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Abstract The variability of renewable energy within microgrids (MGs) necessitates the smoothing of power fluctuations through the effective scheduling of internal power equipment. Otherwise, significant power variations on the tie‐line connecting the MG to the main power grid could occur. This study introduces an innovative scheduling strategy that utilizes a data‐driven approach, employing a deep reinforcement learning algorithm to achieve this smoothing effect. The strategy prioritizes the scheduling of MG's internal power devices, taking into account the stochastic charging patterns of electric vehicles. The scheduling optimization model is initially described as a Markov decision process with the goal of minimizing power fluctuations on the interconnection lines and operational costs of the MG. Subsequently, after preprocessing the historical operational data of the MG, an enhanced scheduling strategy is developed through a neural network learning process. Finally, the results from four scheduling scenarios demonstrate the significant impact of the proposed strategy. Comparisons of reward curves before and after data preprocessing underscore its importance. In contrast to optimization results from deep deterministic policy gradient, soft actor‐critic, and particle swarm optimization algorithms, the superiority of the deep deterministic policy gradient algorithm with the addition of a priority experience replay mechanism is highlighted.

Abstract Since these large‐scale renewable power generation (RPGs) stations are always located far away from load centres, voltage source converters (VSCs) always operate in weak‐grid connected conditions, due to the long distance of transmission line and increasing capacity of RPGs. Large power disturbance of RPGs easily causes weak‐grid connected VSCs (WG‐VSCs) suffering from transient synchronization instability issue, which is lack of theoretical and quantitative analysis. This paper is motivated to fill this gap. By considering the dynamic interaction of outer DC voltage control, reactive power loop, and phase‐locked loop (PLL), an equivalent synchronization model of a WG‐VSC system is established first. Then, the mechanism of transient synchronization instability is revealed by the combination of equal area criterion and numerical integration method. Furthermore, the concept of feasible region of active power disturbance (FR‐APD) is introduced for the first time. With the constructed FR‐APD, the transient stability of the WG‐VSC system can be confirmed. Finally, experimental results based on the RT‐BOX hardware‐in‐the‐loop platform are presented to verify the theoretical analysis.

Digitalization and globalization have radically affected work organization and interaction between workers in the course of performing job duties. Co-creation activity on digital labour platforms is a new phenomenon that has been little studied. The paper aims to explore collaboration as a driving force in the evolution of work organization patterns and investigates its main effects on the labour market. Theory of cooperation and organizational theory constitute the methodological basis of the study. The research methods used are evolutionary analysis, statistical and regression analysis. The empirical evidence is comprised of open data from the European Social Survey (ESS) Round 10 (2020/23). The study identifies the directions for altering the forms of collaborative activities: the key ones are associated with the enhancement of individual value, accumulation of human capital and a rise in worker autonomy. It is shown that organization of work, which is also undergoing significant changes, promotes flexible working practices. The empirical analysis indicates that high-frequency Internet use among self-employed workers significantly increases the probability of engaging in co-creation activities, particularly as education levels rise. The growing intrinsic motivation of participants to such activities leads to higher labour productivity. The findings highlight a critical issue regarding the lack of human resource management practices in platform employment. Designing a new (flexible) model of work organization aligned with the characteristics and effects of co-creation activities can serve as a promising direction for further research.

To investigate the effects of epigallocatechin-3-gallate-bovine bone protein (EGCG-BBP) on the protein structure and storage oxidative stability of emulsified meat products, the effects of adding different concentrations of EGCG-BBP on the physicochemical and structural properties of myofibrillar protein (MP) in raw meat, and on the oxidative stability of meatballs were investigated. The results showed that the addition of 0.8% EGCG-BBP resulted in the highest content of sulfhydryl group of MP (4.06 nmol/mg protein) in the minced meat, while the carbonyl group and surface hydrophobicity values were lowest, effectively improving the antioxidant capacity of the emulsified meat products. Fourier-transform infrared spectroscopy analysis showed that the wave number corresponding to the peak of the amide A band of MP was significantly increased in the minced meat supplemented with EGCG-BBP compared with the control group, indicating corresponding changes in the secondary structure of MP. The fluorescence spectra showed that there was a significant red shift in the strongest MP wavelength in the control group with a prolongation of the storage time. However, this shift was significantly reduced as the concentration of EGCC-BBP increased. This suggested that the addition of EGCG-BBP changed the tertiary structure of MP. Furthermore, analysis of oxidation indices during storage of the emulsified meatballs showed that the addition of 0.8% EGCG-BBP significantly reduced the values of both PV values and TBARS in the meatballs, thereby improving their oxidative stability. In summary, EGCG-BBP can significantly alter both the secondary and tertiary structures of MP and has good oxidation resistance. This indicates its potential to enhance the quality of emulsified meat products and provides a new choice for the application of antioxidant emulsifiers in meat products.

Abstract Gastric cancer (GC) remains a global disease with a high mortality rate, the lack of effective treatments and the high toxicity of side effects are primary causes for its poor prognosis. Hence, urgent efforts are needed to find safe and effective therapeutic strategies. Gypenoside (Gyp) is a widely used natural product that regulates blood glucose to improve disease progression with few toxic side effects. Given the crucial role of abnormal glycometabolism in driving tumor malignancy, it is important to explore the association between Gyp and glycometabolism in GC and understand the mechanism of action by which Gyp influences glycometabolism. In this study, we demonstrated that Gyp suppresses GC proliferation and migration both in vitro and in vivo. We identified that Gyp suppresses the malignant progression of GC by inhibiting glycolysis using network pharmacology and metabolomics. Transcriptome analysis revealed that the Hippo pathway is a key regulator of glycolysis by Gyp in GC. Furthermore, Gyp induced upregulation of LATS1/2 proteins, leading to increased YAP phosphorylation and decreased TAZ protein expression. The YAP agonist XMU-MP-1 rescued the inhibitory effect of Gyp on GC proliferation by reversing glycolysis. These findings confirmed that Gyp inhibits GC proliferation by targeting glycolysis through the Hippo pathway. Our study examined the role of Gyp in the malignant progression of GC, explored its therapeutic prospects, elucidated a mechanism by which Gyp suppresses GC proliferation through interference with the glycolytic process, thus providing a potential novel therapeutic strategy for GC patients.

Abstract Polyhydroxyalkanoates (PHAs) could be used to make sustainable, biodegradable plastics. However, the precise and accurate mechanistic modeling of PHA biosynthesis, especially medium-chain-length PHA (mcl-PHA), for yield improvement remains a challenge to biology. PHA biosynthesis is typically triggered by nitrogen limitation and tends to peak at an optimal carbon-to-nitrogen (C/N) ratio. Specifically, simulation of the underlying dynamic regulation mechanisms for PHA bioprocess is a bottleneck owing to surfeit model complexity and current modeling philosophies for uncertainty. To address this issue, we proposed a quantum-like decision-making model to encode gene expression and regulation events as hidden layers by the general transformation of a density matrix, which uses the interference of probability amplitudes to provide an empirical-level description for PHA biosynthesis. We implemented our framework modeling the biosynthesis of mcl-PHA in Pseudomonas putida with respect to external C/N ratios, showing its optimization production at maximum PHA production of 13.81% cell dry mass (CDM) at the C/N ratio of 40:1. The results also suggest the degree of P. putida’s preference in channeling carbon towards PHA production as part of the bacterium’s adaptative behavior to nutrient stress using quantum formalism. Generic parameters (kD, kN and theta θ) obtained based on such quantum formulation, representing P. putida’s PHA biosynthesis with respect to external C/N ratios, was discussed. This work offers a new perspective on the use of quantum theory for PHA production, demonstrating its application potential for other bioprocesses.

