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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.

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 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 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.

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.

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.

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.

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.

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.

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.

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.

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 effects of partially substituting Al for Cu in Zr59.62Cu18.4-xNi12Al6+xNb3Hf0.78Y0.2 (x = 0, 2, 4, 6, 8 at.%) bulk metallic glasses (BMGs) on their glass-forming ability (GFA), quasi-static and dynamic mechanical properties, and energy characteristics were investigated. The results showed that an appropriate substitution of Al for Cu can improve GFA and reach a critical casting size up to 10 mm. Additionally, with Al replacement of Cu, the change in the distribution and content of free volume inside the BMGs was the main reason for the quasi-static compression plasticity. In contrast, the BMGs exhibited no plasticity during dynamic compression and high-speed impact, owing to the short loading time and thermal softening effect. In terms of energy characteristics, all alloys have a high combustion enthalpy. And on the surface of the fragments collected from impact, the active elements Zr, Al, and Nb reacted because of the adiabatic temperature rise. Further, x = 4 at.% Zr-based BMG with its superior overall performance could penetrate a 6 mm Q235 plate at a speed of 1038 m/s, combining excellent mechanical properties and energy characteristics. This study contributes to the development of Zr-based BMGs as novel energetic structural materials.

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 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

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.

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.

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.

Polypropylene (PP) is one of the most extensively used commodity plastics. In terms of eco-friendliness, it is worth considering preparing high-lignin-filled PP. This study explores the incorporation of high lignin content, derived from acetic acid lignin (AAL) and Kraft lignin (KL), into PP through twin-screw extrusion and injection molding. The challenge lies in maintaining mechanical performance. A compatibilizer—specifically, maleic anhydride-grafted polypropylene (MAPP)—is employed to enhance lignin–PP compatibility by chemically bonding with lignin and physically associating with the PP phase. Results indicate that KL maintains better dispersity than AAL. Compatibilizers with a high maleic anhydride (MA) level (≥0.8 wt.%) and moderate melt flow index (MFI) in the range of 60–100 g 10 min⁻¹ prove favorable in constructing a reinforced PP/KL network. Optimizing with 40 wt.% lignin content and 10 parts per hundred (pph) of compatibilizer yields blends with mechanical performance comparable to neat PP, exhibiting a notable increase in modulus and heat deflection temperature (HDT). Furthermore, utilizing PP/lignin blends can lead to a 20% reduction in expenses and approximately 40% reduction in PP-induced greenhouse gas (GHG) emissions. This approach not only reduces PP costs but also adds value to lignin utilization in a sustainable and cost-effective manner.

Aberrant protein post-translational modification is a hallmark of malignant tumors. Lysine succinylation (Ksucc) plays a vital role in cell energy metabolism in various cancers. However, whether succinylation can be catalyzed by acetyltransferase p300 remains unclear. In this study, we unveiled that p300 is a “writer” for succinylation, and p300-mediated Ksucc promotes cell glycometabolism in lung adenocarcinoma (LUAD). Specifically, our succinylome data revealed that EP300 deficiency leads to the systemic reduction of Ksucc, and 79.55% of the p300-succinylated proteins were found in the cytoplasm, which were primarily enriched in the carbohydrate metabolism process. Interestingly, deleting EP300 led to a notable decrease in Ksucc levels on several glycolytic enzymes, especially Phosphoglycerate Kinase 1 (PGK1). Mutation of the succinylated site of PGK1 notably hindered cell glycolysis and lactic acid excretion. Metabolomics in vivo indicated that p300-caused metabolic reprogramming was mainly attributed to the altered carbohydrate metabolism. In addition, 89.35% of LUAD patients exhibited cytoplasmic localization of p300, with higher levels in tumor tissues than adjacent normal tissues. High levels of p300 correlated with advanced tumor stages and poor prognosis of LUAD patients. Briefly, we disclose the activity of p300 to catalyze succinylation, which contributes to cell glucose metabolic reprogramming and malignant progression of lung cancer.

