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Abstract Background Traditional topical drug delivery for treating inflammatory skin diseases suffers from poor skin penetration and long-term side effects. Metal nanoparticles show promising application in topical drug delivery for inflammatory skin diseases. Methods Here, we synthesized a new type of nanoparticles, azelamide monoethanolamine-functionalized gold nanoparticles (Au-MEA NPs), based on citrate-capped gold nanoparticles (Au-CA NPs) via the ligand exchange method. The physical and chemical properties of Au-CA NPs and Au-MEA NPs were characterized. In vivo studies were performed using imiquimod-induced psoriasis and LL37-induced rosacea animal models, respectively. For in vitro studies, a model of cellular inflammation was established using HaCaT cells stimulated with TNF-α. In addition, proteomics, gelatin zymography, and other techniques were used to investigate the possible therapeutic mechanisms of the Au-MEA NPs. Results We found that Au-MEA NPs exhibited better stability and permeation properties compared to conventional Au-CA NPs. Transcutaneously administered Au-MEA NPs exerted potent therapeutic efficacy against both rosacea-like and psoriasiform skin dermatitis in vivo without overt signs of toxicity. Mechanistically, Au-MEA NPs reduced the production of pro-inflammatory mediators in keratinocytes by promoting SOD activity and inhibiting the activity of MMP9. Conclusion Au-MEA NPs have the potential to be a topical nanomedicine for the effective and safe treatment of inflammatory skin diseases.

Abstract Electrochemical organic synthesis is typically conducted in organic media. The solvent and related supporting electrolytes negatively affect the greenness of electrosynthesis. In this work, with 100% water used as the solvent, we realize aggregation-driven electrochemical radical cross coupling of unsaturated compounds driven by water tension. A key finding is that aggregation of the substrate at the electrode confined the radical intermediate and prevented side reactions, thus providing a way to regulate radical reactions in addition to their native properties. The reaction provides up to 90% yields with almost quantitative chemoselectivity. The pure water system readily yields the products via cold filtration, and the solvent is recycled repeatedly. In particular, the life span of the radical species generated in the reaction increase significantly because of the confined environment in the aggregation state. The greenness of this protocol is further enhanced with readily separation of product from media using cooling and filtration.

Abstract Background Early detection of colorectal cancer (CRC) significantly enhances patient outcomes. Conventional CRC screening tools, like endoscopy and stool-based tests, have constraints due to their invasiveness or suboptimal patient adherence. Recently, liquid biopsy employing plasma cell-free DNA (cfDNA) has emerged as a potential noninvasive screening technique for various malignancies. Methods In this research, we harnessed the Mutation Capsule Plus (MCP) technology to profile an array of genomic characteristics from cfDNA procured from a single blood draw. This profiling encompassed DNA methylation, the 5’ end motif, copy number variation (CNV), and genetic mutations. An integrated model built upon selected multiomics biomarkers was trained using a cohort of 93 CRC patients and 96 healthy controls. Results This model was subsequently validated in another cohort comprising 89 CRC patients and 95 healthy controls. Remarkably, the model achieved an area under the curve (AUC) of 0.981 (95% confidence interval (CI), 0.965–0.998) in the validation set, boasting a sensitivity of 92.1% (95% CI, 84.5%-96.8%) and a specificity of 94.7% (95% CI, 88.1%-98.3%). These numbers surpassed the performance of any single genomic feature. Importantly, the sensitivities reached 80% for stage I, 89.2% for stage II, and were 100% for stages III and IV. Conclusion Our findings underscore the clinical potential of our multiomics liquid biopsy test, indicating its prospective role as a noninvasive method for early-stage CRC detection. This multiomics approach holds promise for further refinement and broader clinical application.

Abstract Artesunate (ART), an effective antimalarial semisynthetic derivative of artemisinin, exhibits antitumour properties, but the mechanism(s) involved remain elusive. In this study, we investigated the antitumour effects of ART on human oesophageal squamous cell carcinoma (ESCC) cell lines. Treatment of ESCC cell lines with ART resulted in the production of excessive reactive oxygen species (ROS) that induced DNA damage, reduced cell proliferation and inhibited clonogenicity via G1-S cell cycle arrest and/or apoptosis in vitro. The administration of ART to nude mice with ESCC cell xenografts inhibited tumour formation in vivo. However, the cytotoxicity of ART strongly differed among the ESCC cell lines tested. Transcriptomic profiling revealed that although the expression of large numbers of genes in ESCC cell lines was affected by ART treatment, these genes could be functionally clustered into pathways involved in regulating cell cycle progression, DNA metabolism and apoptosis. We revealed that p53 and Cdk4/6-p16-Rb cell cycle checkpoint controls were critical determinants required for mediating ART cytotoxicity in ESCC cell lines. Specifically, KYSE30 cells with p53 Mut /p16 Mut were the most sensitive to ART, KYSE150 and KYSE180 cells with p53 Mut /p16 Nor exhibited intermediate responses to ART, and Eca109 cells with p53 Nor /p16 Nor exhibited the most resistance to ATR. Consistently, perturbation of p53 expression using RNA interference (RNAi) and/or Cdk4/6 activity using the inhibitor palbociclib altered ART cytotoxicity in KYSE30 cells. Given that the p53 and Cdk4/6-cyclin D1-p16-Rb genes are commonly mutated in ESCC, our results potentially shed new light on neoadjuvant chemotherapy strategies for ESCC.

The global incidence and prevalence of inflammatory bowel disease (IBD) are gradually increasing. A high-fat diet (HFD) is known to disrupt intestinal homeostasis and aggravate IBD, yet the underlying mechanisms remain largely undefined. Here, a positive correlation between dietary fat intake and disease severity in both IBD patients and murine colitis models is observed. A HFD induces a significant decrease in indole-3-acetic acid (IAA) and leads to intestinal barrier damage. Furthermore, IAA supplementation enhances intestinal mucin sulfation and effectively alleviates colitis. Mechanistically, IAA upregulates key molecules involved in mucin sulfation, including 3’-phosphoadenosine 5’-phosphosulfate synthase 2 (Papss2) and solute carrier family 35 member B3 (Slc35b3), the synthesis enzyme and the transferase of 3’-phosphoadenosine-5’-phosphosulfate (PAPS), via the aryl hydrocarbon receptor (AHR). More importantly, AHR can directly bind to the transcription start site of Papss2. Oral administration of Lactobacillus reuteri, which can produce IAA, contributes to protecting against colitis and promoting mucin sulfation, while the modified L. reuteri strain lacking the iaaM gene (LactobacillusΔiaaM) and the ability to produce IAA fail to exhibit such effects. Overall, IAA enhances intestinal mucin sulfation through the AHR-Papss2-Slc35b3 pathway, contributing to the protection of intestinal homfeostasis.

