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CRISPR‐Cas12a works like a sophisticated algorithm in nucleic acid detection, yet its challenge lies in sometimes failing to distinguish targets with mismatches due to its specificity limitations. Here, the mismatch profiles, including the quantity, location, and type of mismatches in the CRISPR‐Cas12a reaction, are investigated and its various tolerances to mismatches are discovered. By harnessing the specificity defect of the CRISPR‐Cas12a enzyme, a dual‐mode detection strategy is designed, which includes approximate matching and precise querying of target sequences and develop a programmable multiplexed nucleic acid assay. With the assay, 14 high‐risk human papillomavirus (HPV) subtypes are simultaneously detected, collectively responsible for 99% of cervical cancer cases, with attomolar sensitivity. Specifically, the assay not only distinguishes HPV16 and HPV18, the two most common subtypes but also detects 12 other high‐risk pooled HPV subtypes. To enable low‐cost point‐of‐care testing, the assay is incorporated into a paper‐based microfluidic chip. Furthermore, the clinical performance of the paper‐based microfluidic chip is validated by testing 75 clinical swab samples, achieving performance comparable to that of PCR. This programmable multiplexed nucleic acid assay has the potential to be widely applied for sensitive, specific, and simultaneous detection of different pathogens. A CRISPR‐Cas12a‐based dual‐mode assay strategy is developed for multiplexed nucleic acid detection by incorporating precise querying and approximate pattern matching. With the assay, HPV16 and HPV18 are not only distinguished but also 12 other high‐risk pooled HPV subtypes are detected. The assay into a paper‐based microfluidic chip is integrated and its clinical utility with 75 clinical samples, demonstrating significant promise for simple, sensitive, specific, and multiplexed detection of pathogens at the point of care is validated.

Foodborne diseases caused by pathogenic bacteria pose a serious threat to human health. Early and rapid detection of foodborne pathogens is an urgent task for preventing disease outbreaks. Microfluidic devices are simple, automatic, and portable miniaturized systems. Compared with traditional techniques, microfluidic devices have attracted much attention because of their high efficiency and convenience in the concentration and detection of foodborne pathogens. This article firstly reviews the bio-recognition elements integrated on microfluidic chips in recent years and the progress of microfluidic chip development for pathogen pretreatment. Furthermore, the research progress of microfluidic technology based on optical and electrochemical sensors for the detection of foodborne pathogenic bacteria is summarized and discussed. Finally, the future prospects for the application and challenges of microfluidic chips based on biosensors are presented.

The organ-on-a-chip (OOAC) is in the list of top 10 emerging technologies and refers to a physiological organ biomimetic system built on a microfluidic chip. Through a combination of cell biology, engineering, and biomaterial technology, the microenvironment of the chip simulates that of the organ in terms of tissue interfaces and mechanical stimulation. This reflects the structural and functional characteristics of human tissue and can predict response to an array of stimuli including drug responses and environmental effects. OOAC has broad applications in precision medicine and biological defense strategies. Here, we introduce the concepts of OOAC and review its application to the construction of physiological models, drug development, and toxicology from the perspective of different organs. We further discuss existing challenges and provide future perspectives for its application.

Microfluidic chip technology is an emerging tool in the field of biomedical application. Microfluidic chip includes a set of groves or microchannels that are engraved on different materials (glass, silicon, or polymers such as polydimethylsiloxane or PDMS, polymethylmethacrylate or PMMA). The microchannels forming the microfluidic chip are interconnected with each other for desired results. This organization of microchannels trapped into the microfluidic chip is associated with the outside by inputs and outputs penetrating through the chip, as an interface between the macro- and miniature world. With the help of a pump and a chip, microfluidic chip helps to determine the behavioral change of the microfluids. Inside the chip, there are microfluidic channels that permit the processing of the fluid, for example, blending and physicochemical responses. Microfluidic chip has numerous points of interest including lesser time and reagent utilization and alongside this, it can execute numerous activities simultaneously. The miniatured size of the chip fastens the reaction as the surface area increases. It is utilized in different biomedical applications such as food safety sensing, peptide analysis, tissue engineering, medical diagnosis, DNA purification, PCR activity, pregnancy, and glucose estimation. In the present study, the design of various microfluidic chips has been discussed along with their biomedical applications.

We present a novel method for the three-dimensional (3D) control of microrobots within a microfluidic chip. The microrobot body contains a hollow space, producing buoyancy that allows it to float in a microfluidic environment. The robot moves in the z direction by balancing magnetic and buoyancy forces. In coordination with the motion of stages in the xy plane, we achieved 3D microrobot control. A microgripper designed to grasp micron-scale objects was attached to the front of the robot, allowing it to hold and deliver micro-objects in three dimensions. The microrobot had four degrees of freedom and generated micronewton-order forces. We demonstrate the microrobot’s utility in an experiment in which it grips a 200 μm particle and delivers it in a 3D space.