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 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.

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.

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.

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.

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.

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.

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.

High-speed spindle systems could generate sufficient heat when they are operating and would cause thermal deformation that influences spindle accuracy. Heat dissipation is a common and effective way to remove the generated heat. In this paper, heat conductive paths were created on the bearing seat and the spindle housing along the radial direction. Along these paths, the heat was transferred directly from heat sources inside the spindle system to outside and the heat dissipation was enhanced. To limit the heat transferred along the axial direction, the inner wall of the path was coated with a thermal insulation material. Based on an annular plate model, the influences of the affecting parameters of paths on the heat transfer performance were studied. The temperature distributions of the models with and without heat conductive paths were numerically and experimentally investigated. It was found that after using heat conductive paths, the heat dissipation enhanced significantly. Moreover, it is found that as the number and diameter of paths increases, the temperature of internal parts decreases and the gap between the highest and the lowest temperature is narrowed.

As the depth of mineral exploration increases, integrated geophysical methods are increasingly playing a crucial role in prospecting deep structures at the district scale. The Nanling-Xuancheng ore district is the eighth ore district in the middle-lower Yangtze metallogenic belt in China. To reveal the deep structure of the mining district, this study mainly focuses on regional high-precision gravity and magnetic data and integrates the interpretation of magnetotelluric and reflection seismic data from a key area. By using a 2.5D joint inversion method with prior information constraints, new insights into the deep structures, tectonic deformation, and magmatic activity are obtained. Structurally, the Nanling-Xuancheng ore district presents a structural pattern of “two uplifts and two depressions” composed of multi-level thrust-overturned and folds formed by Mesozoic depressions, which has a three-layer structure in the vertical direction (shallower than 10 km). Tectonically, the main faults in the study area trend NW, which intersect with NE-trending and EW-trending faults to form a branching structure from deep to shallow. The fault intersections provide pathways for magma intrusion. The distribution of deep-seated concealed magmatic rocks shows the characteristic pattern of “a primary magma source spawning multiple subsidiary intrusion”.

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.

Abstract Objective Genetic approaches are increasingly advantageous in characterizing treatment-resistant schizophrenia (TRS). We aimed to identify TRS-associated functional brain proteins, providing a potential pathway for improving psychiatric classification and developing better-tailored therapeutic targets. Methods TRS-related proteome-wide association studies (PWAS) were conducted on genome-wide association studies (GWAS) from CLOZUK and the Psychiatric Genomics Consortium (PGC), which provided TRS individuals (n = 10,501) and non-TRS individuals (n = 20,325), respectively. The reference datasets for the human brain proteome were obtained from ROS/MAP and Banner, with 8,356 and 11,518 proteins collected, respectively. We then performed colocalization analysis and functional enrichment analysis to further explore the biological functions of the proteins identified by PWAS. Results In PWAS, two statistically significant proteins were identified using the ROS/MAP and then replicated using the Banner reference dataset, including CPT2 (P PWAS-ROS/MAP = 4.15 × 10−2 and P PWAS-Banner = 3.38 × 10−3) and APOL2 (P PWAS-ROS/MAP = 4.49 × 10−3 and P PWAS-Banner = 8.26 × 10−3). Colocalization analysis identified three variants that were causally related to protein expression in the human brain, including CCDC91 (PP4 = 0.981), PRDX1 (PP4 = 0.894), and WARS2 (PP4 = 0.757). We extended PWAS results from gene-based analysis to pathway-based analysis, identifying 14 gene ontology (GO) terms and the only candidate pathway for TRS, metabolic pathways (all P < 0.05). Conclusions Our results identified two protein biomarkers, and cautiously support that the pathological mechanism of TRS is linked to lipid oxidation and inflammation, where mitochondria-related functions may play a role.

