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In the context of global response to climate change and promoting energy transformation, the rapid popularization of electric vehicles and the widespread application of clean energy have become important components of modern power systems. However, the charging demand of electric vehicles brings new challenges to regional power grids, especially those that rely on clean energy, due to its uncertainty and randomness. This study examines the impact of EV charging demand on the control efficiency of clean energy-based regional power grids. Using real grid data and time-series simulation, we develop a dispatch optimization framework incorporating a master-slave game model based on wind power output distribution. We simulate EV charging patterns, renewable fluctuations, and uncertainties in user behavior and station availability. The results show that unmanaged charging increases peak load by up to 20%, while optimized strategies like Time-of-Use (TOU) pricing, Direct Load Control (DLC), and Vehicle-to-Grid (V2G) reduce the peak-valley gap by 15%, improve renewable energy consumption by 12%, and lower curtailment. These findings offer valuable insights for EV integration and clean energy planning in regional grids. The results show that at a 30% EV penetration rate, the peak charging demand may lead to a 20% increase in the regional grid load, and by optimizing the charging time, the peak-valley load difference can be reduced by 15%. In addition, a reasonable charging strategy can help improve the utilization rate of clean energy, maximize the consumption of wind power and photovoltaic power generation, and reduce dependence on fossil fuel power generation.

Mental health issues among high school students have become increasingly prominent. While physical activity is recognized for its ability to reduce symptoms of anxiety and depression, the underlying psychological mechanisms of this effect remain unclear. Social support and self-esteem, as key psychological resources, may mediate the relationship between physical activity and mental health. The aim of this research is to investigate the connection between physical activity and mental health among high school students with an emphasis on the mediating roles of social support and self-esteem. A random sample of 484 high school students (309 males and 175 females) was chosen to take part in an online survey. The survey utilized the PARS-3, the MSPSS, the RSES, the Adolescent Self-Rating Scale (Depression Dimension), and the SWLS. SPSS Statistics 26 with the PROCESS 4.0 macro was used to examine the chain mediation model. Physical activity was significantly positively correlated with life satisfaction and significantly negatively correlated with depression. Physical activity indirectly influenced mental health through social support or self-esteem, and this effect was further enhanced through the chain mediating roles of both factors (life satisfaction: β  = 0.0023, SE  = 0.0011, 95% CI [0.0002, 0.0047]; depression: β  = − 0.0022, SE  = 0.0005, 95% CI [− 0.0032, − 0.0014]). The findings emphasize the critical role of social support and self-esteem in the connection between physical activity and mental health. Improving social support and self-esteem can effectively increase the positive impact of physical activity. The findings provide valuable insights for designing more effective mental health interventions for high school students.

The circular RNA ciRS-7 has been reported to be involved in the pathogenesis of various tumors, including gastric and colorectal cancer. However, the role of ciRS-7 in esophageal squamous cell carcinoma (ESCC) remains unsolved. In this study, we found that the ciRS-7 expression was significantly upregulated in ESCC cancer tissues compared with matched normal tissues and associated with poor patient survival. Overexpression of ciRS-7 abrogated the tumor-suppressive roles of miR-7 including cell proliferation, migration and invasion in vitro as well as tumor growth and lung metastasis in vivo. Mechanistically, ciRS-7 functioned as the sponge of miR-7 and reactivated its downstream HOXB13-mediated NF-κB/p65 pathway. Conclusively, our findings demonstrate how ciRS-7 induces malignant progression of ESCC and that ciRS-7 may act as a novel prognostic marker and therapeutic target for this lethal disease.

Background Although immune cell therapy has long been used for treating solid cancer, its efficacy remains limited. Interferon (IFN)-producing killer dendritic cells (IKDCs) exhibit cytotoxicity and present antigens to relevant cells; thus, they can selectively induce tumor-associated antigen (TAA)-specific CD8 T cells and may be useful in cancer treatment. Various protocols have been used to amplify human IKDCs from peripheral sources, but the complexity of the process has prevented their widespread clinical application. Additionally, the induction of TAA-specific CD8 T cells through the adoptive transfer of IKDCs to immunocompromised patients with cancer may be insufficient. Therefore, we developed a method for generating an immune cell-based regimen, Phyduxon-T, comprising a human IKDC counterpart (Phyduxon) and expanded TAA-specific CD8 T cells. Methods Peripheral blood mononuclear cells from ovarian cancer patients were cultured with human interleukin (hIL)-15, hIL-12, and hIL-18 to generate Phyduxon-T. Then, its phenotype, cytotoxicity, and antigen-presenting function were evaluated through flow cytometry using specific monoclonal antibodies. Results Phyduxon exhibited the characteristics of both natural killer and dendritic cells. This regimen also exhibited cytotoxicity against primary ovarian cancer cells and presented TAAs, thereby inducing TAA-specific CD8 T cells, as evidenced by the expression of 4-1BB and IFN-γ. Notably, the Phyduxon-T manufacturing protocol effectively expanded IFN-γ-producing 4-1BB + TAA-specific CD8 T cells from peripheral sources; these cells exhibited cytotoxic activities against ovarian cancer cells. Conclusions Phyduxon-T, which is a combination of natural killer cells, dendritic cells, and TAA-specific CD8 T cells, may enhance the efficacy of cancer immunotherapy.

