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Access to clean water is fundamental to public health and safety, serving as the cornerstone of well-being in communities. Despite the significant investments of millions of dollars in water testing and treatment processes, the United States continues to grapple with over 7 million waterborne-related cases annually. This persistent challenge underscores the pressing need for the development of a new, efficient, rapid, low-cost, and reliable method for ensuring water quality. The urgency of this endeavor cannot be overstated, as it holds the potential to safeguard countless lives and mitigate the pervasive risks associated with contaminated water sources. In this study, we introduce a biochip LAMP assay tailored for water source monitoring. Our method swiftly detects even extremely low concentrations of Escherichia coli (E. coli) in water, and 10 copies/μL of E. coli aqueous solution could yield positive results within 15 min on a PC-MEDA biochip. This innovation marks a significant departure from the current reliance on lab-dependent methods, which typically necessitate several days for bacterial culture and colony counting. Our multifunctional biochip system not only enables the real-time LAMP testing of crude E. coli samples but also holds promise for future modifications to facilitate on-site usage, thereby revolutionizing water quality assessment and ensuring rapid responses to potential contamination events.

Digital microfluidic biochips (DMFBs), which are used in various fields like DNA analysis, clinical diagnosis, and PCR testing, have made biochemical experiments more compact, efficient, and user-friendly than the previous methods. However, their reliability is often compromised by their inability to adapt to all kinds of errors. Errors in biochips can be categorized into two types: known errors, and unknown errors. Known errors are detectable before the start of the routing process using sensors or cameras. Unknown errors, in contrast, only become apparent during the routing process and remain undetected by sensors or cameras, which can unexpectedly stop the routing process and diminish the reliability of biochips. This paper introduces a deep reinforcement learning-based routing algorithm, designed to manage not only known errors but also unknown errors. Our experiments demonstrated that our algorithm outperformed the previous ones in terms of the success rate of the routing, in the scenarios including both known errors and unknown errors. Additionally, our algorithm contributed to detecting unknown errors during the routing process, identifying the most efficient routing path with a high probability.

Biochips, a novel technology in the field of biomolecular analysis, offer a promising alternative to conventional testing equipment. These chips integrate multiple functions within a single system, providing a compact and efficient solution for various testing needs. For biochips, a pattern-control micro-electrode-dot-array (MEDA) is a new, universally viable design that can replace microchannels and other micro-components. In a Micro Electrode Dot Array (MEDA), each electrode can be programmatically controlled or dynamically grouped, allowing a single chip to fulfill the diverse requirements of different tests. This capability not only enhances flexibility, but also contributes to cost reduction by eliminating the need for multiple specialized chips. In this paper, we present a visible biochip testing system for tracking the entire testing process in real time, and describe our application of the system to detect SARS-CoV-2.

Organ-on-a-chip systems are miniaturized microfluidic 3D human tissue and organ models designed to recapitulate the important biological and physiological parameters of their in vivo counterparts. They have recently emerged as a viable platform for personalized medicine and drug screening. These in vitro models, featuring biomimetic compositions, architectures, and functions, are expected to replace the conventional planar, static cell cultures and bridge the gap between the currently used preclinical animal models and the human body. Multiple organoid models may be further connected together through the microfluidics in a similar manner in which they are arranged in vivo, providing the capability to analyze multiorgan interactions. Although a wide variety of human organ-on-a-chip models have been created, there are limited efforts on the integration of multisensor systems. However, in situ continual measuring is critical in precise assessment of the microenvironment parameters and the dynamic responses of the organs to pharmaceutical compounds over extended periods of time. In addition, automated and noninvasive capability is strongly desired for long-term monitoring. Here, we report a fully integrated modular physical, biochemical, and optical sensing platform through a fluidics-routing breadboard, which operates organ-on-a-chip units in a continual, dynamic, and automated manner. We believe that this platform technology has paved a potential avenue to promote the performance of current organ-on-a-chip models in drug screening by integrating a multitude of real-time sensors to achieve automated in situ monitoring of biophysical and biochemical parameters.