BackgroundMultifarious factors have a causal relationship with gastric cancer (GC) development. We conducted a comprehensive analysis to evaluate the strength of the evidence examining non-genetic risk factors for gastric cancer.MethodsPubMed, Web of Science, and the Cochrane Library were searched from inception to November 10, 2021 to identify meta-analyses of observational studies examining the association between environmental factors and GC risk. For each meta-analysis, the random effect size, 95% confidence interval, heterogeneity among studies, and evidence of publication bias were assessed; moreover, the evidence was graded using predefined criteria, and the methodological quality was evaluated using AMSTAR 2.ResultsA total of 137 associations were examined in 76 articles. Among these meta-analyses, 93 associations yielded significant estimates (p < 0.05). Only 10 associations had strong epidemiologic evidence, including 2 risk factors (waist circumference and bacon), and 8 protective factors (dietary total antioxidant capacity, vegetable fat, cruciferous vegetable, cabbage, total vitamin, vitamin A, vitamin C, and years of fertility); 26 associations had moderate quality of evidence; and the remaining 57 associations were rated as weak. Ninety-four (68.61%) associations showed significant heterogeneity. Twenty-five (18.25%) associations demonstrated publication bias.ConclusionsIn this comprehensive analysis, multiple associations were found between environmental factors and GC with varying levels of evidence. Healthy dietary habits and lifestyle patterns could reduce the risk for GC. However, further high-quality prospective studies are still necessary to draw more definitive conclusions.

Carbon-based perovskite solar cells (C-PSCs) have the impressive characteristics of good stability and potential commercialization. The insulating layers play crucial roles in charge modulation at the buried perovskite interface in mesoporous C-PSCs. In this work, the effects of three different tunnel oxide layers on the performance of air-processed C-PSCs are scrutinized to unveil the passivating quality. Devices with ZrO2-passivated TiO2 electron contacts exhibit higher power conversion efficiencies (PCEs) than their Al2O3 and SiO2 counterparts. The porous feature and robust chemical properties of ZrO2 ensure the high quality of the perovskite absorber, thus ensuring the high repeatability of our devices. An efficiency level of 14.96% puts our device among the state-of-the-art hole-conductor-free C-PSCs, and our unencapsulated device maintains 88.9% of its initial performance after 11,520 h (480 days) of ambient storage. These results demonstrate that the function of tunnel oxides at the perovskite/electron contact interface is important to manipulate the charge transfer dynamics that critically affect the performance and stability of C-PSCs.

Climate change (CC) is a worldwide environmental issue affecting all economic sectors, especially agriculture. Pakistan is one of the countries most affected by CC due to the country’s vulnerability to catastrophic events and limited ability to adapt. Assessing existing activities for adaptation to CC at the farm level is critical to understanding their success and recommending additional government measures. This study analyzes possible farming practice modifications that Pakistani farmers may adopt to reduce the loss of agricultural output due to the rising prevalence of dangerous weather events by CC. Data for the current research were gathered from 432 wheat farmers in rural Pakistan. This article investigates many factors that impact farmers’ decisions to CC adaptation in crop production utilizing binary logit (BL) and multivariate probit (MVP) models. Gender, education level, farming experience, farm size, level of damage, access to finance, and training participation are characteristics that substantially affect farmers’ likelihood of adapting to CC. Farm size and participation in CC training were the most critical factors influencing farmers’ CC adaptation decisions. Policy recommendations were presented to increase the farmers’ resilience in the study areas to CC. These comprise expanding CC training courses, developing regulations to encourage agricultural integration, and integrating CC and adaptation to CC principles into the operations of regional organizations. Finally, based on the findings, policymakers will be better equipped to address the challenges posed by CC and create a more resilient agricultural sector. This, in turn, will contribute to improving food security, ensuring sustainable agricultural growth.