Budget allocation across multiple advertising channels involves periodically dividing a fixed total budget among various channels. Yet, the challenge of making sequential decisions to optimize long-term benefits rather than short-term gains is often overlooked. Additionally, more apparent connections must be made between actions taken on one advertising channel and the outcomes on others. Furthermore, budget limitations narrow down the range of potential optimal strategies that can be pursued. In response to these challenges, this study unveils a pioneering multi-channel advertising budget allocation approach that leverages a reinforcement learning (RL) Q-learning framework enriched with an advanced Differential Evolution (DE) algorithm to refine the Q-learning methodology. The RL element makes informed sequential decisions, adeptly adjusting strategies to favor long-term rewards by assimilating environmental feedback. Complementing this, the enhanced DE algorithm introduces an inventive clustering-based mutation technique, exploiting key groupings within the DE population to generate novel and practical solutions. The model is further bolstered by a discretization tactic aimed at simplifying the model by streamlining costs. The proposed methodology is rigorously validated using two extensive datasets: the Chinese Internet Company Advertising Dataset (CICAD) and CRITEO-UPLIFT v2, employing metrics like Area Under the Cost Curve (AUCC) and Expected Outcome Metric (EOM) as measures of performance. The empirical results affirm the superiority of the model, showcasing its exceptional performance with significant scores (AUCC =0.750 and EOM =0.736 for CICAD; AUCC =0.813 and EOM =0.829 for CRITEO-UPLIFT v2), thereby illustrating the model’s proficiency in navigating the multifaceted challenges associated with multi-channel budget allocation and establishing a new benchmark in the field.

Abstract Background The overgrowth of Desulfovibrio, an inflammation promoting flagellated bacteria, has been found in ulcerative colitis (UC) patients. However, the molecular mechanism in promoting colitis remains unestablished. Methods The relative abundance Desulfovibrio vulgaris (D. vulgaris) in stool samples of UC patients was detected. Mice were treated with dextran sulfate sodium to induce colitis with or without administration of D. vulgaris or D. vulgaris flagellin (DVF), and the severity of colitis and the leucine-rich repeat containing 19 (LRRC19) signaling were assessed. The interaction between DVF and LRRC19 was identified by surface plasmon resonance and intestinal organoid culture. Lrrc19 −/− and Tlr5 −/− mice were used to investigate the indispensable role of LRRC19. Finally, the blockade of DVF-LRRC19 interaction was selected through virtual screening and the efficacy in colitis was assessed. Results D. vulgaris was enriched in fecal samples of UC patients and was correlated with the disease severity. D. vulgaris or DVF treatment significantly exacerbated colitis in germ-free mice and conventional mice. Mechanistically, DVF could interact with LRRC19 (rather than TLR5) in colitis mice and organoids, and then induce the production of pro-inflammatory cytokines. Lrrc19 knockdown blunted the severity of colitis. Furthermore, typhaneoside, a blockade of binding interfaces, blocked DVF-LRRC19 interaction and dramatically ameliorated DVF-induced colitis. Conclusions D. vulgaris could promote colitis through DVF-LRRC19 interaction. Targeting DVF-LRRC19 interaction might be a new therapeutic strategy for UC therapy. Video Abstract

Abstract Stabilizing active PtNi alloy catalyst toward oxygen reduction reaction is essential for fuel cell. Doping of specific metals is an empirical strategy, however, the atomistic insight into how dopant boosts the stability of PtNi catalyst still remains elusive. Here, with typical examples of Mo and Au dopants, we identify the distinct roles of Mo and Au in stabilizing PtNi nanowires catalysts. Specifically, due to the stronger interaction between atomic orbital for Ni-Mo and Pt-Au, the Mo dopant mainly suppresses the outward diffusion of Ni atoms while the Au dopant contributes to the stabilization of surface Pt overlayer. Inspired by this atomistic understanding, we rationally construct the PtNiMoAu nanowires by integrating the different functions of Mo and Au into one entity. Such catalyst assembled in fuel cell cathode thus presents both remarkable activity and durability, even surpassing the United States Department of Energy technical targets for 2025.

Abstract With the advancement of society, ensuring the safety of personnel involved in municipal construction projects, particularly in the context of pandemic control measures, has become a matter of utmost importance. This paper introduces a security measure for municipal engineering, combining deep learning with object detection technology. It proposes a lightweight artificial intelligence (AI) detection method capable of simultaneously identifying individuals wearing masks and safety helmets. The method primarily incorporates the ShuffleNetv2 feature extraction mechanism within the framework of the YOLOv5s network to reduce computational overhead. Additionally, it employs the ECA attention mechanism and optimized loss functions to generate feature maps with more comprehensive information, thereby enhancing the precision of target detection. Experimental results indicate that this algorithm improves the mean average precision (mAP) value by 4.3%. Furthermore, it reduces parameter and computational loads by 54.8% and 53.8%, respectively, effectively striking a balance between lightweight operation and precision. This study serves as a valuable reference for research pertaining to lightweight target detection in the realm of municipal construction safety measures.

Nanozymes with superior antioxidant properties offer new hope for treating oxidative stress-related inflammatory skin diseases. However, lacking sufficient catalytic activity or having complex material designs limit the application of current metallic nanozymes in inflammatory skin diseases. Here, we report a simple and effective twin-defect platinum nanowires (Pt NWs) enzyme with multiple mimetic enzymes and broad-spectrum ROS scavenging capability for the treatment of inflammatory skin diseases in mice (including psoriasis and rosacea). Pt NWs with simultaneous superoxide dismutase, glutathione peroxidase and catalase mimetic enzyme properties exhibit cytoprotective effects against ROS-mediated damage at extremely low doses and significantly improve treatment outcomes in psoriasis- and rosacea-like mice. Meanwhile, these ultrasmall sizes of Pt NWs allow the nanomaterials to effectively penetrate the skin and do not produce significant biotoxicity. Therefore, Pt NWs have potential applications in treating diseases related to oxidative stress or inflammation.

Introduction: One of the most common malignant tumors affecting women in China is cervical cancer. In the year 2015, 30,500 fatalities and 98,900 new cases of cervical cancer were reported. By 2030, the number of deaths from cervical cancer will grow by over 50%. China has been strengthening its cervical cancer prevention and treatment service system and enhancing the country’s comprehensive prevention and treatment capacity including HPV vaccination. Objective: A systematic review was conducted to examine and describe factors influencing HPV vaccine acceptance among females in mainland China. Method: A systematic search of Web of Science, PubMed, Scopus, EBSCOhost, and China National Knowledge Infrastructure (CNKI) was carried out from January 2000 to April 2023 for articles related to factors influencing HPV vaccine acceptability among females in mainland China. Result: Articles were screened by inclusion and exclusion criteria, and those that met the inclusion criteria were included in the study. Of the 10 included studies, the subjects involved university students, secondary school students, mothers, health professional students, medical professionals, and females. A review of the included studies revealed that there was a low level of acceptance of the HPV vaccine among women in mainland China as a whole. Factors influencing this acceptance included knowledge of the HPV vaccine, hearing about it, family history of infection-related diseases, cost, hearing about HPV/HPV vaccine/cervical cancer, vaccine safety, sex life, and sex education. Conclusion: Awareness of the HPV vaccine among females in mainland China is low, and this leads to a lack of acceptance of the HPV vaccine among females. The HPV vaccination program will benefit more from targeted HPV vaccine promotion campaigns based on factors influencing females' acceptance of the vaccine, such as those conducted through the media, hospital publicity, and community publicity to increase women’s knowledge of the vaccine and improve vaccine acceptance.