The purpose of this review was to examine if maternal hypertensive disorders of pregnancy (HDP) and gestational diabetes mellitus (GDM) result in an increased risk of atopic dermatitis or eczema (AD-E) in childhood. We searched the databases of PubMed, Embase, CENTRAL, Web of Science, and Scopus for cohort or case–control studies up to 25th June 2023. Random-effects meta-analysis was done to generate the odds ratio (OR) of the association between HDP/GDM and AD-E. Eight studies were included. Meta-analysis of five studies showed that GDM in the mother was associated with an increased risk of AD-E in the offspring (OR: 1.35 95% CI: 1.13, 1.61 I2 = 61%). Pooled analysis of four studies demonstrated no association between HDP and risk of AD-E in the offspring (OR: 1.03 95% CI: 0.99, 1.08 I2 = 0%). The results did not change on sensitivity analysis and subgroup analysis based on study type, method of AD-E diagnosis, and sample size. This meta-analysis suggests that GDM may significantly increase the risk of AD-E in childhood, however, HDP does not seem to impact the risk of AD-E. Evidence is limited by the small number of studies and high interstudy heterogeneity. Further studies are needed to improve the quality of evidence.

Abstract The apparent optimum air temperature for vegetation photosynthesis (Topt) is a key temperature parameter in terrestrial ecosystem models estimating daily photosynthesis or gross primary production (GPP, g C/m2/day). To date, most models use biome-specific Topt (Topt-biome) parameter values. Given vegetation acclimation and adaptation to local climate, site-specific Topt (Topt-site) is needed to reduce uncertainties in estimating daily GPP across the scales from site to region and the globe. Previous studies have demonstrated using the Enhanced Vegetation Index (EVI) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) images and daytime air temperature data to estimate the Topt-site at the eddy covariance tower sites. This study used MODIS-derived EVI and ERA5 climate data to estimate and generate global Topt-site data products from 2000 to 2019. The Topt-site of individual pixels within a biome has large variation, which clearly cannot be represented accurately by the widely used Topt-biome. Therefore, using this global dataset of Topt-site estimates might significantly affect GPP simulation in current ecosystem models.

Abstract Background Research on protein production holds significant importance in the advancement of food technology, agriculture, pharmaceuticals, and bioenergy. Aspergillus niger stands out as an ideal microbial cell factory for the production of food-grade proteins, owing to its robust protein secretion capacity and excellent safety profile. However, the extensive oxidative folding of proteins within the endoplasmic reticulum (ER) triggers ER stress, consequently leading to protein misfolding reactions. This stressful phenomenon results in the accelerated generation of reactive oxygen species (ROS), thereby inducing oxidative stress. The accumulation of ROS can adversely affect intracellular DNA, proteins, and lipids. Result In this study, we enhanced the detoxification of ROS in A. niger (SH-1) by integrating multiple modules, including the NADPH regeneration engineering module, the glutaredoxin system, the GSH synthesis engineering module, and the transcription factor module. We assessed the intracellular ROS levels, growth under stress conditions, protein production levels, and intracellular GSH content. Our findings revealed that the overexpression of Glr1 in the glutaredoxin system exhibited significant efficacy across various parameters. Specifically, it reduced the intracellular ROS levels in A. niger by 50%, boosted glucoamylase enzyme activity by 243%, and increased total protein secretion by 88%. Conclusion The results indicate that moderate modulation of intracellular redox conditions can enhance overall protein output. In conclusion, we present a strategy for augmenting protein production in A. niger and propose a potential approach for optimizing microbial protein production system.

Previous studies inferred that the synthesis rate/efficiency of protein in body tissue is probably affected by synchronicity of different amino acid (AA) supply in its metabolic pool. In order to further observe the influence of synchronicity of AA supply on the synthesis of protein in cell level, a cell culture experiment in vitro was conducted with C2C12 myotubes. C2C12 myotubes were cultured for 24 h, meanwhile the culture medium was replaced for each 8 h. Those myotubes were subjected to 3 treatments (1 for controlled and 2 for tested), control myotubes were cultured with same normal complete medium within the whole 24 h, and the 2 tested myotubes were cultured with asynchronous amino acid supply medium in which the levels of different AAs (Lysine, threonine, methionine, leucine, valine and glutamic acid) either increased and then decreased or decreased and then increased, at different replaced medium time point (at 0, 8, and 16 h). However, during the whole experiment period all the 3 treated myotubes received same amount of each AA. The sample of the myotubes were used for myotube morphology, protein, AA, and proteomic analysis. The results showed that asynchronous AA nutrition affect the synthesis and degradation of myotube proteins, and the AAAS in the medium increase, thus decreasing the synthesis rate of myotube proteins (p

Abstract The carbon sink in pantropical biomes play a crucial role in modulating the inter‐annual variations of global terrestrial carbon balance and is threatened by extreme climate events. However, it has not been carefully examined whether an increase in tropical gross primary productivity (GPP) can compensate the decrease during precipitation anomalies. Using the asymmetry index (AI) and multiple GPP products, we assessed responses of pantropical GPP to precipitation anomalies during 2001–2022. Positive AI indicates that GPP increases are greater than GPP decreases during precipitation anomalies, and vice versa. Our results showed an average negative pantropical GPP asymmetry, that is, GPP decreases exceeded the GPP increases during precipitation anomalies. In addition, a positive AI was found in tropical hyper‐arid and arid regions, which is opposite to the negative AI observed in tropical semi‐arid, sub‐humid, and humid regions. This suggest that tropical GPP asymmetry changes from positive to negative as the moisture increases. Notably, a significant decreasing trend of negative AI was observed over the entire tropical region, indicating that the negative effect of inter‐annual precipitation variations on pantropical vegetation productivity has enhanced. Considering the model predicted increasing climate variability and extremes, the negative impact of precipitation variability on tropical carbon cycle may continue to intensify. Lastly, the divergence in AI estimates among multiple GPP products highlight the need to further improve our understanding of the response of tropical carbon cycle to climate changes, especially for the tropical humid regions.