1. Biological invasions constitute a major component of human-induced environmental change and have become a world-wide problem threatening global biodiversity and incurring massive economic costs. Consequently, research on biological invasions proliferates, placing a major emphasis on species traits and habitat characteristics associated with successful invasion. Yet, the mechanisms underlying rapid spread and the resulting patterns remain largely unexplored. 2. Using data collected since 1980 and earlier at the county level all over China, we studied the contribution of potential dispersal vectors – railroads, rail stations, roads, general human activity, rivers and winds – to the spread of 17 of China's worst invasive plant species. Focusing on long-distance dispersal events, we calculated the minimal arrival speed for the first record of each species in each county. We also developed and applied a new method to account for observation bias due to the proximity to roads, using observational data of 776 native (non-invasive) plant species throughout China. 3. We found that human-related vectors are accountable for the vast spread of all 17 invasive plant species we examined. Spread patterns were characterized by long jumps of tens to hundreds of kilometres and extremely fast average spread rates of roughly 2–4 km per year, and a very broad range (0·1–128·2 km per year) with high variability between years. These rates are much higher than those expected from classic dispersal vectors such as water, wind or animals. Commonly used fat-tailed dispersal kernels did not fit the observed distribution of long jumps for any species. 4. Synthesis. We found pervasive empirical evidence for the overriding role of humans in the largescale spread of invasive plants from multiple taxa. The observed spread patterns differ significantly from those portrayed in the literature, emphasizing the need to develop new frameworks to explore large-scale spread in general and invasive spread in particular. With public data sets of invasive species observations becoming increasingly more available, the time is ripe to go beyond exploration of species traits and habitat suitability and to examine the actual patterns and the mechanisms of largescale invasive spread, even at a scale of thousands of kilometres over land.

High-precision time synchronization among nodes of the airborne-based pseudolite navigation augmentation positioning system (A-PNAS) is a crucial indicator for ensuring the accuracy of positioning services. Due to the flight characteristics and external factors’ influence, the airborne platform usually undergoes random motion. Therefore, the time-varying effect errors and Doppler effect errors will be introduced into the clock skew measurement results during the time-synchronous processing. In A-PNAS with meter-level positioning accuracy, the time synchronization accuracy (TSA) between nodes usually needs to be within 2 ns. These dynamic errors will have an impact on the TSA between nodes, which cannot be ignored. Based on the analysis of the principle of dynamic error generation and the available sensors, a multi-sensor combination method for correcting dynamic errors is proposed. This method calculates and corrects the dynamic errors based on the motion measurements from sensors. The simulation test results show that the degree of improvement in correcting dynamic errors by this method is basically close to 80%. It can effectively meet the requirements of high-precision time synchronization system and can provide an effective reference for the high-precision time synchronization processing of similar space-based platform collaborative systems.

Deep brain stimulation (DBS) is a promising therapy for treatment-resistant major depressive disorder (MDD). MDD involves the dysfunction of a brain network that can exhibit complex nonlinear neural dynamics in multiple frequency bands. However, current open-loop and responsive DBS methods cannot track the complex multiband neural dynamics in MDD, leading to imprecise regulation of symptoms, variable treatment effects among patients, and high battery power consumption. Here, we develop a closed-loop brain-computer interface (BCI) system of predictive neuromodulation for treating MDD. We first use a biophysically plausible ventral anterior cingulate cortex (vACC)-dorsolateral prefrontal cortex (dlPFC) neural mass model of MDD to simulate nonlinear and multiband neural dynamics in response to DBS. We then use offline system identification to build a dynamic model that predicts the DBS effect on neural activity. We next use the offline identified model to design an online BCI system of predictive neuromodulation. The online BCI system consists of a dynamic brain state estimator and a model predictive controller. The brain state estimator estimates the MDD brain state from the history of neural activity and previously delivered DBS patterns. The predictive controller takes the estimated MDD brain state as the feedback signal and optimally adjusts DBS to regulate the MDD neural dynamics to therapeutic targets. We use the vACC-dlPFC neural mass model as a simulation testbed to test the BCI system and compare it with state-of-the-art open-loop and responsive DBS treatments of MDD. We demonstrate that our dynamic model accurately predicts nonlinear and multiband neural activity. Consequently, the predictive neuromodulation system accurately regulates the neural dynamics in MDD, resulting in significantly smaller control errors and lower DBS battery power consumption than open-loop and responsive DBS. Our results have implications for developing future precisely-tailored clinical closed-loop DBS treatments for MDD.

