Quantification of functional hemodynamics in aortic valve disease using cardiac computed tomography angiography.

BACKGROUND AND OBJECTIVE: Cardiac computed tomography angiography (CTA) is the preferred modality for preoperative planning in aortic valve stenosis. However, it cannot provide essential functional hemodynamic data, specifically the mean transvalvular pressure gradient (MPG). This study aims to introduce a computational fluid dynamics (CFD) approach for MPG quantification using cardiac CTA, enhancing its diagnostic value. METHODS: Twenty patients underwent echocardiography, cardiac CTA, and invasive catheterization for pressure measurements. Cardiac CTA employed retrospective electrocardiographic gating to capture multi-phase data throughout the cardiac cycle. We segmented the region of interest based on mid-systolic phase cardiac CTA images. Then, we computed the average flow velocity into the aorta as the inlet boundary condition, using variations in end-diastolic and end-systolic left ventricular volume. Finally, we conducted CFD simulations using a steady-state model to obtain pressure distribution within the computational domain, allowing for the derivation of MPG. RESULTS: The mean value of MPG, measured via invasive catheterization (MPGInv), echocardiography (MPGEcho), and cardiac CTA (MPGCT), were 51.3 ± 28.4 mmHg, 44.8 ± 19.5 mmHg, and 55.8 ± 25.6 mmHg, respectively. In comparison to MPGInv, MPGCT exhibited a higher correlation of 0.91, surpassing that of MPGEcho, which was 0.82. Moreover, the limits of agreement for MPGCT ranged from -27.7 to 18.7, outperforming MPGEcho, which ranged from -40.1 to 18.0. CONCLUSIONS: The proposed method based on cardiac CTA enables the evaluation of MPG for aortic valve stenosis patients. In future clinical practice, a single cardiac CTA examination can comprehensively assess both the anatomical and functional hemodynamic aspects of aortic valve disease.

High Fischer Ratio Oligopeptides of Gluten Alleviate Alcohol-Induced Liver Damage by Regulating Lipid Metabolism and Oxidative Stress in Rats.

High Fischer ratio oligopeptides (HFOs) exhibit diverse biological activities, including anti-inflammatory and antioxidant properties. HFOs from gluten origin were prepared through fermentation and enzymatic hydrolysis and then characterized using free amino acid analysis and scanning electron microscopy (SEM). Following intervention, the levels of serum total cholesterol (TC), triglyceride (TG), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and hepatic malondialdehyde (MDA) in the rats significantly decreased (p < 0.05). Simultaneously, there was an increasing trend in superoxide dismutase (SOD) levels, and glutathione (GSH) levels were significantly elevated (p < 0.05). The mRNA expression levels of alcohol metabolism-related genes (ADH4, ALDH2, and CYP2E1) exhibited a significant increase (p < 0.05). Histological examination revealed a reduction in liver damage. The findings indicate that high Fischer ratio oligopeptides, prepared through enzymatic and fermentation methods, significantly improve lipid levels, ameliorate lipid metabolism disorders, and mitigate oxidative stress, and exhibit a discernible alleviating effect on alcoholic liver injury in rats.

Dynamical graph neural network with attention mechanism for epilepsy detection using single channel EEG.

Epilepsy is a chronic brain disease, and identifying seizures based on electroencephalogram (EEG) signals would be conducive to implement interventions to help patients reduce impairment and improve quality of life. In this paper, we propose a classification algorithm to apply dynamical graph neural network with attention mechanism to single channel EEG signals. Empirical mode decomposition (EMD) are adopted to construct graphs and the optimal adjacency matrix is obtained by model optimization. A multilayer dynamic graph neural network with attention mechanism is proposed to learn more discriminative graph features. The MLP-pooling structure is proposed to fuse graph features. We performed 12 classification tasks on the epileptic EEG database of the University of Bonn, and experimental results showed that using 25 runs of ten-fold cross-validation produced the best classification results with an average of 99.83[Formula: see text] accuracy, 99.91[Formula: see text] specificity, 99.78[Formula: see text] sensitivity, 99.87[Formula: see text] precision, and 99.47[Formula: see text] [Formula: see text] score for the 12 classification tasks.

