A film-linked electrostatic self-assembly microfluidic chip.

This article proposes a film-linked electrostatic self-assembly microfluidic chip for the first time, designed to be ready-to-use. Barrier films are used to isolate the gas/liquid path microchannels and the pre-stored reagents of the chip before use. Through the linkage design between the film materials, the motion of barrier films is linked to the structural changes inside the chip. Under the combined action of the rebound force of the elastic substrate, the electrostatic adsorption force between the substrates, and the reaction force of the elastic film, the elastic substrate and the liquid storage substrate are instantly bonded, and the self-assembly of the chip is completed within 1 s. By using six independently output programmable sequences to perform the sequential quantitative pumping of pre-stored reagents, the transfer and mixing of samples and pre-stored reagents are automatically driven in a confined space, which greatly reduces the contamination risk and loss rate of samples/reagents, and improves the accuracy and reproducibility of test results. In addition, the microfluidic multi-step reaction driven in parallel can avoid liquid reflux, accurately control the amount of reactant transfer, and realize the quantitative detection of samples. Multiple reactions can be performed synchronously without interference, saving the test time. Since each gas path is independently controllable, the chip can be extended to a variety of biochemical reactions and has the potential to detect a variety of substances.

Single image dehazing algorithm based on optical diffraction deep neural networks.

Single image dehazing is a challenging task because of the hue and brightness distortion problems due to the atmospheric scattering. These problems limit the perceptual fidelity, as well as information integrity, of a given image. In this paper, we propose an image dehazing method based on the optical neural networks dehazing by simulating optical diffraction. The algorithm is trained from a large number of hazy images and their corresponding clean images. The experimental results demonstrate that the proposed method has reached an advanced level in both PSNR and SSIM dehazing performance indicators, and the amount of calculation is less than most artificial neural networks.

Quantitative viability detection for a single microalgae cell by two-level photoexcitation.

A novel method for quantitative detection of the viability of a single microalgae cell by two-level photoexcitation is proposed in this paper. This method overcomes the difficulty of traditional methods in determining the cell viability by a fixed standard under a single photoexcitation. It is experimentally confirmed that this method is not limited by the species, morphology, size and structure of microalgae cells. An evaluation criterion of universal applicability is presented for the assessment of cell viability based on the large amount of experimental data. To the best of our knowledge, this is the first time that the relative fluorescence yield ratio Fr has been used to characterize the viability of single microalgae cells during cell migration. By using the relative fluorescence yield ratio, this method does not require the intensity of the excitation light to be very low for the assessment of the fluorescence yield of a dark-adapted microalgae cell, nor to be very strong to reach the saturated light level to assess the maximum fluorescence yield. Therefore, this method greatly reduces the technical difficulties of developing a sensor device. Well balanced portability, accuracy and universal applicability make it suitable for on-site real-time detection.

A Microfluidic Prototype System towards Microalgae Cell Separation, Treatment and Viability Characterization.

There are a huge number, and abundant types, of microalgae in the ocean; and most of them have various values in many fields, such as food, medicine, energy, feed, etc. Therefore, how to identify and separation of microalgae cells quickly and effectively is a prerequisite for the microalgae research and utilization. Herein, we propose a microfluidic system that comprised microalgae cell separation, treatment and viability characterization. Specifically, the microfluidic separation function is based on the principle of deterministic lateral displacement (DLD), which can separate various microalgae species rapidly by their different sizes. Moreover, a concentration gradient generator is designed in this system to automatically produce gradient concentrations of chemical reagents to optimize the chemical treatment of samples. Finally, a single photon counter was used to evaluate the viability of treated microalgae based on laser-induced fluorescence from the intracellular chlorophyll of microalgae. To the best of our knowledge, this is the first laboratory prototype system combining DLD separation, concentration gradient generator and chlorophyll fluorescence detection technology for fast analysis and treatment of microalgae using marine samples. This study may inspire other novel applications of micro-analytical devices for utilization of microalgae resources, marine ecological environment protection and ship ballast water management.

A novel microfluidic capture and monitoring method for assessing physiological damage of C. elegans under microgravity.

Spatial microgravity is a significant factor affecting and causing physiological changes of organisms in space environment. On-site assessment of the damage associated to microgravity is very important for future long-term space exploration of mankind. In this paper, a new microfluidic device for analyzing the damage of microgravity on Caenorhabditis elegans (C. elegans) has been developed. This device is mainly composed of a microfluidic chip, a dual imaging module, and an imaging acquisition and processing module, which are integrated into a compact system. The microfluidic chip is designed as a platform for monitoring C. elegans, which is captured in an imaging region through a suction structure in the microfluidic chip. A dual imaging module is designed to obtain the images of bright field and fluorescence of C. elegans. The behaviors of C. elegans are analyzed based on the dual-mode imaging of bright field and fluorescence to assess the degree of damage due to microgravity. A comparative study using a commercial microscope is also conducted to demonstrate the unique advantage of the developed system under the simulated microgravity. The results show that the developed system can evaluate the damage of C. elegans under microgravity accurately and conveniently. Furthermore, this device has compact size and weight, easy operation, and low-cost, which could be highly advantageous for on-site evaluation of the damage to microorganisms under microgravity in a space station.

Detection of non-small cell lung cancer cells based on microfluidic polarization microscopic image analysis.

In early diagnosis of lung cancer, a polarization microscopy is a powerful tool to obtain the optical information of biological tissues. In this paper, a new microfluidic polarization imaging and analysis method was proposed for the detection and classification of cancer-associated fibroblasts and the two kinds of non-small cell lung cancer cells, A549 and H322. A polarizing microscopy system was constructed based on a commercial microscope to obtain 3*3 Mueller matrix of cells. Based on the Muller matrix decomposition algorithm and analysis in spatial domain and frequency domain, appropriate classification parameters were selected for the characterization of different polarization characteristics of cells. Finally, the logistic regression models based on machine learning were applied to determine optimal feature parameters and classify cells. This method integrated the morphological information of the cells, and the polarization characteristics of the cells in different polarization states. It is for the first time that the polarization microscopic image analysis method has been applied to the detection and classification of non-small cell lung cancer cells. The results show that the presented microfluidic polarization microscopic image analysis method could classify cells effectively. Compared with the Muller matrix measurement and calculation methods, the method proposed in this paper was greatly simplified in both the acquisition of polarized images and the analysis and processing of polarized images.