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The Regional Comprehensive Economic Partnership (RCEP) has created favorable conditions for building deeply integrated agricultural value chains (AVC) in Asia-Pacific. Based on the RCEP agreement, this study employed the global trade analysis project (GTAP) model to evaluate the impact of RCEP on AVC of member countries in terms of time, tariff reduction, and reduction of non-tariff barriers (NTB). The results indicate that (1) the implementation of RCEP boosts the value-added to agricultural exports for most member countries, particularly in competitive industries; (2) the increase in domestic production and processing capacity, reflected in domestic value-added (DVA), is the primary factor driving the rise in the value-added of agricultural exports across various industries of member countries; (3) RCEP enhances the participation of most regional countries in AVC, with varying impacts on AVC positioning, thereby fostering regional AVC development; and (4) RCEP has a positive effect on AVC indicators both in the short and long term, with the effect becoming more pronounced over time. Additionally, reducing NTB enhances the positive effects of tariff reductions on AVC indicators. Based on the analyses, the following recommendations are proposed: (1) Leverage the development opportunities arising from RCEP implementation to enhance the agricultural DVA; (2) capitalize on cooperative opportunities created by RCEP to build cohesive regional AVC; and (3) prioritize the effective implementation of RCEP’s high-quality rules.

In this work, the flow behaviors and microstructure evolution of a solid solution Ti55511 alloy deformed in the two-phase region are investigated by hot compression experiments. Subsequently, The spheroidization mechanisms of α phases and the refinement mechanism of β matrix are analyzed. The alloy exhibits obvious work hardening (WH) and flow softening characteristics. The secondary α phases gradually precipitate and spheroidize, while the primary α phases dissolute above the solution temperature or coarsen when the alloy is deformed below the solution temperature. Meanwhile, the β matrix undergoes continuous dynamic recrystallization (CDRX) behavior. The increase of deformation amounts promotes the simultaneous precipitation and spheroidization of lamellar α phases. Raising deformation temperature inhibits the precipitation and spheroidization of lamellar α phases. However, the maximum values of precipitated and spheroidized lamellar α phase occur at 0.01 s−1. Higher strain rate can promote CDRX of β matrix between 1003 and 1033 K, but inhibit it between 1063 and 1123 K, indicating differences in the dynamic recrystallization (DRX) mechanism at different temperature regions. A unified constitutive model based on physical mechanisms is proposed. The model takes into account both WH and grain boundary strengthening effects by coupling all parts of phases. Furthermore, the dynamic softening, including dynamic recovery (DRV), spheroidization of lamellar α phases, and CDRX of the β matrix, are also considered. Material constants are determined using a genetic algorithm (GA), and the experimental data align well with the predicted data. Finally, process parameters are optimized based on the model to achieve favorable microstructures.

Abstract Background/Aims Chemotherapy resistance in liver cancer is a major clinical issue, with CD147 playing a vital role in this process. However, the specific mechanisms underlying these processes remain largely unknown. This study investigates how CD147 internalization leads to cytoprotective autophagy, contributing to chemotherapy resistance in hepatocellular carcinoma (HCC). Methods Utilizing bioinformatics methods for KEGG pathways enrichment and screening key molecules associated with chemotherapy resistance through analyses of GEO and TCGA databases. An overexpression/knockdown system was used to study how CD147 internalization leads to autophagy in vitro and in vivo. The process was observed using microscopes, and molecular interactions and autophagy flux were analyzed. Analyzing the internalization of CD147 intracellular domains and the interaction with G3BP1 in clinical chemotherapy recurrence HCC tissues by immunohistochemistry, tissue immunofluorescence, and mass spectrometry. A tumor xenograft mice model was used to study cytoprotective autophagy induced by CD147 and test the effectiveness of combining cisplatin with an autophagy inhibitor in nude mice models. Results In our study, we identified the tumor-associated membrane protein CD147, which implicated in chemoresistance lysosome pathways, by evaluating its protein degree value and betweenness centrality using Cytoscape. Our findings revealed that CD147 undergoes internalization and interacts with G3BP1 following treatment with cisplatin and methyl-β-cyclodextrin, forming a complex that is transported to lysosomes via Rab7A. Notably, higher doses of cisplatin enhanced CD147-mediated lysosomal transport while concurrently inhibiting SG assembly. The CD147-G3BP1 complex additionally inhibits mTOR activity, promoting autophagy and augmenting chemoresistance in hepatoma cells. In vivo studies investigations and analyses of clinical samples revealed that elevated internalization of CD147 is associated with chemotherapy recurrence in liver cancer and the maintenance of stem cells. Mice experiments found that the combined administration of cisplatin and hydroxychloroquine enhanced the efficacy of treatment. Conclusions This study reveals that CD147 internalization and CD147-G3BP1 complex translocation to lysosomes induce cytoprotective autophagy, reducing chemotherapy sensitivity by suppressing mTOR activity. It is also shown that chemotherapy drugs combined with autophagy inhibitors can improve the therapeutic effect of cancer, providing new insights into potential targeted therapeutic approaches in treating HCC.

The imbalanced allocation of maternal resources to eggs and nestlings may significantly impact the phenotype and fitness of offspring. Moreover, anthropogenic metal pollution has been reported to exert adverse effects on avian offspring. Therefore, we herein evaluated the relationships among offspring characteristics, asymmetric sibling rivalry, and the resulting offspring phenotype in a small passerine bird, Tree Sparrow (Passer montanus), at a polluted site (Baiyin, BY) and a relatively unpolluted site (Liujiaxia, LJX). By initiating incubation before the completion of clutch, asymmetric sibling rivalry might create a core and marginal offspring within the brood. In this study, lower egg mass, fewer core offspring, and more marginal offspring were found at the polluted site. Although eggshell speckling and coloration were relatively similar between the two sites, higher eggshell spotting coverage ratio and lower eggshell lightness (L∗) and hue (h°) were observed in core eggs than in marginal eggs at the unpolluted site. The clutch size had a positive relationship with egg mass at the polluted site and with brood size at hatching at the unpolluted site. The differences in egg measurements across the laying orders in the samples were relatively large for larger clutch sizes. The core and marginal egg masses had a significant positive effect on the size of early core nestlings and late marginal nestlings at the unpolluted site. Fledgling rate was significantly positively related to the incubation period and nestling period, while negative relationship with mean spotting coverage ratio was found at the polluted site. Marginal nestlings at the polluted site showed a higher mortality rate. Overall, although asymmetric sibling competition strongly determines the variation of marginal offspring size, the effect is less dramatic in metal-polluted environments, providing some respite to wild birds that survive pollution-induced stress.

BackgroundThe application of bioprinted hydrogels in the field of bone regeneration is garnering increasing attention. The objective of this study is to provide a comprehensive overview of the current research status, hotspots and research directions in this field through bibliometric methods, and to predict the development trend of this field.MethodsA search was conducted on 27 December 2024, for papers published on the Web of Science from 2010 to 2025. We used the bibliometrix package in the software program R to analyze the retrieved data and VOSviewer and CiteSpace to visualize hotspots and research trends in bioprinted hydrogels for bone regeneration.ResultsWe identified and reviewed 684 articles published in this field between 2010 and 2025. A total of 811 institutions and 1,166 researchers from 41 countries/regions contributed to these publications. Among them, China led in terms of the number of articles published, single-country publications (SCP), and multi-country publications (MCP). Our bibliometric-based visualization analysis revealed that the mechanical properties and osteogenic differentiation capacity of biomaterials have been a focal research topic over the past decade, while emerging research has also concentrated on the in vitro fabrication of stem cells for bone regeneration and osteogenic differentiation, particularly the precise application of in situ stem cell-loaded bioprinted organoids.ConclusionThis study provides an in-depth analysis of the research trajectory in the application of bioprinted hydrogels for bone regeneration. The number of research papers in this field is increasing annually, and the main research hotspots include bone regeneration, 3D printing, scaffolds, and hydrogels. Future research directions may focus on gelatin, additive manufacturing, and growth factors. Additionally, international collaboration is essential to enhance the effectiveness of bioprinted hydrogels in bone regeneration applications.

