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Abstract The gut microbiome has been implicated in various human diseases, though findings across studies have shown considerable variability. In this study, we reanalyzed 6314 publicly available fecal metagenomes from 36 case-control studies on different diseases to investigate microbial diversity and disease-shared signatures. Using a unified analysis pipeline, we observed reduced microbial diversity in many diseases, while some exhibited increased diversity. Significant alterations in microbial communities were detected across most diseases. A meta-analysis identified 277 disease-associated gut species, including numerous opportunistic pathogens enriched in patients and a depletion of beneficial microbes. A random forest classifier based on these signatures achieved high accuracy in distinguishing diseased individuals from controls (AUC = 0.776) and high-risk patients from controls (AUC = 0.825), and it also performed well in external cohorts. These results offer insights into the gut microbiome’s role in common diseases in the Chinese population and will guide personalized disease management strategies.

The accurate determination of coal temperature in the hidden spaces such as goaf has always been a worldwide problem that needs to be solved urgently. The study of acoustic temperature measurement technology is of great practical significance for a fast and accurate detection of loose coal temperature, and the scientific and accurate construction of the mapping relationship between sound velocity and coal temperature is the key to acoustic coal temperature measurement. In this paper, considering the influence of the characteristic parameters of spontaneous combustion process of loose coal on sound wave propagation, a mapping model of sound velocity and coal temperature in the quasi-porous media of loose coal was established. An acoustic temperature measurement experimental system for loose coal was designed and built. By conducting the acoustic temperature measurement tests for the loose coal with various particle sizes (0.6～1.5, 1～3, 3～5 cm), the effect of gas composition and concentration on sound propagation during the low-temperature oxidation stage (30～50 ℃) of coal samples with different particle sizes was studied, and the equivalent path conversion factor λ was determined. Based on the relationship between the measured sound velocity and the equivalent path conversion factor, the medium correction coefficient φ of the gas component was proposed and determined, and the feasibility of the sound-temperature mapping relationship model was verified. The results show that the acoustic wave propagation path of loose coal is affected by the characteristic parameters of coal particle size, temperature and the change of gas component medium, etc. A mapping model of sound velocity and coal temperature was established. At normal temperature, the propagation path of sound waves in the quasi-porous medium of loose coal is mainly affected by the pores between the coal particles. The equivalent path conversion factor λ of sound waves is 1.426 1, 1.371 1 and 1.315 2, respectively, when the coal particle size is 0.6～1.5, 1～3, 3～5 cm, which is negatively correlated with the particle size. The influence of coal temperature on acoustic wave propagation is manifested by the change of gas component medium in the process of spontaneous combustion of coal, which verifies the feasibility of the mapping relationship between sound velocity and coal temperature. The error rate between the inversion model and the experimental coal temperature is 0～6.46%, and the average coal temperature error is 2.52 ℃, which can reflect the coal body temperature well.

Pepper is one of the important vegetable crops and condiments in China. Carrying out researches on pepper genomics is of great significance for understanding the genetics and evolution of peppers, tapping important functional genes of peppers, and using biotechnology to conduct genetic improvement of varieties. The release of the draft pepper genomic map in 2014 marked the entry of pepper into an era of genomics research. Over the past decade, remarkable progress has been made in pepper genomics research, revealing the basic features of pepper genome deeply and constructing a preliminary pan-genome of pepper. Meanwhile, pepper genomics has been widely applied in exploring the interspecific differentiation and gene introgression of pepper, analyzing the evolutionary mechanism of pepper important traits, elucidating the genetic diversity of pepper, revealing the characteristics of artificial domestication of pepper, tracing the history of global range expansion and dissemination of pepper, and exploring the genes controlling the formation of important traits of pepper and so on. In this paper, we review and summarize the progress made in pepper genomics and its applications over the past 10 years, and look forward to the construction of a higher-quality pepper reference genome and pan-genome as well as the improvement of the research platform for pepper functional genomics, with an aim to provide a reference for pepper genomics and related applications.

Fruit color is an important qualitative trait that greatly influences the marketability of peppers. Fruit color can be divided into two categories. Green fruit color denotes commercial maturity, whereas ripe fruit indicates physiological maturity. Herein, segregation populations were created using the ‘D24’ with pale green in the green fruit stage, orange in the mature fruit stage, and ‘D47’ with green in the green fruit stage and red in the mature fruit stage. BSA-seq and genetic linkage map analysis revealed green fruit color was linked to (gyqtl1.1) on Chr1 and (gyqtl10.1) on Chr10, while mature fruit color was linked to Chr6. Using functional annotation, sequence, and expression analysis, we speculate that an SNP mutation in the CapGLK2 gene at the gyqtl10.1 interval could initiate premature termination of translation, thus yielding green to pale green fruits in D47. Conversely, the orange color in mature D24 fruits is due to the Indel-mediated premature termination of translation of the CapCCS gene. Our research offers a theoretical foundation for choosing different varieties of pepper fruit based on their color.

Pepper originated in South America and was introduced to China in the 16th century. With high nutritional value, pepper has an important role in health care, beauty, food, medicine, violence and other industries. It becomes one of the most important vegetable crops in China. With the gradual increase of cultivation area pepper ranks the top among vegetable crops in China in this aspect. In the process of pepper production, it inevitably suffers from various diseases, causing great losses to production. It is the most economical and effective measure to control diseases through selecting disease-resistant varieties, although the chemical control methods and agricultural control measures can reduce the harm to a certain extent. With the development of molecular biology, the combination of molecular breeding and conventional breeding methods for disease resistance is a direction of future breakthroughs. In recent years, great progress has been made in the molecular breeding of pepper disease resistance, especially, the molecular mechanism of disease resistance. Molecular breeding mainly includes two parts: one is marker-assisted breeding, and the other is creating disease-resistant breeding materials by means of genetic engineering. In marker-assisted breeding, molecular markers must be found first. Molecular markers are divided into gene markers, markers obtained by linkage analysis in segregation populations, and markers gotten by association analysis through sequencing of a large number of materials. The premise of genetic engineering is to isolate and obtain disease resistance genes, and then introduce them into pepper breeding materials with good economic traits, or mutate negatively regulated genes through gene editing technology or gene silencing technology to improve disease resistance of plants. In this paper, molecular markers and marker-assisted selection, molecular mechanism of disease resistance and disease-resistant germplasm (resistance to virus, bacterial wilt and Phytophthora capsici) obtained by genetic engineering technology are comprehensively introduced, and the development trend and research focus in the future are prospected.

