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Background: Cytochrome P450 (CYP) 46A1 enzyme is a neuro-specific metabolic enzyme that converts cholesterol to 24-hydroxycholesterol. Inhibition of CYP46A1 activity is of great significance to improve neurodegenerative disorder. Objective: The present study aimed to investigate the inhibitory effect of wolfberry dicaffeoylspermidine derivatives on CYP46A1. Methods: The inhibitory effect of six wolfberry dicaffeoylspermidine derivatives on CYP46A1 activity was investigated using cholesterol as a substrate in vitro. Molecular docking was used to simulate the interactions between wolfberry dicaffeoylspermidine derivatives and CYP46A1. Results: Of these spermidines, lycibarbarspermidines D (1) and A (2) showed highly-selective and strong inhibitory effects on CYP46A1 but not on other human CYP isoforms. Both 1 and 2 exhibit mixed partial competitive inhibition of CYP46A1, with Ki values of 106 nM and 258 nM, respectively. Notably, 1 and 2 had excellent orientations within the active cavity of CYP46A1, and both formed three water-hydrogen bonds with W732 and W765, located near the heme of CYP46A1. Conclusion: Compounds 1 and 2 showed a highly-selective and nanomolar affinity for CYP46A1 in vitro. These findings suggested that compounds 1 and 2 could be used as potent inhibitors of CYP46A1 in vitro.

Outline of the source, purification, synthesis process, physical and chemical properties, intervention to disease and improvement of activity of nattokinase.

The problem of human-computer interaction mental workload in flight driving has great reference value for the prevention of safety hazards in aviation driving. This paper analyzes and studies the classification method of mental workload in flight driving by designing different simulated flight experiment tasks. This study uses a combination of EEG signals and subjective evaluation, through the use of convolutional neural networks and long short-term memory network method of combining EEG signals for research and analysis. The accuracy of EEG signal classification is as high as 94.9 %. NASA-TLX evaluation results show that there is a positive correlation between task load difficulty and evaluation score. The results show that the combination of convolutional neural network and long short-term memory network is suitable for pilots ’ mental workload classification. This study has important practical significance for flight accidents caused by pilots ’ mental workload.

To address the problem of accurate assessment of training effects of flight simulators, an intelligent algorithm using neural networks and reinforcement learning is proposed in the paper. The multi-dimensional data of facial expression features and EEG and EM physiological signals are analyzed, and a new evaluation model for assessing human spatial balance, attention distribution, neurological weakness and other pilot training states is studied through facial expression experiments mainly and eye-movement and EEG experiments supplemented, and the EEG acquisition and analysis during pilot training subjects (take-off and landing) are completed, and the emotional characteristics of pilots during training are identified. We completed data fusion of multi-dimensional channels, constructed mathematical models of pilot maneuver reaction time and attention allocation, monitored and evaluated flight training effects and conducted controlled experiments. The experimental results show that the average recognition rates of 92.598% and 87.013% were achieved for expression and neurasthenia recognition, and the human ergonomic information of facial expression and EEG and eye movements were effectively fused.

Sight is the main source for humans to obtain information from the outside world. Due to the structure of the human eye [1], the range of human sight is limited. For this reason, people need to constantly move their line of sight when observing the surrounding environment and the target, and the movement of the sight is based on the coordinated movement of the head and the eye[2]. Therefore, the key issue for gaze research is how to correctly establish the relationship between head-eye movement and gaze movement. Taking the simulated flight environment as the research background, this paper collects a large number of head-eye images through the designed “three-camera and eight-light source” head-eye data acquisition platform, and proposes a gaze estimation method based on the combination of appearance and features, which effectively combines The relationship of head-eye coordination movement. Then, the ResNet-18 deep residual network structure and the traditional BP neural network structure are used to complete the effective fusion of the head pose and human eye features in the process of capturing the sight target, so as to realize the accurate estimation of the sight drop point, and its average accuracy up to 89.9%.

This study investigated the effects of mung bean protein (MPI) and a MPI-polyphenol complex on oxidative stress levels and intestinal microflora in a D-galactose-induced aging mouse model. MPI and MPI-polyphenol complex intervention significantly increased activity of superoxide dismutase (SOD) and catalase and other antioxidant enzymes, improved the abundance and diversity of intestinal flora, and decreased the Firmicutes to Bacteroidetes ratio. The addition of MPI and MPI-polyphenol complex can help the proliferation of Bacteroidetes, Bifidobacterium and Roseburia in the intestinal tract of aging mice, and inhibit the growth of Firmicutes and Ruminococcus. MPI significantly upregulated five pathways related to lipid and energy metabolism. Roseburia and Muribaculaceae were negatively correlated with malondialdehyde levels and positively correlated with SOD and other antioxidant enzyme indices. Our findings showed that MPI and MPI-polyphenol complexes can delay aging in mice by reducing oxidative damage and regulating intestinal flora. We also found a strong relationship between the abundance of intestinal flora and the levels of oxidative stress-related enzymes. This study provides theoretical support for the health and anti-aging benefits of mung bean food products.