ABSTRACT: In this study, transglutaminase (TG), glucono-δ-lactone (GDL), and citric acid (CA) were used to induce the formation of whey protein isolate (WPI)-milk fat emulsion gels to embed lutein, and the emulsion gels induced in different ways were used for the preparation of processed cheese. The protective effect of emulsion gels induced in different ways on lutein was investigated, and the stability of lutein in emulsion gels and processed cheese was analyzed. The results showed that the acidification rate of CA was higher than that of GDL, which was the key step in acid-induced gels, and that the difference in acidification rate led to differences in gel structure. Compared with the 2 acid inducers (GDL and CA), TG exhibited greater potential for forming gel structures with high strength. The TG-induced emulsion gels showed the best physical stability and the highest embedding efficiency for lutein. After heat treatment (85°C), the GDL-induced emulsion gels had higher retention rate of lutein and showed good thermal stability compared with the CA-induced emulsion gels. The processed cheese added with the TG-induced emulsion gel had higher hardness and springiness compared with the processed cheese added with the other 2 kinds of emulsion gels, whereas the processed cheese added with the CA-induced emulsion gel had a lower density of network structure, showing porosity and a larger aggregated structure, but the highest bioavailability of lutein. These results provide valuable information for the formation of cold-set emulsion gel and provide the possibility for the application of emulsion gel embedding active substances in processed cheese.

Predicting protein–ligand binding sites is an integral part of structural biology and drug design. A comprehensive understanding of these binding sites is essential for advancing drug innovation, elucidating mechanisms of biological function, and exploring the nature of disease. However, accurately identifying protein–ligand binding sites remains a challenging task. To address this, we propose PGpocket, a geometric deep learning-based framework to improve protein–ligand binding site prediction. Initially, the protein surface is converted into a point cloud, and then the geometric and chemical properties of each point are calculated. Subsequently, the point cloud graph is constructed based on the inter-point distances, and the point cloud graph neural network (GNN) is applied to extract and analyze the protein surface information to predict potential binding sites. PGpocket is trained on the scPDB dataset, and its performance is verified on two independent test sets, Coach420 and HOLO4K. The results show that PGpocket achieves a 58% success rate on the Coach420 dataset and a 56% success rate on the HOLO4K dataset. These results surpass competing algorithms, demonstrating PGpocket’s advancement and practicality for protein–ligand binding site prediction.

To achieve large-scale development of triboelectric nanogenerators (TENGs) for water wave energy harvesting and powering the colossal sensors widely distributed in the ocean, facile and scalable TENGs with high output are urgently required. Here, an elastic self-recovering hybrid nanogenerator (ES-HNG) is proposed for water wave energy harvesting and marine environmental monitoring. The elastic skeletal support of the ES-HNG is manufactured using three-dimensional (3D) printing technology, which is more conducive to the large-scale integration of the ES-HNG. Moreover, the combination of a TENG and an electromagnetic generator (EMG) optimizes the utilization of device space, leading to enhanced energy harvesting efficiency. Experimental results demonstrate that the TENG achieves a peak power output of 42.68 mW, and the EMG reaches a peak power output of 4.40 mW. Furthermore, various marine environment monitoring sensors, such as a self-powered wireless meteorological monitoring system, a wireless alarm system, and a water quality monitoring pen, have been successfully powered by the sophisticated ES-HNG. This work introduces an ES-HNG for water wave energy harvesting, which demonstrates potential in marine environment monitoring and offers a new solution for the sustainable development of the marine internet of things.

Abstract Background Lactobacillus species in gut microbiota shows great promise in alleviation of metabolic diseases. However, little is known about the molecular mechanism of how Lactobacillus interacts with metabolites in circulation. Here, using high nucleoside intake to induce hyperuricemia in mice, we investigated the improvement in systemic urate metabolism by oral administration of L. plantarum via different host pathways. Results Gene expression analysis demonstrated that L. plantarum inhibited the activity of xanthine oxidase and purine nucleoside phosphorylase in liver to suppress urate synthesis. The gut microbiota composition did not dramatically change by oral administration of L. plantarum over 14 days, indicated by no significant difference in α and β diversities. However, multi-omic network analysis revealed that increase of L. plantarum and decrease of L. johnsonii contributed to a decrease in serum urate levels. Besides, genomic analysis and recombinant protein expression showed that three ribonucleoside hydrolases, RihA–C, in L. plantarum rapidly and cooperatively catalyzed the hydrolysis of nucleosides into nucleobases. Furthermore, the absorption of nucleobase by intestinal epithelial cells was less than that of nucleoside, which resulted in a reduction of urate generation, evidenced by the phenomenon that mice fed with nucleobase diet generated less serum urate than those fed with nucleoside diet over a period of 9-day gavage. Conclusion Collectively, our work provides substantial evidence identifying the specific role of L. plantarum in improvement of urate circulation. We highlight the importance of the enzymes RihA–C existing in L. plantarum for the urate metabolism in hyperuricemia mice induced by a high-nucleoside diet. Although the direct connection between nucleobase transport and host urate levels has not been identified, the lack of nucleobase transporter in intestinal epithelial cells might be important to decrease its absorption and metabolization for urate production, leading to the decrease of serum urate in host. These findings provide important insights into urate metabolism regulation. Video Abstract

The parameter setting of functional electrical stimulation (FES) is important for active recovery training since it affects muscle health. Among the FES parameters, current amplitude is the most influential factor. To explore the FES effect on the maximum stimulation time, this study establishes a curve between FES current amplitude and the maximum stimulation time based on muscle fatigue. We collect 10 subjects’ surface electromyography under dumbbell weightlifting training and analyze the muscle fatigue state by calculating the root mean square (RMS) of power. By analyzing signal RMS, the fatigue characteristic curves under different fatigue levels are obtained. According to the muscle response under FES, the relationship curve between the current amplitude and the maximum stimulation time is established and FES parameters’ effect on the maximum stimulation time is obtained. The linear curve provides a reference for FES parameter setting, which can help to set stimulation time safely, thus preventing the muscles from entering an excessive fatigue state and becoming more active to muscle recovery training.

Background: Diabetic foot ulcers (DFUs) are a severe complication of diabetes. Persistent inflammation and impaired vascularization present considerable challenges in tissue wound healing. The aim of this study was to identify the crucial regulators of DFU wound healing and investigate their specific mechanisms in DFU. Methods: DFU RNA sequencing data were obtained to identify crucial feature genes. The expression levels of the feature genes and their corresponding microRNAs (miRNAs) were verified in clinical samples. Subsequently, the expression of CD68 was determined in DFU and non-diabetic foot skin samples. RAW 264.7 cells were treated with advanced glycation end products (AGEs) to determine their viability and apoptosis. Finally, the roles of the selected crucial genes and their corresponding miRNAs were investigated using in vitro experiments and a mouse model of diabetes. Results: Bioinformatic analysis showed that five crucial feature genes (CORO1A, CSF1R, CTSH, NFE2L3, and SLC16A10) were associated with DFU wound healing. The expression validation showed that miR-361-3p-CSF1R had a significant negative correlation and was thus selected for further experiments. AGEs significantly inhibited the viability of RAW 264.7 cells and enhanced their apoptosis; furthermore, the AGEs significantly downregulated CSF1R and increased miR-361-3p levels compared with the control cells. Additionally, inhibition of miR-361-3p decreased the cell apoptosis caused by AGEs and increased the levels of p-AKT/AKT and p-PI3K/PI3K, whereas CSF1R knockdown reversed the effects of miR-361-3p. In vivo experiments showed that miR-361-3p inhibition promoted wound healing in diabetic mice and regulated PI3K/AKT levels. Conclusions: AGEs may regulate macrophage apoptosis via the miR-361-3p/CSF1R axis and PI3K/AKT pathway, thereby influencing DFU wound healing.