In the context of carbon neutrality and energy shortage crisis, integrated energy systems achieve low carbon emissions through efficient conversion of various energy sources. However, most scheduling models of integrated energy systems merely regard the electricity, carbon, and natural gas prices as subject to deterministic distributions or simple constants, while their uncertainties are ignored which leads to less practical scheduling plans. In addition, most processing methods of uncertainty take no account of the correlations between uncertainties can result in less accurate evaluations of energy prices. Therefore, a day-ahead joint scheduling model considering coupling uncertainty of electricity, carbon, and gas prices with minimizing total operating costs of multiple park-level integrated energy systems as the objective is proposed to address the above issues. First, the correlation modeling of electricity and gas prices is conducted based on Copula theory, and an initial scenarios generation method of electricity-gas prices is then proposed; next, a typical scenarios construction method of electricity-carbon-gas prices’ coupling uncertainty based on multivariate quadratic polynomial regression-Copula is proposed; after that, the day-ahead joint scheduling model of multiple electricity-gas-thermal park-level integrated energy systems is established considering the typical scenarios of electricity-carbon-gas prices’ coupling uncertainty. Finally, the case studies on 3 energy systems verify the effectiveness of the proposed model. Results demonstrate accurate electricity-carbon-gas prices in typical scenarios with high correlations between uncertainties, and significant reductions in gas consumption and carbon emission by about 29.25% and 24.27% respectively.

Integrated energy systems (IESs) are complex multisource supply systems with integrated source, grid, load, and storage systems, which can provide various flexible resources. Nowadays, there exists the phenomenon of a current power system lacking flexibility. Thus, more research focuses on enhancing the flexibility of power systems by considering the participation of IESs in distribution network optimization scheduling. Therefore, the optimal scheduling of IESs considering virtual heat storage and electric vehicles (EVs) is proposed in this paper. Firstly, the basic structure of IESs and mathematical models for the operation of the relevant equipment are presented. Then, an optimal scheduling strategy of an IES considering virtual heat storage and electric vehicles is proposed. Finally, an IES with an IEEE 33-node distribution network, 20-node Belgian natural gas network, and 44-node heating network topologies is selected to validate the proposed strategy. The proposed models of integrated demand response (IDR), EV orderly charging participation, virtual heat storage, and actual multitype energy storage devices play the role of peak shaving and valley filling, which also helps to reduce the scheduling cost from CNY 11,253.0 to CNY 11,184.4. The simulation results also demonstrate that the proposed model can effectively improve the operational economy of IESs, and the scheduling strategy can promote the consumption of renewable energy, with the wind curtailment rate decreasing from 63.62% to 12.50% and the solar curtailment rate decreasing from 56.92% to 21.34%.

Spontaneous coal combustion adversely affects coal mine safety and restricts safe, efficient, and green coal mining. Inert gas fire prevention and extinguishing technology is a widely used fire prevention and extinguishing method in coal mines. CO2 is often used as the primary raw material for inert gas fire prevention and extinguishing, owing to its good inerting and cooling characteristics. However, the lack of data on the physical and chemical properties and fire extinguishing mechanism of CO2 by field personnel has limited the efficient application of CO2 in coal mine fire prevention and extinguishing. To explore the practical application effects of CO2 fire prevention and extinguishing technology on coal mine sites, this paper summarised and analysed the research and development status of CO2 fire prevention and extinguishing technology and expounded the physical and chemical properties, phase characteristics, and fire prevention and extinguishing mechanisms of CO2. The CO2 pipeline, CO2 pipeline intelligent monitoring and control system, CO2 inerting mechanism, and comprehensive gas fire prevention and extinguishing technology are summarised and discussed. This study provides a systematic theoretical basis for the field application of CO2 fire prevention and extinguishing technology.

The oxidation characteristic parameters of residual coal in working face change with the advance of coal seam. To explore the influence of dynamic oxygen-consuming environments, we examined the influence of reducing the oxygen concentration on the formation characteristics and characteristic parameters of coal oxidation products, conducted with temperature-programmed experiments under staged oxygen consumption. The correlation between the characteristic oxidation parameters was determined, and the critical oxygen concentration that determined the gas yield was obtained. The results show that after staged oxygen-consumption, the oxidation of coal is stronger than that under constant low oxygen, the oxidation products are greatly affected, and the influence of pyrolysis gas is small. The oxidation characteristic parameters such as gas product volume fraction, production rate, and heat release intensity are positively correlated with the oxygen-consumed temperature. We found that the oxidation reaction heat of coal is 180~330 kJ·mol−1, and the maximum and minimum exothermic intensities are significantly linearly correlated with the oxygen consumption rate. Finally, the critical oxygen concentrations for gas production rate under oxygen-consumed conditions were 17, 9, and 5%. These results have practical significance for strengthening the prevention and control of spontaneous combustion disasters in goafs.

Under the background of the Energy Internet and the shared economy, it is of great significance to explore the collaborative planning strategies of multi-energy microgrids (MEMGs) and a shared energy storage operator (SESO) supported by shared energy storage resources. In this context, a joint planning method of SESO and MEMG alliances based on a dynamic game with perfect information is proposed in this paper. First, an upper-level model for energy storage capacity configuration and pricing strategy planning of SESO is proposed to maximize the total planning and operational income of SESO. Then, a lower-level model for the optimal configuration of MEMGs’ alliance considering SES is proposed to minimize the total planning and operational costs of the MEMG alliance. On this basis, a solving algorithm based on the dynamic game theory with perfect information and the backward induction method is proposed to obtain the Nash equilibrium solution of the proposed bi-level optimization models. Finally, a case study with one SESO and an alliance consisting of five MEMGs is conducted, and the simulation results show that the proposed bi-level optimization method can increase SESO’s net income by 1.47%, reduce the average planning costs for each MEMG at least by 1.7%, and reduce model solving time by 62.9% compared with other counterpart planning methods.

Abstract Objective The gut microbial composition has been linked to metabolic and autoimmune diseases, including arthritis. However, there is a dearth of knowledge on the gut bacteriome, mycobiome, and virome in patients with gouty arthritis (GA). Methods We conducted a comprehensive analysis of the multi-kingdom gut microbiome of 26 GA patients and 28 healthy controls, using whole-metagenome shotgun sequencing of their stool samples. Results Profound alterations were observed in the gut bacteriome, mycobiome, and virome of GA patients. We identified 1,117 differentially abundant bacterial species, 23 fungal species, and 4,115 viral operational taxonomic units (vOTUs). GA-enriched bacteria included Escherichia coli_D GENOME144544, Bifidobacterium infantis GENOME095938, Blautia_A wexlerae GENOME096067, and Klebsiella pneumoniae GENOME147598, while control-enriched bacteria comprised Faecalibacterium prausnitzii_G GENOME147678, Agathobacter rectalis GENOME143712, and Bacteroides_A plebeius_A GENOME239725. GA-enriched fungi included opportunistic pathogens like Cryptococcus neoformans GCA_011057565, Candida parapsilosis GCA_000182765, and Malassezia spp., while control-enriched fungi featured several Hortaea werneckii subclades and Aspergillus fumigatus GCA_000002655. GA-enriched vOTUs mainly attributed to Siphoviridae, Myoviridae, Podoviridae, and Microviridae, whereas control-enriched vOTUs spanned 13 families, including Siphoviridae, Myoviridae, Podoviridae, Quimbyviridae, Phycodnaviridae, and crAss-like. A co-abundance network revealed intricate interactions among these multi-kingdom signatures, signifying their collective influence on the disease. Furthermore, these microbial signatures demonstrated the potential to effectively discriminate between patients and controls, highlighting their diagnostic utility. Conclusions This study yields crucial insights into the characteristics of the GA microbiota that may inform future mechanistic and therapeutic investigations.