Tracking aggregation behavior and changes in emulsifying properties of myofibrillar protein from mirror carp (Cyprinus carpio L.) induced by its oxidation during frozen storage under the effect of ice structuring protein were investigated. Solubility, net charge, emulsion properties of the sample without ice structuring protein decreased, meanwhile carbonyl, turbidity, the mean diameter in volume and the mean diameter in surface increased during frozen storage. As ice structuring protein addition increased, water-holding capacity and emulsifying properties of samples showed a trend of first increasing and then decreasing, while the tendency of oxidation and aggregation was opposite. Ice structuring protein of 2.0 (g/L) caused the most significant results (P

Fatigue is an important factor affecting modern flight safety. It can easily lead to a decline in the pilot's operational capabilities, misjudgments and flight illusions. Moreover, it may even cause serious flight accidents. In this paper, a wearable wireless physiological device is used to obtain pilot electrocardiogram data in simulated flight experiments. Bioelectric signals have higher reliability than image information, and are not easily affected by the external environment (such as shooting angle and light intensity). On the other hand, neural networks have been widely used in various classification and regression tasks. In this study, the EEG was collected in the driving flight simulator, and after simple filtering and preprocessing, the time domain data was sent directly to the convolutional neural network, eliminating the need for additional feature extraction operations. We found that the convolutional neural network can effectively amplify the fluctuation details of the time domain data and train the pilot fatigue state recognition model. The results show that the recognition accuracy of the convolutional neural network model reaches 98%, which is 26% and 12% higher than the traditional k-nearest neighbor classification algorithm (KNN) and support vector machine (SVM) model, respectively. The recognition model based on convolutional neural network established in this paper is suitable for the recognition of pilot fatigue status. This has important practical significance for reducing flight accidents caused by pilot fatigue, and provides a theoretical basis for pilot fatigue risk management and the development of intelligent aircraft autopilot systems.

The line of sight reflects the focus of human attention. Gaze estimation technology has a wide range of application prospects in human-computer interaction, human emotion analysis, commercial advertising, and so on. Gaze estimation needs to be jointly determined by eye movement and head movement because the human gaze is often with the head movement. In this paper, a gaze estimation system with head movement is implemented by a monocular camera, using eye movement features and head movement posture changes to estimate the gaze point. A camera is used as the information acquisition device to extract the eye movement feature information, and the offset of head movement is estimated at the same time. The final fixation point position coordinates are obtained by compensating the fixation point position in the case of head movement, and then the fixation point position coordinates are estimated. For the compensated gaze drop point, the average pixel error on the X-axis is estimated to be 118 pixels, and the average pixel error on the Y-axis is estimated to be 136 pixels.

The structural elucidation and investigation of the immunostimulatory effects of crude polysaccharides (ECPs), non-starch polysaccharides (ECPs-I), and deproteinated non-starch polysaccharides (ECPs-II) derived from finger millet (Eleusine coracana) were performed. The extracted ECPs, ECPs-I, and ECPs-II primarily comprised different levels of carbohydrate (82.9, 41.9 and 62.0%), protein (5.3, 38.4 and 22.0%) and uronic acid (0.5, 2.4 and 0.7%). Monosaccharide composition analysis showed that glucose (88.2 and 40.6) was the main sugar unit present in ECPs and ECPs-I, followed by galactose, arabinose, xylose, rhamnose, and mannose; however, ECPs-II contained galactose (42.2%) as a major unit. The average molecular weights of ECPs, ECPs-I, and ECPs-II were found to be 120, 78 and 43 kDa, respectively. The polysaccharides as well as non-starch polysaccharides did not show any toxic effects on RAW 264.7 cells. ECPs-II treatment significantly enhanced the activation of RAW 264.7 cells by inducing nitric oxide (NO) production, upregulating inducible nitric oxide synthase (iNOS) and various pro-inflammatory cytokines including interleukin (IL)-1β, IL-6, IL-10, and tumor necrosis factor alpha (TNF-α). Furthermore, the RAW 264.7 cells were activated after ECPs-II treatment via the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), and mitogen-activated protein kinase signaling (MAPK) pathways induced by a cluster of differentiation 40 (CD40) expression. The structure of ECPs-II mainly consists of (1→3,4)-linked galactopyranosyl and (1→3,5) arabinopyranosyl.

