From the perspective of individual resource and social capital, this paper aims to explain how employees’ political skill affect their job satisfaction and turnover intention, through the mediating role of popularity. Using a sample of 237 dyad surveys from supervisors and employees in the Yangtze River Delta of China, we found that: 1) political skill is positively correlated with job satisfaction and negatively correlated with turnover intention, and that these correlations are partially mediated by individual popularity; 2) positive affect (PA) moderates the relationship between political skill and job satisfaction, and negative affect (NA) moderates the relationship between political skill and turnover intention. The implications of our findings and future research directions are discussed.

As the largest energy consumer and carbon emitter, China has made substantial efforts to improve energy efficiency for decrease energy consumption, while the energy rebound effect determines its effectiveness. The embodied energy consumption of construction projects accounted for nearly one-sixth of the total economy's energy consumption in China. This paper is based on the logical relationship among capital input, technological progress, economic growth, and energy consumption, adapting an alternative estimation model to estimate the energy rebound effect for the construction industry in China for the first time. Empirical results in our paper reveal that the energy rebound effect for the construction industry in China is about 59.5% for the period of 1990–2014. The results indicate that the energy rebound effect does exist in China’s construction industry and it presented a fluctuating declining trend. This implies that half of the energy savings by technological progress is achieved. In addition, China’s government should implement proper energy pricing reforms and energy taxes to promote the sustainable development of China’s construction industry.

The load of power system changes with the development of economy, short-term load forecasting play a very important role in dispatching and management of power system. In this paper, the Ant Lion Optimizer (ALO) is introduced to improve the input weights and hidden-layer Matrix of extreme learning machine (ELM), after the parameters of ELM are optimized by ALO, then input nodes, hidden layer nodes and output nodes are determined, so a load forecasting model based on ALO-ELM combined algorithm is established. The proposed method is illustrated based on the historical load data of a city in China. The results show that the average absolute error of short-term load demand predicted by ALO-ELM model is 1.41, while that predicted by ELM is 4.34, the proposed ALO-ELM algorithm is superior to the ELM and meet the requirements of engineering accuracy, which proves the effectiveness of proposed method.

Drug-target affinity (DTA) prediction is crucial for understanding molecular interactions and aiding drug discovery and development. While various computational methods have been proposed for DTA prediction, their predictive accuracy remains limited, failing to delve into the structural nuances of interactions. With increasingly accurate and accessible structure prediction of targets, we developed a novel deep learning model, named S2DTA, to accurately predict DTA by fusing sequence and structural knowledge of drugs, targets, and pockets using heterogeneous models based on graph and semantic networks. Experimental findings underscored that complex feature representations imparted negligible enhancements to the model’s performance. However, the integration of heterogeneous models demonstrably bolstered predictive accuracy. In comparison to three state-of-the-art methodologies, the supremacy of S2DTA became strikingly apparent. It showcased a noteworthy 25.2% reduction in Mean Absolute Error (MAE) and an impressive 20.1% decrease in Root Mean Square Error (RMSE). Furthermore, S2DTA exhibited substantial advancements in other pivotal metrics, including Pearson Correlation Coefficient (PCC), Spearman, Concordance Index (CI), and R2. These metrics experienced remarkable increments of at least 19.6%, 17.5%, 8.1%, and a remarkable 49.4%, respectively. Finally, we conducted interpretability analysis on the effectiveness of S2DTA by bidirectional self-attention mechanism, fully proving that S2DTA is a valuable and accurate tool for predicting DTA. For further exploration, the source data and code repository can be accessed at https://github.com/dldxzx/S2DTA.

Hyperlipidaemia (HLP) is a disorder with disturbed lipid metabolism and a major risk factor for various diseases. This study focused on the effect of moxibustion with seed-sized moxa cone on HLP and the relative metabolites and pathways. Levels of total cholesterol (TC), triglyceride (TG) and low-density lipoprotein cholesterol (LDC-C) in healthy controls (HC), HLP patients, HLP patients before (BMT) and after (AMT) moxibustion treatment were measured. Using the liquid chromatograph-mass spectrometry (LC-MS) technique, we detected the plasma metabolites in the aforementioned groups. Pathway analysis was performed for the differential metabolites. Results revealed significantly high levels of TC, TG and LDC-C and low levels of HDC-C were measured in HLP compared to HC. After moxibustion treatment, the levels of TC and TG significantly decreased. Total 87 and 51 differential metabolites were identified in HLP vs HC and AMT vs BMT, respectively, and 21 were common differential metabolites. The differential metabolites in HLP vs HC and AMT vs BMT both significantly enriched in the pathways of Glycerophospholipid metabolism and Sphingolipid metabolism. In conclusion, moxibustion with seed-sized moxa cone effectively improved HLP, might be by affecting the levels of TC and TG, and the regulating of the Glycerophospholipid metabolismand Sphingolipid metabolism pathways.

