Organocatalytic Enantioselective Synthesis of Inherently Chiral Calix[4]arenes.

Inherently chiral calix[4]arenes are an excellent structural scaffold for enantioselective synthesis, chiral recognition, sensing, and circularly polarized luminescence. However, their catalytic enantioselective synthesis remains challenging. Herein, we report an efficient synthesis of inherently chiral calix[4]arene derivatives via cascade enantioselective cyclization and oxidation reactions. The three-component reaction features a broad substrate scope (33 examples), high efficiency (up to 90 % yield), and excellent enantioselectivity (>95 % ee on average). The potential applications of calix[4]arene derivatives are highlighted by their synthetic transformation and a detailed investigation of their photophysical and chiroptical properties.

Novel functionalized poly(glycidyl methacrylate-co-ethylene dimethacrylate) microspheres for the solid-phase extraction of glycopeptides/glycoproteins.

Novel 3-aminophenylboronic acid functionalized poly(glycidyl methacrylate-co-ethylene dimethacrylate) microspheres were prepared for the solid-phase extraction of glycopeptides/glycoproteins. The adsorption efficiency, maximum adsorption capacity, and specific recognition of the microspheres to glycoprotein were investigated. The results indicated excellent adsorption of glycoproteins by the microspheres, which are attributed to the well-defined boronic acid brushes on the microsphere surfaces. Furthermore, a solid-phase extraction microcolumn filled with the microspheres was used to efficiently enrich glycopeptides from enzymatic hydrolysates from human serum samples. The mass spectrometry results demonstrated that the method is suitable for the separation and enrichment of glycopeptides/glycoproteins from complex biological samples.

Arrhythmia Classification Algorithm Based on a Two-Dimensional Image and Modified EfficientNet.

The classification and identification of arrhythmias using electrocardiogram (ECG) signals are of great practical significance in the early prevention and diagnosis of cardiovascular diseases. In this study, we propose an arrhythmia classification algorithm based on two-dimensional (2D) images and modified EfficientNet. First, we developed a method for converting original one-dimensional (1D) ECG signals into 2D image signals. In contrast with the existing classification method that uses only the time-domain features of a 1D ECG signal, the classification of 2D images can consider the spatiotemporal characteristics of the signal. Then, to better assign feature weights, we introduced an attention feature fusion module (AFF) into the EfficientNet network to replace the addition operation in the mobile inverted bottleneck convolution (MBConv) structure of the network. We selected EfficientNet for modification because, compared with most convolutional neural networks (CNNs), EfficientNet does not require manual adjustment of parameters, which improves the accuracy and speed of the network. Finally, we combined the 2D images and the improved EfficientNet network and tested its performance as an arrhythmia classification method. Our experimental results show that the network training of the proposed method requires less equipment and training time, and this method can effectively distinguish eight types of heartbeats in the MIT-BIH arrhythmia database, with a classification accuracy of 99.54%. Thus, the model has a good classification effect.

Improved performance of α-amylase immobilized on poly(glycidyl methacrylate-co-ethylenedimethacrylate) beads.

α-Amylase was successfully immobilized onto poly(glycidyl methacrylate-co-ethylenedimethacrylate) (PGMA/EDMA) beads with high immobilization efficiency of 87.8%. PGMA/EDMA beads with a relatively uniform diameter of 2-3 µm were prepared by single-step swelling polymerization. After amination with ethanediamine and activation with glutaraldehyde, PGMA/EDMA beads showed commendable α-amylase immobilization capacity of 35.1 mg g(-1) carrier. Compared with free form, immobilized α-amylase had increasement of 12.94 mg mL(-1) for Km and 0.124 mmol mL(-1) min(-1) for Vmax, improved acid resistance (the optimal pH from 7 to 5), presented better thermal stability by retaining 61% activity than 40% at 90 °C, and displayed high operational reusability by retaining 58% of its initial activity after nine uses. Moreover, less than 10% of the free enzyme and more than 80% of the immobilized enzyme retained activity after 180 min pre-incubation at 50 °C. The easy modification, high immobilization efficiency and good properties of immobilized α-amylase in the present study indicate that PGMA/EDMA beads are suitable for α-amylase immobilization. The enhancement of acid resistance and thermo stability is doubtless of benefit for the industrial use of α-amylase.