Graphical Abstract Non-starch polysaccharides derived from natural resources play a significant role in the field of food science and human health due to their extensive distribution in nature and less toxicity. In this order, the immunostimulatory activity of a non-starch polysaccharide (CQNP) from Chenopodium quinoa was examined before and after deproteination in murine macrophage RAW 264.7 cells. The chemical composition of CQNP and deproteinated-CQNP (D-CQNP) were spectrometrically analysed that revealed the presence of carbohydrate (22.7 ± 0.8% and 39.5 ± 0.8%), protein (41.4 ± 0.5% and 20.8 ± 0.5%) and uronic acid (8.7 ± 0.3% and 6.7 ± 0.2%). The monosaccharide composition results exposed that CQNP possesses a high amount of arabinose (34.5 ± 0.3) followed by galactose (26.5 ± 0.2), glucose (21.9 ± 0.3), rhamnose (7.0 ± 0.1), mannose (6.0 ± 0.1) and xylose (4.2 ± 0.2). However, after deproteination, a difference was found in the order of the monosaccharide components, with galactose (41.1 ± 0.5) as a major unit followed by arabinose (34.7 ± 0.5), rhamnose (10.9 ± 0.2), glucose (6.6 ± 0.2), mannose (3.4 ± 0.2) and xylose (3.2 ± 0.2). Further, D-CQNP potentially stimulate the RAW 264.7 cells through the production of nitric oxide (NO), upregulating inducible nitric oxide synthase (iNOS) and various pro-inflammatory cytokines including interleukin (IL)-1β, IL-6, IL-10, and tumor necrosis factor-alpha (TNF-α). Moreover, stimulation of RAW 264.7 cells by D-CQNP takes place along the NF-κB and the MAPKs signaling pathways through the expression of cluster of differentiation 40 (CD40). This results demonstrate that RAW 264.7 cells are effectively stimulated after removal of the protein content in C. quinoa non-starch polysaccharides, which could be useful for develop a new immunostimulant agent.

In this work, (1 [Formula: see text])(0.92NaNbO3–0.08BaTiO3)–[Formula: see text]Ca[Formula: see text]La[Formula: see text]TiO3 (NNBT – [Formula: see text]CLT) ceramics were successfully designed and prepared by the solid-state reaction method. Investigations on the structure, dielectric, and energy storage properties were performed. The NNBT – 0.25CLT ceramic with orthorhombic phase at room temperature was found to exhibit extremely small grain size and compacted microstructure. A large [Formula: see text] of 3.1 J/cm3 and a high [Formula: see text] of 91.5% under the electric field of 360 kV/cm were achieved simultaneously in the sample. In addition, the energy storage performance of the sample exhibits thermal stability over the temperature range of 25–140[Formula: see text]C and the frequency range of 5–500 Hz. The charge and discharge tests reveal that the ceramic shows a large current density [Formula: see text] of 965 A/cm2 and power density [Formula: see text] of 154 MW/cm3. This work demonstrates that the NNBT–0.25CLT ceramic is a prospective energy storage material for potential application in the field of pulsed power devices.

Human cytochrome P450 1B1 (CYP1B1) is an extrahepatic enzyme overexpressed in many tumors and associated with angiogenesis. Ginkgetin, isoginkgetin, sciadopitysin, and amentoflavone, the primary biflavones found in Ginkgo biloba, have excellent anti-inflammatory and anti-tumor effects. However, the effect of biflavones on CYP1B1 activities remains unknown. In this study, 7-ethoxyresorufin O-deethylation (EROD) was used to characterize the activities of CYP1 families. The impacts of four ginkgo biflavones on CYP1B1 activity and the cellular protein expression of CYP1B1 were systematically investigated. The results showed that amentoflavone with six hydroxyl substituents exhibited the most potent selective inhibitory effect on CYP1B1 activity with IC50 of 0.054 µM in four biflavones. Sciadopitysin, with three hydroxyl and three methoxy substituents, had the weakest inhibitory activity against CYP1B1. Ginkgetin and isoginkgetin, both with four hydroxyl and two methoxy substituents, showed similar inhibitory intensity towards CYP1B1 with IC50 values of 0.289 and 0.211 µM, respectively. Kinetic analysis showed that ginkgetin and amentoflavone inhibited CYP1B1 in a non-competitive mode, whereas sciadopitysin and isoginkgetin induced competitive or mixed types of inhibition. Notably, four ginkgo biflavones were also confirmed to suppress the protein expressions of CYP1B1 and AhR in MCF-7. Furthermore, molecular docking studies indicated more hydrogen bonds formed between amentoflavone and CYP1B1, which might explain the strongest inhibitory action towards CYP1B1. In summary, these findings suggested that biflavones remarkably inhibited both the activity and protein expression of CYP1B1 and the inhibitory activities enhanced with the increasing hydroxyl substitution, providing new insights into the anti-tumor potentials of biflavones.

Traditional intention inference methods rely solely on EEG, eye movement or tactile feedback, and the recognition rate is low. To improve the accuracy of a pilot’s intention recognition, a human-computer interaction intention inference method is proposed in this paper with the fusion of EEG, eye movement and tactile feedback. Firstly, EEG signals are collected near the frontal lobe of the human brain to extract features, which includes eight channels, i.e., AF7, F7, FT7, T7, AF8, F8, FT8, and T8. Secondly, the signal datas are preprocessed by baseline removal, normalization, and least-squares noise reduction. Thirdly, the support vector machine (SVM) is applied to carry out multiple binary classifications of the eye movement direction. Finally, the 8-direction recognition of the eye movement direction is realized through data fusion. Experimental results have shown that the accuracy of classification with the proposed method can reach 75.77%, 76.7%, 83.38%, 83.64%, 60.49%,60.93%, 66.03% and 64.49%, respectively. Compared with traditional methods, the classification accuracy and the realization process of the proposed algorithm are higher and simpler. The feasibility and effectiveness of EEG signals are further verified to identify eye movement directions for intention recognition.