The recovery of tellurium and bismuth from bismuth telluride waste is of great significance in improving the utilization levels of renewable resources, protecting the ecological environment and alleviating the problem of resource shortages. In this paper, tellurium and bismuth were recovered from bismuth telluride waste by selective sulfidation–vacuum volatilization. The Gibbs free energy, phase diagram and thermodynamic equilibrium diagram for the core reaction were calculated and analyzed to determine the possible reactions and the conditions required for the stability of bismuth telluride during the sulfidation process. After calculating the saturated vapor pressures, it was concluded that tellurium and bismuth sulfide could be separated by vacuum volatilization. The thermogravimetric analyses and differential scanning calorimetry were then used to analyze the reaction between bismuth telluride and sulfur. The results indicated that the temperature range for the sulfidation reaction should be 491–620 K. The volatilization temperature of tellurium should be greater than 695 K. The evaporation kinetics for tellurium and bismuth sulfide showed that the evaporation rate of tellurium was much higher than that of bismuth sulfide. Furthermore, experiments were conducted to verify the reliability of the theoretical analysis, and these were in good agreement with the thermodynamic and kinetic results. The direct yields of tellurium and bismuth were 99.65% and 99.49%, respectively. These results confirmed that the selective sulfidation-vacuum volatilization method is a feasible alternative for recovery of tellurium and bismuth from bismuth telluride waste.

In light of China’s carbon-neutral policy and the Energy Internet, it is crucial to reduce the carbon emissions resulting from the operation of the electricity–gas integrated energy system (EGIES). To address this issue, this paper proposes an optimal scheduling strategy for EGIES in line with the carbon-neutrality goal. Firstly, the oxygen-enriched combustion power plant, equipped with a power to gas unit, is modeled to maximize its carbon capture ability. Next, an optimal scheduling model for EGIES is proposed, which considers the bonus-penalty ladder carbon price and the oxygen-enriched combustion power plant, with the aim of minimizing the total operation costs and carbon emissions of the EGIES. Finally, the proposed model is applied to an EGIES, consisting of a 33-bus electric distribution network and a 20-bus natural gas network. The simulation results demonstrate that the proposed method can reduce the operation costs of the EGIES by up to 22.5% and the carbon emissions by up to 75.1t when compared to existing models.

Flexible resources, including district heat networks (DHN) and battery energy storage systems (BESS), can provide flexible regulation capability for distribution networks (DN), thereby increasing the absorption capacity for renewable energy. In order to improve the operation economy of DN and ensure the information privacy of different operators, a distributed cooperative dispatch method of DN with DHN and BESS considering flexible regulation capability is proposed. First, a distributed cooperative dispatch framework of DN-DHN-BESS is constructed. Then, an optimal dispatch model of DHN under constant flow-variable temperature control strategy is established in order to utilize the heat storage capacity to provide flexible regulation capability for DN. Next, the optimal dispatch models of BESS and DN are established with the objective of minimizing the operation cost, respectively. Finally, a solution method based on the alternating direction multiplier method of distributed cooperative dispatch for DN-DHN-BESS is proposed. Case studies are performed on a system consisting of a 33-node DN and a 44-node DHN, and simulation results demonstrate that the proposed method differs from the centralized dispatch method by only 0.52% in the total system cost, and the proposed method reduces the total system cost by 34.5% compared to that of the independent dispatch method.

Odors existing in natural environment are typically mixtures of a large variety of chemical compounds in specific proportions. It is a challenging task for an electronic nose to recognize the gas mixtures. Most current research is based on the overall response of sensors and uses relatively simple datasets, which cannot be used for complex mixtures or rapid monitoring scenarios. In this study, a novel electronic nose (E-nose) using a spiking neural network (SNN) model was proposed for the detection and recognition of gas mixtures. The electronic nose integrates six commercial metal oxide sensors for automated gas acquisition. SNN with a simple three-layer structure was introduced to extract transient dynamic information and estimate concentration rapidly. Then, a dataset of mixed gases with different orders of magnitude was established by the E-nose to verify the model’s performance. Additionally, random forests and the decision tree regression model were used for comparison with the SNN-based model. Results show that the model utilizes the dynamic characteristics of the sensors, achieving smaller mean squared error (MSE < 0.01) and mean absolute error (MAE) with less data compared to random forest and decision tree algorithms. In conclusion, the electronic nose system combined with the bionic model shows a high performance in identifying gas mixtures, which has a great potential to be used for indoor air quality monitoring in practical applications.

Luffa spp. is an important worldwide cultivated vegetable and medicinal plant from the Cucurbitaceae family. In this study, we report a high-quality chromosome-level genome of the high-generation inbred line SG261 of Luffa acutangula. The genomic sequence was determined by PacBio long reads, Hi-C sequencing reads, and 10× Genomics sequencing, with an assembly size of 739.82 Mb, contig N50 of 18.38 Mb, and scaffold N50 of 56.08 Mb. The genome of L. acutangula SG261 was predicted to contain 27,312 protein-coding genes and 72.56% repetitive sequences, of which long terminal repeats (LTRs) were an important form of repetitive sequences, accounting for 67.84% of the genome. Phylogenetic analysis reveals that L. acutangula evolved later than Luffa cylindrica, and Luffa is closely related to Momodica charantia. Comparing the genome of L. acutangula SG261 and L. cylindrica with PacBio data, 67,128 high-quality structural variations (SVs) and 55,978 presence-absence variations (PAVs) were identified in SG261, resulting in 2424 and 1094 genes with variation in the CDS region, respectively, and there are 287 identical genes affected by two different structural variation analyses. In addition, we found that the transcription factor FY (FLOWERING LOCUS Y) families had a large expansion in L. acutangula SG261 (flowering in the morning) compared to L. cylindrica (flowering in the afternoon), which may result in the early flowering time in L. acutangula SG261. This study provides valuable reference for the breeding of and pan-genome research into Luffa species.

Abstract Information encryption technique has broad applications in individual privacy, military confidentiality, and national security, but traditional electronic encryption approaches are increasingly unable to satisfy the demands of strong safety and large bandwidth of high-speed data transmission over network. Optical encryption technology could be more flexible and effective in parallel programming and multiple degree-of-freedom data transmitting application. Here, we show a dual-layer optical encryption fluorescent polymer waveguide chip based on optical pulse-code modulation technique. Fluorescent oligomers were doped into epoxy cross-linking SU-8 polymer as a gain medium. Through modifying both the external pumping wavelength and operating frequency of the pulse-code modulation, the sender could ensure the transmission of vital information is secure. If the plaintext transmission is eavesdropped, the external pumping light will be switched, and the receiver will get warning commands of ciphertext information in the standby network. This technique is suitable for high-integration and high-scalability optical information encryption communications.