Background: The hedgehog signaling system (HHS) plays an important role in the regulation of cell proliferation and differentiation during the embryonic phases. However, little is known about the involvement of HHS in the malignant transformation of cells. This study aimed to detect the role of HHS in the malignant transformation of human bronchial epithelial (16HBE) cells. Methods: In this study, two microfluidic chips were designed to investigate cigarette smoke extract (CSE)-induced malignant transformation of cells. Chip A contained a concentration gradient generator, while chip B had four cell chambers with a central channel. The 16HBE cells cultured in chip A were used to determine the optimal concentration of CSE for inducing malignant transformation. The 16HBE cells in chip B were cultured with 12.25% CSE (Group A), 12.25% CSE + 5 μmol/L cyclopamine (Group B), or normal complete medium as control for 8 months (Group C), to establish the in vitro lung inflammatory-cancer transformation model. The transformed cells were inoculated into 20 nude mice as cells alone (Group 1) or cells with cyclopamine (Group 2) for tumorigenesis testing. Expression of HHS proteins was detected by Western blot. Data were expressed as mean ± standard deviation. The t-test was used for paired samples, and the difference among groups was analyzed using a one-way analysis of variance. Results: The optimal concentration of CSE was 12.25%. Expression of HHS proteins increased during the process of malignant transformation (Group B vs. Group A, F = 7.65, P < 0.05). After CSE exposure for 8 months, there were significant changes in cellular morphology, which allowed the transformed cells to grow into tumors in 40 days after being inoculated into nude mice. Cyclopamine could effectively depress the expression of HHS proteins (Group C vs. Group B, F = 6.47, P < 0.05) and prevent tumor growth in nude mice (Group 2 vs. Group 1, t = 31.59, P < 0.01). Conclusions: The activity of HHS is upregulated during the CSE-induced malignant transformation of 16HBE cells. Cyclopamine can effectively depress expression of HHS proteins in vitro and prevent tumor growth of the transformed cells in vivo.

Immunoassays are critical for clinical diagnostics and biomedical research. However, two major challenges remaining in conventional immunoassays are precise quantification and development of immunoassays for small‐molecule detection. Here, a two signal‐mode small‐molecule immunoassay containing an internal reference that provides high stability and reproducibility compared to conventional small‐molecule immunoassays is presented. A system is developed for quantitative monitoring of the digoxin concentration in plasma in the clinically relevant range (0.6–2.6 nm). Furthermore, the model system is integrated into a simple gravity‐driven microfluidic chip (G‐Chip) requiring only 10 µL plasma. The G‐Chip allows fast detection without any complex operation and can be recycled for at least 50 times. The assay, and the G‐Chip in particular, has the potential for further development of point‐of‐care (POC) diagnostics. Aiming at two major challenges in conventional immunoassays, precise quantification of the amount of target analyte and development of immunoassays for small‐molecule detection, a two signal‐mode small‐molecule immunoassay containing an internal reference is presented to provide high stability and reproducibility. Furthermore, the digoxin detection model system is integrated into a simple and recyclable gravity‐driven microfluidic chip (G‐Chip).

The development of pharmaceutical analytical methods represents one of the most significant aspects of drug development. Recent advances in microfabrication and microfluidics could provide new approaches for drug analysis, including drug screening, active testing and the study of metabolism. Microfluidic chip technologies, such as lab-on-a-chip technology, three-dimensional (3D) cell culture, organs-on-chip and droplet techniques, have all been developed rapidly. Microfluidic chips coupled with various kinds of detection techniques are suitable for the high-throughput screening, detection and mechanistic study of drugs. This review highlights the latest (2010–2018) microfluidic technology for drug analysis and discusses the potential future development in this field.

Capillary microfluidic chips (CMCs) enable passive liquid transport via surface tension and wettability gradients, making them central to point-of-care diagnostics and biomedical sensing. However, accurate analysis of capillary-driven flow experiments remains constrained by the labour-intensive, time-consuming, and inconsistent nature of manual fluid path tracking. Here, we present AI-CMCA, an artificial intelligence framework designed for capillary microfluidic chip analysis, which automates fluid path detection and tracking using deep learning-based segmentation. AI-CMCA combines transfer learning-based feature initialization, encoder-decoder-based semantic segmentation to recognize fluid in each frame, and sequential frame analysis to track then quantify fluid progression. Among the five tested architectures, including U-Net, PAN, FPN, PSP-Net, and DeepLabV3+, the U-Net model with MobileNetV2 achieved the highest performance, with a validation IoU of 99.24% and an F1-score of 99.56%. Its lightweight design makes it well suited for smartphone or edge deployment. AI-CMCA demonstrated a strong correlation with manually extracted data while offering superior robustness and consistency in fluid path analysis. AI-CMCA performed fluid path analysis up to 100 times faster and over 10 times more consistently than manual tracking, reducing analysis time from days to minutes while maintaining high precision and reproducibility across diverse CMC architectures. By eliminating the need for manual annotation, AI-CMCA significantly enhances efficiency, precision, and automation in microfluidic research.

Eight out of 10 breast cancer patients die within 5 years after the primary tumor has spread to the bones. Tumor cells disseminated from the breast roam the vasculature, colonizing perivascular niches around blood capillaries. Slow flows support the niche maintenance by driving the oxygen, nutrients, and signaling factors from the blood into the interstitial tissue, while extracellular matrix, endothelial cells, and mesenchymal stem cells regulate metastatic homing. Here, we show the feasibility of developing a perfused bone perivascular niche-on-a-chip to investigate the progression and drug resistance of breast cancer cells colonizing the bone. The model is a functional human triculture with stable vascular networks within a 3D native bone matrix cultured on a microfluidic chip. Providing the niche-on-a-chip with controlled flow velocities, shear stresses, and oxygen gradients, we established a long-lasting, self-assembled vascular network without supplementation of angiogenic factors. We further show that human bone marrow-derived mesenchymal stem cells, which have undergone phenotypical transition toward perivascular cell lineages, support the formation of capillary-like structures lining the vascular lumen. Finally, breast cancer cells exposed to interstitial flow within the bone perivascular niche-on-a-chip persist in a slow-proliferative state associated with increased drug resistance. We propose that the bone perivascular niche-on-a-chip with interstitial flow promotes the formation of stable vasculature and mediates cancer cell colonization.