Rapid urbanization is a global phenomenon that has altered many ecosystems and created ecological risks. Landscape ecological risk (LER) reflects the extent to which ecosystems are threatened by human activities and environmental change. LER can be also employed to effectively monitor and assess environmental quality. A large number of studies have been conducted to explore the LER in the basin from the perspective of Land Use and Land Cover (LUCC). Ecological environmental issues such as land degradation have seriously hindered the sustainable development of the Yellow River Basin (YRB). Based on the LUCC data of the YRB in the four periods of 1990, 2000, 2010 and 2020, this study aims to determine the most suitable spatial analysis scale using the coefficient of variation and semi-variogram, and analyzes the landscape pattern and LER of the YRB. We found that the landscape pattern of the YRB exhibits obvious scale dependence, and the analysis effect is most effective at the scale of 90 km × 90 km. Throughout the study period, the landscape pattern exhibited increasing fragmentation, a decrease in the degree of aggregation and an increase in the heterogeneity of distribution. In terms of LER, it is in a better state as most of the LER levels have shifted from higher to lower levels, and the proportion of lower and lowest risk is constantly increasing. This study improves the precision of spatial scale investigations and offers valuable insights for future studies on landscape pattern and LER in the basin.

After more than five decades, Moore’s Law for transistors is approaching the end of the international technology roadmap of semiconductors (ITRS). The fate of complementary metal oxide semiconductor (CMOS) architecture has become increasingly unknown. In this era, 3D transistors in the form of gate-all-around (GAA) transistors are being considered as an excellent solution to scaling down beyond the 5 nm technology node, which solves the difficulties of carrier transport in the channel region which are mainly rooted in short channel effects (SCEs). In parallel to Moore, during the last two decades, transistors with a fully depleted SOI (FDSOI) design have also been processed for low-power electronics. Among all the possible designs, there are also tunneling field-effect transistors (TFETs), which offer very low power consumption and decent electrical characteristics. This review article presents new transistor designs, along with the integration of electronics and photonics, simulation methods, and continuation of CMOS process technology to the 5 nm technology node and beyond. The content highlights the innovative methods, challenges, and difficulties in device processing and design, as well as how to apply suitable metrology techniques as a tool to find out the imperfections and lattice distortions, strain status, and composition in the device structures.

In the context of urban expansion and climate change, the world is under pressure from multiple ecological risks. Key ecological protection areas play a pivotal role in preserving ecological stability and promoting development. Due to its unique geographical conditions, the Yellow River basin has been facing huge ecological risk pressure. In the affected area of the Lower Yellow River (AALYR) as an agricultural hub, ecological protection has gradually become a key factor restricting the development of cities and agriculture. Taking AALYR as an example, the landscape ecological risk assessment (LERA) system is established based on three aspects “natural environment—human society—landscape pattern”. We construct a comprehensive cumulative resistance surface based on the risk assessment results as the basis for the future study. Ecological corridors are identified by minimum cumulative resistance (MCR) models to establish and optimize Ecological security pattern (ESP) in the AALYR. We found that the landscape ecological risks (LER) in the study area show a uniform spatial distribution, with a slightly higher distribution in the northeast than the southwest. The ecological risk levels are generally high in AALYR, indicating a more severe risk problem in this area. A total of 56 ecological sources were identified, with a total area of 21176 km2. The ecological sensitivity of AALYR was high, and 99 ecological corridors and 59 ecological nodes were extracted. Ecological corridors and nodes were consistently and densely distributed throughout the study area. The network analysis method improves the stability of the network structure after optimization. Based on the key components of the ESP, with the combination of geographical characteristics and local policy planning guidance, we constructed the “One Belt and One Axis, Two Cores and Two Corridors, Four zones” ESP. The study results may offer guidance and suggestions for the construction of ESP and ecological environment protection system in the world’s major river basins, and may also provide information for ecological planning of other similar river basins in the world.

Abstract Background Increasing evidence has supported a link between obstructive sleep apnea (OSA) and cognition, and blood-brain barrier (BBB) dysfunction which can be reflected by paroxysmal slow wave events (PSWEs) may be a potential mechanism. The purpose of our study was to investigate the correlation between the PSWEs and cognitive impairment in patients with OSA, with a focus on the possible mechanism. Methods In total, 339 subjects with subjective snoring complaints from the Sleep Medicine Center underwent magnetic resonance imaging and whole-night polysomnography. OSA was defined as apnea-hypopnea index (AHI) ≥ 5 events/h. MCI was defined as the MoCA < 26 and met the criteria: (1) subjective cognitive impairment; (2) objective impairment in one or more cognitive domains; (3) slightly impaired complex instrumental daily abilities, but independent daily living abilities; and (4) no dementia. The PSWEs calculated by self-developed Python scripts were defined for EEG recordings as a median power frequency of < 6 Hz for more than five consecutive seconds. Serum cyclophilin A (CyPA) and matrix metalloproteinase-9 (MMP-9) levels and amyloid-β 42 levels in neuron-derived exosomes were determined. The participants who received continuous positive airway pressure (CPAP) were followed up and their PSWEs were recalculated after 1 year of treatment. Results A total of 339 participants were divided into the OSA+MCI group (n = 157), OSA-MCI group (n = 118), and controls (normal cognitive state without OSA) (n = 64). The total PSWEs and the occurrence per minute of PSWEs at stage REM in the OSA+MCI group were higher than those in the OSA-MCI and control groups. The duration ratio of PSWEs at stage REM in the OSA+MCI group significantly increased. The total PSWEs and PSWEs at the F4-M1, O1-M2, and O2-M1 channels in stage REM were independently associated with cognitive impairment in OSA patients. There were positive correlations between the PSWEs and serum CyPA and MMP-9 levels in patients with OSA. The mediation analysis showed that the relationship between mean SaO2 and percentage of sleep time spent with oxygen saturation

Controlling the enantioselectivity of radical reactions is a persistent challenge in organic synthesis. Here, the authors report a method to form asymmetric pyridine derivatives via the combination of chiral palladium catalysis and electrochemistry.

BackgroundAutism spectrum disorder (ASD) is a neurodevelopmental disorder that can cause difficulty with communication and social interactions as well as complicated family dynamics. Digital health interventions can reduce treatment costs and promote healthy lifestyle changes. These therapies can be adjunctive or replace traditional treatments. However, issues with cooperation and compliance prevent preschool patients with ASD from applying these tools. In this open-label, randomized controlled trial, we developed a nonwearable digital therapy called virtual reality–incorporated cognitive behavioral therapy (VR-CBT). ObjectiveThe aim of this study was to assess the adjunctive function of VR-CBT by comparing the effects of VR-CBT plus learning style profile (LSP) intervention with those of LSP-only intervention in preschool children with ASD. MethodsThis trial was performed in China on 78 preschool children (age 3-6 years, IQ>70) diagnosed with ASD who were randomized to receive a 20-week VR-CBT plus LSP intervention (intervention group, 39/78, 50%) or LSP intervention only (control group, 39/78, 50%). The primary outcome was the change of scores from baseline to week 20, assessed by using the parent-rated Autism Behavior Checklist (ABC). Secondary outcomes included the Childhood Autism Rating Scale (CARS), Attention-Deficit/Hyperactivity Disorder Rating Scale-IV (ADHD-RS-IV), and behavioral performance data (accuracy and reaction time) in go/no-go tasks. All primary and secondary outcomes were analyzed in the intention-to-treat population. ResultsAfter the intervention, there was an intervention effect on total ABC (β=–5.528; P