Mushroom poisoning, predominantly caused by α-amanitin, is a critical food safety concern in worldwide, with severe cases leading to hepatotoxicity and fatalities. This study delves into the hepatotoxic effects of α-amanitin, focusing on the NLRP3 inflammasome and PPAR-γ's regulatory role in inflammation. In vitro studies with L-02 cells showed that α-amanitin reduces cell viability and triggers NLRP3 inflammasome activation, increasing NF-κB phosphorylation and pro-inflammatory cytokines IL-18 and IL-1β. The NLRP3 inhibitor MCC950 mitigated these effects without impacting NF-κB. Conversely, PPAR-γ knockdown intensified the inflammatory response. In vivo, α-amanitin induced dose-dependent liver injury in mice, evident by elevated serum ALT and AST, and histological liver damage. MCC950 pretreatment offered protection against hepatotoxicity, while PPAR-γ inhibition with GW9662 worsened the condition. The study highlights the interplay between α-amanitin, NLRP3, and PPAR-γ in hepatotoxicity, proposing potential therapeutic targets for mushroom poisoning-induced liver diseases.

Abstract In recent years, researchers have taken the many-objective optimization algorithm, which can optimize 5, 8, 10, 15, 20 objective functions simultaneously, as a new research topic. However, the current research on many-objective optimization technology also encounters some challenges. For example: Pareto resistance phenomenon, difficult diversity maintenance. Based on the above problems, this paper proposes a many-objective evolutionary algorithm based on three states (MOEA/TS). Firstly, a feature extraction operator is proposed. It can extract the features of the high-quality solution set, and then assist the evolution of the current individual. Secondly, based on Pareto front layer, the concept of “individual importance degree” is proposed. The importance degree of an individual can reflect the importance of the individual in the same Pareto front layer, so as to further distinguish the advantages and disadvantages of different individuals in the same front layer. Then, a repulsion field method is proposed. The diversity of the population in the objective space is maintained by the repulsion field, so that the population can be evenly distributed on the real Pareto front. Finally, a new concurrent algorithm framework is designed. In the algorithm framework, the algorithm is divided into three states, and each state focuses on a specific task. The population can switch freely among these three states according to its own evolution. The MOEA/TS algorithm is compared with 7 advanced many-objective optimization algorithms. The experimental results show that the MOEA/TS algorithm is more competitive in many-objective optimization problems.

In order to explore the weldability and widen the applicability of high entropy alloys (HEAs), dissimilar friction stir lap welding of pure copper and Al0.1CoCrFeNi alloy was investigated in this research. The results indicate that a sound dissimilar weld without tunnels and voids is produced, where a ∼20 μm thick interfacial layer is evident at the Cu-HEA interface. The lap joint is fractured at the upper Cu sheet rather than the lap surface during tensile shear test, suggesting an effective bonding of the dissimilar materials. The lap weld roughly consists of three layers along the plate thickness direction, i.e. welds of Cu, HEA and Cu-HEA interface, respectively. The interface of weld, which has experienced the most severe Cu-HEA interaction during welding, is characterized by uniformly distributed and highly recrystallized ultra-fine grains (∼0.79 μm). Meanwhile, intermetallic compounds particles (Al13Cr2 and Al13Co4) ranging in size of 150∼400 nm are generated at the fine grain boundaries. Fast diffusion of Al, Cr and Co elements and easy segregation of these elements during welding result in the formation of the particles. The sufficient DDRX and the pinning effect of particles are responsible for the formation of ultra-fine grains in the weld interface. The present study lays a theoretical foundation for the joining of conventional Cu and the multi-component HEA, which contributes to the improvement of HEA availability in the field of manufacturing industry.

BackgroundIt is challenging to predict the occurrence of non-suicidal self-injury (NSSI) among adolescents over short periods. Moreover, the predictive value of indices for NSSI remains elusive. Thus, this study aimed to identify predictors of NSSI within 6 months among adolescents after psychiatric hospitalization by establishing a risk assessment model.MethodsA total of 632 high-risk participants were included in this study. The distribution characteristics of adolescent NSSI were initially assessed through a cross-sectional survey, following which risk factors were identified using logistic regression analysis. The risk score method was then used to construct a 6-month risk assessment model for NSSI. Lastly, the predictive effect of the model was evaluated by indicators such as the area under the receiver operating characteristic (ROC) curve and the positive predictive value.ResultsAfter 6 months, 412 cases of NSSI were identified. According to the logistic regression model, the frequency of relapses, medication status, and NSSI history were identified as influencing factors. Higher scores on the Impulsive Behavior Scale and Pittsburgh Sleep Quality Index were associated with a higher risk of NSSI. Conversely, higher scores on the Pain and Belief Perception Scale were correlated with a lower risk of NSSI. Moreover, the area under the ROC curve for the predictive model was 0.9989, with a 95% confidence interval of (0.9979, 0.9999), highlighting its high predictive ability and accuracy. The predictive model was validated using 78 patients, yielding an area under the ROC curve of 0.9703 and a 95% confidence interval of (0.9167, 0.9999), demonstrating outstanding predictability.ConclusionThese results collectively showed that the predictive model could accurately predict adolescent NSSI. Thus, the model’s primary variables may be applied to predict the risk of NSSI in the clinical setting.

Summary: Background: Obesity represents a major global health challenge with important clinical implications. Despite its recognized importance, the global disease burden attributable to high body mass index (BMI) remains less well understood. Methods: We systematically analyzed global deaths and disability-adjusted life years (DALYs) attributable to high BMI using the methodology and analytical approaches of the Global Burden of Disease Study (GBD) 2021. High BMI was defined as a BMI over 25 kg/m2 for individuals aged ≥20 years. The Socio-Demographic Index (SDI) was used as a composite measure to assess the level of socio-economic development across different regions. Subgroup analyses considered age, sex, year, geographical location, and SDI. Findings: From 1990 to 2021, the global deaths and DALYs attributable to high BMI increased more than 2.5-fold for females and males. However, the age-standardized death rates remained stable for females and increased by 15.0% for males. Similarly, the age-standardized DALY rates increased by 21.7% for females and 31.2% for males. In 2021, the six leading causes of high BMI-attributable DALYs were diabetes mellitus, ischemic heart disease, hypertensive heart disease, chronic kidney disease, low back pain and stroke. From 1990 to 2021, low-middle SDI countries exhibited the highest annual percentage changes in age-standardized DALY rates, whereas high SDI countries showed the lowest. Interpretation: The worldwide health burden attributable to high BMI has grown significantly between 1990 and 2021. The increasing global rates of high BMI and the associated disease burden highlight the urgent need for regular surveillance and monitoring of BMI. Funding: National Natural Science Foundation of China and National Key R&D Program of China.