Background: Studies about the combined effects of gaseous air pollutants and particulate matters are still rare. Objectives: This study was performed based on baseline survey of the Diverse Life-Course Cohort in the Beijing-Tianjin-Hebei (BTH) Region of North China to evaluate the association of long-term air pollutants with blood pressure and the combined effect of the air pollutants mixture among 32821 natural han population aged 20 years or above. Methods: Three-year average exposure to air pollutants (PM10, PM2.5, PM1, O3, SO2, NO2, and CO) and PM2.5 components [black carbon (BC), ammonium (NH4+), nitrate (NO3−), sulfate (SO42−), and organic matter (OM)] of residential areas were calculated based on well-validated models. Generalized linear mixed models (GLMMs) were used to estimate the associations of air pollutants exposure with the systolic blood pressure (SBP), diastolic blood pressure (DBP), Mean arterial pressure (MAP), pulse pressure (PP) and prevalent hypertension. Quantile g-Computation and Bayesian Kernel Machine Regression (BKMR) were employed to assess the combined effect of the air pollutant mixture. Results: We found that long-term exposures of O3, PM2.5, and PM2.5 components were stably and strongly associated with elevated SBP, DBP, and MAP and prevalent hypertension. O3 increased SBP, DBP, and MAP at a similar extent, but with greater effects; while, PM2.5 and PM2.5 components had a greater impact on SBP than DBP, which increased PP simultaneously. In multi-pollutant models, the combined effects of the air pollutant mixture on blood pressure and prevalent hypertension was predominantly influenced by O3, PM2.5, and O3, OM in different models, respectively. For example, O3, PM2.5 contributed 57.25 %, 39.22 % of the positive combined effect of the air pollutant mixture on SBP; and O3, OM positively contributed 70.00 %, 30.00 % on prevalent hypertension, respectively. There were interactions between O3, CO, SO2 and PM2.5 components on hbp, SBP and PP. Conclusions: The results showed positive associations of air pollutant mixtures with blood pressure, where O3 and PM2.5 (especially OM) might be primary contributors. There were interactions between gaseous air pollutants and PM2.5 components on blood pressure and prevalent hypertension.

Objective: This study aimed to investigate the nutrient composition and the optimal enzymatic conditions for the peptides of Aspongopus and lay the groundwork for the creation of Aspongopus protein resources. Methods: The fat, protein, crude polysaccharide content, and fatty acid composition were determined according to the national standard method, and the total flavonoid and polyphenol content was determined by the standard curve method. Response surface methodology was used to optimize the enzymatic process conditions of Aspongopus based on the peptide yield; Amino acid analyzer and high-performance gel permeation chromatography was used to determine the amino acid composition and the relative molecular mass distribution of Aspongopus digest; The scavenging ability of Aspongopus digest of DPPH radicals and ABTS+ radicals as well as the total reducing ability were investigated. Results: Aspongopus crude fat content was 43.40%, and protein content was 37.08%; The contents of total sugar, total flavonoids and total phenols were 7.64%, 1.67%, 1.90% respectively; The optimum enzymatic digestion process of Aspongopus was stewing for 5 h and then digesting for was 6 h at pH 10 and 55 ℃, and the peptide yield was 35.74% under these conditions. The ratio of essential amino acids to non-essential amino acids of Aspongopus digest was 70.46%, the percentage of Aspongopus digest relative molecular mass + clearance rate was 88.44% at the concentration of 1.0 mg/mL of the enzymatic digest of Aspongopus. Conclusion: Under the control of the optimal procession conditions, the peptide yield of Aspongopus was 35.74%, with high nutritional value and good antioxidant activity.

Flavor compounds are important indicators of edible quality and nutritional value of corn. The quality deterioration of corn during storage is closely related to its flavor compounds. Corn samples harvested in four years from 2019 to 2022 were detected by solid phase microextraction-gas chromatography-triple quadrupole mass spectrometry (SPME-GC-MS/MS), and multivariate statistical analysis of flavor compounds relative content was carried out by principal component analysis and partial least squares discriminant analysis. The results showed that 129 volatile flavor compounds were detected in corn, including alcohols, aldehydes, ketones, esters, benzenes, heterocycles, acids, ethers, hydrocarbons and phenols. The multivariate statistical analysis showed that volatile flavor compounds and storage years of corn were correlated. According to the importance of variable projection, 47 compounds had significant diversity between corn samples with various storage years. Among them, the relative contents of 1-octen-3-ol, neryl butyrate and 2-pentylfuran increased with the extension of corn storage years, while the relative content of pantolactone, methyl octanoate and 2-acetylfuran decreased with the extension of corn storage years. These 6 compounds were identified as characteristic differential compounds. The partial least squares discriminant analysis classification model was constructed, and had good discrimination for corn storage years (R2=0.99, Q2=0.97, prediction accuracy was 1). The model will provide technical means for dynamic monitoring of corn storage quality, which is of great significance for ensurance national food security and reduce grain loss.

Abstract Bleeding and thrombosis are known as common complications of polycythemia for a long time. However, the role of coagulation system in erythropoiesis is unclear. Here, we discover that an anticoagulant protein tissue factor pathway inhibitor (TFPI) plays an essential role in erythropoiesis via the control of heme biosynthesis in central macrophages. TFPI levels are elevated in erythroblasts of human erythroblastic islands with JAK2 V617F mutation and hypoxia condition. Erythroid lineage-specific knockout TFPI results in impaired erythropoiesis through decreasing ferrochelatase expression and heme biosynthesis in central macrophages. Mechanistically, the TFPI interacts with thrombomodulin to promote the downstream ERK1/2-GATA1 signaling pathway to induce heme biosynthesis in central macrophages. Furthermore, TFPI blockade impairs human erythropoiesis in vitro, and normalizes the erythroid compartment in mice with polycythemia. These results show that erythroblast-derived TFPI plays an important role in the regulation of erythropoiesis and reveal an interplay between erythroblasts and central macrophages.

【Objective】The study aims to explore the change law of fruit quality of the main citrus varieties in Ruili area of Yunnan Province during maturity, offering a theoretical foundation for identifying the appropriate time for fruit harvesting.【Method】Four citrus varieties including Orah, Bingtang, Murcott, and W·Murcott were used as tested materials. Fruits were harvested 150-330 d after flowering (August 12, 2020 to February 8, 2021) and 240-405 d after flowering (November 8, 2021 to April 28, 2022). Samples were taken every fifteen days routinely, and the quality of the fruits was determined.【Result】The single fruit quality and the fruit horizontal and longitudinal diameters of the four citrus varieties exhibited a trend of growing first and then flattening as the maturity of fruits. Orah, Bingtang, Murcott and W·Murcott fruits terminated their rapid growth and expansion period before 270, 255, 300 and 285 days after flowering, respectively. In a span of two years, except for Murcott (with transition period being consistent in the first and the second year), the color transition period of W·Murcott peel was earlier in the first year, and the color transition period of Orah and Bingtang was later than the first year. Bingtang, Orah, Murcott and W·Murcott all showed stable mass fractions of total soluble solids content (TSS) after 240, 315, 300 and 270 days of flowering, respectively; while the mass fractions of titratable acid content (TA) showed no significant change at 180, 210, 240 and 240 d of flowering, respectively.【Conclusion】Combining the indicators such as single fruit weight, horizontal and longitudinal diameter, peel colour, and mass fraction of internal substance content, the fruits of Orah, Bingtang, Murcott, and W·Murcott reach harvest maturity at 315, 255, 300, and 285 d after flowering, which are suitable for harvesting.