In order to improve the quality of medical image fusion, preserve the spectral characteristics of the original image and avoid spectral degradation of the fused image, we propose a new medical image fusion method based on the nonsubsampled contourlet transform (NSCT) and adaptive pulse coupled neural network (PCNN). NSST is used to decompose the source image into high and low-frequency. The improved PCNN is used to fuse the low-frequency sub-band coefficients, and the square error sum of pixels is used as the excitation factor. The sum of directional gradients is selected as the link strength. The high-frequency sub-band coefficients with large computational load are fused by using the feature-based rule. The fused image is obtained by NSST inverse transformation. Experimental results show that compared with the NSCT and the other combinations of NSST and PCNN algorithms, the proposed algorithm can obtain better results, and the running time is shorter. The average values of information entropy, spatial frequency, standard deviation, clarity, edge information with proposed method are 6.6191, 23.3014, 64.3961, 9.4683 and 0.7213, respectively.

Brain-computer interface (BCI) is a useful device for people without relying on peripheral nerves and muscles. However, the performance of the event-related potential (ERP)-based BCI declines when applying it to real environments, especially in cross-state and cross-subject conditions. Here we employ temporal modeling and adversarial training to improve the visual ERP-based BCI under different mental workload states and to alleviate the problems above. The rationality of our method is that the ERP-based BCI is based on electroencephalography (EEG) signals recorded from the scalp’s surface, continuously changing with time and somewhat stochastic. In this paper, we propose a hierarchical recurrent network to encode all ERP signals in each repetition at the same time and model them with a temporal manner to predict which visual event elicited an ERP. The hierarchical architecture is a simple yet effective method for organizing recurrent layers in a deep structure to model long sequence signals. Taking a cue from recent advances in adversarial training, we further applied dynamic adversarial perturbations to create adversarial examples to enhance the model performance. We conduct our experiments on one published visual ERP-based BCI task with 15 subjects and 3 different auditory workload states. The results indicate that our hierarchical method can effectively model the long sequence EEG raw data, outperform the baselines on most conditions, including cross-state and cross-subject conditions. Finally, we show how deep learning-based methods with limited EEG data can improve ERP-based BCI with adversarial training. Our code is available at https://github.com/aispeech-lab/VisBCI.

Inflammatory bowel disease (IBD), comprising Crohn’s disease (CD) and ulcerative colitis (UC), is a set of clinically chronic, relapsing gastrointestinal inflammatory disease and lacks of an absolute cure. Although the precise etiology is unknown, developments in high-throughput microbial genomic sequencing significantly illuminate the changes in the intestinal microbial structure and functions in patients with IBD. The application of microbial metabolomics suggests that the microbiota can influence IBD pathogenesis by producing metabolites, which are implicated as crucial mediators of host-microbial crosstalk. This review aims to elaborate the current knowledge of perturbations of the microbiome–metabolome interface in IBD with description of altered composition and metabolite profiles of gut microbiota. We emphasized and elaborated recent findings of several potentially protective metabolite classes in IBD, including fatty acids, amino acids and derivatives and bile acids. This article will facilitate a deeper understanding of the new therapeutic approach for IBD by applying metabolome-based adjunctive treatment.

Graph neural network-based recommender systems are blossoming recently, and it can explicitly express user-item high-order connectivity information, so it can significantly improve the recommendation performance. However, the existing methods usually assume that the users’ interests are invariant, but temporal relationships is left insufficient exploration to charactertize the user’s dynamic interest. In this paper, we propose a Neural Graph Collaborative Filtering recommendation model fused with Item Temporal Sequence relationships (NGCF-ITS), that is, a hybrid recommendation model that fuses with user-item interactions information and item temporal sequence relationships. It divides the item temporal sequences into several groups of subsequences through the sliding window strategy, then constructs the item temporal sequence relationships graph and aggregates the characteristics of item temporal sequences information. At the last, deeply depicts the dynamic changes of users’ interests, and uses the bipartite graph neural network to map the high-dimensional information of user-item and item-item into the low-dimensional space. The hybrid embedding of user-item historical interactions and item temporal sequence relationships are realized, and the expression of user-item interactions is enhanced. In this way, the heterogeneous multi-relational graphs are fused for the feature propagation, which largely refines the user and item representation for model prediction. Extensive experiments demonstrate the our proposed model significantly improve the recommendation performance compared to the state-of-the-art GNN-based models both in accuracy and training efficiency.

Brain–computer interface (BCI) is a typical direction of integration of human intelligence and robot intelligence. Shared control is an essential form of combining human and robot agents in a common task, but still faces a lack of freedom for the human agent. This paper proposes a Centroidal Voronoi Tessellation (CVT)-based road segmentation approach for brain-controlled robot navigation by means of asynchronous BCI. An electromyogram-based asynchronous mechanism is introduced into the BCI system for self-paced control. A novel CVT-based road segmentation method is provided to generate optional navigation goals in the road area for arbitrary goal selection. An event-related potential of the BCI is designed for target selection to communicate with the robot. The robot has an autonomous navigation function to reach the human selected goals. A comparison experiment in the single-step control pattern is executed to verify the effectiveness of the CVT-based asynchronous (CVT-A) BCI system. Eight subjects participated in the experiment, and they were instructed to control the robot to navigate toward a destination with obstacle avoidance tasks. The results show that the CVT-A BCI system can shorten the task duration, decrease the command times, and optimize navigation path, compared with the single-step pattern. Moreover, this shared control mechanism of the CVT-A BCI system contributes to the promotion of human and robot agent integration control in unstructured environments.

Thinning plays a vital role in controlling stand density of plantation forests to get quality wood and more ecological function. However, the specific effects of thinning on forest biomass connected with forest age are usually overlooked especially in semi-arid regions. Here, we examined the effects of thinning on individual tree growth and stand biomass in a chronosequence of 20-, 30-, 40-, and 50-year-old Chinese pine (Pinus tabulaeformis) plantations on the Loess Plateau, China. We found that under different thinning managements, both mean diameter at breast height (DBH) and tree height followed the logistic growth pattern, and thinning promoted tree radial growth more than height. The effects of thinning on tree biomass differed between the individual tree and stand level. Thinning could promote individual tree biomass irrespective of stand ages, while stand biomass did not differ between the thinned and unthinned stands at different stand ages. Furthermore, the multiple linear regression analysis and structure equation model showed that individual tree growth was the primary contributor of stand biomass. Thus, we infer that the stand biomass loss after thinning could be mainly compensated by enhanced tree growth, especially radial growth, after a period of recovery (no more than 20 years). The results could provide helpful guidance for forest management and highlighted that reasonable thinning treatment could result in both high individual tree product and stand level harvests in the long term.

