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Rapid nucleic acid testing is central to infectious disease surveillance. Here, we report an assay for rapid COVID-19 testing and its implementation in a prototype microfluidic device. The assay, which we named DISCoVER (for diagnostics with coronavirus enzymatic reporting), involves extraction-free sample lysis via shelf-stable and low-cost reagents, multiplexed isothermal RNA amplification followed by T7 transcription, and Cas13-mediated cleavage of a quenched fluorophore. The device consists of a single-use gravity-driven microfluidic cartridge inserted into a compact instrument for automated running of the assay and readout of fluorescence within 60 min. DISCoVER can detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in saliva with a sensitivity of 40 copies μl-1, and was 94% sensitive and 100% specific when validated (against quantitative PCR) using total RNA extracted from 63 nasal-swab samples (33 SARS-CoV-2-positive, with cycle-threshold values of 13-35). The device correctly identified all tested clinical saliva samples (10 SARS-CoV-2-positive out of 13, with cycle-threshold values of 23-31). Rapid point-of-care nucleic acid testing may broaden the use of molecular diagnostics.

The existing evaluation method of mine ventilation system is to evaluate it as a whole from the overall perspective of mine ventilation system. The evaluation conclusions are static and comprehensive, which cannot precisely locate the ventilation situation in the wind range of the mine and discover its problems, and can not reflect the current state of ventilation quality in real time. In order to solve the above problems, a dynamic evaluation model of mine ventilation quality based on fuzzy comprehensive evaluation method-analytic hierarchy process(FCE-AHP) is established to evaluate the ventilation quality of coal mines in real time. Firstly, according to the requirements and functions of mine ventilation, the ventilation area is divided into five areas, namely, air inlet section, air return section, coal working face, heading face and chamber. And the corresponding evaluation index system is determined according to each type of ventilation area. Secondly, according to the evaluation index system, the data monitored in real time by the sensors of corresponding wind measuring points are obtained, the evaluation index weights of each area are determined by AHP. And the membership degree of the evaluation level belonging to the real-time monitoring data is calculated by the Cauchy distribution membership function. Finally, the rating weights are calculated by applying FCE, and the regional ventilation quality level is determined by the confidence recognition principle so as to complete the dynamic evaluation of the ventilation quality of each region. Taking the south wing of return airway of Dongtan Coal Mine as an example, the FCE-AHP model is used to evaluate the ventilation quality of Dongtan Coal Mine in real time. The evaluation results show that the ventilation quality is good and is consistent with the actual situation, which proves the reliability of the model. The FCE-AHP model can evaluate the ventilation quality of different ventilation areas of coal mines in real time based on the data monitored in real time, determine the safety level of coal mine ventilation quality, then achieve a comprehensive evaluation of mine ventilation quality, and provide a basis for improving the quality of coal mine ventilation systems.

BACKGROUND: Drug repositioning (DR) refers to a method used to find new targets for existing drugs. This method can effectively reduce the development cost of drugs, save time on drug development, and reduce the risks of drug design. The traditional experimental methods related to DR are time-consuming, expensive, and have a high failure rate. Several computational methods have been developed with the increase in data volume and computing power. In the last decade, matrix factorization (MF) methods have been widely used in DR issues. However, these methods still have some challenges. (1) The model easily falls into a bad local optimal solution due to the high noise and high missing rate in the data. (2) Single similarity information makes the learning power of the model insufficient in terms of identifying the potential associations accurately. OBJECTIVE: We proposed self-paced learning with dual similarity information and MF (SPLDMF), which introduced the self-paced learning method and more information related to drugs and targets into the model to improve prediction performance. METHODS: Combining self-paced learning first can effectively alleviate the model prone to fall into a bad local optimal solution because of the high noise and high data missing rate. Then, we incorporated more data into the model to improve the model's capacity for learning. RESULTS: Our model achieved the best results on each dataset tested. For example, the area under the receiver operating characteristic curve and the precision-recall curve of SPLDMF was 0.982 and 0.815, respectively, outperforming the state-of-the-art methods. CONCLUSION: The experimental results on five benchmark datasets and two extended datasets demonstrated the effectiveness of our approach in predicting drug-target interactions. [ABSTRACT FROM AUTHOR]

Wide‐bandgap (WBG) perovskite solar cells (PSCs) have drawn great attention owing to their promising potential for constructing efficient tandem solar cells. However, the rapid crystallization results in poor film properties and easy formation of defects, thereby greatly restricting the acquisition of a small open‐circuit voltage (VOC) deficit due to the severe nonradiative recombination. Herein, it introduced the triethanolamine borate (TB) to effectively slow down the rapid crystallization for preparing highly crystalline and uniform WBG perovskite films with reduced defects. The strong intermolecular interaction (e.g., coordination and hydrogen bond) between TB and perovskite can suppress the halide vacancy formation and inhibit phase segregation for improving long‐term stability. The devices based on a 1.65 eV perovskite absorber achieved a high efficiency of 21.55% with a VOC of 1.24 V, demonstrating the VOC deficit is as low as 0.41 V, which is one of the lowest reports. By combining a semitransparent WBG subcell with a narrow‐bandgap tin‐based PSC, the four‐terminal tandem solar cell delivers a high efficiency of 26.48%. [ABSTRACT FROM AUTHOR]