Abstract Previous studies have shown that the three-dimensional (3D) geometric and electronic structure of molecules play a crucial role in determining their key properties and intermolecular interactions. Therefore, it is necessary to establish a quantum chemical (QC) property database containing the most stable 3D geometric conformations and electronic structures of molecules. In this study, a high-quality QC property database, called QuanDB, was developed, which included structurally diverse molecular entities and featured a user-friendly interface. Currently, QuanDB contains 154,610 compounds sourced from public databases and scientific literature, with 10,125 scaffolds. The elemental composition comprises nine elements: H, C, O, N, P, S, F, Cl, and Br. For each molecule, QuanDB provides 53 global and 5 local QC properties and the most stable 3D conformation. These properties are divided into three categories: geometric structure, electronic structure, and thermodynamics. Geometric structure optimization and single point energy calculation at the theoretical level of B3LYP-D3(BJ)/6-311G(d)/SMD/water and B3LYP-D3(BJ)/def2-TZVP/SMD/water, respectively, were applied to ensure highly accurate calculations of QC properties, with the computational cost exceeding 107 core-hours. QuanDB provides high-value geometric and electronic structure information for use in molecular representation models, which are critical for machine-learning-based molecular design, thereby contributing to a comprehensive description of the chemical compound space. As a new high-quality dataset for QC properties, QuanDB is expected to become a benchmark tool for the training and optimization of machine learning models, thus further advancing the development of novel drugs and materials. QuanDB is freely available, without registration, at https://quandb.cmdrg.com/ .

Abstract Background The identification of essential proteins can help in understanding the minimum requirements for cell survival and development to discover drug targets and prevent disease. Nowadays, node ranking methods are a common way to identify essential proteins, but the poor data quality of the underlying PIN has somewhat hindered the identification accuracy of essential proteins for these methods in the PIN. Therefore, researchers constructed refinement networks by considering certain biological properties of interacting protein pairs to improve the performance of node ranking methods in the PIN. Studies show that proteins in a complex are more likely to be essential than proteins not present in the complex. However, the modularity is usually ignored for the refinement methods of the PINs. Methods Based on this, we proposed a network refinement method based on module discovery and biological information. The idea is, first, to extract the maximal connected subgraph in the PIN, and to divide it into different modules by using Fast-unfolding algorithm; then, to detect critical modules according to the orthologous information, subcellular localization information and topology information within each module; finally, to construct a more refined network (CM-PIN) by using the identified critical modules. Results To evaluate the effectiveness of the proposed method, we used 12 typical node ranking methods (LAC, DC, DMNC, NC, TP, LID, CC, BC, PR, LR, PeC, WDC) to compare the overall performance of the CM-PIN with those on the S-PIN, D-PIN and RD-PIN. The experimental results showed that the CM-PIN was optimal in terms of the identification number of essential proteins, precision-recall curve, Jackknifing method and other criteria, and can help to identify essential proteins more accurately.

Economic security, as a key aspect of state strategy, continues to remain at the forefront of political research and public debates. In light of contemporary global challenges, including geopolitical tensions and economic disruptions such as the COVID-19 pandemic and Russia’s war against Ukraine in 2022, which continues to cause significant harm to the lives, security, and health of individuals in Ukraine and other countries, it is important to consider not only macroeconomic indicators but also the individual economic conditions of citizens. This study is based on data obtained within the framework of the seventh wave of the World Values Survey (WVS), conducted in South Korea. I applied the ordered logit regression (OLR) method and conducted statistical analysis using Stata software to explore the relationship between objective and subjective indicators of individuals and the consequences of subjective feelings of anxiety, level of happiness on the perception of one’s own health. The obtained results clearly demonstrate a strong positive correlation between individuals’ personal economic indicators and their subjective sense of satisfaction and happiness. This indicates that individual economic conditions significantly influence psychological well-being and overall life satisfaction. Moreover, data analysis highlights the need for the development and implementation of effective social programs and strategies aimed at supporting citizens’ economic well-being. Thus, there is a call for active government involvement in creating conditions to improve the economic status of the population with the aim of enhancing happiness levels and overall societal well-being, particularly for those countries with abundant resources to ensure economic prosperity but instead of prioritizing the economic security of their citizens, focus on external threats and under the pretext of security initiate wars against other countries. It is recommended to adopt an approach that balances attention to macroeconomic aspects with consideration of individual citizens’ needs, thereby contributing to sustainable and harmonious societal development. The scientific findings of this study can serve as a basis for the development and implementation of more effective social and economic policy strategies aimed at improving citizens’ quality of life and public welfare.

Polysaccharides are the main active ingredients of edible fungi, which have been widely utilized in the food industry. As a member of the truffle family, Tuber are rich in polysaccharides. Previous studies mainly focused on solvent, ultrasound-assisted, microwave-assisted, enzyme-assisted and pressurized liquid extractions regarding the extraction methods of Tuber polysaccharides. The molecular weight, monosaccharide composition and content, configuration, and ligation mechanism of sugar residues, along with the polysaccharide types of Tuber polysaccharides, have all been studied in relation to the characterization of chemical structures. Additionally, the antioxidant, antitumor, hypoglycemia, anti-fatigue, and immunomodulatory activities have been evaluated as well. In food processing, polysaccharides have been currently applied in the production of pastries and lozenges. Therefore, the purpose of this research is to discuss the most current developments in extraction techniques, including chemical structures, functional properties, and applications of Tuber polysaccharides. This provides a theoretical foundation for future growth in their food applications.

Abstract Background Acute lung injury (ALI) is a fatal respiratory disease caused by overreactive immune reactions (e.g., SARS-CoV-2 infection), with a high mortality rate. Its treatment is often compromised by inefficient drug delivery barriers and insufficient potency of the currently used drugs. Therefore, developing a highly effective lung-targeted drug delivery strategy is a pressing clinical need. Results In this study, the micro-sized inclusion cocrystal of asiatic acid/γ-cyclodextrin (AA/γCD, with a stoichiometry molar ratio of 2:3 and a mean size of 1.8 μm) was prepared for ALI treatment. The dissolution behavior of the AA/γCD inclusion cocrystals followed a “spring-and-hover” model, which meaned that AA/γCD could dissolve from the cocrystal in an inclusion complex form, thereby promoting a significantly improved water solubility (nine times higher than free AA). This made the cyclodextrin-based inclusion cocrystals an effective solid form for enhanced drug absorption and delivery efficiency. The biodistribution experiments demonstrated AA/γCD accumulated predominantly in the lung (Cmax = 50 µg/g) after systemic administration due to the micron size-mediated passive targeting effect. The AA/γCD group showed an enhanced anti-inflammatory therapeutic effect, as evidenced by reduced levels of pro-inflammatory cytokines in the lung and bronchoalveolar lavage fluids (BALF). Histological examination confirmed that AA/γCD effectively inhibited inflammation reactions. Conclusion The micro-sized inclusion cocrystals AA/γCD were successfully delivered into the lungs by pulmonary administration and had a significant therapeutic effect on ALI. Graphic abstract

Molecular conformations generation (MCG) aims to efficiently obtain reasonable and stable three-dimensional (3D) atomic coordinates of the atoms in the molecule from scratch, providing a structural foundation for molecular representation learning models and advanced downstream molecular design tasks such as molecular property prediction, molecular generation, and molecular docking. Existing MCG methods mostly rely on indirect distance-based strategies, which which can result in geometrically unrealistic conformations, or direct coordinate-based methods, which have larger search spaces and are prone to overfitting. Therefore, this study introduces Conf-GEM, a novel geometric information-assisted direct conformation generation model based on E-GeoGNN, a geometrically augmented 3D graph neural network with multiple scales. Pre-training and divide-and-conquer strategies, are integrated into the proposed model. Conf-GEM outperforms RDKit and nine deep-learning-based MCG models on the GEOM-QM9 and GEOM-Drugs datasets, achieving conformational coverage of 96.69% and 96.07%, respectively, without force field optimization. It also excels on the X-ray diffraction crystal structure dataset with up to 97.04% conformational coverage. In conclusion, Conf-GEM provides a novel solution for stabilizing 3D conformations generation. We provide an online prediction service (https://confgem.cmdrg.com) with a user-friendly interface for researchers.