Engaging in regular exercise and physical activity contributes to delaying the onset of cardiovascular diseases (CVDs). However, the physiological mechanisms underlying the benefits of regular exercise or physical activity in CVDs remain unclear. The disruption of mitochondrial homeostasis is implicated in the pathological process of CVDs. Exercise training effectively delays the onset and progression of CVDs by significantly ameliorating the disruption of mitochondrial homeostasis. This includes improving mitochondrial biogenesis, increasing mitochondrial fusion, decreasing mitochondrial fission, promoting mitophagy, and mitigating mitochondrial morphology and function. This review provides a comprehensive overview of the benefits of physical exercise in the context of CVDs, establishing a connection between the disruption of mitochondrial homeostasis and the onset of these conditions. Through a detailed examination of the underlying molecular mechanisms within mitochondria, the study illuminates how exercise can provide innovative perspectives for future therapies for CVDs.

Abstract Laser tracers are a three-dimensional coordinate measurement system that are widely used in industrial measurement. We propose a geometric error identification method based on multi-station synchronization laser tracers to enable the rapid and high-precision measurement of geometric errors for gantry-type computer numerical control (CNC) machine tools. This method also improves on the existing measurement efficiency issues in the single-base station measurement method and multi-base station time-sharing measurement method. We consider a three-axis gantry-type CNC machine tool, and the geometric error mathematical model is derived and established based on the combination of screw theory and a topological analysis of the machine kinematic chain. The four-station laser tracers position and measurement points are realized based on the multi-point positioning principle. A self-calibration algorithm is proposed for the coordinate calibration process of a laser tracer using the Levenberg–Marquardt nonlinear least squares method, and the geometric error is solved using Taylor’s first-order linearization iteration. The experimental results show that the geometric error calculated based on this modeling method is comparable to the results from the Etalon laser tracer. For a volume of 800 mm × 1000 mm × 350 mm, the maximum differences of the linear, angular, and spatial position errors were 2.0 μm, 2.7 μrad, and 12.0 μm, respectively, which verifies the accuracy of the proposed algorithm. This research proposes a modeling method for the precise measurement of errors in machine tools, and the applied nature of this study also makes it relevant both to researchers and those in the industrial sector.

Abstract Objective This study aimed to identify candidate loci and genes related to sleep disturbances in depressed individuals and clarify the co-occurrence of sleep disturbances and depression from the genetic perspective. Methods The study subjects (including 58,256 self-reported depressed individuals and 6,576 participants with PHQ-9 score ≥ 10, respectively) were collected from the UK Biobank, which were determined based on the Patient Health Questionnaire (PHQ-9) and self-reported depression status, respectively. Sleep related traits included chronotype, insomnia, snoring and daytime dozing. Genome-wide association studies (GWASs) of sleep related traits in depressed individuals were conducted by PLINK 2.0 adjusting age, sex, Townsend deprivation index and 10 principal components as covariates. The CAUSALdb database was used to explore the mental traits associated with the candidate genes identified by the GWAS. Results GWAS detected 15 loci significantly associated with chronotype in the subjects with self-reported depression, such as rs12736689 at RNASEL (P = 1.00 × 10− 09), rs509476 at RGS16 (P = 1.58 × 10− 09) and rs1006751 at RFX4 (P = 1.54 × 10− 08). 9 candidate loci were identified in the subjects with PHQ-9 ≥ 10, of which 2 loci were associated with insomnia such as rs115379847 at EVC2 (P = 3.50 × 10− 08), and 7 loci were associated with daytime dozing, such as rs140876133 at SMYD3 (P = 3.88 × 10− 08) and rs139156969 at ROBO2 (P = 3.58 × 10− 08). Multiple identified genes, such as RNASEL, RGS16, RFX4 and ROBO2 were reported to be associated with chronotype, depression or cognition in previous studies. Conclusion Our study identified several candidate genes related to sleep disturbances in depressed individuals, which provided new clues for understanding the biological mechanism underlying the co-occurrence of depression and sleep disorders.

Abstract Background Knee osteoarthritis (KOA) characterized by degeneration of knee cartilage and subsequent bone hyperplasia is a prevalent joint condition primarily affecting aging adults. The pathophysiology of KOA remains poorly understood, as it involves complex mechanisms that result in the same outcome. Consequently, researchers are interested in studying KOA and require appropriate animal models for basic research. Chinese herbal compounds, which consist of multiple herbs with diverse pharmacological properties, possess characteristics such as multicomponent, multipathway, and multitarget effects. The potential benefits in the treatment of KOA continue to attract attention. Purpose This study aims to provide a comprehensive overview of the advantages, limitations, and specific considerations in selecting different species and methods for KOA animal models. This will help researchers make informed decisions when choosing an animal model. Methods Online academic databases (e.g., PubMed, Google Scholar, Web of Science, and CNKI) were searched using the search terms “knee osteoarthritis,” “animal models,” “traditional Chinese medicine,” and their combinations, primarily including KOA studies published from 2010 to 2023. Results Based on literature retrieval, this review provides a comprehensive overview of the methods of establishing KOA animal models; introduces the current status of advantages and disadvantages of various animal models, including mice, rats, rabbits, dogs, and sheep/goats; and presents the current status of methods used to establish KOA animal models. Conclusion This study provides a review of the animal models used in recent KOA research, discusses the common modeling methods, and emphasizes the role of traditional Chinese medicine compounds in the treatment of KOA.

Reducing carbon emissions in crop production not only aligns with the goal of high-quality agricultural development but also contributes to achieving the “dual carbon goals”. Based on panel data from 31 provinces in China between 2010 and 2019, this paper explores the impact of Agricultural Socialized Services on carbon emissions in China’s crop production. Utilizing the classical IPCC carbon emission calculation model and spatial econometrics models, this study analyzes the temporal and spatial distribution characteristics of crop production carbon emissions and their driving factors, with a particular focus on evaluating the role of Agricultural Socialized Services in reducing carbon emissions in crop production. The empirical results reveal a “reverse U-shaped” curve for carbon emissions in crop production from 2010 to 2019, with a peak in 2015. Agricultural Socialized Services significantly reduced carbon emissions in crop production, especially in terms of emissions reductions from fertilizer and pesticide use, although the impact on other carbon sources such as plastic mulch, diesel, and tillage was relatively limited. Furthermore, Agricultural Socialized Services exhibited significant spatial spillover effects, effectively reducing local carbon emissions and generating positive carbon reduction effects in neighboring regions through cross-regional services. Based on these findings, the paper suggests improving the Agricultural Socialized Services system according to regional conditions to fully leverage its positive role in reducing carbon emissions in crop production. It also advocates accelerating the innovation of low-carbon agricultural technologies, encouraging farmers’ participation, and utilizing the organizational advantages of village collectives to jointly promote the development of Agricultural Socialized Services and achieve carbon reduction goals.

Summary: Time-restricted eating (TRE) is a promising obesity management strategy, but weight-loss efficacy varies among participants, and the underlying mechanism is unclear. The study aimed to investigate the role of gut microbiota in weight-loss response during long-term TRE intervention. We analyzed data from 51 obese adults in a 12-month TRE program, categorizing them into distinct weight loss groups (DG) and moderate weight loss groups (MG) based on their TRE responses. Shotgun metagenomic sequencing analysis revealed a significant increase in species closely associated with weight loss effectiveness and metabolic parameter changes in the DG group. Pathways related to fatty acid biosynthesis, glycogen biosynthesis, and nucleotide metabolism were reduced in the DG group and enhanced in the MG group. Next, we identified nine specific species at baseline that contributed better responses to TRE intervention and significant weight loss. Collectively, gut microbiota contributes to responsiveness heterogeneity in TRE and can predict weight-loss effectiveness.