From Forearm to Wrist: Deep Learning for Surface Electromyography-Based Gesture Recognition.

Though the forearm is the focus of the prostheses, myoelectric control with the electrodes on the wrist is more comfortable for general consumers because of its unobtrusiveness and incorporation with the existing wrist-based wearables. Recently, deep learning methods have gained attention for myoelectric control but their performance is unclear on wrist myoelectric signals. This study compared the gesture recognition performance of myoelectric signals from the wrist and forearm between a state-of-the-art method, TDLDA, and four deep learning models, including convolutional neural network (CNN), temporal convolutional network (TCN), gate recurrent unit (GRU) and Transformer. It was shown that with forearm myoelectric signals, the performance between deep learning models and TDLDA was comparable, but with wrist myoelectric signals, the deep learning models outperformed TDLDA significantly with a difference of at least 9%, while the performance of TDLDA was close between the two signal modalities. This work demonstrated the potential of deep learning for wrist-based myoelectric control and would facilitate its application into more sections.

Theoretical and experimental study on the photothermal effect of palladium nanoparticles based on a finite element model.

Palladium nanoparticles (Pd NPs) show significant promise as agents for the photothermal treatment of tumors due to their high photothermal conversion efficiency and thermal stability. theoretical calculations were conducted to investigate the electric field and solid heat conduction of Pd NPs with various sizes and particle distances, aiming to achieve the maximum photothermal conversion efficiency during laser irradiation. Subsequently, Pd NPs with optimal size and structure were synthesized. In vitro and in vivo experiments were conducted to evaluate photothermal conversion. The theoretical results indicated that a peak temperature of 90.12 °C is achieved when the side length is 30 nm with a distance of 2 nm. In vitro experiments demonstrated that the photothermal conversion efficiency of Pd NPs can reach up to 61.9%. in vivo experiments revealed that injecting Pd NPs into blood vessels can effectively reduce the number of laser pulses by 22.22%, thereby inducing obvious vasoconstriction.

Research on left hard shoulder width of super multilane highway based on PTSU operation.

Part-time shoulder use (PTSU) is a traffic strategy that temporarily uses the shoulder as a lane when necessary. Research has shown that, when a hard shoulder is required to set the traffic function, the left hard shoulder is preferable. Super multilane highways are usually equipped with left hard shoulders of sufficient width, but the wide cross-sectional characteristics make it difficult for vehicles to turn into the emergency parking lane to avoid a breakdown or accident in the lane, which is an ideal implementation object of PTSU. In this study, two virtual simulation scenarios for PTSU were created: one with the left hard shoulder open and used as a travel lane, and the other with the left hard shoulder closed and its original function restored. Vehicle driving data were collected through driving simulation experiments to reveal the influence of the left hard shoulder on vehicle handling stability. The optimal width of the left hard shoulder was determined by ANOVA and comparison of the mean and standard deviation. The purpose of this study was to quantify the effect of the width of the left hard shoulder on the driving stability of vehicles in the inside lane under PTSU and determine the ideal shoulder width by comparing the stability parameters of vehicles.

Hippocampal BAIAP2 prevents chronic mild stress-induced depression-like behaviors in mice.