Commented article: LIU, Z. Y. The concept of music education from a philosophical perspective. Trans/Form/Ação: revista de filosofia da Unesp, v. 47, n. 5, “Eastern thought 2”, e02400161, 2024. Available at: https://revistas.marilia.unesp.br/index.php/transformacao/article/view/15083.

Abstract Addition of organic compounds containing O/N heteroatoms to aqueous electrolytes such as ZnSO4 (ZS) solutions is one of the effective strategies to inhibit Zn anode dendrites and side reactions. However, addressing the stability of Zn plating/stripping at high current densities and areal capacities by this method is still a challenge, especially in capacitors known for high power and long life. Herein, an organic heterocyclic compound of 1, 4, 7, 10‐tetraazacyclododecane (TC) containing four symmetrically distributed N atoms is employed as ZS additive, expanding the life of Zn anodes from ≈ 30 h to 1000 and 240 h at deep plating/stripping conditions of 10 and 20 mA cm−2/mAh cm−2, respectively; the cumulative capacity is as high as 5.0 Ah cm−2 with 99% Coulombic efficiency, far exceeding reported additives. TC with higher binding energies than H2O for Zn species tends to adsorb to Zn (002) in a lying manner and participate in the solvation shell of Zn2+, thus avoiding Zn dendrites and side‐reaction damage, especially at high current densities. The TC‐endowed Zn anode's stability under such extreme conditions is verified in Zn‐ion capacitors (i.e., > 94.6% capacity retention after 28 000 cycles), providing new insights into the development of high‐power Zn‐based energy storage devices.

The combination of well-balanced mechanical performance, high transparency and appealing eco-friendly attributes endows poly(lactic acid) (PLA) with significantly potential for wide-ranging applications in high-value packaging sectors. However, effectively toughening PLA without compromising its transparency and stiffness remains a formidable challenge. In this study, we synthesized a series of graft copolymers by incorporating hydroxyl-functionalized linear low density polyethylene (LLDPEOH) and copolymers of cycloolefin (COCOH) as the main chain and PLA as the side chain, which were subsequently employed as novel toughening agents for commercial PLA. The achievement of high-performance PLA blends with a balanced combination of toughness, strength, and transparency can be realized through meticulous tuning of the structure and mass fraction of the blended graft copolymers. The maximum elongation at break for the PLA blends increased by about 50 times that of neat PLA, reaching up to 300 %. Furthermore, these materials retained their high strength (54 MPa) and excellent transparency (light transmittance up to 90 %). The excellent properties of PLA blends could be ascribed to the well-designed chain structure of the graft copolymer which leaded to and excellent compatibility with the PLA matrix and unique phase morphology. This work is significant in guiding the design and synthesis of graft copolymers as toughening agents for PLA, thereby expanding its application range in areas where high transparency and toughness are required.

This study investigates the long-term performance of laboratory dam concrete in different curing environments over ten years and the microstructure of 17-year-old laboratory concrete and actual concrete cores drilled from the Three Gorges Dam. The mechanical properties of the laboratory dam concrete, whether cured in natural or standard environments, continued to improve over time. Furthermore, the laboratory dam concrete exhibited good resistance to diffusion and a refined microstructure after 17 years. However, curing and long-term exposure to the local natural environment reduced the frost resistance. Microstructural analyses of the laboratory concrete samples demonstrated that moderate-heat cement and fine fly ash (FA) particles were almost fully hydrated to form compact microstructures consisting of large quantities of homogeneous calcium (alumino)silicate hydrate (C-(A)-S-H) gels and a few crystals. No obvious interfacial transition zones were observed in the microstructure owing to the long-term pozzolanic reaction. This dense and homogenous microstructure was the crucial reason for the excellent long-term performance of the dam concrete. A high FA volume also played a significant role in the microstructural densification and performance growth of dam concrete at a later age. The concrete drilled from the dam surface exhibited a loose microstructure with higher microporosity, indicating that concrete directly exposed to the actual service environment suffered degradation caused by water and wind attacks. In this study, both macro-performance and microstructural analyses revealed that the application of moderate-heat cement and FA resulted in a dense and homogenous microstructure, which ensured the excellent long-term performance of concrete from the Three Gorges Dam after 17 years. Long-term exposure to an actual service environment may lead to microstructural degradation of the concrete surface. Therefore, the retained long-term dam concrete samples need to be further researched to better understand its microstructural evolution and development of its properties.

In the last few years, Transformer has revolutionized the area of medical image segmentation. Several similar studies have used the UNet architecture to combine convolutional neural networks with transformers. However, these approaches fail to account for the speed at which segmentation occurs and the ability to extract features within the Transformer. They fail to consider the fact that changing the shape of the feature maps in a subtle way can be used for rapid extraction of local and global information. To solve the above problems, CTBANet (Convolutional Transformer and Bidirectional Attention Based for Medical Image Segmentation) is proposed, which has two prominent components, CTblock (Convolutional Combined Transformer module) and BAblock (Bidirectional Attentionblock). CTblock integrates the strengths of CNNs and Transformers, enabling it to extract spatial details and global data. In order to improve the speed and accuracy of the model, multi-scale pyramid pooling is embedded into PAM, named APAM (Asymmetric PAM), and strip convolution is embedded into CAM, named ACAM (Asymmetric CAM). Medical image segmentation is a critical issue in the medical field, and the experimental results of the benchmarks show that our model is obviously more accurate and faster than the other methods in segmenting medical images.

Accurately estimating gross primary production (GPP) in terrestrial ecosystems is crucial for gaining a deeper understanding of the carbon cycle within the ecosystem and for predicting climate change. Although many GPP datasets are available, they often have low resolution, typically around 500 m or lower, which restricts their effectiveness in monitoring fragmented croplands and areas with high heterogeneity. In this study, we utilized optical satellite data from Landsat-8/9 and Sentinel-2A/B, along with meteorological data from ERA5, to generate a GPP dataset with a spatial resolution of 30 m for three provinces in Northeast China. This dataset was developed based on the Vegetation Photosynthesis Model and exhibited robust validation results when compared with SIF data and other existing GPP datasets. It provides a high-resolution GPP product that significantly enhances the precision of carbon cycle research in Northeast China. This research underscores the feasibility of producing high spatial resolution GPP products using Landsat-8/9 and Sentinel-2A/B optical satellite data. The resulting dataset offers a more refined GPP estimate for studies related to the terrestrial carbon cycle.

