Current Progress in Natural Deep Eutectic Solvents for the Extraction of Active Components from Plants.

In the last decade, natural deep eutectic solvents (NADESs) have gained more and more attention due to their green, convenient preparation, low toxicity and biodegradability. It is widely used in various fields, especially in the extraction of active components from plants, formed by the combination of hydrogen bond donors (HBDs) and hydrogen bond acceptors (HBAs) at a certain condition. In this article, six preparation methods of NADESs were summarized and the interactions that occur in the eutectic behavior of NADES including hydrogen bonding, electrostatic interaction and van der Waals force were also reviewed. What is more, its significant extraction capacity on flavonoids, phenols, alkaloids and plant pigments endows its extensive applications in the extraction of active components from medicinal plants. Extraction factors including solvents properties (viscosity, carbon chain length, number of hydroxyl groups), extraction condition (water content, extraction temperature, extraction time, solid-liquid ratio), extraction method and recycling method were discussed. In addition, NADESs can also be combined with other technologies, like molecular imprinting, monolithic column, to achieve efficient and specific extraction of active ingredients. Further systematic studies on the biodegradability and biotoxicity are put forward to be urgent.

Automatic identification of harmful algae based on multiple convolutional neural networks and transfer learning.

The monitoring of harmful phytoplankton is very important for the maintenance of the aquatic ecological environment. Traditional algae monitoring methods require professionals with substantial experience in algae species, which are time-consuming, expensive, and limited in practice. The automatic classification of algae cell images and the identification of harmful phytoplankton images were realized by the combination of multiple convolutional neural networks (CNNs) and deep learning techniques based on transfer learning in this work. Eleven common harmful and 31 harmless phytoplankton genera were collected as input samples; the five CNNs classification models of AlexNet, VGG16, GoogLeNet, ResNet50, and MobileNetV2 were fine-tuned to automatically classify phytoplankton images; and the average accuracy was improved 11.9% when compared to models without fine-tuning. In order to monitor harmful phytoplankton which can cause red tides or produce toxins severely polluting drinking water, a new identification method of harmful phytoplankton which combines the recognition results of five CNN models was proposed, and the recall rate reached 98.0%. The experimental results validate that the recognition performance of harmful phytoplankton could be significantly improved by transfer learning, and the proposed identification method is effective in the preliminary screening of harmful phytoplankton and greatly reduces the workload of professional personnel.

Optimization of the extraction process of flavonoids from Trollius ledebouri with natural deep eutectic solvents.

In recent years, natural deep eutectic solvents have been favored greatly due to their environment friendly, mild biological toxicity and simple biodegradability. Natural deep eutectic solvents gradually applied for the extracting bioactive compounds from natural products efficiently. In this study, 20 natural deep eutectic solvents were prepared and their physical and chemical properties were tested. The ultrasonic-assisted extraction method was used to extract flavonoids from Trollius ledebouri and high-performance liquid chromatography-ultraviolet was applied to examine two main bioactive flavonoids (orientin and vitexin). Compared with traditional solvents (water and 60% ethanol solution), natural deep eutectic solvents composed of L(-)-proline and levulinic acid (molar ratio 1:2) show a super extraction efficiency. On this basis, the response surface method was used to optimize the extraction temperature, extraction time, water contents, and solid-liquid ratio. As a consequence, the extraction temperature 60℃, extraction time 18 min, water content 14% (v/v), and the solid-liquid ratio 48 mL·g-1 were chosen as the best extraction process. This study shows that natural deep eutectic solvents can effectively extract flavonoids from T. ledebouri, laying a foundation for the further application of natural deep eutectic solvents to extract bioactive compounds from natural products.

[Development of operation patient security detection system].

This paper describes a patient security detection system developed with two dimensional bar codes, wireless communication and removal storage technique. Based on the system, nurses and correlative personnel check code wait operation patient to prevent the defaults. The tests show the system is effective. Its objectivity and currency are more scientific and sophisticated than current traditional method in domestic hospital.