Abstract Objective Sjögren’s syndrome (SS) is an inflammatory autoimmune disease characterized by high levels of chronic lymphocyte infiltration. Differences and dysfunction in the gut microbiota and metabolites may be closely related to the pathogenesis of SS. The purpose of this study was to reveal the relationship between the gut microbiota and metabolome in NOD mice as a model of SS and the role of FuFang Runzaoling (FRZ), which is a clinically effective in treating SS. Methods NOD mice were gavaged with FRZ for 10 weeks. The ingested volume of drinking water, submandibular gland index, pathologic changes of the submandibular glands, and serum cytokines interleukin (IL)-6, IL-10, IL-17 A, and tumor necrosis factor-alpha (TNF-α) were determined. The roles of FRZ on gut microbiota and fecal metabolites were explored by 16 S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MC), respectively. The correlation between them was determined by Pearson correlation analysis. Results Compared with the model group, the drinking water volume of NOD mice treated with FRZ increased and the submandibular gland index decreased. FRZ effectively ameliorated lymphocyte infiltration in the small submandibular glands in mice. Serum levels of IL-6, TNF-α, and IL-17 A decreased, and IL-10 increased. The Firmicutes/Bacteroidetes ratio in the FRZ treatment group was higher. FRZ significantly downregulated the relative abundance of the family Bacteroidaceae and genus Bacteroides, and significantly upregulated the relative abundance of genus Lachnospiraceae_UCG-001. Orthogonal projections to latent structures discriminant analysis (OPLS-DA) revealed the significant change in fecal metabolites after FRZ treatment. Based on criteria of OPLS-DA variable influence on projection > 1, P 50, a total of 109 metabolites in the FRZ-H group were differentially regulated (47 downregulated and 62 upregulated) compared to their expressions in the model group. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed enriched metabolic of sphingolipid metabolism, retrograde endocannabinoid signaling, GABAergic synapse, necroptosis, arginine biosynthesis, and metabolism of histidine, alanine, aspartate, and glutamate. Correlation analysis between gut microbiota and fecal metabolites suggested that the enriched bacteria were related to many key metabolites. Conclusions Taken together, we found FRZ could reduce the inflammatory responses in NOD mice by regulating the gut microbiota, fecal metabolites, and their correlation to emerge a therapeutic effect on mice with SS. This will lay the foundation for the further studies and applications of FRZ, and the use of gut microbiotas as drug targets to treat SS. Graphical Abstract

ObjectiveSystemic sclerosis(SSc) remains unclear, studies suggest that inflammation may be linked to its pathogenesis. Hence, we conducted a bidirectional Mendelian randomization (MR) analysis to evaluate the association between cytokine and growth factor cycling levels and the risk of SSc onset.MethodsIn our study, the instrumental variables(IVs) for circulating cytokines were sourced from the genome-wide association study (GWAS) dataset of 8293 Finnish individuals. The SSc data comprised 302 cases and 213145 controls, and was included in the GWAS dataset. We employed four methods for the MR analysis: MR Egger, Inverse variance weighted (IVW), Weighted medium, and Weighted Mode, with IVW being the primary analytical method. Sensitivity analyses were performed using heterogeneity testing, horizontal pleiotropy testing, and the Leave One Out (LOO) method. We also conducted a reverse MR analysis to determine any reverse causal relationship between SSc and circulating cytokines.ResultsAfter Bonferroni correction, MR analysis revealed that the Interleukin-5 (IL-5) cycle level was associated with a reduced risk of SSc [odds ratio (OR)=0.48,95% confidence interval (CI): 0.27-0.84, P=0.01]. It also indicated that the Stem cell growth factor beta (SCGF-β) cycling level might elevate the risk of SSc (OR = 1.36, 95% CI: 1.01-1.83, P = 0.04). However, the reverse MR analysis did not establish a causal relationship between SSc and circulating cytokine levels. Additionally, sensitivity analysis outcomes affirm the reliability of our results.ConclusionOur MR study suggests potential causal relationships between IL-5, SCGF-β, and the risk of SSc. Further research is essential to determine how IL-5 and SCGF-β influence the development of SSc.

ObjectiveOsteoarthritis (OA) is the most prevalent joint disease globally, serving as a primary cause of pain and disability. However, the pathological processes underlying OA remain incompletely understood. Several studies have noted an association between cytokines and OA, yet the causal link between them remains ambiguous. This study aims to identify cytokines potentially causally related to OA using Mendelian randomization (MR) analysis, informing early clinical diagnosis and treatment decisions.MethodsWe conducted a genome-wide association study (GWAS) on 12 OA traits involving 177,517 cases and 649,173 controls from 9 international cohorts. For discovery MR analysis, we used 103 cytokines from two European populations as instrumental variables (IVs). Concurrently, another European population OA GWAS database (36,185 cases and 135,185 controls) was used to replicate MR analysis, employing the inverse variance weighted (IVW) method as the primary analytic approach. Additional methods tested included MR Egger, Weighted median, and Weighted mode. We merged the MR findings through meta-analysis. Heterogeneity testing, level pleiotropy testing (MR Egger intercept test and MRPRESSO), and sensitivity analysis via Leave One Out (LOO) were conducted to verify result robustness. Lastly, reverse MR analysis was performed.ResultsThe meta-analysis merger revealed a correlation between CX3CL1 cycle levels and increased OA risk (OR=1.070, 95% CI: 1.040-1.110; P

The accurate determination of coal temperature in hidden space such as goaf has always been a worldwide problem that needs to be solved. The research of coal temperature prediction model has important practical significance for the accurate detection of loose coal temperature. Based on the coal natural ignition experiment and coal spontaneous combustion gas characterization index as the initial data set GRU neurons are used to mine the nonlinear relationship between the index gas and temperature, and the GRU model parameters are optimized by PSO to obtain the predicted value of coal body temperature. The results show that the predicted MAE value of the PSO-GRU model is 1.37 °C, 6.51 °C, 11.40 °C, 15.90 °C, 20.20 °C lower than that of the PSO-SVM, PSO-BP, BP, RF and SVM prediction models respectively. The RMSE value decreased by 0.45 °C, 4.44 °C, 10.33 °C, 15.71 °C and 24.24 °C respectively. The judgment coefficient R2 on the test set and the training set of the PSO-GRU model is 0.99, and the generalization, prediction accuracy and robustness are all good. The experimental results show that the inversion temperature error of the model is within the range of 3.87 %, the maximum temperature difference is 5.69 °C, and the average temperature difference is 2.83 °C, which can meet the accuracy requirements of the field temperature measurement.

Flowering Chinese cabbage is an important vegetable crop widely cultivated in southern China. However, flowering Chinese cabbage plants are susceptible to diverse environmental influences that mainly affect crop quality and production. The BASIC PENTACYSTEINE (BPC) transcription factor is an essential regulator of plant development and abiotic stress responses. However, the function and molecular mechanism of the BPC family genes in flowering Chinese cabbage remain unclear. This study aimed to investigate the molecular mechanisms of the BcBPC gene in abiotic stress tolerance. In flowering Chinese cabbage, 12 BcBPC family genes have been identified and found to be unequally distributed on eight chromosomes. Comprehensive analyses of BcBPC gene structure, motif analysis, cis-regulatory elements, and subcellular localization were performed. BcBPC genes were classified into three groups based on their sequence composition, phylogenetic relationships, and conserved domains, which were highly linked to those of other species. BcBPC family gene promoter consists 69.92% stress-responsive, 32.38% hormone-responsive, and 5.30%, related to growth- and biological process-responsive cis-regulatory elements. Subsequent qRT-PCR results showed that BcBPC genes were highly upregulated under abiotic stress, especially under NaCl and Cd stress. The overexpression of BcBPC9 increases Cd stress tolerance in yeast. BcBPC9 is located in the nucleus, but moves to the cell wall when exposed to Cd stress. BcBPC9 transient overexpression tobacco were improved growth and upregulated the antioxidant enzymes genes expression when exposed to Cd stress. These findings facilitate further investigation of the functional and molecular characteristics of BcBPC9 in response to abiotic stress. The outcomes of this study provide a crucial foundation for future research on improving plant growth and protecting vegetable production.