Abstract Objectives To explore the prevalence and associated factors of obesity in Tibetan adults in Qinghai, China, and to determine the association between the FTO (rs1121980 and rs17817449) and MC4R gene (rs17782313 and rs12970134) polymorphisms with obesity. Methods A cross-sectional survey was conducted in 2015 in Qinghai to selected Tibetan adults aged 20 to 80 years. Prevalence of obesity (BMI ≥ 28 kg/m2) and overweight (BMI 24 ~ 27.9 kg/m2) were evaluated. Multivariable logistic models were used to determine the associated factors. Pair-matched subjects of obesity cases and normal-weight controls were selected for the gene polymorphism analyses. Conditional logistic models were used to assess the association between gene polymorphisms with obesity. Additive and multiplicative gene-environment interactions were tested. Results A total of 1741 Tibetan adults were enrolled. The age- and sex- standardized prevalence of obesity and overweight was 18.09% and 31.71%, respectively. Male sex, older age, heavy level of leisure-time exercise, current smoke, and heavy level of occupational physical activity were associated with both obesity and overweight. MC4R gene polymorphisms were associated with obesity in Tibetan adults. No significant gene-environment interaction was detected. Conclusion The prevalence of obesity and overweight in Tibetan adults was high. Both environmental and genetic factors contributed to the obesity prevalent.

BackgroundThe current rate of organ donation in China falls significantly below the global average and the actual demand. Nursing students play a crucial role in supporting and promoting social and public welfare activities. This study primary aims to analyze the levels of knowledge, attitudes, willingness toward organ donation, and attitudes toward death among nursing students, and investigate the mediating role of attitude in the relationship between knowledge and willingness. The secondary aims to identify factors that may influence the willingness.MethodsA convenience sample of nursing students completed online-administered questionnaires measuring the level of knowledge, attitudes, and willingness toward organ donation before and after clinical internship. Spearman correlation and mediation analyses were used for data analyses.ResultsBefore the clinical internship, there were 435 nursing students who had not yet obtained their degrees and were completing their clinical internships. After the internship, this number decreased to 323. The mean score for knowledge before and after the clinical internship (7.17 before and 7.22 after, with no significant difference), the attitude (4.58 before and 4.36 after, with significant difference), the willingness (12.41% before and 8.67% after, with significant difference), the Death Attitude Profile-Revised (DAP-R) score (94.41 before and 92.56 after, with significant difference). The knowledge indirectly affected nursing students’ willingness to organ donation through attitude. Knowledge had a direct and positive impact on attitudes (β = 1.564). Additionally, nursing students’ attitudes positively affected their willingness (β = 0.023). Attitudes played a mediating role in the relationship between knowledge and willingness (β = 0.035). Additionally, attitude toward death, fear of death, and acceptance of the concept of escape were found to be correlated with their willingness.ConclusionOrgan donation willingness was found to be low among nursing students. Positive attitudes were identified as a mediating factor between knowledge and willingness. Additionally, DAP-R was a related factor. Therefore, it is recommended to focus on improving knowledge and attitude, as well as providing death education to help nursing students establish a positive attitude toward death. These efforts can contribute to the promotion of organ donation.

Abstract ‘Shuijingmiyou’ pummelo (SJ), one of the most popular fruits in Yunnan province of China, is of relatively low fruit shape (FS) quality. In this study, we compared the FS promoting effects of cross pollinations using pollens from seven pummelo varieties, and found that ‘Guanximiyou’ pummelo (GX) cross-pollination showed the best FS promoting effects on SJ fruits by shortening its fruit neck. To explore the underlying mechanism, physiochemical and transcriptomic differences between self- and cross-pollinated SJ ovaries (SJO and GXO) were investigated. Higher salicylic acid, gibberellin and indole acetic acid contents and superoxide dismutase, peroxidase and catalase activities, and lower polyphenol oxidase activity were determined in GXO compared with SJO. Enrichment analysis of the identified 578 differentially expressed genes (123 up-regulated and 455 down-regulated) in GXO showed that genes involved in solute transport, RNA biosynthesis, phytohormone action and cell wall organization were significantly enriched. The results obtained in this study will be helpful in understanding the influences of cross-pollination on pummelo ovary and fruit development, and can provide the basis for clarifying the underlying mechanism of cross-pollination improved fruit quality.

Megalurothrips usitatus (Bagnall, 1913) (Thysanoptera: Thripidae) is a widely distributed pest in Asia that primarily affects the production of snap beans and cowpea. The complete mitochondrial genome of Megalurothrips usitatus has been sequenced and annotated in this study, which is 17,209 bp long and contains 13 protein-coding genes (PCGs), two rRNAs, and 22 tRNA genes. Most of the protein-coding genes (PCGs) start with ATG except ND4 using TTG. Meanwhile, eight PCGs stop with TAA, four PCGs have an incomplete stop codon, and the gene Cytb ends with TAG. Phylogenetic analysis showed that M. usitatus is closely related to Frankliniella intonsa and F. occidentalis, providing a basis for the study of the mitochondrial evolution of Thripinae.

Abstract Vaccination with E2 subunit vaccines is currently the main measure to control classical swine fever virus (CSFV), which is an endemic disease, and detection of antibodies against CSFV E2 is the most effective way to evaluate herd immunity. In the present study, the E2 protein was expressed by a baculovirus expression system, and two monoclonal antibodies (mAbs), namely, 3A9 and 4F7, were successfully produced using techniques for the isolation of single B cells from splenocytes from mice immunized with the E2 protein. Moreover, two linear B-cell epitopes, 25GLTTTWKEYSHDLQL39 and 259GNTTVKVHASDERGP273, reactive to 3A9 and 4F7, respectively, were identified using epitope mapping of the E2 protein. In addition, the diagnostic performance of the two mAbs was evaluated using blocking enzyme-linked immunosorbent assay (bELISA), and the results showed that the two mAbs had high diagnostic specificity (96.08%, 94.38%) and diagnostic sensitivity (97.49%, 95.97%). Together, these findings identify two ideal candidate peptides and matching mAbs for a new method of CSFV diagnosis, which will contribute to the control and eradication of classical swine fever.

Digital sports, also known as online sports, are a new form of sport that users have tried in recent years. Despite the rapid growth of online sports, the factors influencing users’ willingness to sustain their use are currently unknown. Based on the theory of planned behavior (TPB) and expectation-confirmation theory (ECT), this study empirically investigates the factors influencing the persistent use of online sports videos. Questionnaires were administered to participants. A total of 305 participants completed the questionnaire. Structural equation modeling showed that all hypotheses’ paths were significant, except for H11 and H12. The results indicated that perceived usefulness, expectation confirmation, and coach social presence had a significant positive effect on users’ satisfaction in using online sports videos. Moreover, satisfaction, behavioral attitudes, subjective norms, and perceived behavioral control had a significant positive effect on users’ willingness to consistently use online sports videos, with gender moderating the impact of satisfaction and behavioral attitudes on the willingness to consistently use. We discuss the practical implications and recommendations for applying this study’s findings.