IntroductionScutellariae Radix (SR), derived from the root of Scutellaria baicalensis Georgi, is a traditional Chinese medicine (TCM) for clearing heat and cooling blood. It has been used as a traditional herbal medicine and is popular as a functional food in Asian countries today.MethodsIn this study, UPLC-Q-TOF-MS was first employed to identify the chemical components in the ethanol extract of SR. Then, the extraction process was optimized using star point design-response surface methodology. Fingerprints of different batches and processed products were established, and chemical markers were screened through a combination of various artificial neural network models. Finally, network pharmacology and molecular simulation techniques were utilized for verification to determine the quality markers.ResultsA total of 35 chemical components in SR were identified, and the optimal extraction process was determined as follows: ultrasonic extraction with 80% methanol at a ratio of 120:1 for 70 minutes, with a soaking time of 30 minutes. Through discriminant analysis using various artificial neural network models, the samples of SR could be classified into two categories based on their growth years: Kuqin (dried roots of older plants) and Ziqin (roots of younger plants). Moreover, the samples within each category could be further clustered according to their origins. The four different processed products of SR could also be distinguished separately. Finally, through the integration of network pharmacology and molecular simulation techniques, it was determined that baicalin, baicalein, wogonin, norwogonin, norwogonin-8-O-glucuronide, skullcapflavone II, hispidulin, 8, 8"-bibaicalein, and oroxylin A-7-O-beta-D-glucuronide could serve as quality markers for SR.DiscussionThe primary factors affecting the quality of SR were its growth years. The geographic origin of SR was identified as a secondary factor affecting its quality. Processing also had a significant impact on its quality. The selected quality markers have laid the foundation for the quality control of SR, and this research strategy also provides a research paradigm for improving the quality of TCM.

Abstract Rolling bearings are essential parts in machine equipment and detecting damage in the early stage is crucial for ensuring the safe production and machine life. However, it is difficult to extract weak fault features under strong background noise, discrete harmonic frequency interference and non‐stationary service conditions. This investigation proposes a hybrid fault diagnosis approach utilizing transient structure‐optimal variational mode decomposition (TS‐OVMD) and adaptive group sparse coding (AGSC) for addressing the formidable problem. According to the singular value structure between transient signal and the interference signal, this work investigates the singular value shrinkage (SVS) technique to adaptively obtain the independent components number. Then, we present a transient structure measure (TSM) to adaptively optimize the balance factor. This measure index systematically quantifies the typical characteristics of the bearing fault signal, which can maximize the fault information representation and effectively reduces the useful information loss caused by improper selection of VMD parameters. Finally, a sparse coding model called AGSC is furthermore designed to enhance the fault impulses readability and suppress residual noise based on the sparsity within group property and the TSM. The proposed approach is verified using experimental data and is found to be superiority comparison with the state‐of‐the‐art method.

Abstract In recent years, biometrics has been the most popular style of personal identification. The finger vein is an intrinsic and stable trait, and with the ability to detect liveness, it receives academic and industry attention. However, convolution neural networks (CNNs) based finger vein recognition generally can only cover a small input region by using small kernels. Hence, the performance is poor, facing low-quality finger vein images. It is a challenge to effectively use the critical feature of multi-scale for finger veins. In this article, we extract multi-scale features via pyramid convolution. We propose scale attention, namely, the scale-aware attention (SA) module, which enables dynamic adjustment of the weight of each scale to information aggregation. Utilize the complementation of different scale detail features to enhance the discriminativeness of extracted features, thus improving the finger vein recognition performance. In order to verify the present method’s efficiency, we carried out experiments on two public data sets and one internal data, and the wide range of experimental results proves the proposed method’s effectiveness.

Abstract Background Radiomics analysis of orbital magnetic resonance imaging (MRI) shows preliminary potential for intravenous glucocorticoid (IVGC) response prediction of thyroid eye disease (TED). The current region of interest segmentation contains only a single organ as extraocular muscles (EOMs). It would be of great value to consider all orbital soft tissues and construct a better prediction model. Methods In this retrospective study, we enrolled 127 patients with TED that received 4·5 g IVGC therapy and had complete follow-up examinations. Pre-treatment orbital T2-weighted imaging (T2WI) was acquired for all subjects. Using multi-organ segmentation (MOS) strategy, we contoured the EOMs, lacrimal gland (LG), orbital fat (OF), and optic nerve (ON), respectively. By fused-organ segmentation (FOS), we contoured the aforementioned structures as a cohesive unit. Whole-orbit radiomics (WOR) models consisting of a multi-regional radiomics (MRR) model and a fused-regional radiomics (FRR) model were further constructed using six machine learning (ML) algorithms. Results The support vector machine (SVM) classifier had the best performance on the MRR model (AUC = 0·961). The MRR model outperformed the single-regional radiomics (SRR) models (highest AUC = 0·766, XGBoost on EOMs, or LR on OF) and conventional semiquantitative imaging model (highest AUC = 0·760, NaiveBayes). The application of different ML algorithms for the comparison between the MRR model and the FRR model (highest AUC = 0·916, LR) led to different conclusions. Conclusions The WOR models achieved a satisfactory result in IVGC response prediction of TED. It would be beneficial to include more orbital structures and implement ML algorithms while constructing radiomics models. The selection of separate or overall segmentation of orbital soft tissues has not yet attained its final optimal result.

Preeclampsia (PE) is a pregnancy-related disorder associated with serious complications. Its molecular mechanisms remain undefined; hence, we aimed to identify molecular subgroups of patients with PE using bioinformatics to aid treatment strategies. R software was used to analyze gene expression data of 130 patients with PE and 138 healthy individuals from the Gene Expression Omnibus database. Patients with PE were divided into two molecular subgroups using the unsupervised clustering learning method. Clinical feature analysis of subgroups using weighted gene co-expression network analysis showed that the patients in subgroup I were primarily characterized by early onset of PE, severe symptoms at disease onset, and induced labor as the main delivery method. Patients in subgroup II primarily exhibited late PE onset, relatively mild symptoms, and natural delivery as the main delivery method. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses revealed that the significant enrichment of calcium ion channels in subgroup II indicated the potential efficacy of calcium antagonists and magnesium sulfate therapy. In conclusion, the establishment of PE molecular subgroups can aid in diagnosing and treating PE.

IntroductionArrhythmia is an important indication of underlying cardiovascular diseases (CVD) and is prevalent worldwide. Accurate diagnosis of arrhythmia is crucial for timely and effective treatment. Electrocardiogram (ECG) plays a key role in the diagnosis of arrhythmia. With the continuous development of deep learning and machine learning processes in the clinical field, ECG processing algorithms have significantly advanced the field with timely and accurate diagnosis of arrhythmia.MethodsIn this study, we combined the wavelet time-frequency maps with the novel Swin Transformer deep learning model for the automatic detection of cardiac arrhythmias. In specific practice, we used the MIT-BIH arrhythmia dataset, and to improve the signal quality, we removed the high-frequency noise, artifacts, electromyographic noise and respiratory motion effects in the ECG signals by the wavelet thresholding method; we used the complex Morlet wavelet for the feature extraction, and plotted wavelet time-frequency maps to visualise the time-frequency information of the ECG; we introduced the Swin Transformer model for classification and achieve high classification accuracy of ECG signals through hierarchical construction and self attention mechanism, and combines windowed multi-head self-attention (W-MSA) and shifted window-based multi-head self-attention (SW-MSA) to comprehensively utilise the local and global information.ResultsTo enhance the confidence of the experimental results, we evaluated the performance using intra-patient and inter-patient paradigm analyses, and the model classification accuracies reached 99.34% and 98.37%, respectively, which are better than the currently available detection methods.DiscussionThe results reveal that our proposed method is superior to currently available methods for detecting arrhythmia ECG. This provides a new idea for ECG based arrhythmia diagnosis.