BackgroundRapid eye movement (REM) sleep behavior disorder (RBD) predicts cognitive decline in Parkinson’s disease (PD) patients without dementia. However, underlying mechanisms remain unknown. Accumulating studies suggest glutamatergic system dysregulation is associated.ObjectiveTo examine the effect of RBD on the rate of cognitive decline in PD patients and investigate whether plasma levels of the neuroexosomal vesicular glutamate transporter-1 (VGLUT-1) and excitatory amino acid transporter-2 (EAAT-2) are altered in PD patients with RBD.MethodsThis study included 157 newly diagnosed cognitive normal PD patients and 70 healthy controls (HCs). Based on one-night polysomnography recordings, the PD subjects were divided into PD with and without RBD (PD-RBD and PD-nRBD) groups. All participants received a complete clinical and neuropsychological evaluation at baseline. Plasma levels of neuroexosomal VGLUT-1 and EAAT-2 were measured by ELISA kits. After a 3-year follow-up, we evaluated baseline plasma levels of neuroexosomal glutamate transporters in each group as a predictor of cognitive decline using MoCA score changes over 3 years in regression models.ResultsPlasma levels of neuron-derived exosomal EAAT-2 and VGLUT-1 were significantly lower in PD patients than in HCs. Plasma levels of neuroexosomal EAAT-2 were significantly lower in PD-RBD than PD-nRBD group at baseline. At the 3-year follow-up, PD-RBD patients presented greater cognitive decline. Lower baseline blood neuroexosomal EAAT-2 predicted cognitive decline over 3 years in PD-RBD patients (β = 0.064, P = 0.003).ConclusionThese findings indicate that blood neuroexosomal EAAT-2 is associated with cognitive decline in PD with RBD.

The exposure of recycled concrete (RCA) to a sulphate environment in cold regions makes it crucial to overcome the freeze–thaw cycling effects of recycled concrete. Based on steel and basalt fiber reinforced recycled concrete, the freeze–thaw cycle resistance of recycled concrete was studied by exposure to a sulphate environment. The mass loss, dynamic elastic modulus loss and compressive strength loss of the specimens were studied through freeze–thaw cycle experiments. SEM techniques were used to explore the effect of fiber distribution on the freeze–thaw resistance of recycled concrete. The freeze–thaw mechanism of the basalt fiber and steel fiber recycled concrete exposed to a sulphate environment has also been summarized. The results show that, based on the sulphate environment, the composite fiber recycled concrete has a higher stability in terms of mass loss and relative dynamic modulus of elasticity than single fiber concrete. The compressive strength of S0.9RC (recycled concrete with 0.9% steel fibers) and BF5.5RC (recycled concrete containing 5.5 kg/m3 basalt fibers) increased by 8.62% and 13.62%, respectively, compared to normal recycled concrete after 28 days of maintenance; and after 150 freeze–thaw cycles, the compressive strength increased by 41.39% and 47.54%, respectively; compared to ordinary natural aggregate concrete, the compressive strength of S0.9RC and BF5.5RC increased by 32.90% and 27.36%, respectively. The compressive strength of the S1.5BF7.5RC (recycled concrete with 1.5% steel fibers and 7.5 kg/m3 basalt fibers) composite basalt fiber–steel fiber concrete also increased by 42.82%. SEM techniques indicated that the basalt fiber in the recycled concrete exhibited fracture damage, which inhibited the development of microcracks within the concrete. When the recycled concrete is subjected to coupled sulphate and freeze–thaw cycles, freezing occurs from the outside in, with ice crystals extending along the cracks into the matrix. Prior to freezing, a negative pressure is created by the compression of the air and the contraction of the salt solution, which pulls the external solution inwards. The brine is in a state where ice and water coexist during the continuous cooling process. The salt solution migrates from the inside to the outside during heating and melting.

Our previous study established an asynchronous BCI system by using the oddball paradigm to simultaneously induce event-related potentials (ERPs) and visual evoked potentials (VEPs) (E-V BCIs). We found that stimulus onset asynchrony (SOA) is an important factor for performance since it significantly affects the ERP and VEP. Increasing the SOA increases the ERP, which improves the accuracy of detecting target stimuli. However, a larger SOA leads to a lower VEP frequency, which causes the VEP to have poor accuracy when discriminating between the brain states. How to balance the two potentials and accuracies is a problem. This study established eight SOAs from 100 ms to 375 ms that were composed of different interstimulus intervals and the same stimulus duration of 80 ms. We used a probability-based Fisher linear discriminant analysis (P-FLDA) classifier to calculate the classification accuracies of the ERP-based visual speller, VEP-based brain state discrimination, and E-V BCI. The results show that as the SOA increases, the amplitudes of N200 and P300 increase, and the accuracy also shows an increasing trend. However, the frequency of the VEP and the accuracies of state discrimination show downward trends. The change in accuracies of the E-V BCI system combining these two parts is nonlinear, and the SOA optimal value is 125 ms. The SOA of 125 ms yields the best accuracies of 95.83% and practical bit rate of 57.17 bits/min in the E-V BCI system, which provides a guideline for selecting the SOA to improve the performance.

Carbon fiber (CF) reinforced composites are widely used due to their excellent properties. However, the smooth surface and few functional groups of CFs can lead to fiber fractures and pullout, which reduce the service life of the composites. The overall performance of composites can be improved by growing carbon nanotubes (CNTs) on the CF surface. Before this, CF surface should be modified to enhance the loading amount of catalyst particles and thus make the CNTs more uniform. In this paper, CNTs were grown on a CF surface by one-step chemical vapor deposition to prepare multi-scale CNTs/CF reinforcements, and the effects of different methods on the CF surface modification were explored. After setting four intensities of electrochemical anodic oxidation, i.e., 50 C/g, 100 C/g, 150 C/g and 200 C/g, it was found that the distribution and quantity of CNTs were improved under both the 100 C/g and 150 C/g conditions. Considering the influence of electrical intensity on the (002) interplanar spacing of CFs, which affects the mechanical properties of the samples, 100 C/g was finally selected as the optimal electrochemical treatment intensity. This finding provides a reference for continuous and large-scale modification of CF surfaces to prepare CNTs/CF multi-scale reinforcements.

The prevalence of inflammatory bowel disease (IBD) is increasing worldwide and correlates with dysregulated immune response because of gut microbiota dysbiosis. Some adverse early life events influence the establishment of the gut microbiota and act as risk factors for IBD. Prenatal maternal stress (PNMS) induces gut dysbiosis and perturbs the neuroimmune network of offspring. In this study, we aimed to investigate whether PNMS increases the susceptibility of offspring to colitis in adulthood. The related index was assessed during the weaning period and adulthood. We found that PNMS impaired the intestinal epithelial cell proliferation, goblet cell and Paneth cell differentiation, and mucosal barrier function in 3-week-old offspring. PNMS induced low-grade intestinal inflammation, but no signs of microscopic inflammatory changes were observed. Although there was no pronounced difference between the PNMS and control offspring in terms of their overall measures of alpha diversity for the gut microbiota, distinct microbial community changes characterized by increases in Desulfovibrio, Streptococcus, and Enterococcus and decreases in Bifidobacterium and Blautia were induced in the 3-week-old PNMS offspring. Notably, the overgrowth of Desulfovibrio persisted from the weaning period to adulthood, consistent with the results observed using fluorescence in situ hybridization in the colon mucosa. Mechanistically, the fecal microbiota transplantation experiment showed that the gut microbiota from the PNMS group impaired the intestinal barrier function and induced low-grade inflammation. The fecal bacterial solution from the PNMS group was more potent than that from the control group in inducing inflammation and gut barrier disruption in CaCo-2 cells. After treatment with a TNF-α inhibitor (adalimumab), no statistical difference in the indicators of inflammation and intestinal barrier function was observed between the two groups. Finally, exposure to PNMS remarkably increased the values of the histopathological parameters and the inflammatory cytokine production in a mouse model of experimental colitis in adulthood. These findings suggest that PNMS can inhibit intestinal development, impair the barrier function, and cause gut dysbiosis characterized by the persistent overgrowth of Desulfovibrio in the offspring, resulting in exacerbated experimental colitis in adulthood.