Background: The pathogenesis of depression is closely related to changes in hippocampal synaptic plasticity; however, the underlying mechanism is still unclear. Brain-specific angiogenesis inhibitor 1-associated protein 2 (BAIAP2), a postsynaptic scaffold protein in excitatory synapses important for synaptic plasticity, is highly expressed in the hippocampus and has been implicated in several psychiatric disorders. However, the role of BAIAP2 in depression remains poorly understood. Methods: In the present study, a mouse model of depression was established via exposure to chronic mild stress (CMS). An adeno-associated virus (AAV) vector expressing BAIAP2 was injected into the hippocampal brain region of mice and a BAIAP2 overexpression plasmid was transfected into HT22 cells to upregulate BAIAP2 expression. Depression- and anxiety-like behaviors and dendritic spine density were examined in mice using behavioral tests and Golgi staining, respectively. In vitro, hippocampal HT22 cells were treated with corticosterone (CORT) to simulate the stress state, and the effect of BAIAP2 on CORT-induced cell injury was explored. Reverse transcription-quantitative PCR and western blotting were employed to determine the expression levels of BAIAP2 and those of the synaptic plasticity-related proteins glutamate receptor ionotropic, AMPA 1 (GluA1), and synapsin 1 (SYN1). Results: Mice exposed to CMS exhibited depression- and anxiety-like behaviors accompanied by decreased levels of BAIAP2 in the hippocampus. In vitro, the overexpression of BAIAP2 increased the survival rate of CORT-treated HT22 cells and upregulated the expression of GluA1 and SYN1. Consistent with the in vitro data, the AAV-mediated overexpression of BAIAP2 in the hippocampus of mice significantly inhibited CMS-induced depression-like behavior, concomitant with increases in dendritic spine density and the expression of GluA1 and SYN1 in hippocampal regions. Conclusion: Our findings indicate that hippocampal BAIAP2 can prevent stress-induced depression-like behavior and may be a promising target for the treatment of depression or other stress-related diseases.

Biomaterials for chimeric antigen receptor T cell engineering.

Chimeric antigen receptor T (CAR-T) cells have achieved breakthrough efficacies against hematological malignancies, but their unsatisfactory efficacies in solid tumors limit their applications. The prohibitively high prices further restrict their access to broader populations. Novel strategies are urgently needed to address these challenges, and engineering biomaterials can be one promising approach. The established process for manufacturing CAR-T cells involves multiple steps, and biomaterials can help simplify or improve several of them. In this review, we cover recent progress in engineering biomaterials for producing or stimulating CAR-T cells. We focus on the engineering of non-viral gene delivery nanoparticles for transducing CAR into T cells ex vivo/in vitro or in vivo. We also dive into the engineering of nano-/microparticles or implantable scaffolds for local delivery or stimulation of CAR-T cells. These biomaterial-based strategies can potentially change the way CAR-T cells are manufactured, significantly reducing their cost. Modulating the tumor microenvironment with the biomaterials can also considerably enhance the efficacy of CAR-T cells in solid tumors. We pay special attention to progress made in the past five years, and perspectives on future challenges and opportunities are also discussed. STATEMENT OF SIGNIFICANCE: Chimeric antigen receptor T (CAR-T) cell therapies have revolutionized the field of cancer immunotherapy with genetically engineered tumor recognition. They are also promising for treating many other diseases. However, the widespread application of CAR-T cell therapy has been hampered by the high manufacturing cost. Poor penetration of CAR-T cells into solid tissues further restricted their use. While biological strategies have been explored to improve CAR-T cell therapies, such as identifying new cancer targets or integrating smart CARs, biomaterial engineering provides alternative strategies toward better CAR-T cells. In this review, we summarize recent advances in engineering biomaterials for CAR-T cell improvement. Biomaterials ranging from nano-, micro-, and macro-scales have been developed to assist CAR-T cell manufacturing and formulation.

Effect of fermentation on structural properties and antioxidant activity of wheat gluten by Bacillus subtilis.

