Ultra-thin temperature controllable microwell array chip for continuous real-time high-resolution imaging of living single cells

Monolithic 3D nanoelectrospray emitters based on a continuous fluid-assisted etching strategy for glass droplet microfluidic chip-mass spectrometry

Glass microfluidic chips are suitable for coupling with mass spectrometry (MS) due to their flexible design, optical transparency and resistance to organic reagents. However, due to the high hardness and brittleness of glass, there is a lack of simple and feasible technology to manufacture a monolithic nanospray ionization (nESI) emitter on a glass microchip, which hinders its coupling with mass spectrometry. Here, a continuous fluid-assisted etching strategy is proposed to fabricate monolithic three-dimensional (3D) nESI emitters integrated into glass microchips. A continuous fluid of methanol is adopted to protect the inner wall of the channels and the bonding interface of the glass microfluidic chip from being wet-etched, forming sharp 3D nESI emitters. The fabricated 3D nESI emitter can form a stable electrospray plume, resulting in consistent nESI detection of acetylcholine with an RSD of 4.5% within 10 min. The fabricated 3D emitter is integrated on a glass microfluidic chip designed with a T-junction droplet generator, which can realize efficient analysis of acetylcholine in picoliter-volume droplets by nESI-MS. Stability testing of over 20 000 droplets detected by the established system resulted in an RSD of 9.1% over approximately 180 min. The detection of ten neurochemicals in rat cerebrospinal fluid droplets is achieved. The established glass droplet microfluidic chip-MS system exhibits potential for broad applications such as in vivo neurochemical monitoring and single-cell analysis in the future.

A Chamber-Based Digital PCR Based on a Microfluidic Chip for the Absolute Quantification and Analysis of KRAS Mutation

The Kirsten rat sarcoma virus gene (KRAS) is the most common tumor in human cancer, and KRAS plays an important role in the growth of tumor cells. Normal KRAS inhibits tumor cell growth. When mutated, it will continuously stimulate cell growth, resulting in tumor development. There are currently few drugs that target the KRAS gene. Here, we developed a microfluidic chip. The chip design uses parallel fluid channels combined with cylindrical chamber arrays to generate 20,000 cylindrical microchambers. The microfluidic chip designed by us can be used for the microsegmentation of KRAS gene samples. The thermal cycling required for the PCR stage is performed on a flat-panel instrument and detected using a four-color fluorescence system. "Glass-PDMS-glass" sandwich structure effectively reduces reagent volatilization; in addition, a valve is installed at the sample inlet and outlet on the upper layer of the chip to facilitate automatic control. The liquid separation performance of the chip was verified by an automated platform. Finally, using the constructed KRAS gene mutation detection system, it is verified that the chip has good application potential for digital polymerase chain reaction (dPCR). The experimental results show that the chip has a stable performance and can achieve a dynamic detection range of four orders of magnitude and a gene mutation detection of 0.2%. In addition, the four-color fluorescence detection system developed based on the chip can distinguish three different KRAS gene mutation types simultaneously on a single chip.

Pollution-Free and Highly Sensitive Lactate Detection in Cell Culture Based on a Microfluidic Chip

Cell metabolite detection is important for cell analysis. As a cellular metabolite, lactate and its detection play an important role in disease diagnosis, drug screening and clinical therapeutics. This paper reports a microfluidic chip integrated with a backflow prevention channel for cell culture and lactate detection. It can effectively realize the upstream and downstream separation of the culture chamber and the detection zone, and prevent the pollution of cells caused by the potential backflow of reagent and buffer solutions. Due to such a separation, it is possible to analyze the lactate concentration in the flow process without contamination of cells. With the information of residence time distribution of the microchannel networks and the detected time signal in the detection chamber, it is possible to calculate the lactate concentration as a function of time using the de-convolution method. We have further demonstrated the suitability of this detection method by measuring lactate production in human umbilical vein endothelial cells (HUVEC). The microfluidic chip presented here shows good stability in metabolite quick detection and can work continuously for more than a few days. It sheds new insights into pollution-free and high-sensitivity cell metabolism detection, showing broad application prospects in cell analysis, drug screening and disease diagnosis.

Artificial intelligence-assisted smartphone-based sensing for bioanalytical applications: A review

Artificial intelligence (AI) has received great attention since the concept was proposed, and it has developed rapidly in recent years with applications in many fields. Meanwhile, newer iterations of smartphone hardware technologies which have excellent data processing capabilities have leveraged on AI capabilities. Based on the desirability for portable detection, researchers have been investigating intelligent analysis by combining smartphones with AI algorithms. Various examples of the application of AI algorithm-based smartphone detection and analysis have been developed. In this review, we give an overview of this field, with a particular focus on bioanalytical detection applications. The applications are presented in terms of hardware design, software algorithms, and specific application areas. We also discuss the existing limitations of AI-based smartphone detection and analytical approaches, and their future prospects. The take-home message of our review is that the application of AI in the field of detection analysis is restricted by the limitations of the smartphone's hardware as well as the model building of AI for detection targets with insufficient data. Nevertheless, at this juncture, while bioanalytical diagnostics and health monitoring have set the pace for AI-based smartphone applicability, the future should see the technology making greater inroads into other fields. In relation to the latter, it is likely that the ordinary or average person will play a greater participatory role.

Nanokit coupled electrospray ionization mass spectrometry for analysis of angiotensin converting enzyme 2 activity in single living cell

Angiotensin-converting enzyme 2 (ACE2) is not only an enzyme but also a functional receptor on cell membrane for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, the activity of ACE2 in single living cell is firstly determined using a nanokit coupled electrospray ionization mass spectrometry (nanokit-ESI-MS). Upon the insertion of a micro-capillary into the living hACE2-CHO cell and the electrochemical sorting of the cytosol, the target ACE2 enzyme hydrolyses angiotensin II inside the capillary to generate angiotensin 1-7. After the electrospray of the mixture at the tip of the capillary, the product is differentiated from the substrate in molecular weight to achieve the detection of ACE2 activity in single cells. The further measurement illustrates that the inflammatory state of cells does not lead to the significant change of ACE2 catalytic activity, which elucidates the relationship between intracellular ACE2 activity and inflammation at single cell level. The established strategy will provide a specific analytical method for further studying the role of ACE2 in the process of virus infection, and extend the application of nanokit based single cell analysis.