Abstract Diagnostic and therapeutic illumination on internal organs and tissues with high controllability and adaptability in terms of spectrum, area, depth, and intensity remains a major challenge. Here, we present a flexible, biodegradable photonic device called iCarP with a micrometer scale air gap between a refractive polyester patch and the embedded removable tapered optical fiber. ICarP combines the advantages of light diffraction by the tapered optical fiber, dual refractions in the air gap, and reflection inside the patch to obtain a bulb-like illumination, guiding light towards target tissue. We show that iCarP achieves large area, high intensity, wide spectrum, continuous or pulsatile, deeply penetrating illumination without puncturing the target tissues and demonstrate that it supports phototherapies with different photosensitizers. We find that the photonic device is compatible with thoracoscopy-based minimally invasive implantation onto beating hearts. These initial results show that iCarP could be a safe, precise and widely applicable device suitable for internal organs and tissue illumination and associated diagnosis and therapy.

Abstract In this work, on-chip three-dimensional (3D) photonic integrated optical sources based on active fluorescent polymer waveguide microdisks are proposed for light display application. Fluorescent green and red oligomers with high-efficiency photoluminescence are doped into epoxy crosslinking SU-8 polymer as the waveguide gain medium. The microdisk-based on-chip optically pumping light sources are designed and fabricated using the organic functionalized materials by direct UV written process. The promising stacking dual-microdisk structures with double gain layers could provide white signal light source generated perpendicular to the chip, and green signal light source stimulated in the chip. The approach could realize the monolithically on-chip assembled vertical and horizontal bright emitters. The optical pumping threshold power is obtained as 50 mW with continuous-wave (CW) pumping. The average gain coefficient of a white light source is measured by vertical fiber coupling as 112 dB/W, and that of green light source by horizontal fiber coupling as 137 dB/W, respectively. The rising and falling response time of the on-chip optical sources are 60 and 80 µs under modulating pulsed pumping. This technique is very promising for achieving 3D integrated light display application, including photonic circuits and optical information encryption.

In the event of a major power outage in the power systems, there is an urgent need to investigate entire-process coordinated restoration strategies for the transmission systems (TSs) and distribution systems (DSs), aiming to accelerate the restoration speed of generating units, network reconfiguration, and load restoration. Furthermore, it is imperative to address the multiple uncertainties that arise during the restoration process to mitigate potential security risks associated with the restoration. Hence, an adaptive ADMM-based entire-process distributed restoration method of TSs and DSs considering CVaR is proposed in this paper. Firstly, an entire-process distributed restoration model of TSs and DSs considering CVaR is proposed to maximize the total restoration benefits of TSs and DSs. Then, an adaptive ADMM-based distributed solving algorithm for the coordinated restoration model of the TSs and DSs is introduced, which incorporates adaptive penalty parameter adjustments, leading to faster convergence compared to the standard ADMM. Finally, case studies on an improved 179-bus transmission system are employed to verify that the proposed restoration method can achieve higher restoration benefits and faster convergence speed compared to existing restoration models.

Extensive studies have focused on single-straight tunnels or subway bifurcation tunnel fire. However, the effect of large angle bifurcation on longitudinal maximum temperature rise attenuation in Urban Traffic Link Tunnel（UTLT）needs to be further studied. In this study, based on the theoretical analysis, a double exponential prediction model for longitudinal temperature rise attenuation in bifurcation tunnels is established. To obtain the correlation coefficients, a series of full-scale numerical fire simulation experiments were carried out in an UTLT-like tunnels using Fire Dynamics Simulator. The results revealed that the bifurcation structure of the large-angle bifurcation angle tunnels impeded the longitudinal movement of the fire smoke and hot smoke diversion. Without longitudinal ventilation conditions, the longitudinal decay of the temperature rise in each region can be expressed as the sum of double exponential expressions with different coefficients. The law governing the effect of the bifurcation angle on the longitudinal decay of the temperature rise is the quadratic equation of the angle sin α. A prediction model for the longitudinal decay of the temperature rise in the tunnel downstream of the fire source under longitudinal ventilation is proposed. The findings of the numerical simulation corresponded to those of the model prediction.

Under the background of dual-carbon goal, renewable energy-oriented power system and integrated energy are the trends of energy system. In order to cope with the uncertainty and volatility of renewable energy output, gas-fired unit can serve as a superior peak-regulation source to effectively solve the supply-demand mismatch problem. Nevertheless, rotor loss of gas-fired unit in the peak-regulation process weakens the operation performance and increases the practical cost of providing peak-regulation service. There is security risk of gas-fired unit in the peak-regulation process, especially during deep peak-regulation and startup/shutdown process, which leads to deficiency in the willingness to provide peak-regulation service. In this context, an optimal scheduling model of integrated electricity and gas system (IEGS) considering peak-regulation loss and renewable energy consumption is proposed in the paper. Firstly, peak-regulation loss and peak-regulation cost model is built under startup/shutdown regulation and variable-load regulation mode of gas-fired unit, respectively. On this basis, the optimal IEGS scheduling model taking gas-fired unit’s peak-regulation loss and renewable energy consumption into account is established, aiming at minimizing the total scheduling cost including operation cost considering peak-regulation loss, renewable energy abandoning penalty, load shedding cost and carbon emission cost under gas network constraints, peak-regulation constraints and other constraints. Finally, a case study on a modified IEGS with a high proportion of renewable energy from Guangdong province, China is conducted to verify the effectiveness of the proposed model, and the simulation results demonstrate that the proposed model could obtain the higher renewable energy consumption level and less carbon emission, and could relieve the rotor loss of gas-fired unit.

Driven by the gradual increase of the renewable energy installed capacity, shared energy storage (SES) has the potential to play an important role in the renewable energy accommodation scenario. In the process of accommodating renewable energy, SES users can also provide reactive power services to earn revenue and further improve the utilization rate of energy storage resources. In this context, a pricing model of reactive power services of SES is proposed in this paper to make SES users obtain reasonable revenue from the provided reactive power response capability. Firstly, based on the analysis of the cost composition, capacity constraint and application value of reactive power services, a cost-based time-variant capacity price is designed considering the investment cost and the opportunity cost of SES users. Moreover, the baseline power for renewable energy accommodation is proposed to quantify the opportunity cost caused by reactive power services in the renewable energy accommodation scenario. Finally, a case study based on the actual data of an SES trading pilot project in Qinghai, China, shows that the proposed pricing model can effectively reflect the costs of reactive power services which are highly coupled to the active power for renewable energy accommodation, and make SES users obtain the reasonable revenue covering the costs.