Bacillus subtilis has been extensively studied for its ability to inhibit the growth of harmful microorganisms and its high protease activity. In this study, Bacillus subtilis was used to ferment gluten and assess the effects of the fermentation process on the physicochemical, microstructure and antioxidant properties of gluten. The results of Fourier infrared spectroscopy (FT-IR) and circular chromatography (CD) showed a significant decrease in the content of α-helix structures and a significant increase in the content of ß-sheet structures in gluten after fermentation (p < 0.05). Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) showed that glutenin was degraded into small molecular peptides with a molecular weight of less than 26 kDa after 24 h of fermentation; meanwhile, the fermentation process significantly increased the free amino acid content of the samples (p < 0.05), reaching 1923.38 µg/mL at 120 h of fermentation, which was 39.46 times higher than that at 24 h of fermentation (p < 0.05). In addition, the fermented back gluten has higher free radical scavenging activity and iron reduction capacity. Therefore, fermented gluten may be used as a functional food to alleviate oxidative stress. This study provides a reference for the high-value application of gluten.

Transformer-based multi-task learning for classification and segmentation of gastrointestinal tract endoscopic images.

Despite being widely utilized to help endoscopists identify gastrointestinal (GI) tract diseases using classification and segmentation, models based on convolutional neural network (CNN) have difficulties in distinguishing the similarities among some ambiguous types of lesions presented in endoscopic images, and in the training when lacking labeled datasets. Those will prevent CNN from further improving the accuracy of diagnosis. To address these challenges, we first proposed a Multi-task Network (TransMT-Net) capable of simultaneously learning two tasks (classification and segmentation), which has the transformer designed to learn global features and can combine the advantages of CNN in learning local features so that to achieve a more accurate prediction in identifying the lesion types and regions in GI tract endoscopic images. We further adopted the active learning in TransMT-Net to tackle the labeled image-hungry problem. A dataset was created from the CVC-ClinicDB dataset, Macau Kiang Wu Hospital, and Zhongshan Hospital to evaluate the model performance. Then, the experimental results show that our model not only achieved 96.94% accuracy in the classification task and 77.76% Dice Similarity Coefficient in the segmentation task but also outperformed those of other models on our test set. Meanwhile, active learning also produced positive results for the performance of our model with a small-scale initial training set, and even its performance with 30% of the initial training set was comparable to that of most comparable models with the full training set. Consequently, the proposed TransMT-Net has demonstrated its potential performance in GI tract endoscopic images and it through active learning can alleviate the shortage of labeled images.

Fermented Wheat Germ Alleviates Depression-like Behavior in Rats with Chronic and Unpredictable Mild Stress.

Depression is a chronic mental illness with devastating effects on a person's physical and mental health. Studies have reported that food fermentation with probiotics can enrich the nutritional values of food and produce functional microorganisms that can alleviate depression and anxiety. Wheat germ is an inexpensive raw material that is rich in bioactive ingredients. For example, gamma-aminobutyric acid (GABA) is reported to have antidepressant effects. Several studies concluded that Lactobacillus plantarum is a GABA-producing bacteria and can alleviate depression. Herein, fermented wheat germs (FWGs) were used to treat stress-induced depression. FWG was prepared by fermenting wheat germs with Lactobacillus plantarum. The chronic unpredictable mild stress (CUMS) model was established in rats, and these rats were treated with FWG for four weeks to evaluate the effects of FWG in relieving depression. In addition, the study also analyzed the potential anti-depressive mechanism of FWG based on behavioral changes, physiological and biochemical index changes, and intestinal flora changes in depressed rats. The results demonstrated that FWG improved depression-like behaviors and increased neurotransmitter levels in the hippocampus of CUMS model rats. In addition, FWG effectively altered the gut microbiota structure and remodeled the gut microbiota in CUMS rats, restored neurotransmitter levels in depressed rats through the brain-gut axis, and restored amino acid metabolic functions. In conclusion, we suggest that FWG has antidepressant effects, and its potential mechanism may act by restoring the disordered brain-gut axis.

SD-HRNet: Slimming and Distilling High-Resolution Network for Efficient Face Alignment.