Soybean production, integral to sustainable agriculture and reliant on imports, faces vulnerability to international risk factors impacting domestic food security. The 2021 Central Rural Work Conference advocated strategic adjustments for sustainable soybean production amidst resource constraints, trade conflicts, and the lingering impact of COVID-19. This study scrutinizes the developmental framework of China’s soybean industry within current domestic policies. This paper uses the soybean sown area and soybean production in each province of China from 1995 to 2020 to measure China’s soybean concentration, production layout, and comparative advantage of regional scale, to analyze in depth the overall situation of China’s soybean production as well as the differences between regions, and to pave the way for the subsequent soybean production forecast. Further, taking the domestic soybean supply and demand situation in China in 2020 as the base period, while considering the growth values of soybean production under different scenarios, the potential forecasting model is utilized to estimate China’s soybean production under different scenarios. The results show that, in terms of inter-annual variability, revealing an upward trajectory from 1995 to 2020, with a shift to major soybean producing areas, notably in the northeast and the Huanghe-Huaihe-Haihe area. From inter-provincial changes, Soybean production on the left and right sides of the “Hu-Huanyong line” has significant heterogeneity; specifically, east of the “Hu-Huanyong line,” soybean production advantages are more obvious. Additionally, the study considered the actual planting situation of soybeans and envisaged two scenarios of compound planting and strip planting. The soybean production range in 2030 is expected to be 20.73–22.32 million tons and 21.15–27.55 million tons, with self-sufficiency rates varying from 18.57 to 19.98% and 18.95 to 24.68%, respectively. The research aims to provide a comprehensive understanding of China’s soybean industry and its potential trajectories, employing a model combining historical trends, policy analysis, and technological advancements. Results suggest a promising future with strategic adjustments in planting structures. Recommendations emphasize policymakers’ prioritization of technological investments and sustainable planting practices to achieve projected production targets. Policy interventions must address challenges tied to resource limitations, trade conflicts, and the ongoing COVID-19 effects, ensuring soybean industry resilience.

Choroid plexus papilloma (CPP) is a rare benign intracranial tumor origin that predominantly manifests in the lateral ventricle in children, accounting for 0.3%–0.6% of all primary intracranial tumors. It is extremely rare to have the CPP in the trigone of the lateral ventricle through the contralateral posterior interhemispheric transfalcine transprecuneus approach (PITTA). Herein, we report this rare case. A 7-year-old girl presented with headache. Magnetic resonance imaging of the brain showed periatrial lesions, and histopathological examination confirmed CPP (WHO grade I). The contralateral PITTA is a safe, effective, reasonable, and appropriate for some lesions in the trigone of the lateral ventricle. It provides a wider surgical angle (especially for the lateral extension) and reduces the risk of disturbance of the optic radiation compared with the conventional approaches. The use of multiple modern neurosurgical techniques, including interventional embolization, intraoperative navigation, microscope, and electrophysiological monitoring, make the procedure much easier and more accurate, and the neuroendoscope adds to the visualization of the microscope and can reduce surgical complications.

Aluminum alloys are widely used in the fields like aerospace, automotive and manufacturing industries due to their excellent comprehensive performances and low mass and density. With the rapid development of the industries above mentioned, the requirements of aluminum alloys properties are increasingly raised. Therefore, it is especially significant to choose reasonable treatment methods to upgrade the related performances of aluminum alloys. As a green, low-cost and no pollution new heat treatment process, deep cryogenic treatment (DCT) can significantly improve the microstructures and performances of the metals with little variation in their sizes and shapes. The present paper summarizes the characteristics and mechanisms of the DCT influence on the structure-performance evolutions of aluminum alloys. When the DCT parameters are selected appropriately, ultra-low temperature can lead to refinement and preferred orientation of grains, increase of dislocation density and optimization of secondary phase distribution for aluminum alloys. Besides, mechanical properties, residual stress, corrosion resistance, wear resistance and electrical conductivity of aluminum alloys can be considerably improved due to the various microstructure evolutions induced by DCT. The present paper not only concludes major findings of the previous researches but also suggests future recommendations for aluminum alloys processed by DCT.

Aiming at the problems of the basic ant colony algorithm in path planning, such as long convergence time, poor global path quality and not being suitable for dynamic environments and unknown environments, this paper proposes a path planning method for mobile robots in complex environments based on an improved ant colony (CBIACO) algorithm. First, a new probability transfer function is designed for an ant colony algorithm, the weights of each component in the function are adaptively adjusted to optimize the convergence speed of the algorithm, and the global path is re-optimized by using the detection and optimization mechanism of diagonal obstacles. Second, a new unknown environment path exploration strategy (UPES) is designed to solve the problem of poor path exploration ability of the ant colony algorithm in unknown environment. Finally, a collision classification model is proposed for a dynamic environment, and the corresponding dynamic obstacle avoidance strategy is given. The experimental results show that CBIACO algorithm can not only rapidly generate high-quality global paths in known environments but also enable mobile robots to reach the specified target points safely and quickly in a variety of unknown environments. The new dynamic obstacle avoidance strategy enables the mobile robot to avoid dynamic obstacles in different directions at a lower cost.

The dorsal raphe nucleus (DRN) has gained attention owing to its involvement in various physiological functions, such as sleep–awake, feeding, and emotion, with its analgesic role being particularly significant. It is described as the “pain inhibitory nucleus” in the brain. The DRN has diverse projections from hypothalamus, midbrain, and pons. In turn, the DRN is a major source of projections to diverse cortex, limbic forebrain thalamus, and the midbrain and contains highly heterogeneous neuronal subtypes. The activation of DRN neurons in mice prevents the establishment of neuropathic, chronic pain symptoms. Chemogenetic or optogenetic inhibition neurons in the DRN are sufficient to establish pain phenotypes, including long-lasting tactile allodynia, that scale with the extent of stimulation, thereby promoting nociplastic pain. Recent progress has been made in identifying the neural circuits and cellular mechanisms in the DRN that are responsible for sensory modulation. However, there is still a lack of comprehensive review addressing the specific neuron types in the DRN involved in pain modulation. This review summarizes the function of specific cell types within DRN in the pain regulation, and aims to improve understanding of the mechanisms underlying pain regulation in the DRN, ultimately offering insights for further exploration.

The rising prevalence of obesity has resulted in an increased demand for innovative and effective treatment strategies. Houttuynia cordata Thunb. (H. cordata) has demonstrated promising potential in preventing obesity. However, the mechanism underlying the anti-obesity effects of H. cordata and its bioactive component, sodium houttuybonate (SH), remains unclear. Our study reveals that SH treatment promotes the browning of inguinal white adipose tissue (iWAT) and prevents the obesity induced by a high-fat diet. SH significantly mitigates ferroptosis by upregulating glutathione peroxidase 4 (Gpx4) and decreasing malondialdehyde (MDA) levels, while also enhancing superoxide dismutase (SOD) levels. Furthermore, SH promotes the phosphorylation of AMP-activated protein kinase (AMPK), which subsequently increases the expression of nuclear factor erythroid 2-related factor 2 (NRF2) and heme oxygenase-1 (HO-1) in the iWAT. However, the effects of SH were attenuated by ML385, an Nrf2 inhibitor. Collectively, our findings suggest that SH induces iWAT browning and prevents diet-induced obesity primarily through the AMPK/NRF2/HO-1 pathway by inhibiting ferroptosis.