Sarcasm is a complex implicit emotion that poses a significant challenge in sentiment analysis, particularly in social network sentiment analysis.Effective sarcasm detection holds immense practical significance in the analysis of network public opinion.The contradictory nature of sarcastic texts, which exhibit implicit semantics opposite to the real emotions of users, often leads to misclassification by traditional sentiment analysis methods.Moreover, sarcasm in daily communication is often conveyed through non-textual cues such as intonation and demeanor.Consequently, sarcasm detection methods solely relying on text semantics fail to incorporate non-textual information, thereby limiting their effectiveness.To leverage the power of text semantics and social behavior information, a sarcasm text detection method based on heterogeneous graph information fusion was proposed.The approach involved the construction of a heterogeneous information network encompassing users, texts, and emotional words.A graph neural network model was then designed to handle the representations of the heterogeneous graph.The model employed a dual-channel attention mechanism to extract social behavior information, captured the deep semantics of text through emotional subgraphs, and ultimately combined text semantics and social behavior information.Extensive experiments conducted on the Twitter dataset demonstrate the superiority of the proposed method over existing approaches for sarcasm text detection and classification.

Abstract Background Hand grip strength (HGS) is a powerful indicator of sarcopenia and other adverse health outcomes. Normative values for HGS for general Chinese people with a broad age spectrum are lacking. This study aims to establish normative values of HGS and explore the correlations between HGS and body composition among unselected people aged 8–80 in China. Methods From 2012 to 2017, 39 655 participants aged 8–80 years in the China National Health Survey were included. Absolute HGS was measured using a Jamar dynamometer. The relative HGS was normalized by body mass index. Body composition indexes included body mass index, body fat percentage, muscle mass, fat mass index (FMI) and muscle mass index (MMI). Sex‐specific smoothed centile tables for the P1, P5, P25, P50, P75, P95 and P99 centiles of HGS and body composition were generated using lambda‐mu‐sigma method. The correlations between muscle strength and body composition were estimated by partial Spearman correlation analysis. Results The median values (25th and 75th percentile) of HGS in boys and girls (8–19 years old) were 22 (14, 34) kg and 18 (12, 22) kg, respectively; in men and women aged 20–80 were 39 (33, 44) kg and 24 (20, 27) kg, respectively. Values of upper and lower HGS across ages had three periods: an increase to a peak in the 20 s in men (with the 5th and 95th values of 30 and 55 kg, respectively) and 30 s in women (with the 5th and 95th values of 18 and 34 kg, respectively), preservation through midlife (20s–40 s), and then a decline after their 50 s. The lowest HGS values in both sexes were in the 70‐ to 80‐year‐old group, with the 5th and 95th percentile values of 16 and 40 kg in men, and 10 and 25 kg in women. There were substantial sex differences in body composition in the life course (all P values

Objective: To investigate the effect of combined repetitive peripheral magnetic stimulation and transcranial magnetic stimulation on upper extremity function in subacute stroke patients. Design: Pilot study. Subjects: Subacute stroke patients. Methods: Included patients were randomized into 3 groups: a central-associated peripheral stimulation (CPS) group, a central-stimulation-only (CS) group, and a control (C) group. The CPS group underwent a new paired associative stimulation (combined repetitive peripheral magnetic stimulation and transcranial magnetic stimulation), the CS group underwent repetitive transcranial magnetic stimulation, and the C group underwent sham stimulation. All 3 groups received physiotherapy after the stimulation or sham stimulation. The treatment comprised 20 once-daily sessions. Primary outcome was the Fugl-Meyer Assessment Upper Extremity (FMA-UE) score, and secondary outcomes were the Barthel Index and Comprehensive Functional Assessment scores, and neurophysiological assessments were mainly short-interval intracortical inhibition. A 3-group (CPS, CS, C) × 2-time (before, after intervention) repeated measures analysis of variance was conducted to determine whether changes in scores were significantly different between the 3 groups. Results: A total of 45 patients were included in the analysis. Between-group comparisons on the FMA-UE demonstrated a significant improvement (group × time interaction, F2,42 = 4.86; p = 0.013; C vs CS, p = 0.020; C vs CPS, p = 0.016; CS vs CPS, p = 0.955). Correlation analysis did not find any substantial positive correlation between changes in FMA-UE and short-interval intracortical inhibition variables (C, r = –0.196, p = 0.483; CS, r = –0.169, p = 0.546; CPS, r = –0.424, p = 0.115). Conclusion: This study suggests that the real-stimulus (CS and CPS) groups had better outcomes than the control (C) group. In addition, the CPS group showed a better trend in clinical and neurophysiological assessments compared with the CS group.

IntroductionRecently, researchers have begun to pay more attention to topics related to the adoption of mobile devices for supporting second or foreign language learning. Mobile-assisted language learning (MALL) is now prevalent among language learners and educators because of its convenient and enjoyable features. This study combined and extended the Technology Acceptance Model (TAM) and Expectation Confirmation Theory (ECT) to investigate the factors influencing English as a Foreign Language (EFL) students’ behavioral intentions to use MALL at two universities in Bangkok, Thailand.MethodsQuantitative methods were utilized in this study and the researchers obtained a total of 507 valid responses by using three-step sampling. After using confirmatory factor analysis (CFA) to determine that the study had enough construct validity, structural equation modeling (SEM) was applied to test the research’s hypotheses.ResultsThe findings revealed that all 15 hypotheses were supported, except that social influence cannot significantly influence behavioral intention.Discussion and implicationBy acquiring a deeper understanding of the factors that impact the behavioral intentions of language learners to utilize MALL, developers and providers can improve their capacity to design more enjoyable and effective applications that align with customer expectations and enhance financial gains. By understanding students’ behavioral intentions towards MALL, educators can efficiently raise awareness of its benefits and provide effective training, enabling students to utilize available resources and enhance their language learning experience.

This research examines the synchronized progression of regional logistics and environmental support systems in China’s central region. Utilizing a comprehensive evaluation index system, the study employs a combination of entropy methods, TOPSIS analysis, and coupling coordination modeling to assess the development levels of regional logistics and environmental support systems across six central provinces from 2011 to 2020. The analysis focuses on comprehensive scores, coupling coordination degrees, and spatiotemporal evolution characteristics. The results indicate a synergistic relationship between the two systems in the six central provinces, with both comprehensive scores and coupling coordination D values demonstrating consistent growth over time. The study reveals a coordinated and orderly developmental pattern in the coupling and coordination relationship between the six provinces and the two systems within the central region. The overall degree of coupling and coordination in the central region exhibits a well-coordinated status, with provinces ranked as follows: Henan > Anhui and Hubei > Hunan > Shanxi and Jiangxi. This ranking demonstrates a spatial characteristic of high coordination in the middle and lower coordination at both extremities. The research identifies the underdeveloped state of regional logistics as the primary limiting factor. From the notable findings, this study’s conclusions offer valuable insights for policy formulation regarding the coordinated development of regional logistics and environmental support systems in China’s central region.