Face alignment is widely used in high-level face analysis applications, such as human activity recognition and human-computer interaction. However, most existing models involve a large number of parameters and are computationally inefficient in practical applications. In this paper, we aim to build a lightweight facial landmark detector by proposing a network-level architecture-slimming method. Concretely, we introduce a selective feature fusion mechanism to quantify and prune redundant transformation and aggregation operations in a high-resolution supernetwork. Moreover, we develop a triple knowledge distillation scheme to further refine a slimmed network, where two peer student networks could learn the implicit landmark distributions from each other while absorbing the knowledge from a teacher network. Extensive experiments on challenging benchmarks, including 300W, COFW, and WFLW, demonstrate that our approach achieves competitive performance with a better trade-off between the number of parameters (0.98 M-1.32 M) and the number of floating-point operations (0.59 G-0.6 G) when compared to recent state-of-the-art methods.

Research and Application of Energy-Efficient Management Approach for Wireless Sensor Networks.

Wireless sensor networks (WSNs) are widely used in industrial applications. However, many of them have limited lifetimes, which has been a considerable constraint on their widespread use. As a typical application of WSNs, distributed measurement of the electric field under high-voltage direct-current (HVDC) transmission lines also suffers from this issue. This paper first introduces the composition of the electric-field measurement system (EFMS) and its working principle. Considering the actual power supply of the system, this paper mainly introduces the composition of the wireless sensor node (WSND) and analyzes the power consumption and potential working state transformation of the WSND, together with a comprehensive study on parameters affecting the power consumption of the wireless communication unit. Moreover, an energy-efficient scheduling approach is proposed after specially designing a working sequence and the study on system parameters. The proposed approach is verified by experiments on not only the experimental line of the national HVDC test base, but also a commercial operation HVDC transmission line with the challenge of long endurance, which is considered in this paper with a new strategy. The results show that the proposed method can greatly extend the lifetime of the WSND.

Magnetorheological properties of Fe-Co nanoparticles with high saturation magnetization and low coercivity.

Fe-Co alloys exhibit an excellent saturation magnetization, which makes them become a potential candidate for the high property magnetic particles in magnetorheological fluids (MRFs). How to decrease their coercivity and residual magnetization without sacrificing the saturation magnetization is a crucial problem to be solved. In this study, Fe-Co nanoparticles were prepared by DC arc discharge and further disposed through low temperature annealing in Ar atmosphere. The successful synthesis of Fe-Co nanoparticles was proved by x-ray diffraction and EDS. The vibrating sample magnetometer results revealed that the prepared Fe-Co nanoparticles had a saturation magnetization of 208 emu g-1, while the coercivity and remanent magnetization were 58 Oe and 5.8 emu g-1, respectively. The MR properties of Fe-Co nanoparticles based MRFs (FeCoNP-MRFs) with 10% particles by volume fraction were systematically investigated. The FeCoNP-MRFs showed up to 4.61 kPa dynamic shear stress at 436 kA m-1magnetic field and an excellent reversibility. The MR properties of FeCoNP-MRFs were fitted well by Bingham and power law model, and described by Seo-Seo and Casson fluid model. Meanwhile, the sedimentation ratio of FeCoNP-MRFs was still 87.3% after 72 h, indicating an excellent sedimentation stability.

The role of wheat embryo globulin nutrients in improving cognitive dysfunction in AD rats.

Neuroinflammation and intestinal microbiota cause pathological progression of Alzheimer's disease (AD), leading to neurodegeneration and cognitive decline. This study investigates the effects of wheat embryo globulin nutrient (WEGN) on depression, neuroinflammation, and intestinal microbial disorder caused by AD and its protective mechanism on cognitive impairment. Results demonstrated that rats in the WEGN group have lower feed intake but higher body weight than those in the control group. Notably, rats in the WEGN group have a higher number of cross grids and uprights and a smaller amount of fecal particles than those in the control group. Biochemical examinations revealed that rats in the WEGN group had lower expression of interleukin-1ß, interleukin-6, and tumor necrosis factor α in hippocampus tissue and the expression of genes and proteins related to the TLR4/MyD88/NF-κB signaling pathway in AD rats was down-regulated compared to those in the control group. The 16S rRNA gene sequencing results demonstrated that WEGN treatment inhibits the increase of Erysipelotrichaceae, Erysipelatoclostridium, Erysipelotrichaceae, Corynebacterium, and Frisingicoccus, and the reduction of Lactobacillus in AD rats. WEGN has potential value as a practical food in alleviating neuroinflammation-related diseases such as AD.

