperse droplets for ddPCR experiments. The volume of PCR reagent and the number of droplets could be flexibly adjusted according to the requirements of the ddPCR analysis. The quantitative results showed that emulsions prepared by the SE device could achieve ddPCR detection with high accuracy, good repeatability, and an adaptive dynamic range, which also demonstrated the robustness and reliability of such devices in the droplet preparation. Thus, this compact SE device provides an inexpensive, flexible, and simplified droplet preparation method for digital PCR quantitative analysis. [ABSTRACT FROM AUTHOR]

Cell-free (cf) nucleic acids are considered important and have been used as selective biomarkers. Conventional techniques for cf nucleic acid biomarker isolation from blood are generally time-consuming, complicated, and expensive. This study describes a lab-on-a-disk system equipped with newly developed immiscible filtration assisted by surface tension (IFAST), which can achieve the rapid isolation of cfDNA from whole blood. The principle of centrifugal IFAST (C-IFAST) is introduced. An arch-like channel for magnetic bead transfer in the immiscible phase is designed, which builds both a virtual water–air “wall” and an air–oil “wall” to prevent the blending of water and oil. The entire process requires less than 15 min and achieves the recovery of 65% of cfDNA from plasma and 30% from whole blood. Experiments were performed to test the validity of the chip, showing that this technique takes less time to obtain results of identical quality compared to commercial kits. The proposed C-IFAST method enables rapid and reliable cfDNA isolation from large whole blood volume (4 ml) and can potentially be used in “liquid biopsy” point-of-care diagnosis. [ABSTRACT FROM AUTHOR]