Underwater image quality assessment.

To obtain high-visual-quality underwater images by image post-processing, many underwater image restoration and enhancement methods have been proposed. Underwater image quality assessment (UIQA) methods have been developed to compare these restoration and enhancement methods. This paper comprehensively summarizes the subjective and objective UIQA methods, metrics, and datasets. Experiments are conducted on two underwater image datasets to analyze the performance of several typical UIQA metrics. Suggestions for further research directions are put forward as well.

Surface acoustic wave manipulation of bioparticles.

The introduction of surface acoustic waves (SAWs) into lab-on-a-chip microfluidic systems has contributed to the development of a new cutting-edge technology-SAW-based micro/nano manipulation. Recently, the SAW technology has emerged as an important tool for manipulating micro/nano particles/cell populations by virtue of its simplicity, biocompatibility, non-invasiveness, scalability, and versatility. In custom-designed acoustic fields, this technology can be used to manipulate cells, bacteria, exosomes, and even worms precisely, and it has been used in applications such as biomedical and point-of-care diagnostic systems. In this review paper, we start by providing a comprehensive overview of the fundamental working principle and numerical simulation of SAW-based manipulation. Then, we introduce the recent advancements in the manipulation of organisms based on standing and traveling SAWs, including separation, concentration, and transport. At the end of the review, we discuss the current challenges to and future prospects of SAW-based manipulation. The conclusion is that the SAW technology will open up a new frontier in the microfluidics field and contribute significantly to the development of bioengineering research and applications.

Accurate and Automatic Extraction of Cell Self-Rotation Speed in an ODEP Field Using an Area Change Algorithm.

Cells are complex biological units that can sense physicochemical stimuli from their surroundings and respond positively to them through characterization of the cell behavior. Thus, understanding the motions of cells is important for investigating their intrinsic properties and reflecting their various states. Computer-vision-based methods for elucidating cell behavior offer a novel approach to accurately extract cell motions. Here, we propose an algorithm based on area change to automatically extract the self-rotation of cells in an optically induced dielectrophoresis field. To obtain a clear and complete outline of the cell structure, dark corner removal and contrast stretching techniques are used in the pre-processing stage. The self-rotation speed is calculated by determining the frequency of the cell area changes in all of the captured images. The algorithm is suitable for calculating in-plane and out-of-plane rotations, while addressing the problem of identical images at different rotation angles when dealing with rotations of spherical and flat cells. In addition, the algorithm can be used to determine the motion trajectory of cells. The experimental results show that the algorithm can efficiently and accurately calculate cell rotation speeds of up to ~155 rpm. Potential applications of the proposed algorithm include cell morphology extraction, cell classification, and characterization of the cell mechanical properties. The algorithm can be very helpful for those who are interested in using computer vision and artificial-intelligence-based ideology in single-cell studies, drug treatment, and other bio-related fields.

Non-invasive acquisition of mechanical properties of cells via passive microfluidic mechanisms: A review.

The demand to understand the mechanical properties of cells from biomedical, bioengineering, and clinical diagnostic fields has given rise to a variety of research studies. In this context, how to use lab-on-a-chip devices to achieve accurate, high-throughput, and non-invasive acquisition of the mechanical properties of cells has become the focus of many studies. Accordingly, we present a comprehensive review of the development of the measurement of mechanical properties of cells using passive microfluidic mechanisms, including constriction channel-based, fluid-induced, and micropipette aspiration-based mechanisms. This review discusses how these mechanisms work to determine the mechanical properties of the cell as well as their advantages and disadvantages. A detailed discussion is also presented on a series of typical applications of these three mechanisms to measure the mechanical properties of cells. At the end of this article, the current challenges and future prospects of these mechanisms are demonstrated, which will help guide researchers who are interested to get into this area of research. Our conclusion is that these passive microfluidic mechanisms will offer more preferences for the development of lab-on-a-chip technologies and hold great potential for advancing biomedical and bioengineering research studies.

Recent advances in AFM-based biological characterization and applications at multiple levels.

Atomic force microscopy (AFM) has found a wide range of bio-applications in the past few decades due to its ability to measure biological samples in natural environments at a high spatial resolution. AFM has become a key platform in biomedical, bioengineering and drug research fields, enabling mechanical and morphological characterization of live biological systems. Hence, we provide a comprehensive review on recent advances in the use of AFM for characterizing the biomechanical properties of multi-scale biological samples, ranging from molecule, cell to tissue levels. First, we present the fundamental principles of AFM and two AFM-based models for the characterization of biomechanical properties of biological samples, covering key AFM devices and AFM bioimaging as well as theoretical models for characterizing the elasticity and viscosity of biomaterials. Then, we elaborate on a series of new experimental findings through analysis of biomechanics. Finally, we discuss the future directions and challenges. It is envisioned that the AFM technique will enable many remarkable discoveries, and will have far-reaching impacts on bio-related studies and applications in the future.

Determination of Dielectric Properties of Cells using AC Electrokinetic-based Microfluidic Platform: A Review of Recent Advances.

