MXene-Based Pressure Sensor with a Self-Healing Property for Joule Heating and Friction Sliding.

As a kind of flexible electronic device, flexible pressure sensor has attracted wide attention in medical monitoring and human-machine interaction. With the continuous deepening of research, high-sensitivity sensor is developing from single function to multi-function. However, Current multifunctional sensors lack the ability to integrate joule heating, detect sliding friction, and self-healing. Herein, a MXene/polyurethane (PU) flexible pressure sensor with a self-healing property for joule heating and friction sliding is fabricated. The MXene/PU sensitive layer with special spinosum structure is prepared by a simple spraying method. After face-to-face assembly of the sensitive layers, the MXene/PU flexible pressure sensor is obtained and showed excellent sensitivity (150.65 kPa-1), fast response/recovery speed (75.5/63.9 ms), and good stability (10 000 cycles). Based on the self-healing property of PU, the sensor also has the ability to heal after mechanical damage. In addition, the sensor realizes the joule heating function under low voltage, and has the real-time monitoring ability of sliding objects. Combined with low cost and simple manufacturing method, the multi-functional MXene/PU flexible sensor shows a wide range of application potential in human activity monitoring, thermal management, and slip recognition.

PPII-AEAT: Prediction of protein-protein interaction inhibitors based on autoencoders with adversarial training.

Protein-protein interactions (PPIs) have shown increasing potential as novel drug targets. The design and development of small molecule inhibitors targeting specific PPIs are crucial for the prevention and treatment of related diseases. Accordingly, effective computational methods are highly desired to meet the emerging need for the large-scale accurate prediction of PPI inhibitors. However, existing machine learning models rely heavily on the manual screening of features and lack generalizability. Here, we propose a new PPI inhibitor prediction method based on autoencoders with adversarial training (named PPII-AEAT) that can adaptively learn molecule representation to cope with different PPI targets. First, Extended-connectivity fingerprints and Mordred descriptors are employed to extract the primary features of small molecular compounds. Then, an autoencoder architecture is trained in three phases to learn high-level representations and predict inhibitory scores. We evaluate PPII-AEAT on nine PPI targets and two different tasks, including the PPI inhibitor identification task and inhibitory potency prediction task. The experimental results show that our proposed PPII-AEAT outperforms state-of-the-art methods.

Optimisation of isolation of polyphenols from Malus pumila Mill. Leaves by high-speed countercurrent chromatography using response surface methodology.

Considering comprehensive utilization of natural products, isolation and activity determination processes of bioactive compounds are essential. In this study, a combined high-speed countercurrent chromatography (HSCCC) with preparative HPLC method was developed to isolate the five antioxidant polyphenols from 75% ethanol extract of Malus pumila Mill. leaves. The HSCCC conditions were optimized by response surface methodology (RSM) considering two response indexes including retention of stationary phase and analysis time. The optimal HSCCC conditions were flow rate of 2.11 mL/min, revolution speed of 717 rpm, and temperature of 25℃, with a solvent system of ethyl acetate/methanol/water (10:1:10, v/v/v). The unseparated fractions obtained from HSCCC were subjected to preparative HPLC for further isolation. As a result, phloridzin (15.3 mg), isoquercitrin (2.1 mg), quercetin 3-O-xyloside (1.9 mg), quercetin-3-O-arabinoside (4.0 mg), and quercitrin (2.0 mg) were isolated from 200.0 mg extracts. The purities of these compounds were all above 92%. Their chemical structures were identified by mass spectrometer and nuclear magnetic resonance. The five isolated compounds were further investigated for their rat hippocampal neuroprotective effects against hydrogen peroxide-induced oxidative stress. No cytotoxicity was observed in all tested concentrations. While all five compounds except phloridzin showed significantly neurogenic activities and neuroprotective effects, especially at the concentration of 0.5 mg/L. These results demonstrate that RSM is a suitable technique for optimisation of HSCCC and the isolated polyphenols can be used as antioxidants in pharmaceutical and food products.