Abstract With the rapid development of renewable energy generation and multi‐energy system technologies, reviewing and discussing the emerging power system restoration methods and key technologies suitable for renewable‐dominated electric power systems and the Energy Internet are important. Based on this, the backgrounds of renewable‐dominated electric power systems and the Energy Internet are first introduced here. Subsequently, the power system restoration process is divided into three phases: the black‐start, network reconfiguration, and the load restoration phases; relative restoration strategy research on these three phases is reviewed. Moreover, the boundaries between these three phases are occasionally not sufficiently apparent or even cross in most cases owing to the severity of blackouts and other various factors. Therefore, the key technologies for power system restoration considering multiple phases are analysed in detail. Moreover, the major gaps between existing research and real‐world applications and the outlooks on the restoration technologies under renewable‐dominated electric power systems are discussed.

In recent years, stricter environmental rules have affected the entire bamboo industry in China. The increased costs for managing environmental issues hinder the growth of the bamboo forest harvesting and transportation sector in the upstream part of the industry chain. Analyzing how environmental changes affect the entire bamboo industry can give a deeper understanding of the regional transfer within the bamboo industry in China, and it can give more experience to the bamboo industry in developing countries. This study, based on the Pollution Haven Hypothesis and the theory of externalities, collected panel data from 16 provinces in China from 2000 to 2020 and examined the discrepancies in bamboo industry development and the varying intensities of market-oriented environmental regulation (MER). By constructing a fixed effects model and employing econometric methods, this study analyzed the spatiotemporal impact of MER on the output value of the bamboo harvesting and transportation industry (BHTI) and explored whether MER is a crucial factor causing the transfer of the bamboo industry across regions. The findings indicate that there is a noticeable shift of BHTI from the eastern to the central and western regions. Additionally, there is a substantial adverse effect of MER on the BHTI output value, especially in the eastern region. This confirms the transfer of industries between regions, which is a novel contribution of this article. Based on the findings of this study, some recommendations have been given for the response to the environmental regulation for bamboo industries in the future.

With the development of active distribution network (ADN), the situation that multiple users such as distributed generations and loads are connected to multiple nodes of ADN at the same time may occur. In this case, the power flow of ADN will change a lot when compared with the situation that a user is connected to only one node of ADN. Therefore, a maximum openable capacity optimization model of ADN considering multiple users access is proposed in this paper to deal with the situation that multiple users such as distributed generations and loads are connected to multiple nodes of ADN at the same time. The improved non-dominated sorting genetic algorithm (NSGA-II) is utilized to solve the proposed model, and case study based on IEEE 33-bus ADN is performed for verifying the effectiveness of the proposed maximum openable capacity optimization method.

Park-level integrated energy system (PIES) is a typical application of multi-energy coupling and supply, whose configuration can effectively improve its energy efficiency. A PIES optimal configuration model considering integrated demand response (IDR) and construction time sequence is proposed in this paper to further stimulate the multi-energy complementary and improve the planning economy of PIES. First, PIES considering IDR is modeled and the mathematical models of energy conversion and storage devices are established. Then, the PIES configuration model considering IDR and construction time sequence is established. Finally, a case study on an electric-heat coupling commercial PIES is carried out to demonstrate the effectiveness of the proposed model, which shows that the proposed model is effective in terms of improving the device utilization rate, cutting the planning costs of PIES and realizing “peak-cutting and valley-filling”.

Rheumatoid arthritis is troublesome to treat effectively and often requires concomitant long-term treatment. Meanwhile, synovial fibroblasts could induce inflammation response and lead to joint erosion, finally causing progressive joint destruction, disability, and increased mortality. This study focussed on the role of SLAM family member 8 (SLAMF8) in mediating cell function from rheumatoid arthritis synovial fibroblasts stimulated with TNF-α. Cell Counting Kit-8 (CCK-8) and colony-forming unit assay were used to evaluate cell proliferation. SLAMF8 expression was analysed by reverse transcription-quantitative PCR (RT-qPCR) and western blot. Annexin V‐FITC/PI double staining was used to measure the apoptosis rate. The cell migration and invasion in TNF-α-stimulated MH7A (human rheumatoid arthritis synovial cell line) and HFLS-RA cells (human fibroblast-like synoviocytes: rheumatoid arthritis) were tested via wound healing assay and transwell migration assay. In the present study, after TNF-α treatments, the SLAMF8 mRNA and protein expression in both MH7A and HFLS-RA cell lines have a time-dependent increase. The attenuation of SLAMF8 ameliorated TNF-α-induced proliferation, invasion and migration in MH7A and HFLS-RA cells. Simultaneously, when SLAMF8 was silenced, the expression of p-ERK, MMP-1, and MMP-13 was suppressed significantly. In summary, these results indicated that the knockdown of the SLAMF8 significantly attenuated TNF-α-induced proinflammatory responses in MH7A and HFLS-RA cells. Therefore, SLAMF8 exhibits therapeutic potential for the management of inflammation in rheumatoid arthritis.

The organization of chromatin into self-interacting domains is universal among eukaryotic genomes. Here, the authors report a reference-grade pepper genome assembly and use this reference to help describe the relationship among 3D chromatin conformation, chromatin function, and gene expression.

Previous studies have found that literacy acquisition modulates configural face processing (i.e., holistic and second-order configural processing). However, it remains unclear how literacy acquisition impacts the configural processing indexed by the inversion effect of normal or filtered faces. We asked Chinese illiterate and literate adults to judge whether two sequentially-presented stimuli, including faces, houses (experiment 1), and high- or low-pass filtered faces (experiment 2) were identical. Literate adults outperformed illiterate controls in the upright face and house conditions (experiment 1) and the upright high- and low-pass filtered conditions (experiment 2) but not in the inverted conditions. Notably, the size of an inversion effect (i.e., subtracting inverted accuracy from upright accuracy) was greater among literate adults than that among illiterate adults in both experiments. These findings support that literacy acquisition promotes configural face processing.

IntroductionAnkylosing spondylitis (AS), a chronic autoimmune disease, has been linked to the gut bacteriome.MethodsTo investigate the characteristics of the gut virome in AS, we profiled the gut viral community of 193 AS patients and 59 healthy subjects based on a metagenome-wide analysis of fecal metagenomes from two publicly available datasets.ResultsAS patients revealed a significant decrease in gut viral richness and a considerable alteration of the overall viral structure. At the family level, AS patients had an increased abundance of Gratiaviridae and Quimbyviridae and a decreased abundance of Drexlerviridae and Schitoviridae. We identified 1,004 differentially abundant viral operational taxonomic units (vOTUs) between patients and controls, including a higher proportion of AS-enriched Myoviridae viruses and control-enriched Siphoviridae viruses. Moreover, the AS-enriched vOTUs were more likely to infect bacteria such as Flavonifractor, Achromobacter, and Eggerthellaceae, whereas the control-enriched vOTUs were more likely to be Blautia, Ruminococcus, Collinsella, Prevotella, and Faecalibacterium bacteriophages. Additionally, some viral functional orthologs differed significantly in frequency between the AS-enriched and control-enriched vOTUs, suggesting the functional role of these AS-associated viruses. Moreover, we trained classification models based on gut viral signatures to discriminate AS patients from healthy controls, with an optimal area under the receiver operator characteristic curve (AUC) up to 0.936, suggesting the clinical potential of the gut virome for diagnosing AS.DiscussionThis work provides novel insight into the AS gut virome, and the findings may guide future mechanistic and therapeutic studies for other autoimmune diseases.