Long-lasting effects of postweaning sleep deprivation on cognitive function and social behaviors in adult mice.

Sleep deprivation (SD) has adverse effects on physical and mental health. Recently increasing attention has been given to SD in the early-life stage. However, the effects and mechanisms of postweaning SD on cognitive function and social behaviors are still unclear. In this study, SD was conducted in mice from postnatal Day 21 (PND21) to PND42, 6 h a day. Meanwhile, changes in body weight, food and water intake were continuously monitored. Behavioral tests were carried out in adulthood of mice. The levels of serum corticosterone, the proinflammatory cytokines interleukin-1ß (IL-1ß) and tumor necrosis factor-α (TNF-α), and the anti-inflammatory cytokines interleukin-10 (IL-10), vasopressin (VP) and oxytocin (OT) were measured by ELISA. Golgi staining was used to calculate neural dendritic spine density in the dorsal hippocampus (dHPC) CA1 region and medial prefrontal cortex (mPFC). We found that postweaning SD increased the food intake and the weight of female mice. Behavioral results showed that postweaning SD caused cognitive impairment and lowered social dominance in adult male mice but not in female mice. ELISA results showed that SD increased the levels of serum corticosterone, VP and OT in male mice and serum OT in female mice. Golgi staining analysis showed that SD decreased neural dendritic spine density in the dHPC in male mice. These results suggest that postweaning SD has a long-term effect on social dominance and cognitive function in male mice, which may provide a new insight into the role of SD in regulating cognitive function and social behaviors.

Long-lasting and Sex-dependent Effects of Postweaning Swimming Exercise on Social Dominance in Adult Mice.

Increasing evidence has shown that early life events exert long-lasting effects on brain function and mental diseases. Exercise has been proven to have many positive effects on behaviors, such as reducing anxiety- and depression-like behaviors and alleviating cognitive impairment. However, the long-lasting and even short-term effects of regular swimming exercise on social dominance remain unclear. The purpose of this study was to investigate the potential effects of postweaning swimming exercise on social dominance and metabolic adaptation in adult mice. Three-week-old mice performed 1 h of swimming exercise in warm water for 4 weeks. A series of behavioral tests, such as the social dominance test (SDT), open field test (OFT), and forced swim test (FST), were conducted. Behavioral test results showed that both male and female mice in the swimming group had a higher rank than those in the sedentary group in the SDT of early adulthood, while only female mice in the swimming group maintained the social dominance in late adulthood. There was no difference between the swimming and sedentary groups in anxiety- and depression-like behaviors. Metabolomics analysis showed that there were alterations in particular metabolites and signaling pathways after one month of swimming exercise, including sphingolipid metabolism, neuroactive ligand-receptor interaction and caffeine metabolism. In conclusion, our results provide the first evidence that postweaning swimming exercise has long-lasting and sex-dependent effects on social dominance, which may be caused by metabolic adaptation.

Structural, Physicochemical, and Functional Properties of Wheat Bran Insoluble Dietary Fiber Modified With Probiotic Fermentation.