Background Studies have shown that autophagy was closely involved in host defense against mycobacteria, and genetic variations in autophagy genes were related to susceptibility to multiple diseases. We conducted this observational study to analyze the role of autophagy related genes polymorphisms and promoter methylation in the pathogenesis of pulmonary tuberculosis (PTB). Methods Ten single nucleotide polymorphisms (SNPs) in four autophagy related genes ( ATG16L1 , ATG5 , IRGM , ULK1 ) were genotyped in 496 PTB patients and 498 controls using SNPscan technique, and the methylation levels of these genes were detected by MethylTarget technique in 98 PTB patients and 97 controls. Results We found that ATG16L1 gene rs2241880 GG genotype frequency was significantly increased in PTB patients than that in controls. While, no significant association was found between PTB risk and ATG16L1 rs6754677, ATG5 rs2245214, rs510432, IRGM rs1000113, rs10065172, rs12658239 , ULK1 rs7138581, rs9481, rs12297124 . Haplotype analysis showed that ATG16L1 GA haplotype was associated with the increased risk to PTB, and ATG5 CC haplotype was related to the decreased risk to PTB. Stratification analysis demonstrated that ATG16L1 rs6754677, IRGM rs1000113, rs10065172 polymorphism were associated with pulmonary infection, and ULK1 rs7138581 polymorphism was related to fever, drug-induced liver injury in PTB patients. Compared with controls, ATG16L1 methylation level was significantly decreased in PTB, while ATG5 , IRGM methylation levels were not significantly changed. Rs1000113, rs10065172, rs12658239 variants in IRGM had a major impact on IRGM methylation level in PTB patients. Conclusion ATG16L1 , ATG5 genes variation and ATG16L1 gene methylation level were associated with the genetic background of PTB, while IRGM , ULK1 genes variations showed no significant association with PTB.

Halyomorpha halys has been recognized as a global cross-border pest species. Along with well-established pheromone trapping approaches, there have been many attempts to utilize botanical odorant baits for field monitoring. Due to sensitivity, ecological friendliness, and cost-effectiveness for large-scale implementation, the selection of botanical volatiles as luring ingredients and/or synergists for H. halys is needed. In the current work, botanical volatiles were tested by olfactometer and electrophysiological tests. Results showed that linalool oxide was a potential candidate for application as a behavioral modifying chemical. It drove remarkable attractiveness toward H. halys adults in Y-tube assays, as well as eliciting robust electroantennographic responsiveness towards antennae. A computational pipeline was carried out to screen olfactory proteins related to the reception of linalool oxide. Simulated docking activities of four H. halys odorant receptors and two odorant binding proteins to linalool oxide and nerolidol were performed. Results showed that all tested olfactory genes were likely to be involved in plant volatile-sensing pathways, and they tuned broadly to tested components. The current work provides insights into the later development of field demonstration strategies using linalool oxide and its molecular targets.

All-solid-state sodium batteries (ASSSBs) are promising candidates for grid-scale energy storage. However, there are no commercialized ASSSBs yet, in part due to the lack of a low-cost, simple-to-fabricate solid electrolyte (SE) with electrochemical stability towards Na metal. In this work, we report a family of oxysulfide glass SEs (Na 3 PS 4− x O x , where 0 <  x  ≤ 0.60) that not only exhibit the highest critical current density among all Na-ion conducting sulfide-based SEs, but also enable high-performance ambient-temperature sodium-sulfur batteries. By forming bridging oxygen units, the Na 3 PS 4− x O x SEs undergo pressure-induced sintering at room temperature, resulting in a fully homogeneous glass structure with robust mechanical properties. Furthermore, the self-passivating solid electrolyte interphase at the Na|SE interface is critical for interface stabilization and reversible Na plating and stripping. The new structural and compositional design strategies presented here provide a new paradigm in the development of safe, low-cost, energy-dense, and long-lifetime ASSSBs. Single sodium-ion solid electrolyte that meets the requirements of practical applications is difficult to design. Here, the authors show how kinetic stability via the creation of a self-passivating solid electrolyte interphase allows a homogenous glass solid electrolyte to exhibit remarkable electrochemical stability with sodium metal.