This study explores the application of biochip recognition technology to analyze the mechanical interaction and wear characteristics of pick-type truncated teeth used in mining operations. By employing advanced biotechnological methods, including Nano pore sequencing, the research converts the adsorption-induced deformation or vibration signals of the pick-type teeth into mechanical vibration data. These signals are then analyzed to understand the effects of variables such as pH value and ionic strength on the deformation and mechanical properties of the teeth during their interaction with coal rock. A comprehensive mechanical model was developed to investigate the impact of tooth wear and cutting forces on the performance of the pick-type teeth, with measurements conducted using a biochip recognition detector. The results indicate that for a jet diameter of 0.5 mm, the impact force remains relatively stable, ranging between 30 to 50 MPa, with minimal variation. However, when the jet diameter increases to 1.0 mm, the impact force varies significantly with velocity, showing differences of approximately 50 MPa. This study provides critical insights into the wear mechanisms of pick teeth in mining equipment under actual underground working conditions. The integration of biochip technology offers a novel approach to enhancing the durability and efficiency of mining tools, demonstrating both theoretical significance and practical value. This research aligns with the scope of the Journal of Commercial Biotechnology by showcasing the application of biotechnological innovations in industrial processes, particularly in improving the performance and reliability of critical mining equipment.

With the growing interest in biochips, numerous efforts have been made to recapitulate a more reliable and physiologically relevant environment within chips, resulting in significant advances in biochip technologies. Although there have been substantial improvements in biochip fabrication technologies, less effort has been devoted to improving imaging or microscopic methods specialized for observing in-chip structures. As biochip structures become increasingly sophisticated and the complexity of scaffolds mixed with cells and the extracellular matrix grows, the demand for customized imaging technology for biochips is expected to increase rapidly. In response to these demands, in this review, we briefly introduce various imaging technologies based on the complexity and size of imaging targets embedded in the chip.

Biochips have been widely used in many fields in recent years, and the quality of biochips determines the accuracy of the detection results of virtual reality technology. This paper first studies the detection of biochip work piece size and position offset. The curve energy generalization is minimized by continuous iteration to find the target edge profile. At the same time, the least squares method is used to fit the straight line and the Hough straight line fit to obtain the straight line parameters and calculate the workpiece size and the offset angle. Then, based on biochip-mediated virtual reality technology characteristics, we study the application cases of VR technology in the fields of interior design, landscape design, and urban planning and derive the trend of VR in environmental art design. The experimental samples are selected, correlation analysis is performed, and the results show that all of them are positively correlated at a 0.01 significance level, and their correlation coefficients are 0.776, 0.481, and 0.831, respectively. Except for the low correlation coefficient between fun and satisfaction, immersion and manipulability strongly correlate with presence. This study enriches the application of VR technology in the design field and catalyzes the development of environmental art design.

Digital microfluidic biochips are becoming an alternative for laboratory experiments like DNA analysis, immunoassays and safety clinical diagnostics. Reliability is a critical issue for them. MEDA biochips are a new kind of digital microfluidic biochips which are based on microelectrode-dot-array. Daisy chain is the key component of a MEDA biochip, if there is one fault exist in one cell, the whole daisy chain is broken down, the biochip has to be discarded. Therefore, daisy chain’s reliability is especially critical. The paper proposes a new daisy chain online repair scheme, where the cells of daisy chain are repaired during the time of the functional data shifted in. The emphasis is on identifying and repairing the fail daisy chain cells when bioassay is running, without any influence on the executing bioassay. Besides, the online self-repair scheme does not contribute to electrode degradation, and takes no additional time. The experimental results also prove the efficiency of the scheme.

Digital microfluidic biochip is a promising alternative to the traditional cumbersome laboratory equipment. Such automated biochips are used in many critical applications. Hence dependability is an essential attribute before the chip is in use. Due to mixed integration technologies, these chips have some unique failures. Hence robust offline and online tests are proposed to check the health of the biochips. When a chip undergoes a test in offline mode, then the entire biochip should be available for testing, whereas for the online mode test droplet might be stalled due to unavailability of the next cell in the routing path. However, in both the scenarios one or more droplets route across the chip and the arrival time is also recorded at the destination. So here we have proposed two test schemes to know the correctness of any biochip. Diagnosability is an important feature to find the exact position of the faulty electrode. Our proposed scheme reduces the overall testing and diagnosis time significantly. It also provides an alternative routing path in biochip for fault tolerance.

Cell models are one of the most widely used basic models in biological research, and a variety of in vitro cell culture techniques and models have been developed recently to simulate the physiological microenvironment in vivo. However, regardless of the technique or model, cell culture is the most fundamental but crucial component. As a result, we have developed a cell culture monitoring system to assess the functional status of cells within a biochip. This article focuses on a mini-microscope made from a readily available camera for in situ continuous observation of cell growth within a biochip and a pH sensor based on optoelectronic sensing for measuring pH. With the aid of this monitoring system, scientists can keep an eye on cell growth in real time and learn how the pH of the culture medium affects it. This study offers a new approach for tracking cells on biochips and serves as a valuable resource for enhancing cell culture conditions.