Abstract The aim of this study was to investigate the possible interaction of mitochondrial dysfunction and inflammatory cytokines in the risk of anxiety and depression. We utilized the UK Biobank for the sample of this study. A mitochondria-wide association(MiWAS) and interaction analysis was performed to investigate the interaction effects of mitochondrial DNA (mtDNA)×C-reactive protein (CRP) on the risks of self-reported anxiety (N = 72,476), general anxiety disorder (GAD-7) scores (N = 80,853), self-reported depression (N = 80,778), Patient Health Questionnaire (PHQ-9) scores (N = 80,520) in total samples, females and males, respectively, adjusting for sex, age, Townsend deprivation index (TDI), education score, alcohol intake, smoking and 10 principal components. In all, 25 mtSNPs and 10 mtSNPs showed significant level of association with self-reported anxiety and GAD-7 score respectively. A total of seven significant mtDNA × CRP interactions were found for anxiety, such as m.3915G>A(MT-ND1) for self-reported anxiety in total subjects (P = 6.59 × 10−3), m.4561T>C(MT-ND2) (P = 3.04 × 10−3) for GAD-7 score in total subjects. For depression, MiWAS identified 17 significant mtSNPs for self-reported depression and 14 significant mtSNPs for PHQ-9 scores. 17 significant mtDNA associations (2 for self-reported depression and 15 for PHQ-9 score) was identified, such as m.14869G>A(MT-CYB; P = 2.22 × 10−3) associated with self-reported depression and m.4561T>C (MT-ND2; P value = 3.02 × 10−8) associated with PHQ-9 score in all subjects. In addition, 5 common mtDNA shared with anxiety and depression were found in MiWAS, and 4 common mtDNA variants were detected to interact with CRP for anxiety and depression, such as m.9899T>C(MT-CO3). Our study suggests the important interaction effects of mitochondrial function and CRP on the risks of anxiety and depression.

Abstract Background Both low‐carbohydrate (LC) and calorie-restricted (CR) diets have been shown to have metabolic benefits. However, the two regimens have yet to be thoroughly compared. We conducted a 12-week randomized trial to compare the effects of these diets separately and in combination on both weight loss and metabolic risk factors in overweight/obese individuals. Methods A total of 302 participants were randomized to LC diet (n = 76), CR diet (n = 75), LC + CR diet (n = 76), or normal control (NC) diet (n = 75) using a computer-based random number generator. The primary outcome was the change in body mass index (BMI). The secondary outcomes included body weight, waist circumference, waist-to-hip ratio, body fat, and metabolic risk factors. All participants attended health education sessions during the trial. Results A total of 298 participants were analyzed. BMI change over 12 weeks was − 0.6 (95% CI, − 0.8 to − 0.3) kg/m2 in NC, − 1.3 (95% CI, − 1.5 to − 1.1) kg/m2 in CR, − 2.3 (95% CI, − 2.6 to − 2.1) kg/m2 in LC, and − 2.9 (95% CI, − 3.2 to − 2.6) kg/m2 in LC + CR. LC + CR diet was more effective than LC or CR diet alone at reducing BMI (P = 0.001 and P

With the development of tyrosine kinase inhibitor (TKI) resistance, finding the novel effective chemotherapeutic agent is of seminal importance for chronic myelogenous leukemia (CML) treatment. This study aims to find the effective anti-leukemic candidates and investigate the possible underlying mechanism. We synthesized the novel coumarin derivatives and evaluated their anti-leukemic activity. Cell viability assay revealed that compound DBH2 exhibited the potent inhibitory activity on the proliferation of CML K562 cells and TKI resistant K562 cells. Morphological observation and flow cytometry confirmed that DBH2 could selectively induce cell apoptosis and cell cycle arrest at G2/M phase of the K562 cells, which was further confirmed on the bone marrow cells from CML transgenic model mice and CD34+ bone marrow leukemic cells from CML patients. Treatments of DBH2 in combination with imatinib could prolong the survival rate of SCL-tTA-BCR/ABL transgenic model mice significantly. Quantitative RT-PCR revealed that DBH2 inhibited the expression of STAT3 and STAT5 in K562 cells, and caspase-3 knockout alleviated the DBH2 induced apoptosis. Furthermore, DBH2 could induce the expression of PARP1 and ROCK1 in K562 cells, which may play the important role in caspase-dependent apoptosis. Our results concluded that coumarin derivative DBH2 serves as a promising candidate for the CML treatment, especially in the combination with imatinib for the TKI resistant CML, and STAT/caspase-3 pathway was involved in the molecular mechanism of anti-leukemic activity of DBH2.

Objective Our objective was to explore the national traditional Chinese medicine by studying master Diangui Li's medication experience in treating atrophic gastritis (AG) concomitant with Helicobacter pylori (Hp) infection based on data mining, and to provide the reference for the clinical treatment of relevant diseases.

Cysteine (Cys), one of the important participants in protecting cells from oxidative stress, is closely associated with the occurrence and development of various diseases. Moreover, cell viscosity as a pivotal microenvironmental parameter has recently attracted increasing attention due to its dominant role in governing intracellular signal transduction and diffusion of reactive metabolites. Thus, simultaneous detection of Cys and viscosity is imperative for investigating their pathophysiological functions and cross-link. Herein we present a mitochondria-targetable dual-channel fluorescence probe ABDSP by grafting the acrylate modified pyridinium unit to dimethylaminobenzene. Whilst the probe is a seemingly simple, it could simultaneously discriminate Cys and viscosity in a fashion of distinguishable signals. Furthermore, the probe was successfully employed for visualizing mitochondrial Cys and viscosity, and probe into their cross-link during acetaminophen-induced hepatotoxicity.

There is a notable correlation between mitochondrial homeostasis and metabolic disruption. In this review, we report that obesity-induced disruption of mitochondrial homeostasis adversely affects lipid metabolism, adipocyte differentiation, oxidative capacity, inflammation, insulin sensitivity, and thermogenesis in thermogenic fat. Elevating mitochondrial homeostasis in thermogenic fat emerges as a promising avenue for developing treatments for metabolic diseases, including enhanced mitochondrial function, mitophagy, mitochondrial uncoupling, and mitochondrial biogenesis. The exerkines (e.g., myokines, adipokines, batokines) released during exercise have the potential to ameliorate mitochondrial homeostasis, improve glucose and lipid metabolism, and stimulate fat browning and thermogenesis as a defense against obesity-associated metabolic diseases. This comprehensive review focuses on the manifold benefits of exercise-induced exerkines, particularly emphasizing their influence on mitochondrial homeostasis and fat thermogenesis in the context of metabolic disorders associated with obesity.