Carbon fiber composites as pantograph slide materials are in the development stage, in which copper is the conductive phase, and the addition form and size need to be designed. Herein, the effects of the copper morphology, the size of the copper mesh on the performance, and the influence of the contact mode between the sliding plate and bracket on the temperature rise were compared and analyzed. The resistivity is 11.2 μΩ·m with the addition of 20 wt% copper mesh, a relative reduction of 91.77%. Importantly, the impact strength is increased by 14.19%, and the wear is reduced by 13.21%; hence, the copper mesh laid in layers is the ideal structure. Further study of the distribution and quality of the copper mesh shows that the resistivity is related only to the quality of the copper mesh; in addition, the number of layers of the copper mesh cannot exceed 16, and it is determined that the best type of copper mesh is 5#. Notably, the performance can be improved by appropriately reducing the thickness of the copper mesh and increasing the aperture while the sliding plate and the bracket are connected by copper mesh with conductive adhesive, which has the slowest heating rate of 2.27 °C/min and the smallest resistance. Therefore, the influence of copper content and distribution on the electrical conductivity are systematically investigated, and the mechanical properties and electrical conductivity are optimized through the design of the laminate structure of the compound material.

As a class of the commonly used drugs in clinical practice, non-steroidal anti-inflammatory drugs (NSAIDs) can cause a series of adverse events including gastrointestinal injuries. Besides upper gastrointestinal injuries, NSAID enteropathy also attracts attention with the introduction of capsule endoscopy and double balloon enteroscopy. However, the pathogenesis of NSAID enteropathy remains to be entirely clarified. Growing evidence from basic and clinical studies presents that gut microbiota is a critical factor in NSAID enteropathy progress. We have reviewed the recent data about the interplay between gut microbiota dysbiosis and NSAID enteropathy. The chronic medication of NSAIDs could change the composition of the intestinal bacteria and aggravate bile acids cytotoxicity. Meanwhile, NSAIDs impair the intestinal barrier by inhibiting cyclooxygenase and destroying mitochondria. Subsequently, intestinal bacteria translocate into the mucosa, and then lipopolysaccharide released from gut microbiota combines to Toll-like receptor 4 and induce excessive production of nitric oxide and pro-inflammatory cytokines. Intestinal injuries present in the condition of intestinal inflammation and oxidative stress. In this paper, we also have reviewed the possible strategies of regulating gut microbiota for the management of NSAID enteropathy, including antibiotics, probiotics, prebiotics, mucosal protective agents, and fecal microbiota transplant, and we emphasized the adverse effects of proton pump inhibitors on NSAID enteropathy. Therefore, this review will provide new insights into a better understanding of gut microbiota in NSAID enteropathy.

The ultraviolet–visible imaging spectropolarimeter (UVISP), developed by the Anhui Institute of Optics and Fine Mechanics (AIOFM), Chinese Academy of Science (CAS), is a dual-beam snapshot instrument for measuring the spectral, radiometric, and linear polarization information of absorbing aerosol in a wavelength range from 340 to 520 nm. In this paper, we propose a complete set of calibration methods for UVISP to ensure the accuracy of the measured radiation polarization data, thus guaranteeing the reliability of inversion results. In geometric calibration, we complete the assignment of the field of view (FOV) angle to each pixel of the detector using a high precision turntable and parallel light source. In addition, the geometric calibration accuracy of the S beam and P beam is also analyzed. The results show that the residuals of all row pixels are less than 0.12°. Based on geometric calibration, a spectral calibration is conducted at each spectrum of the S beam and P beam for the given FOV, and the relation between the wavelength and pixel is obtained by a linear fitting procedure. For radiometric calibration, the uniformity of spectral responsivity is corrected, and the function between spectral radiance and output digital data is established. To improve the accuracy of the polarimetric measurement, a polarimetric calibration is proposed, and validated experimental results show that the root mean square (RMS) errors for the demodulated value are all within 0.011 for the input linear polarized light with different angles of linear polarization (AoLPs). Finally, field measurements are conducted, and the absolute deviations are all within 0.01 when the UVISP and CE-318 sun–sky polarimetric radiometer (CE318N) simultaneously measure the degree of linear polarization (DoLP) of the sky at different zenith angles. These experimental results demonstrate the efficiency and accuracy of the proposed calibration methods.

Lithium-ion batteries play an important role in large-scale energy storage systems. However, the power inconsistency of the battery packs restricts the developments of modern technologies in energy storage area. The motivation of the present study is to serve the growing needs of the energy balance for lithium-ion battery packs. The present study proposes a flexible multiphase interleaved converter for the energy equalization of a lithium battery pack with series configuration. Moreover, the graph theory is applied to the analysis of equalization circuits. It is intended to establish a unified standard for the comparison. The parameter of average efficiency is considered as an important indicator to evaluate the characteristics of the equilibrium system. The proposed method is verified by constructing a lithium-ion battery pack with the equalization circuit. It is observed that the proposed multiphase interleaved converter has flexible characteristics, while it has low energy loss compared with the conventional methods. It is found that the proposed method simplifies the complex equalization circuits into graphs and facilitates the comparison of the average efficiency of the system. It is concluded that this method is a feasible and powerful method for evaluating the battery equalization circuit. This approach can be applied for solving complex problems in other engineering applications.

Independent microgrids are widely used in islands and remote townships. However, power imbalance often leads to fluctuations in voltage and frequency, which inhibit the development of AC microgrids. To overcome such problems, this paper proposes an optimized full-bridge converter energy storage structure to realize power balance and optimization of the microgrid. The proposed structure has the characteristics of simple design, easy modularization, and flexible power regulation. First, the working structure and mathematical model are analyzed, and the power model is then established. From the viewpoint of capacitor charging and discharging and inverter, the active and reactive power control technology of the full-bridge structure is analyzed, and a multimode power coordinated control strategy is adopted to adjust and optimize the target power. Finally, the feasibility of the structure and control strategy is verified through a simulation and an experiment. In summary, this study is of great significance to the future promotion and application of AC microgrids.

Seasonal variations in local catchments and connected rivers lead to complex hydrological behaviours in river-lake systems. Poyang Lake is a seasonally dynamic lake with frequent low levels in spring and autumn, which may be triggered by the local catchment and Yangtze River. Based on two typical years, a hydrodynamic model combined with long term hydrological observations was applied to quantify the spatiotemporal impacts of the local catchment and Yangtze River on spring and autumn low water levels in Poyang Lake. As a first attempt, this study explored the spatial differences of the two influences. Simulation results showed that the contributions of the catchment and the Yangtze River were approximately 70% and 30% in spring 1963, and 5% and 95% in autumn 2006, respectively. The area of catchment influence was mainly distributed in channels and southern floodplains, with relatively uniform water levels. The area impacted by the Yangtze River mainly spanned from the northern portion of the waterway to the central lake, with strong spatial variability. This study focused on two typical years; however, the results can be extended to explain common hydrological phenomena and improve future strategies of water resource management in this river-lake system.

