Neural Network-Based Optimization of an Acousto Microfluidic System for Submicron Bioparticle Separation

The use of droplet-based microfluidic technologies for accelerated selection of Yarrowia lipolytica and Phaffia rhodozyma yeast mutants

Microorganisms are widely used for the industrial production of various valuable products, such as pharmaceuticals, food and beverages, biofuels, enzymes, amino acids, vaccines, etc. Research is constantly carried out to improve their properties, mainly to increase their productivity and efficiency and reduce the cost of the processes. The selection of microorganisms with improved qualities takes a lot of time and resources (both human and material); therefore, this process itself needs optimization. In the last two decades, microfluidics technology appeared in bioengineering, which allows for manipulating small particles (from tens of microns to nanometre scale) in the flow of liquid in microchannels. The technology is based on small-volume objects (microdroplets from nano to femtolitres), which are manipulated using a microchip. The chip is made of an optically transparent inert to liquid medium material and contains a series of channels of small size (<1 mm) of certain geometry. Based on the physical and chemical properties of microparticles (like size, weight, optical density, dielectric constant, etc.), they are separated using microsensors. The idea of accelerated selection of microorganisms is the application of microfluidic technologies to separate mutants with improved qualities after mutagenesis. This article discusses the possible application and practical implementation of microfluidic separation of mutants, including yeasts like Yarrowia lipolytica and Phaffia rhodozyma after chemical mutagenesis will be discussed.

High-throughput microfluidic systems accelerated by artificial intelligence for biomedical applications

High-throughput microfluidic systems are widely used in biomedical fields for tasks like disease detection, drug testing, and material discovery. Despite the great advances in automation and throughput, the large amounts of data generated by the high-throughput microfluidic systems generally outpace the abilities of manual analysis. Recently, the convergence of microfluidic systems and artificial intelligence (AI) has been promising in solving the issue by significantly accelerating the process of data analysis as well as improving the capability of intelligent decision. This review offers a comprehensive introduction on AI methods and outlines the current advances of high-throughput microfluidic systems accelerated by AI, covering biomedical detection, drug screening, and automated system control and design. Furthermore, the challenges and opportunities in this field are critically discussed as well.

Recent Progress and Perspectives on Neural Chip Platforms Integrating PDMS-Based Microfluidic Devices and Microelectrode Arrays

Recent years have witnessed a spurt of progress in the application of the encoding and decoding of neural activities to drug screening, diseases diagnosis, and brain-computer interactions. To overcome the constraints of the complexity of the brain and the ethical considerations of in vivo research, neural chip platforms integrating microfluidic devices and microelectrode arrays have been raised, which can not only customize growth paths for neurons in vitro but also monitor and modulate the specialized neural networks grown on chips. Therefore, this article reviews the developmental history of chip platforms integrating microfluidic devices and microelectrode arrays. First, we review the design and application of advanced microelectrode arrays and microfluidic devices. After, we introduce the fabrication process of neural chip platforms. Finally, we highlight the recent progress on this type of chip platform as a research tool in the field of brain science and neuroscience, focusing on neuropharmacology, neurological diseases, and simplified brain models. This is a detailed and comprehensive review of neural chip platforms. This work aims to fulfill the following three goals: (1) summarize the latest design patterns and fabrication schemes of such platforms, providing a reference for the development of other new platforms; (2) generalize several important applications of chip platforms in the field of neurology, which will attract the attention of scientists in the field; and (3) propose the developmental direction of neural chip platforms integrating microfluidic devices and microelectrode arrays.

Recent advances in acoustofluidic separation technology in biology

Acoustofluidic separation of cells and particles is an emerging technology that integrates acoustics and microfluidics. In the last decade, this technology has attracted significant attention due to its biocompatible, contactless, and label-free nature. It has been widely validated in the separation of cells and submicron bioparticles and shows great potential in different biological and biomedical applications. This review first introduces the theories and mechanisms of acoustofluidic separation. Then, various applications of this technology in the separation of biological particles such as cells, viruses, biomolecules, and exosomes are summarized. Finally, we discuss the challenges and future prospects of this field.