Abstract Thin-walled parts are typically difficult-to-cut components due to the complex dynamics in cutting process. The dynamics is variant for part during machining, but invariant for machine tool. The variation of the relative dynamics results in the difference of cutting stage division and cutting parameter selection. This paper develops a novel method for whole cutting process optimization based on the relative varying dynamic characteristic of machining system. A new strategy to distinguish cutting stages depending on the dominated dynamics during machining process is proposed, and a thickness-dependent model to predict the dynamics of part is developed. Optimal cutting parameters change with stages, which can be divided by the critical thickness of part. Based on the dynamics comparison between machine tool and thickness-varying part, the critical thicknesses are predicted by an iterative algorithm. The proposed method is validated by the machining of three benchmarks. Good agreements have been obtained between prediction and experimental results in terms of stages identification, meanwhile, the optimized parameters perform well during the whole cutting process.

Abstract Background Longevity is one of the most complex phenotypes, and its genetic basis remains unclear. This study aimed to explore the genetic correlation and potential causal association between gut microbiota and longevity. Results Linkage disequilibrium score (LDSC) regression analysis and a bi-directional two-sample Mendelian Randomization (MR) analysis were performed to analyze gut microbiota and longevity-related traits. LDSC analysis detected four candidate genetic correlations, including Veillonella (genetic correlation = 0.5578, P = 4.67 × 10− 2) and Roseburia (genetic correlation = 0.4491, P = 2.67 × 10− 2) for longevity, Collinsella (genetic correlation = 0.3144, P = 4.07 × 10− 2) for parental lifespan and Sporobacter (genetic correlation = 0.2092, P = 3.53 × 10− 2) for healthspan. Further MR analysis observed suggestive causation between Collinsella and parental longevity (father’s age at death) (weighted median: b = 1.79 × 10− 3, P = 3.52 × 10− 2). Reverse MR analysis also detected several causal effects of longevity-related traits on gut microbiota, such as longevity and Sporobacter (IVW: b = 7.02 × 10− 1, P = 4.21 × 10− 25). Statistical insignificance of the heterogeneity test and pleiotropy test supported the validity of the MR study. Conclusion Our study found evidence that gut microbiota is causally associated with longevity, or vice versa, providing novel clues for understanding the roles of gut microbiota in aging development.

Background The associations of oral contraceptive (OC) use with cardiovascular disease (CVD) and all‐cause death remains unclear. We aimed to determine the associations of OC use with incident CVD and all‐cause death. Methods and Results This cohort study included 161 017 women who had no CVD at baseline and reported their OC use. We divided OC use into ever use and never use. Cox proportional hazard models were used to calculate hazard ratios and 95% CIs for cardiovascular outcomes and death. Overall, 131 131 (81.4%) of 161 017 participants reported OC use at baseline. The multivariable‐adjusted hazard ratios for OC ever users versus never users were 0.92 (95% CI, 0.86–0.99) for all‐cause death, 0.91 (95% CI, 0.87–0.96) for incident CVD events, 0.88 (95% CI, 0.81–0.95) for coronary heart disease, 0.87 (95% CI, 0.76–0.99) for heart failure, and 0.92 (95% CI, 0.84–0.99) for atrial fibrillation. However, no significant associations of OC use with CVD death, myocardial infarction, or stroke were observed. Furthermore, the associations of OC use with CVD events were stronger among participants with longer durations of use (P for trend

Abstract For underground water-sealed oil storage, the spatial variability of the surrounding rock has a significant impact on the water-sealed effect of a water curtain system. This study presents a methodology for the probabilistic analysis of water curtain performance in underground oil storage, considering the spatial variability of hydraulic conductivity of the surrounding rock based on field data. Anisotropic random fields representing the spatial variability of hydraulic conductivity were established through spatial statistical analysis of field data and introduced into the finite element model of underground oil storage for water-sealed reliability analysis. The water-sealed performance of different water curtain system schemes was studied using Monte Carlo simulation (MCS). The results showed that the difference between the horizontal spatial correlation and the vertical spatial correlation of the surrounding rock has a significant impact on the water-sealed effect of the water curtain system. An excessively large pressure of water curtain boreholes provided a small contribution to improving water curtain performance. The distance between the water curtain holes and the caverns had the less significant affecting the water-sealed reliability of the storage cavern. Finally, the optimal design of the water curtain system is discussed. This study provides valuable insights and a theoretical basis for the optimisation of water curtain system design parameters for underground water-sealed oil storage.

The human gut microbiome has primarily been studied through the use of fecal samples, a practice that has generated vital knowledge on the composition and functional capacities of gastrointestinal microbial communities. However, this reliance on fecal materials limits the investigation of microbial dynamics in other locations along the gastrointestinal tract (in situ), and the infrequent availability of fecal samples prevents analysis at finer temporal scales (e.g., hours). In our study, we utilized colonic transendoscopic enteral tubing, a technology originally developed for fecal microbiota transplantation, to sample the ileocecal microbiome twice daily; metagenomic and metatranscriptomic analyses were then conducted on these samples. A total of 43 ileocecal and 28 urine and fecal samples were collected from five healthy volunteers. The ileocecal and fecal microbiomes, as profiled in the five volunteers, were found to be similar in metagenomic profiling, yet their active genes (metatranscriptome) were found to be highly distinct. Both microbiomes were perturbed after laxative exposure; over time, they exhibited reduced dissimilarity to their pre-treatment state, thereby demonstrating resilience as an innate property of the gut microbiome, although they did not fully recover within our observation time window. Sampling of the ileocecal microbiome during the day and at night revealed the existence of diurnal rhythms in a series of bacterial species and functional pathways, particularly those related to short-chain fatty acid production, such as Propionibacterium acnes and coenzyme A biosynthesis II. Autocorrelation analysis and fluctuations decomposition further indicated the significant periodicity of the diurnal oscillations. Metabolomic profiling in the fecal and urine samples mirrored the perturbance and recovery in the gut microbiome, indicating the crucial contribution of the gut microbiome to many key metabolites involved in host health. This study provides novel insights into the human gut microbiome and its inner resilience and diurnal rhythms, as well as the potential consequences of these to the host.

This paper describes control algorithm of minimum energy loss in the aeration process of wastewater treatment in the activated sludge system. The basic equations of the aeration process have been proposed in this paper with the dissolved oxygen concentration (DO) and the amount of sludge discharge (QW) being dual-parameter control variables and the organic matter concentration S and the microbial concentration X in the aeration tank being the state variables. Based on the present study on optimization control of wastewater treatment, the multivariable optimal control model with restriction factors have been presented in the paper. The model with modern control theory and system analysis are introduced into the field of activated sludge wastewater treatment. It takes the two most important control parameters (DO &QW), effluent quality as restriction factor. The minimum energy consumption in the aeration process is used as the objective function. This approach has been carried out and the results show that adopting optimal control strategy in the aeration process can effectively conserve energy with the assurance of effluent water quality.