Growth-regulating factors (GRFs) are a unique family of transcription factors with well-characterized functions in plant growth and development. However, few studies have evaluated their roles in the absorption and assimilation of nitrate. In this study, we characterized the GRF family genes of flowering Chinese cabbage (Brassica campestris), an important vegetable crop in South China. Using bioinformatics methods, we identified BcGRF genes and analyzed their evolutionary relationships, conserved motifs, and sequence characteristics. Through genome-wide analysis, we identified 17 BcGRF genes distributed on seven chromosomes. A phylogenetic analysis revealed that the BcGRF genes could be categorized into five subfamilies. RT-qPCR analysis showed that BcGRF1, 8, 10, and 17 expression clearly increased in response to nitrogen (N) deficiency, particularly at 8 h after treatment. BcGRF8 expression was the most sensitive to N deficiency and was significantly correlated with the expression patterns of most key genes related to N metabolism. Using yeast one-hybrid and dual-luciferase assays, we discovered that BcGRF8 strongly enhances the driving activity of the BcNRT1.1 gene promoter. Next, we investigated the molecular mechanism by which BcGRF8 participates in nitrate assimilation and N signaling pathways by expressing it in Arabidopsis. BcGRF8 was localized in the cell nucleus and BcGRF8 overexpression significantly increased the shoot and root fresh weights, seedling root length, and lateral root number in Arabidopsis. In addition, BcGRF8 overexpression considerably reduced the nitrate contents under both nitrate-poor and -rich conditions in Arabidopsis. Finally, we found that BcGRF8 broadly regulates genes related to N uptake, utilization, and signaling. Our results demonstrate that BcGRF8 substantially accelerates plant growth and nitrate assimilation under both nitrate-poor and -rich conditions by increasing the number of lateral roots and the expression of genes involved in N uptake and assimilation, providing a basis for crop improvement.

Abstract Thanks to the gustatory system, humans can experience the flavors in foods and drinks while avoiding the intake of some harmful substances. Although great advances in the fields of biotechnology, microfluidics, and nanotechnologies have been made in recent years, this astonishing recognition system can hardly be replaced by any artificial sensors designed so far. Here, taste organoids are coupled with an extracellular potential sensor array to form a novel bioelectronic organoid and developed a taste organoids‐on‐a‐chip system (TOS) for highly mimicking the biological sense of taste ex vivo with high stability and repeatability. The taste organoids maintain key taste receptors expression after the third passage and high cell viability during 7 days of on‐chip culture. Most importantly, the TOS not only distinguishs sour, sweet, bitter, and salt stimuli with great specificity, but also recognizes varying concentrations of the stimuli through an analytical method based on the extraction of signal features and principal component analysis. It is hoped that this bioelectronic tongue can facilitate studies in food quality controls, disease modelling, and drug screening.

Abstract Under the background of carbon neutrality and large‐scale penetration of renewable energy, the integrated local energy system (ILES) has been extensively recognized as an effective way to reduce carbon emissions and improve renewable energy consumption level due to its high energy utilization and multiple energy complementarity. Hence, an optimal low‐carbon scheduling model of ILES considering oxygen‐enriched combustion plant (OECP) and generalized energy storages (GESs) is proposed in this paper to reduce the carbon emissions, improve the renewable energy consumption level and reduce the operating costs of ILES. More specifically, the cooperation mechanism between OECP and power to gas (P2G) is established to maintain a high carbon capture level during peak load periods; the GESs under the background of ILES is modelled, which can make full use of the multiple energy complementarity to improve the renewable energy consumption level of ILES. Case studies are performed on an IES that consists of an IEEE 33‐bus distribution network, a 44‐node district heating network and a 20‐node natural gas network to verify the effectiveness and advantages of the proposed model.

ABSTRACT The gut microbiota plays an essential role in the regulation of the immune system and the etiology of human autoimmune diseases. However, a holistic understanding of the gut bacteriome, mycobiome, and virome in patients with osteoarthritis (OA) remains lacking. Here, we explored the gut microbiotas of 44 OA patients and 46 healthy volunteers via deep whole-metagenome shotgun sequencing of their fecal samples. The gut bacteriome and mycobiome were analyzed using a reference-based strategy. Gut viruses were identified from the metagenomic assembled contigs, and the gut virome was profiled based on 6,567 nonredundant viral operational taxonomic units (vOTUs). We revealed that the gut microbiome (including bacteriome, mycobiome, and virome) of OA patients is fundamentally altered, characterized by a panel of 279 differentially abundant bacterial species, 10 fungal species, and 627 vOTUs. The representative OA-enriched bacteria included Anaerostipes hadrus (GENOME147149), Prevotella sp900313215 (GENOME08259), Eubacterium_E hallii (GENOME000299), and Blautia A (GENOME001004), while Bacteroides plebeius A (GENOME239725), Roseburia inulinivorans (GENOME 001770), Dialister sp900343095 (GENOME075103), Phascolarctobacterium faecium (GENOME233517), and several members of Faecalibacterium and Prevotella were depleted in OA patients. Fungi such as Debaryomyces fabryi (GenBank accession no. GCA_003708665), Candida parapsilosis (GCA_000182765), and Apophysomyces trapeziformis (GCA_000696975) were enriched in the OA gut microbiota, and Malassezia restricta (GCA_003290485), Aspergillus fumigatus (GCA_003069565), and Mucor circinelloides (GCA_010203745) were depleted. The OA-depleted viruses spanned Siphoviridae (95 vOTUs), Myoviridae (70 vOTUs), and Microviridae (5 vOTUs), while 30 Siphoviridae vOTUs were enriched in OA patients. Functional analysis of the gut bacteriome and virome also uncovered their functional signatures in relation to OA. Moreover, we demonstrated that the OA-associated gut bacterial and viral signatures are tightly interconnected, suggesting that they may impact disease together. Finally, we showed that the multikingdom signatures are effective in discriminating the OA patients from healthy controls, suggesting the potential of gut microbiota for the prediction of OA and related diseases. Our results delineated the fecal bacteriome, mycobiome, and virome landscapes of the OA microbiota and provided biomarkers that will aid in future mechanistic and clinical intervention studies. IMPORTANCE The gut microbiome of OA patients was completely altered compared to that in healthy individuals, including 279 differentially abundant bacterial species, 10 fungal species and 627 viral operational taxonomic units (vOTUs). Functional analysis of the gut bacteriome and virome also revealed their functional signatures in relation to OA. We found that OA-associated gut bacterial and viral signatures were tightly interconnected, indicating that they may affect the disease together. The OA patients can be discriminated effectively from healthy controls using the multikingdom signatures, suggesting the potential of gut microbiota for the prediction of OA and related diseases.

