Digital microfluidic (DMF) technology is widely used in bioanalysis and chemical reactions due to its accuracy and flexibility in manipulating droplets. However, most DMF systems usually rely on complex electrode fabrication and high driving voltages. Sensor integration in DMF systems is also quite rare. In this study, a programmable magnetic digital microfluidic (PMDMF) platform integrated with electrochemical detection system was proposed. It enables non-contact, flexible droplet manipulation without complex processes and high voltages, meeting the requirements of automated electrochemical detection. The platform includes a magnetic control system, a microfluidic chip, and an electrochemical detection system. The magnetic control system consists of a microcoil array circuit board, a N52 permanent magnet, and an Arduino control module. N52 magnets generate localized magnetic fields to drive droplet movement, while the Arduino module enables programmable control for precise manipulation. The maximum average velocity of the droplet is about 3.9 cm/s. The microfluidic chip was fabricated using 3D printing and the superhydrophobic surface of chip was fabricated by spray coating. The electrochemical detection system consists of the MoS₂@CeO₂/PVA working electrode, Ag/AgCl reference electrode, and carbon counter electrode. To evaluate the practical value of the integrated platform, glucose in sweat was automatically and accurately detected. The proposed platform has a wide linear detection range (0.01–0.25 mM), a lower LOD (6.5 μM), a superior sensitivity (7833.54 μA·mM⁻¹·cm⁻²), and excellent recovery rate (88.1–113.5%). It has an extensive potential for future application in the fields of medical diagnostics and point-of-care testing.

Waterborne pathogens seriously threaten human life and can cause diarrhea, gastrointestinal disorders, and more serious systemic infections. These pathogens are usually caused by contaminated water sources that contain disease-causing microorganisms, such as bacteria, viruses, and parasites, which cause infection and disease when they enter the human body through drinking water or other means. Due to the wide range of transmission routes and the high potential risk of waterborne pathogens, there is an urgent need for an ultrasensitive, rapid, and specific pathogenic microorganism monitoring platform to meet the critical monitoring needs of some water bodies’ collection points daily monitoring needs. Microfluidics-based pathogen surveillance methods are an important stage towards automated detection through real-time and multi-targeted monitoring, thus enabling a comprehensive assessment of the risk of exposure to waterborne pathogens and even emerging microbial contaminants, and thus better protection of public health. Therefore, this paper reviews the latest research results on the isolation and detection of waterborne pathogens based on microfluidic methods. First, we introduce the traditional methods for isolation and detection of pathogens. Then, we compare some existing microfluidic pathogen isolation and detection methods and finally look forward to some future research directions and applications of microfluidic technology in waterborne pathogens monitoring.

Nucleic acid nanotechnology-based artificial transcriptional components (aTCs) can be integrated into synthetic transcriptional circuits to recognize external signals, process information, and execute decision-based functions.

Droplet manipulation constitutes a fundamental operation in numerous bio-microfluidic applications, including but not limited to medical diagnostics and targeted drug delivery. Among the various technologies developed for this purpose, magnetic digital microfluidics (MDMF) has emerged as a compelling approach due to its inherent advantages of contamination-free actuation, low cost, and configurational flexibility. Nevertheless, conventional MDMF remains constrained by its reliance on bulky instrumentation and substantial power consumption for generating controllable magnetic fields, which limit its in-field applications. To address these limitations, this work presents a programmable and portable electromagnetic microfluidic droplet manipulation platform that synergistically integrates static and dynamic magnetic fields to enable non-contact, high-precision droplet control under ultra-low power conditions. The proposed system comprises an electromagnetic actuation module, a permanent magnet, and a glass substrate coated with Teflon film. The entire system is secured by a PMMA support structure, within which a glass substrate is mounted and spatially separated from the permanent magnet. The PMMA support is fabricated using a milling process, offering a simple manufacturing procedure and high structural reusability and reproducibility. The control logic is implemented on a field-programmable gate array (FPGA) development board, facilitating fully autonomous operation powered by a standard battery. The platform operates at a low voltage of 3.5 V and a driving current of 180 mA, corresponding to a total power consumption of merely 0.63 W, while achieving robust manipulation of droplets in the volume range of 0.5 to 5 μL. A maximum average droplet velocity of up to 0.6 cm/s was attained under optimal conditions. The proposed platform offers a scalable and energy-efficient solution for portable droplet-based assays and holds significant promise for integration into point-of-care diagnostic tools and field-ready biochemical analysis systems. The platform demonstrates excellent operational stability and reproducibility, as validated by repeated actuation experiments with a positioning deviation of approximately 0.1 mm under optimized conditions. The fabrication process also exhibits high reliability with consistent performance across multiple experimental runs.

Periprosthetic joint infection (PJI) is a severe and difficult-to-treat complication following artificial joint replacement, occurring in approximately 1–2% of total joint arthroplasties and normally caused by the adhesion of bacteria to the prosthesis and the formation of biofilms. Since this disease lacks a single definitive diagnostic indicator, a comprehensive judgment needs to be made by combining serum inflammatory indicators, joint synovial fluid tests, microbial cultures, imaging, and intraoperative pathology. Although microbial culture remains the gold standard, it usually requires more than 3 days. Microfluidics breaks through the limitations of traditional cultivation and conventional nucleic acid testing, which are characterized by long time consumption, large sample requirements, complex operations, and bulky equipment. Microfluidics has the irreplaceable advantage in real-time, micro-scale, and multi-indicator synchronous detection of bacterial pathogens, while the serious consequences of PJI require more advanced and rapid detection technologies to enable more effective treatment. In this review, in addition to summarizing the advances of microfluidic technology in the field of bacterial detection over the past five years, we also propose and analyze the microfluidic technology strategies that are likely to develop in the field of PJI detection in the future.

Flexible graphene field-effect transistors (FGr-FETs) possess ultra-high detection sensitivity, excellent mechanical flexibility, and extensive interface signal transduction mechanisms, driving the innovative development of flexible electronics. However, the accurate extraction of signals in complex physiological scenarios remains a key factor limiting the advancement of FGr-FET. This review systematically examines the mechanisms underlying the sensing and transduction of electrophysiological, mechanical, and biochemical signals in FGr-FET. We summarize strategies for enhancing FGr-FET sensing performance, including material modification, structural optimization, and the amplification of optical and magnetic signals. This paper highlights the latest advances in multimodal sensing and precision medicine applications and analyzes key challenges related to Debye screening, device reliability, inter-device variability, long-term operational stability, and clinical translation. Finally, we discuss the potential application of artificial intelligence algorithms in the precise extraction of physiological signals from FGr-FETs. These reviews provide a theoretical foundation for the development of next-generation precision medicine platforms.