Plant-derived diterpene synthases (PdiTPSs) play a critical role in the formation of structurally and functionally diverse diterpenoids. However, the specificity or promiscuity of PdiTPSs remains unclear. In order to gain more understanding of this, the sequences of 199 functionally characterized PdiTPSs and their corresponding 3D structures were collected and manually corrected. Then, the correlations among sequences, domains, structures and their corresponding products were comprehensively analyzed. However, those features alone was insufficient for ef-fective product-specific classification of PdiTPSs as these methods could not establish a clear mapping between the enzymes and products. Nevertheless, local structural analysis can identify residues that have been experimentally proven to influence product outcomes through mutagenesis, and these residues exhibit conservation in spatial positioning and physicochemical properties. And aromatic residues surrounding the substrate exhibited selectivity towards its chemical structure. Specifically, tryptophan (W) was preferentially located around the linear substrate geranylgeranyl pyrophosphate (GGPP), while phenylalanine (F) and tyrosine (Y) were preferentially located around the initial cyclized diterpene intermediate. This analysis revealed the functional space of residues surrounding the substrate of PdiTPSs, most of which have not been experimentally explored. These findings provide guidance for screening specific residues for mutation studies to change the catalytic products of PdiTPSs.

As two commonly-used non-selective herbicides, glyphosate (GP) and diquat (DQ) are easily co-resided in lateritic paddy soil due to the rich iron/aluminum oxides, nevertheless there is limited information on their co-impact on microbial diversity and community structure in this type soil. In this study, the short-term effects of combined GP and DQ on soil microbial diversity and community structure shifts were investigated in lateritic paddy soil from a tropical agricultural region (Hainan, China) based on 16S rRNA and ITS high-throughput sequencing technology. The results showed that mixed herbicides promoted the abundance of Streptomyces in bacteria (0.45-1.84%) and Curvularia in fungi (0.01-5.85%), while GP and DQ had inhibitory effects on the abundance of Streptomyces (0.13-2.21%) and Curvularia (0.03-1.13%), which were significantly different with their single exposure (p < 0.05); the combined application of the two herbicides aggravate the adverse effect on the diversity of soil fungal community (p < 0.05), although their mixture did not have a greater impact on the soil bacteria abundance/diversity and fungi abundance (p > 0.05). Results suggested that the combined application of GP and DQ affected the fungal diversity although they did not cause other significant negative effects on soil microorganisms, hinting that more attention should be paid to the mixed effect caused by GP and DQ on specific fungal populations in lateritic paddy soil.

To further explore the bearing capacity and sustainable construction of vacuum drainage pipe (VDP) piles, field tests were carried out to compare and analyze the ultimate single pile bearing capacity, pile side friction and pile end resistance of ordinary piles and vacuum drainage pipe piles. The effect of the VDP pile on energy conservation and emission reduction in practical projects is discussed. The results shows that the VDP pile basically eliminated the soil squeeze and did not cause excessive relative displacement of pile and soil after vacuum consolidation. The VDP pile enhances pile side friction resistance, resulting in a 17.6% increase in ultimate bearing capacity compared to traditional piles. The VDP pile method can reduce carbon emissions by 31.4% compared to traditional methods. This study provides guidance for the production and design of VDP piles in the future and demonstrates their potential for energy conservation and emission reduction benefits compared to traditional methods.

Although several protocols for genetic transformation of citrus have been published, it is highly desirable to further improve its efficiency. Here we report treatments of Agrobacterium cells and citrus explants prior to and during co-cultivation process to enhance transformation efficiency using a commercially used rootstock 'Carrizo' Citrange as a model plant. We pre-cultured Agrobacterium cells in a 1/10 MS, 0.5 g/L 2-(N-morpholino) ethanesulfonic acid (MES) and 100 µM acetosyringone liquid medium for 6 hours at 25 ℃ before used to infect citrus explants. We incubated epicotyl segments in an MS liquid medium containing 13.2 µM 6-BA, 4.5 µM 2,4-D, 0.5 µM NAA for 3 hours at 25℃ prior to Agrobacterium infection. In the co-cultivation medium, we added 30 µM paclobutrazol and 10 µM lipoic acid. Each of these three treatments significantly increased the efficiencies of transformation. When the three treatments were combined, we observed that the transformation efficiency was enhanced from 11.5% to 52.3%. The improvement of genetic transformation efficiency mediated by these three simple treatments may facilitate more efficient applications of transgenic and gene editing technologies for functional characterization of citrus genes and for genetic improvement of cultivated citrus varieties.