Agricultural production and advancement is significantly affected by climate change (CC), especially in drought-prone regions where farmers depend primarily on rainfall for their livelihoods. One of the main threats to the agricultural sector for decades has been global warming, and the sector is particularly susceptible to climatic circumstances. CC has become a crucial concern impeding sustainable development due to rapid changes in urbanization, industry, and agricultural systems. Food security, which is a worldwide concern, is another essential component connected to a country’s economy and people’s livelihoods. In view of these adverse consequences, the main objective of this study was to examine the impact of CC and food security on sustainable agricultural development in Pakistan. The study area was selected from twenty-four districts in two provinces of Pakistan (Khyber Pakhtunkhwa and Balochistan). Collectively, the current research offers possible solutions to the dilemmas described above, which could have a significant impact on improving efficiency and technological progress. To address these issues, we introduced a slack-based approach to quantify inefficiencies in overall agricultural production. In addition, this study further scrutinized the decomposition of specific variables. The results show that Pakistan has an agricultural inefficiency of 0.62 under CC and food security constraints, of which 0.29 is primarily attributable to food security limitations. In the end, this study will help policymakers to make appropriate decisions to minimize the impact of CC on sustainable agriculture growth and improve human living standards and food security.

Abstract Background Gut microbiota is closely associated with host health and disease occurrence. Host genetic factor plays an important role in shaping gut microbial communities. The specific mechanism of host-regulated gene expression affecting gut microbiota has not been elucidated yet. Here we conducted a transcriptome-wide association study (TWAS) for gut microbiota by leveraging expression imputation from large-scale GWAS data sets. Results TWAS detected multiple tissue-specific candidate genes for gut microbiota, such as FUT2 for genus Bifidobacterium in transverse colon (P PERM.ANL = 1.68 × 10–3) and SFTPD for an unclassified genus of Proteobacteria in transverse colon (P PERM.ANL = 5.69 × 10–3). Fine mapping replicated 3 candidate genes in TWAS, such as HELLS for Streptococcus (PIP = 0.685) in sigmoid colon, ANO7 for Erysipelotrichaceae (PIP = 0.449) in sigmoid colon. Functional analyses detected 94 significant GO terms and 11 pathways for various taxa in total, such as GO_NUCLEOSIDE_DIPHOSPHATASE_ACTIVITY for Butyrivibrio (FDR P = 1.30 × 10–4), KEGG_RENIN_ANGIOTENSIN_SYSTEM for Anaerostipes (FDR P = 3.16 × 10–2). Literature search results showed 12 genes prioritized by TWAS were associated with 12 diseases. For instance, SFTPD for an unclassified genus of Proteobacteria was related to atherosclerosis, and FUT2 for Bifidobacterium was associated with Crohn’s disease. Conclusions Our study results provided novel insights for understanding the genetic mechanism of gut microbiota, and attempted to provide clues for revealing the influence of genetic factors on gut microbiota for the occurrence and development of diseases.

The rough back of a wall causes the deflection of the soil stress direction behind the wall. At present, there are few studies on the influence of the deflection of the soil stress direction on the earth pressure in cohesive soils. For this reason, this paper firstly discusses the deflection law of the principal stress of the soil behind the wall, and adopts a layered formation of curved thin-layer elements along the principal stress trace. By analyzing the force of the curved thin-layer element, the static balance equation of the curved thin-layer element is established, and the formula for the distribution of the earth pressure of the cohesive soil along the wall height in the translational mode is derived, and the new analysis method of the cohesive earth pressure is obtained. Finally, the method in this paper is compared with the actual measurement results and the existing theory and the parameters are analyzed to verify the reliability and rationality of the method in this paper. The research results show that the calculation results considering the effect of wall-soil friction can more accurately reflect the distribution law of cohesive soil along the wall height; the magnitude of earth pressure decreases with the increasing cohesion. With the increase of wall-soil friction angle soil, the pressure resultant force gradually decreases, and the height of the point of application increases slowly.