Cell dielectric properties, a type of intrinsic property of cells, can be used as electrophysiological biomarkers that offer a label-free way to characterize cell phenotypes and states, purify clinical samples, and identify target cancer cells. Here, we present a review of the determination of cell dielectric properties using alternating current (AC) electrokinetic-based microfluidic mechanisms, including electro-rotation (ROT) and dielectrophoresis (DEP). The review covers theoretically how ROT and DEP work to extract cell dielectric properties. We also dive into the details of differently structured ROT chips, followed by a discussion on the determination of cell dielectric properties and the use of these properties in bio-related applications. Additionally, the review offers a look at the future challenges facing the AC electrokinetic-based microfluidic platform in terms of acquiring cell dielectric parameters. Our conclusion is that this platform will bring biomedical and bioengineering sciences to the next level and ultimately achieve the shift from lab-oriented research to real-world applications.

Label-free characterization of different kinds of cells using optoelectrokinetic-based microfluidics.

We report a novel, to the best of our knowledge, method to rapidly characterize different kinds of cells and drug-treated cancer cells using a label-free biomarker of self-rotation in an optoelectrokinetics (OEK)-based microfluidic platform. OEK incorporates optics and electrokinetics into microfluidics, thereby offering a contact-free, label-free, and rapid approach to the cellular manipulation community. Self-rotational behaviors of four different kinds of cells were experimentally investigated by the frequency-sweeping of an AC bias potential in an optically induced nonuniform and irrotational electric field. The results revealed that these kinds of cells displayed a Gaussian distribution versus the AC frequency as well as different self-rotational speeds under the same conditions. Furthermore, the peak self-rotational speed varied from one kind of cell to another, with that of cancer cells higher than that of normal cells. In addition, MCF-7 cells treated by various concentrations of drug showed remarkably different self-rotational speeds. This finding suggests a high potential of developing a new label-free biomarker to rapidly distinguish different kinds of cancer cells and quantitatively monitor the response of cancer patients to various treatments.

A Review on Optoelectrokinetics-Based Manipulation and Fabrication of Micro/Nanomaterials.

Optoelectrokinetics (OEK), a fusion of optics, electrokinetics, and microfluidics, has been demonstrated to offer a series of extraordinary advantages in the manipulation and fabrication of micro/nanomaterials, such as requiring no mask, programmability, flexibility, and rapidness. In this paper, we summarize a variety of differently structured OEK chips, followed by a discussion on how they are fabricated and the ways in which they work. We also review how three differently sized polystyrene beads can be separated simultaneously, how a variety of nanoparticles can be assembled, and how micro/nanomaterials can be fabricated into functional devices. Another focus of our paper is on mask-free fabrication and assembly of hydrogel-based micro/nanostructures and its possible applications in biological fields. We provide a summary of the current challenges facing the OEK technique and its future prospects at the end of this paper.

Accurate Extraction of the Self-Rotational Speed for Cells in an Electrokinetics Force Field by an Image Matching Algorithm.

We present an image-matching-based automated algorithm capable of accurately determining the self-rotational speed of cancer cells in an optically-induced electrokinetics-based microfluidic chip. To automatically track a specific cell in a video featuring more than one cell, a background subtraction technique was used. To determine the rotational speeds of cells, a reference frame was automatically selected and curve fitting was performed to improve the stability and accuracy. Results show that the algorithm was able to accurately calculate the self-rotational speeds of cells up to ~150 rpm. In addition, the algorithm could be used to determine the motion trajectories of the cells. Potential applications for the developed algorithm include the differentiation of cell morphology and characterization of cell electrical properties.

Distinctive translational and self-rotational motion of lymphoma cells in an optically induced non-rotational alternating current electric field.

In this paper, the translational motion and self-rotational behaviors of the Raji cells, a type of B-cell lymphoma cell, in an optically induced, non-rotational, electric field have been characterized by utilizing a digitally programmable and optically activated microfluidics chip with the assistance of an externally applied AC bias potential. The crossover frequency spectrum of the Raji cells was studied by observing the different linear translation responses of these cells to the positive and negative optically induced dielectrophoresis force generated by a projected light pattern. This digitally projected spot served as the virtual electrode to generate an axisymmetric and non-uniform electric field. Then, the membrane capacitance of the Raji cells could be directly measured. Furthermore, Raji cells under this condition also exhibited a self-rotation behavior. The repeatable and controlled self-rotation speeds of the Raji cells to the externally applied frequency and voltage were systematically investigated and characterized via computer-vision algorithms. The self-rotational speed of the Raji cells reached a maximum value at 60 kHz and demonstrated a quadratic relationship with respect to the applied voltage. Furthermore, optically projected patterns of four orthogonal electrodes were also employed as the virtual electrodes to manipulate the Raji cells. These results demonstrated that Raji cells located at the center of the four electrode pattern could not be self-rotated. Instead any Raji cells that deviated from this center area would also self-rotate. Most importantly, the Raji cells did not exhibit the self-rotational behavior after translating and rotating with respect to the center of any two adjacent electrodes. The spatial distributions of the electric field generated by the optically projected spot and the pattern of four electrodes were also modeled using a finite element numerical simulation. These simulations validated that the electric field distributions were non-uniform and non-rotational. Hence, the non-uniform electric field must play a key role in the self-rotation of the Raji cells. As a whole, this study elucidates an optoelectric-coupled microfluidics-based mechanism for cellular translation and self-rotation that can be used to extract the dielectric properties of the cells without using conventional metal-based microelectrodes. This technique may provide a simpler method for label-free identification of cancerous cells with many associated clinical applications.