The advancement of mass spectrometry technologies has revolutionised plant metabolomics research by enabling the acquisition of raw metabolomics data. However, the identification, analysis, and visualisation of these data require specialised tools. Existing solutions lack a dedicated plant-specific metabolite database and pose usability challenges. To address these limitations, we developed PlantMetSuite, a web-based tool for comprehensive metabolomics analysis and visualisation. PlantMetSuite encompasses interactive bioinformatics tools and databases specifically tailored for plant metabolomics data, facilitating upstream-to-downstream analysis in metabolomics and supporting integrative multi-omics investigations. PlantMetSuite can be accessed directly through a user's browser without the need for installation or programming skills. The tool is freely available at https://plantmetsuite.verygenome.com/ and will undergo regular updates and expansions to incorporate additional libraries and newly published metabolomics analysis methods. The tool's significance lies in empowering researchers with an accessible and customisable platform for unlocking plant metabolomics insights.

Respiratory Syncytial Virus (RSV) causes severe inflammation and airway pathology in children and the elderly by infecting the epithelial cells of the upper and lower respiratory tract. RSV replication is sensed by intracellular pattern recognition receptors upstream of the IRF and NF-B transcription factors. These proteins coordinate an innate inflammatory response via Bromodomain containing protein 4 (BRD4), a protein that functions as a scaffold for unknown transcriptional regulators. To better understand the pleiotropic regulatory function of BRD4, we examine the BRD4 interactome and identify how RSV infection dynamically alters it. To accomplish these goals, we leverage native immunoprecipitation and Parallel Accumulation – Serial Fragmentation (PASEF) mass spectrometry to examine BRD4 complexes isolated from human alveolar epithelial cells in the absence or presence of RSV infection. In addition, we explore the role of BRD4’s acetyl-lysine binding bromodomains in mediating these interactions by using a highly selective competitive bromodomain inhibitor. We identify 101 proteins that are significantly enriched in the BRD4 complex and are responsive to both RSV-infection and BRD4 inhibition. These proteins are highly enriched in transcription factors and transcriptional coactivators. Among them, we identify members of the AP1 transcription factor complex, a complex important in innate signaling and cell stress responses. We independently confirm the BRD4/AP1 interaction in primary human small airway epithelial cells. We conclude that BRD4 recruits multiple transcription factors during RSV infection in a manner dependent on acetyl-lysine binding domain interactions. This data suggests that BRD4 recruits transcription factors to target its RNA processing complex to regulate gene expression in innate immunity and inflammation.

Aborycin is a type I lasso peptide with a stable interlocked structure, offering a favorable framework for drug development. The aborycin biosynthetic gene cluster gul from marine sponge-associated Streptomyces sp. HNS054 was cloned and integrated into the chromosome of S. coelicolor hosts with different copies. The 3-copy gul-integration strains S. coelicolor M1346::3gul showed better production than one-copy or 2-copy gul-integration strains, and the total titer reached approximately 10.4 mg/L, i.e., 2.1 times that of the native strain. Then, five regulatory genes, phoU (SCO4228), wblA (SCO3579), SCO1712, orrA (SCO3008) and gntR (SCO1678), which were reported to have negative effects on secondary metabolism, were further knocked out from the M1346::3gul genome by CRISPR/Cas9 technology. While the ΔSCO1712 mutant showed a significant decrease (4.6 mg/L) and the ΔphoU mutant showed no significant improvement (12.1 mg/L) in aborycin production, the ΔwblA, ΔorrA and ΔgntR mutations significantly improved the aborycin titers to approximately 23.6 mg/L, 56.3 mg/L and 48.2 mg/L, respectively, which were among the highest heterologous yields for lasso peptides in both Escherichia coli systems and Streptomyces systems. Thus, this study provided important clues for future studies on enhancing antibiotic production in Streptomyces systems.