Understanding the evolutionary dynamics of foodborne pathogens throughout host-associated habitats is of utmost importance. Bacterial pan-genomes, as dynamic entities, are strongly influenced by ecological lifestyles. As a phenotypically diverse species in the Bacillus cereus group, Bacillus paranthracis is recognized as an emerging foodborne pathogen and a probiotic simultaneously. This poorly understood species is a suitable study model for adaptive pan-genome evolution. In this study, we determined the biogeographic distribution, abundance, genetic diversity, and genotypic profiles of key genetic elements of B. paranthracis. Metagenomic read recruitment analyses demonstrated that B. paranthracis members are globally distributed and abundant in host-associated habitats. A high-quality pan-genome of B. paranthracis was subsequently constructed to analyze the evolutionary dynamics involved in ecological adaptation comprehensively. The open pan-genome indicated a flexible gene repertoire with extensive genetic diversity. Significant divergences in the phylogenetic relationships, functional enrichment, and degree of selective pressure between the different components demonstrated different evolutionary dynamics between the core and accessory genomes driven by ecological forces. Purifying selection and gene loss are the main signatures of evolutionary dynamics in B. paranthracis pan-genome. The plasticity of the accessory genome is characterized by horizontal gene transfer (HGT), massive gene losses, and weak purifying or positive selection, which might contribute to niche-specific adaptation. In contrast, although the core genome dominantly undergoes purifying selection, its association with HGT and positively selected mutations indicates its potential role in ecological diversification. Furthermore, host fitness-related dynamics are characterized by the loss of secondary metabolite biosynthesis gene clusters (BGCs) and CAZyme-encoding genes and the acquisition of antimicrobial resistance (AMR) and virulence genes via HGT. This study offers a case study of pan-genome evolution to investigate the ecological adaptations reflected by biogeographical characteristics, thereby advancing the understanding of intraspecific diversity and evolutionary dynamics of foodborne pathogens.

China is advancing its economic agenda by shifting from a resource and energy-intensive framework to one centered on digitalization and innovation, highlighting the digital economy as a cornerstone for sustainable, high-quality development. The coordinated development of the digital economy with high-quality development strategies is pivotal for achieving balanced regional growth. This analysis delves into these dynamics within Henan Province, utilizing sophisticated analytical tools such as the Entropy entropy-weighted topics method, Coupled Coordination Model, Dagum Gini coefficient, and panel Tobit regression to evaluate the spatial-temporal interplay and disparities in development, along with identifying critical determinants. The results indicate a nuanced landscape of coordination between the digital economy and high-quality development across Henan. The province exhibits a pattern of strong coupling but only moderate coordination, with distinct regional variations. Development is more pronounced in the western and northern regions compared to their eastern and southern counterparts, with Zhengzhou, emerging as a strategic center from which development radiates outward, progressively lessening from west to east and from north to south. Furthermore, while initial disparities between cities were relatively small, they have widened over time, with the most significant differences manifesting between various city groups. This divergence follows a distinct pattern, most markedly from west to north to south to east. Additionally, the study identifies that while the degree of digitalization positively correlates with enhanced coordination, factors such as economic robustness, government fiscal policies, and innovation capacity appear to impede it. Based on these findings, the study concludes with targeted strategic recommendations for policymakers. These recommendations aim to mitigate the development disparities and foster an integrated advancement of both the urban digital economy and high-quality economic growth across Henan Province.

Uncertainty exists widely in various fields, especially in industrial manufacturing. From traditional manufacturing to intelligent manufacturing, uncertainty always exists in the manufacturing process. With the integration of rapidly developing intelligent technology, the complexity of manufacturing scenarios is increasing, and the postdecision method cannot fully meet the needs of the high reliability of the process. It is necessary to research the pre-elimination of uncertainty to ensure the reliability of process execution. Here, we analyze the sources and characteristics of uncertainty in manufacturing scenarios and propose a meta-model architecture and uncertainty quantification (UQ) framework for uncertainty modeling. On the one hand, our approach involves the creation of a meta-model structure that incorporates various strategies for uncertainty elimination (UE). On the other hand, we develop a comprehensive UQ framework that utilizes quantified metrics and outcomes to bolster the UE process. Finally, a deterministic model is constructed to guide and drive the process execution, which can achieve the purpose of controlling the uncertainty in advance and ensuring the reliability of the process. In addition, two typical manufacturing process scenarios are modeled, and quantitative experiments are conducted on a simulated production line and open-source data sets, respectively, to illustrate the idea and feasibility of the proposed approach. The proposed UE approach, which innovatively combines the domain modeling from the software engineering field and the probability-based UQ method, can be used as a general tool to guide the reliable execution of the process.

Summary: The increasing demand for chemical raw materials has provided opportunities for the ammonia (NH3) industry. However, little attention has been devoted to the economic feasibility of renewable-to-ammonia (RE2A). Therefore, this paper proposes a technoeconomic model to research the optimal capacity configuration and quantify the levelized cost of ammonia (LCOA) for RE2A, which is a retrofitted plant based on coal-to-ammonia (C2A). A cost model of C2A is established as a benchmark to evaluate the economic feasibility of RE2A. A case study in Inner Mongolia is adopted, which shows that the monthly NH3 output is 7–11×103t, which satisfies actual industrial production. The LCOA of RE2A is 469$/t, with investment in wind turbines accounting for 58%, which is lower than the NH3 market price (605$–650$/t). The LCOA of RE2A will equal that of C2A with a carbon tax of 47.1$/t CO2, which confirms the economic advantages of RE2A in the future.

Autophagy selectively degrades viral particles or cellular components, either facilitating or inhibiting viral replication. Conversely, most viruses have evolved strategies to escape or exploit autophagy. Moreover, autophagy collaborates with the pattern recognition receptor signaling, influencing the expression of adaptor molecules involved in the innate immune response and regulating the expression of interferons (IFNs). The intricate relationship between autophagy and IFNs plays a critical role in the host cell defense against microbial invasion. Therefore, it is important to summarize the interactions between viral infections, autophagy, and the host defense mechanisms against viruses. This review specifically focuses on the interactions between autophagy and IFN pathways during viral infections, providing a comprehensive summary of the molecular mechanisms utilized or evaded by different viruses.

Abstract. Background:. The prevalence of hypertension is high among Chinese adults, thus, identifying non-hypertensive individuals at high risk for intervention will help to improve the efficiency of primary prevention strategies. Methods:. The cross-sectional data on 9699 participants aged 20 to 80 years were collected from the China National Health Survey in Gansu and Hebei provinces in 2016 to 2017, and they were nonrandomly split into the training set and validation set based on location. Multivariable logistic regression analysis was performed to develop the diagnostic prediction model, which was presented as a nomogram and a website with risk classification. Predictive performances of the model were evaluated using discrimination and calibration, and were further compared with a previously published model. Decision curve analysis was used to calculate the standardized net benefit for assessing the clinical usefulness of the model. Results:. The Lasso regression analysis identified the significant predictors of hypertension in the training set, and a diagnostic model was developed using logistic regression. A nomogram with risk classification was constructed to visualize the model, and a website (https://chris-yu.shinyapps.io/hypertension_risk_prediction/) was developed to calculate the exact probabilities of hypertension. The model showed good discrimination and calibration, with the C-index of 0.789 (95% confidence interval [CI]: 0.768, 0.810) through internal validation and 0.829 (95% CI: 0.816, 0.842) through external validation. Decision curve analysis demonstrated that the model was clinically useful. The model had a higher area under receiver operating characteristic curves in training and validation sets compared with a previously published diagnostic model based on Northern China population. Conclusion:. This study developed and validated a diagnostic model for hypertension prediction in Gansu Province. A nomogram and a website were developed to make the model conveniently used to facilitate the individualized prediction of hypertension in the general population of Han and Yugur.