Insoluble dietary fiber (IDF) were isolated from wheat bran (WB) after microbial fermentation with single or mixed strain [Lactobacillus plantarum, Lactobacillus acidophilus, Bacillus subtilis or mixed lactic acid bacteria (L. plantarum and L. acidophilus with ration of 1:1)]. Structure, physicochemical, functional properties, and antioxidant activity of the wheat bran insoluble dietary fiber (W-IDF) modified by fermentation were studied. Fourier transformed infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM) analysis suggested the successful modification of W-IDF. After fermentation with L. plantarum and mixed lactic acid bacteria, the water retention capacity (WRC), oil retention capacity (ORC), and water swelling capacity (WSC) of W-IDF were improved. The sodium cholate adsorption capacity (SCAC), and cation exchange capacity (CEC) of W-IDF modified with L. acidophilus fermentation were significantly increased. Although the cholesterol adsorption capacity (CAC) of W-IDF decreased after modification with probiotic fermentation, nitrite ion adsorption capacity (NIAC), and total phenolic content (TPC) were enhanced. Additionally, W-IDF modified by fermentation with B. subtilis or mixed lactic acid bacteria exhibited superior antioxidant capacity verified by DPPH, ABTS and total reducing power assays. Results manifested that microbial fermentation is a promising methods to modify the W-IDF to provide high-quality functional IDF for food processing and human health management.

Molecular Dynamics Simulations and Experimental Studies of the Microstructure and Mechanical Properties of a Silicone Oil/Functionalized Ionic Liquid-Based Magnetorheological Fluid.

Magnetorheological (MR) fluids are smart materials that show enormous potential in vibration control, mechanical engineering, etc. However, the effects of the solid-liquid interface strength and the interaction strength between carrier liquid molecules on the mechanical properties and sedimentation stability of MR fluids have always been unresolved issues. This work presents a new type of MR fluid that has a novel carrier liquid, i.e., silicone oil (SO) mixed with a hydroxyl-functionalized ionic liquid (IL-OH). An all-atomic Fe/SO/IL-OH interface model for studying the relationship between mechanical properties and interface strength and intermolecular interactions is established. On the basis of simulation results and theoretical analyses, the mechanical properties and sedimentation stability of the SO/IL-OH-based MR fluids are thoroughly investigated by experiments. The results show that functional ionic liquids significantly improve the mechanical properties and sedimentation stability of MR fluids. These results are essentially attributed to the stronger solid-liquid interface strength, van der Waals forces, and hydrogen bonds between the silicone oil and the functional ionic liquid. The explicit results not only help elucidate the numerous phenomena involved in the research process for MR fluids at the atomic scale but also provide insightful information on the fabrication of high-performance MR fluids.

Systems pharmacology-based drug discovery and active mechanism of natural products for coronavirus pneumonia (COVID-19): An example using flavonoids.

BACKGROUND: Recently, the value of natural products has been extensively considered because these resources can potentially be applied to prevent and treat coronavirus pneumonia 2019 (COVID-19). However, the discovery of nature drugs is problematic because of their complex composition and active mechanisms. METHODS: This comprehensive study was performed on flavonoids, which are compounds with anti-inflammatory and antiviral effects, to show drug discovery and active mechanism from natural products in the treatment of COVID-19 via a systems pharmacological model. First, a chemical library of 255 potential flavonoids was constructed. Second, the pharmacodynamic basis and mechanism of action between flavonoids and COVID-19 were explored by constructing a compound-target and target-disease network, targets protein-protein interaction (PPI), MCODE analysis, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. RESULTS: In total, 105 active flavonoid components were identified, of which 6 were major candidate compounds (quercetin, epigallocatechin-3-gallate (EGCG), luteolin, fisetin, wogonin, and licochalcone A). 152 associated targets were yielded based on network construction, and 7 family proteins (PTGS, GSK3ß, ABC, NOS, EGFR, and IL) were included as central hub targets. Moreover, 528 GO items and 178 KEGG pathways were selected through enrichment of target functions. Lastly, molecular docking demonstrated good stability of the combination of selected flavonoids with 3CL Pro and ACEⅡ. CONCLUSION: Natural flavonoids could enable resistance against COVID-19 by regulating inflammatory, antiviral, and immune responses, and repairing tissue injury. This study has scientific significance for the selective utilization of natural products, medicinal value enhancement of flavonoids, and drug screening for the treatment of COVID-19 induced by SARS-COV-2.