Variations in a lake area constitute an important indicator of the modifications of the lake hydrology. This paper explores the inter-annual variations of the Poyang Lake area during the dry seasons occurring within the 1961 to 2010 period and further quantifies the severity of dryness recently endured during the 2000s. A physically based hydrodynamic model of Poyang Lake established the relation between the lake area and lake level. The lake area was calculated using the observed lake water level. Results indicated the average lake area in the dry seasons was 1,015 km2. There was a considerable inter-annual variation of the minimum lake area that varied from 702.8 km2 to 1,259.7 km2. Poyang Lake experienced the most severe dryness in the 2000s, resulting in an average lake area during 2001 to 2010 of 124 km2 less than that of the preceding period. During the dry seasons, the catchment of the river discharge is likely the primary cause of the changes in lake area. This study evaluated the inter-annual variations of the Poyang Lake over a period of 50 years. Our results may provide support for an integrated management of the lake-catchment system, securing the water supply.

Poyang lake floodplains are hydrologically complex and dynamic systems which exhibit dramatic intra-annual wetting and drying. The flow regime of the Yangtze River was previously known to play an important role in affecting Poyang Lake and its extremely productive floodplains (river−lake relationship). The recent severe declines and recessions in the lake are closely linked to the changed river−lake relationship, resulting in significant hydrological, ecological, and economic problems. This study aims to examine the spatiotemporal heterogeneity of the floodplain hydrodynamic behaviors with respect to impacts of the changed river−lake relationship, characterized by the lake water level, inundation area, and inundation duration based on a floodplain hydrodynamic model of Poyang Lake, and to further quantify the severity of dryness recently endured since 2000. Simulation results show that, in general, the current modified river−lake relationship is more likely to affect the hydrological seasonality of the floodplain system since 2000, relative to the flooding and drying cycles during past decades (1953−2000). The present hydrodynamic behaviors suffered significant change due to the greatest interference from the altered river−lake relationship, particularly for the falling period in October. On average, the floodplain water level and inundation duration decreased by 6 m and 12 days during October, respectively. Additionally, the highest monthly shrinkage rate in floodplain inundation shifted from the period of October−November to September−October, with the mean inundation area decreasing by around 50%, demonstrating an advanced and prolonged dry condition. The spatial responses of the hydrodynamics in the low-slope floodplains are most likely to be affected by the dynamic river−lake relationship, as expected. This study assessed the effects of the altered river−lake relationship on the hydrological regime of the Poyang Lake floodplains in terms of spatiotemporal distributions and changing processes for the periodic inundated behavior, which can support the relevant study of the subsequent ecological effects on the wetlands.

The performance of the event-related potential (ERP)-based brain−computer interface (BCI) declines when applying it into the real environment, which limits the generality of the BCI. The sound is a common noise in daily life, and whether it has influence on this decline is unknown. This study designs a visual-auditory BCI task that requires the subject to focus on the visual interface to output commands and simultaneously count number according to an auditory story. The story is played at three speeds to cause different workloads. Data collected under the same or different workloads are used to train and test classifiers. The results show that when the speed of playing the story increases, the amplitudes of P300 and N200 potentials decrease by 0.86 μV (p = 0.0239) and 0.69 μV (p = 0.0158) in occipital-parietal area, leading to a 5.95% decline (p = 0.0101) of accuracy and 9.53 bits/min decline (p = 0.0416) of information transfer rate. The classifier that is trained by the high workload data achieves higher accuracy than the one trained by the low workload if using the high workload data to test the performance. The result indicates that the sound could affect the visual ERP-BCI by increasing the workload. The large similarity of the training data and testing data is as important as the amplitudes of the ERP on obtaining high performance, which gives us an insight on how make to the ERP-BCI generalized.

Background/Aims: Integrin activation and lymphocyte migration to the vascular intima is a key event in early atherosclerosis. α4β7 integrin (LPAM-1) and its ligand, mucosal addressin cell adhesion molecule (MAdCAM-1) are known to play an important role in homing of activated lymphocytes to gut-associated lymphoid tissues. However, it is unclear whether α4β7 integrin is involved in the pathogenesis of atherosclerosis. Methods: The expressions of α4β7 integrin and its ligands in atherosclerosis plaques from 12 week high fat diet (HFD) fed ApoE-/- and C57BL/6 mice were examined using immunofluorescent and immunohistochemical assays, respectively. We also generated ApoE/β7 double deficient mice and compared atherosclerotic lesion development in β7+/+ApoE-/- and β7-/-ApoE-/- mice that were fed with HFD for 12 weeks. Results: We found an upregulation of α4β7 integrin and its ligands VCAM-1 and MAdCAM-1 at atherosclerosis plaques in Apolipoprotein E deficient (ApoE-/-) mice fed with HFD for 12 weeks. Over the 12 week HFD period, peripheral blood lymphocyte (PBL) expression of α4β7 integrin increased in parallel with aortic lesion size. A removal of α4β7 integrin by genetic deletion of the β7 chain in the ApoE-/- mouse resulted in a markedly decreased 12 week-HFD atherosclerotic plaque area. β7-/- ApoE-/- macrophages showed reduced acetylated and native LDL uptake and phagocytic activity, revealing possible roles for α4β7 at two distinct stages of macrophage dysfunction during atherogenesis. Finally, a reduced activity of integrin downstream signalling components focal adhesion kinase (FAK) and MAPK/ERK1/2 in macrophage indicates their possible engagement during α4β7 integrin signalling in atherosclerosis. Conclusions: Together our results reveal a critical role of α4β7 in diet-induced atherosclerosis in mouse.

In this paper, we evaluate the control performance of SSVEP (steady-state visual evoked potential)- and P300-based models using Cerebot-a mind-controlled humanoid robot platform. Seven subjects with diverse experience participated in experiments concerning the open-loop and closed-loop control of a humanoid robot via brain signals. The visual stimuli of both the SSVEP- and P300- based models were implemented on a LCD computer monitor with a refresh frequency of 60 Hz. Considering the operation safety, we set the classification accuracy of a model over 90.0% as the most important mandatory for the telepresence control of the humanoid robot. The open-loop experiments demonstrated that the SSVEP model with at most four stimulus targets achieved the average accurate rate about 90%, whereas the P300 model with the six or more stimulus targets under five repetitions per trial was able to achieve the accurate rates over 90.0%. Therefore, the four SSVEP stimuli were used to control four types of robot behavior; while the six P300 stimuli were chosen to control six types of robot behavior. Both of the 4-class SSVEP and 6-class P300 models achieved the average success rates of 90.3% and 91.3%, the average response times of 3.65 s and 6.6 s, and the average information transfer rates (ITR) of 24.7 bits/min 18.8 bits/min, respectively. The closed-loop experiments addressed the telepresence control of the robot; the objective was to cause the robot to walk along a white lane marked in an office environment using live video feedback. Comparative studies reveal that the SSVEP model yielded faster response to the subject's mental activity with less reliance on channel selection, whereas the P300 model was found to be suitable for more classifiable targets and required less training. To conclude, we discuss the existing SSVEP and P300 models for the control of humanoid robots, including the models proposed in this paper.