In order to understand the genetic diversity of germplasm resources of kumquat in Guangxi, 14 kumquat germplasm resources in Guangxi and 12 accessions from other provinces were analyzed by using SRAP markers. In total, 19 primer pairs with high stability, good reproducibility, and high polymorphism were chosen for analysis of all the 26 kumquat genotypes. Among the 101 amplified bands, 87 (86.14%) were polymorphic. SRAP markers were analyzed by employing Principal Coordinate Analysis, Population Structure Analysis and Hierarchical Cluster Analysis (UPGMA). The classification results showed that 26 kumquat germplasm could be divided into 5 groups, including cultivated kumquat, intergeneric hybrid, wild kumquat from other provinces, wild kumquat from Guangxi and hybrid kumquat from Guangxi. Guangxi kumquat germplasm occurred high genetic diversity, which were clearly divided into 3 groups like cultivated kumquat, wild kumquat and kumquat hybrid. And the 8 cultivated kumquat varieties in Guangxi were further divided into two subgroups. Wild kumquat in Guangxi and wild kumquat in other provinces belong to different groups, meanwhile the hybrids of Guangxi kumquat form independent groups, thus indicated that Guangxi wild kumquat and kumquat hybrid possessed certain specificity, or they maybe belonged to different species. Among the tested 26 kumquat accessions, 23 unique genotype-specific SRAP markers were detected for 14 kumquat genotypes, which made it possible to surely identify them. For the remaining 12 accessions without genotype-specific markers, they were distinguished by various combinations of markers. These results may have certain importance for kumquat genetic research and cultivar selection.

Osteoporosis is an abnormal bone remodeling condition characterized by decreased bone density, which leads to high risks of broken bones. Previous studies have demonstrated that Lycii Radicis Cortex (LRC) extract inhibits bone loss in ovariectomized (OVX) mice by enhancing the osteoblast differentiation. A bioactive compound, Kukoamine B (KB), was identified from a fractionation of LRC extract as a candidate component responsible for an anti-osteoporotic effect. This study investigated the anti-osteoporotic effects of KB using in vitro and in vivo osteoporosis models. KB treatment significantly increased the osteoblastic differentiation and mineralized nodule formation of osteoblastic MC3T3-E1 cells, while it significantly decreased the osteoclast differentiation of primary-cultured monocytes derived from mouse bone marrow. The effects of KB on osteoblastic and osteoclastic differentiations under more physiological conditions were also examined. In the co-culture of MC3T3-E1 cells and monocytes, KB promoted osteoblast differentiation but did not affect osteoclast differentiation. For the in vivo experiments, KB significantly inhibited OVX-induced bone mineral density loss and restored the impaired bone structural properties in osteoporosis model mice. These results suggest that KB may be a potential therapeutic candidate for the treatment of osteoporosis.

The rapid development of China’s textile industry leads to consumption and pollution of large volumes of water. Therefore, the textile industry has been the focus of water conservation and waste reduction in China’s 13th Five-Year Plan (2016–2020). The premise of sustainable development is to achieve decoupling of economic growth from water consumption and wastewater discharge. In this work, changes in blue water (water consumption), grey water (water pollutants), and water footprints of the textile industry from 2001 to 2014 were calculated. The relationship between water footprint and economic growth was then examined using the Tapio decoupling model. Furthermore, factors influencing water footprint were determined through logarithmic mean Divisia index (LMDI) method. Results show that the water footprint of China’s textile industry has strongly decoupled for five years (2002, 2006, 2008, 2011, and 2013) and weakly decoupled for four years (2002, 2007, 2009, and 2010). A decoupling trend occurred during 2001–2014, but a steady stage of decoupling has not been achieved yet. Based on the decomposition analysis, the total water footprint is mainly increased by production scale and inhibited by the technology. In addition, the effect of industrial structure adjustment is relatively weak.

Hepatitis E virus (HEV) is a common cause of acute hepatitis worldwide, accounting for approximately 25% of deaths among pregnant women. We previously reported that pregnancy serum facilitates HEV replication in vitro. However, the differences in host cells with HEV infection induced by pregnancy serum and fetal bovine serum (FBS) are unclear. In this study, differentially expressed proteins were identified in HEV-infected hepatoma cells (HepG2) supplemented with different sera by using isobaric tags for relative and absolute quantitation. Proteomic analysis indicated that HEV infection significantly induced 1014 differentially expressed proteins in HEV-infected HepG2 cells when supplemented with FBS compared with pregnancy serum. Further validation by Western blot confirmed that filamin A, heat-shock proteins 70 and 90, Cytochrome c, and Thioredoxin were associated with HEV infection. This comparative analysis provides an important basis to further investigate HEV pathogenesis in pregnant women and HEV replication.