Abstract Psychiatric disorders and neuroticism are closely associated with central nervous system, whose proper functioning depends on efficient protein renewal. This study aims to systematically analyze the association between anxiety / depression / neuroticism and each of the 439 proteins. 47,536 pQTLs of 439 proteins in brain, plasma and cerebrospinal fluid (CSF) were collected from recent genome-wide association study. Polygenic risk scores (PRS) of the 439 proteins were then calculated using the UK Biobank cohort, including 120,729 subjects of neuroticism, 255,354 subjects of anxiety and 316,513 subjects of depression. Pearson correlation analyses were performed to evaluate the correlation between each protein and each of the mental traits by using calculated PRSs as the instrumental variables of protein. In general population, six correlations were identified in plasma and CSF such as plasma protease C1 inhibitor (C1-INH) with neuroticism score (r = − 0.011, P = 2.56 × 10− 9) in plasma, C1-INH with neuroticism score (r = -0.010, P = 3.09 × 10− 8) in CSF, and ERBB1 with self-reported depression (r = − 0.012, P = 4.65 × 10− 5) in CSF. C1-INH and ERBB1 may induce neuroticism and depression by affecting brain function and synaptic development. Gender subgroup analyses found that BST1 was correlated with neuroticism score in male CSF (r = − 0.011, P = 1.80 × 10− 5), while CNTN2 was correlated with depression score in female brain (r = − 0.013, P = 6.43 × 10− 4). BST1 and CNTN2 may be involved in nervous system metabolism and brain health. Six common candidate proteins were associated with all three traits (P

Abstract Multiple previous studies explored the associations between early life factors and the age at onset of the depression. However, they only focused on the influence of environmental or genetic factors, without considering the interactions between them. Based on previous genome-wide association study (GWAS) data, we first calculated polygenic risk score (PRS) for depression. Regression analyses were conducted to assess the interacting effects of depression PRS and 5 early life factors, including felt hated by family member (N = 40,112), physically abused by family (N = 40,464), felt loved (N = 35633), and sexually molested (N = 41,595) in childhood and maternal smoking during pregnancy (N = 38,309), on the age at onset of the depression. Genome-wide environment interaction studies (GWEIS) were then performed to identify the genes interacting with early life factors for the age at onset of the depression. In regression analyses, we observed significant interacting effects of felt loved as a child and depression PRS on the age at onset of depression in total sample (β = 0.708, P = 5.03 × 10−3) and males (β = 1.421, P = 7.64 × 10−4). GWEIS identified a novel candidate loci interacting with felt loved as a child at GSAP (rs2068031, P = 4.24 × 10–8) and detected several genes with suggestive significance association, such as CMYA5 (rs7343, P = 2.03 × 10–6) and KIRREL3 (rs535603, P = 4.84 × 10–6) in males. Our results indicate emotional care in childhood may affect the age at onset of depression, especially in males, and GSAP plays an important role in their interaction.

Adipose tissue undergoes changes with aging, leading to increased adiposity, inflammatory cell infiltration, reduced angiogenesis, heightened oxidative stress, and alterations in its metabolic function. Regular exercise has been recognized as a powerful intervention that can positively influence adipose tissue health and mitigate the effects of aging. However, the molecular mechanisms underlying the benefits of regular exercise on aging adipose tissue function remain poorly understood. Adipokines released through regular exercise play a potential role in mitigating adipose tissue aging, enhancing the metabolism of glucose and lipids, reducing inflammation and fibrosis, and promoting fat browning and thermogenesis. This review comprehensively summarizes the benefits of regular exercise in addressing the age-related decline in adipose tissue function. Utilizing relevant examples of this approach, we address the possibility of designing therapeutic interventions based on these molecular mechanisms.

Aim: This study investigates the effects of ginsenoside Rb1 (GsRb1) on methamphetamine (METH)-induced toxicity in SH-SY5Y neuroblastoma cells and METH-induced conditioned place preference (CPP) in adult Sprague-Dawley rats. It also examines whether GsRb1 can regulate these effects through the NR2B/ERK/CREB/BDNF signaling pathways. Methods: SH-SY5Y cells were pretreated with GsRb1 (20 μM and 40 μM) for 1 h, followed by METH treatment (2 mM) for 24 h. Rats were treated with METH (2 mg/kg) or saline on alternating days for 10 days to allow CPP to be examined. GsRb1 (5, 10, and 20 mg/kg) was injected intraperitoneally 1 h before METH or saline. Western blot was used to examine the protein expression of NR2B, ERK, P-ERK, CREB, P-CREB, and BDNF in the SH-SY5Y cells and the rats' hippocampus, nucleus accumbens (NAc), and prefrontal cortex (PFC). Results: METH dose-dependently reduced the viability of SH-SY5Y cells. Pretreatment of cells with 40 μM of GsRb1 increased cell viability and reduced the expression of METH-induced NR2B, p-ERK, p-CREB and BDNF. GsRb1 also attenuated the expression of METH CPP in a dose-dependent manner in rats. Further, GsRb1 dose-dependently reduced the expression of METH-induced NR2B, p-ERK, p-CREB, and BDNF in the PFC, hippocampus, and NAc of rats. Conclusion: GsRb1 regulated METH-induced neurotoxicity in vitro and METH-induced CPP through the NR2B/ERK/CREB/BDNF regulatory pathway. GsRb1 could be a therapeutic target for treating METH-induced neurotoxicity or METH addiction.

Background The association between menstrual cycle characteristics and cardiovascular outcomes remains unclear. This study was undertaken to evaluate whether menstrual cycle regularity and length throughout the life course are associated with cardiovascular outcomes. Methods and Results This cohort study included 58 056 women who had no cardiovascular disease (CVD) at baseline and reported their menstrual cycle regularity and length. Hazard ratios (HRs) and 95% CIs for CVD events were estimated using Cox proportional hazards models. During the median 11.8 years of follow‐up, 1623 incident CVD cases were documented, including 827 incident cases of coronary heart disease, 199 myocardial infarctions, 271 strokes, 174 cases of heart failure, and 393 cases of atrial fibrillations. Compared with women with regular menstrual cycles, the HRs for women with irregular menstrual cycles were 1.19 (95% CI, 1.07–1.31) for CVD events and 1.40 (95% CI, 1.14–1.72) for atrial fibrillation. The multivariable‐adjusted HRs for short (≤21 days) or long (35 days) menstrual cycles during follow‐up were 1.29 (95% CI, 1.11–1.50) and 1.11 (95% CI, 0.98–1.56) for CVD events, respectively. Similarly, long or short cycle length were more likely to be associated with increased risk of atrial fibrillation (HR, 1.30 [95% CI, 1.01–1.66]; and HR, 1.38 [95% CI, 1.02–1.87]), and short cycle length was more likely to be associated with increased risk of coronary heart disease and myocardial infarction. However, these associations for stroke and heart failure were not significant. Conclusions Long or short menstrual cycle length was associated with increased risks of CVD and atrial fibrillation but not myocardial infarction, heart failure, or stroke. Short cycle length was associated with a greater risk of coronary heart disease and myocardial infarction.

Digital images are characterized by high redundancy and strong interpixel correlation. Breaking the correlation between data and improving sensitivity are crucial to protecting image information. To effectively achieve this goal, a chaotic encryption algorithm based on Josephus cycle scrambling diffusion is proposed in this paper. First, the adaptive key is generated by the Hash function to generate the initial value of the chaotic system, which is highly related to the plaintext image. The generation of the adaptive key can effectively resist plaintext attacks. Second, the pseudorandom sequence generated by the two-difference chaotic mapping is applied as the step sequence and direction sequence of Josephus traversal and optimizes Josephus traversal via variable steps and directions; the ranks of plain-text images are scrambled by the Josephus cycle to break the strong correlation between pixels. Finally, the initial cipher-text is divided into blocks to complete the Josephus cycle scrambling diffusion of image blocks, intrablock pixel bits and bit planes. The double permutations at the pixel level and bit level break the high correlation between pixels. Compared with the previous studies, our algorithm’s average entropy of encrypted images is 7.9994, which has slightly improved. The correlation coefficient of the cryptographic image fluctuates up and down by approximately 0. In addition, the algorithm has the advantages of a large key space, high key sensitivity, anti-robust attack, and feasible encryption efficiency.