Rheumatoid arthritis (RA) is a chronic progressive autoimmune disease characterized with high recurrence, high disability, poor prognosis, and long treatment cycles. Versus western medicine, traditional Chinese medicine has the traits of definite efficacy, low toxicity, and side effects in the treatment of RA. Moreover, traditional Chinese medicine also has the advantages of multiple targets, multiple links, and multiple approaches. This study was committed to exploring the effect of Jinwujiangu prescription on peripheral blood osteoclasts in those patients with RA and relevant molecular mechanisms. We first identified 159 common targets by online pharmacology, and there were correlations among these targets; besides, the main signaling pathways involved were inclusive TNF signaling pathway, rheumatoid arthritis, IL-17 signaling pathway, NF-kappa B signaling pathway, Toll-like receptor signaling pathway, etc. Through experimental verification, we found that PBMC cells extracted from human peripheral blood could be successfully induced into osteoclasts, and Jinwujiangu prescription inhibited the generation of osteoclasts from PBMCs of RA patients. CCK-8 and flow cytometry showed that osteoclast viability was significantly decreased and osteoclast apoptosis was significantly increased in the HIF-1α interference group; low-, medium-, and high-dose Jinwujiangu prescription groups; sinapine group; and hydroxychloroquine control group. Moreover, Jinwujiangu prescription and sinapine could inhibit the production of cytokines in peripheral blood osteoclasts and inhibit autophagy in RA patients. The expression level of mTOR was significantly increased in both Jinwu middle- and high-dose groups. In conclusion, this study demonstrated that sinapine, the active target in Jinwujiangu prescription, can act as a HIF-1α inhibitor; activate the mTOR pathway; downregulate the level of autophagy rate, ATG5, beclin-1, and LC3 expression; and inhibit the occurrence of autophagy. The trial registration number of the study is KYW2021010.

BackgroundSystemic lupus erythematosus (SLE) is a systemic autoimmune disease that has been linked to the dysbiosis of the gut microbiome and virome. However, the potential characterization of the gut virome in SLE patients needs to be explored more extensively.MethodsHerein, we analyzed the gut viral community of 16 SLE patients and 31 healthy controls using both bulk and virus-like particle (VLP)-based metagenomic sequencing of their fecal samples. A total of 15,999 non-redundant viral operational taxonomic units (vOTUs) were identified from the metagenomic assembled contigs and used for gut virome profiling.ResultsSLE patients exhibited a significant decrease in gut viral diversity in the bulk metagenome dataset, but this change was not significant in the VLP metagenome dataset. Also, considerable alterations of the overall gut virome composition and remarkable changes in the viral family compositions were observed in SLE patients compared with healthy controls, as observed in both two technologies. We identified 408 vOTUs (177 SLE-enriched and 231 control-enriched) with significantly different relative abundances between patients and controls in the bulk virome, and 18 vOTUs (17 SLE-enriched in 1 control-enriched) in the VLP virome. The SLE-enriched vOTUs included numerous Siphoviridae, Microviridae, and crAss-like viruses and were frequently predicted to infect Bacteroides, Parabacteroides, and Ruminococcus_E, while the control-enriched contained numerous members of Siphoviridae and Myoviridae and were predicted to infect Prevotella and Lachnospirales_CAG-274. We explored the correlations between gut viruses and bacteria and found that some Lachnospirales_CAG-274 and Hungatella_A phages may play key roles in the virus-bacterium network. Furthermore, we explored the gut viral signatures for disease discrimination and achieved an area under the receiver operator characteristic curve (AUC) of above 0.95, suggesting the potential of the gut virome in the prediction of SLE.ConclusionOur findings demonstrated the alterations in viral diversity and taxonomic composition of the gut virome of SLE patients. Further research into the etiology of SLE and the gut viral community will open up new avenues for treating and preventing SLE and other autoimmune diseases.

Neutral events preceding emotional experiences can be better remembered, likely by assigning them as significant to guide possible use in future. Yet, the neurobiological mechanisms of how emotional learning enhances memory for past mundane events remain unclear. By two behavioral studies and one functional magnetic resonance imaging study with an adapted sensory preconditioning paradigm, we show rapid neural reactivation and connectivity changes underlying emotion-charged retroactive memory enhancement. Behaviorally, emotional learning retroactively enhanced initial memory for neutral associations across the three studies. Neurally, emotional learning potentiated trial-specific reactivation of overlapping neural traces in the hippocampus and stimulus-relevant neocortex. It further induced rapid hippocampal-neocortical functional reorganization supporting such retroactive memory benefit, as characterized by enhanced hippocampal-neocortical coupling modulated by the amygdala during emotional learning, and a shift of hippocampal connectivity from stimulus-relevant neocortex to distributed transmodal prefrontal-parietal areas at post-learning rests. Together, emotional learning retroactively promotes memory integration for past neutral events through stimulating trial-specific reactivation of overlapping representations and reorganization of associated memories into an integrated network to foster its priority for future use.

With the increasing seriousness of environmental and energy shortage problems, new technologies such as photovoltaic distributed generations and energy storage devices will be the development trend of future rural distribution network. In this paper, a bi-layer optimal planning model of rural distribution network is established, where the optimal planning problem on the long time scale is solved in the upper-layer model, and the optimal operation problem on the short time scale is solved in the lower-layer model. Then, the lower-layer optimal operating model is converted and added into the constraints of the upper-layer model according to the Karush–Kuhn–Tucker (KKT) conditions, and the Big-M method is used to linearize the nonlinear problems in the constraints of the proposed model. Finally, the case study of a rural distribution network in Zhejiang, China is demonstrated for verifying the effectiveness and advantages of the proposed bi-layer model on alleviating the pressure of power supply and increase profits from electricity sales.

The microgrid (MG) is an effective way to alleviate the impact of the large-scale penetration of distributed generations. Due to the seasonal characteristics of rural areas, the load curve of the rural MG is different from the urban MG. Besides, the economy and stability of MG’s scheduling may be impacted due to the uncertainty of the distributed generations’ output. To adapt the seasonal characteristics of the rural microgrid, a Wasserstein distance-based distributionally robust optimal scheduling model of rural microgrid considering the coordinated interaction among source-grid-load-storage is proposed to minimize the operating costs of the rural microgrid in this paper, and the distributionally robust optimization method based on the Wasserstein distance is utilized to deal with the uncertainty of distributed generations’ output in the proposed model, which can balance the robustness and economy of MG’s scheduling when compared with the robust optimization method and stochastic optimization method. The case study shows that the proposed model can achieve better economical and robust scheduling strategies of source-grid-load-storage than the robust optimization-based model and the stochastic optimization-based model. Besides, the robustness and economy of rural MG’s scheduling strategies are adjusted flexibly by the proposed model.

The fruit development and ripening process involve a series of changes regulated by fine-tune gene expression at the transcriptional level. Acetylation levels of histones on lysine residues are dynamically regulated by histone acetyltransferases (HATs) and histone deacetylases (HDACs), which play an essential role in the control of gene expression. However, their role in regulating fruit development and ripening process, especially in pepper (Capsicum annuum), a typical non-climacteric fruit, remains to understand. Herein, we performed genome-wide analyses of the HDAC and HAT family in the pepper, including phylogenetic analysis, gene structure, encoding protein conserved domain, and expression assays. A total of 30 HAT and 15 HDAC were identified from the pepper genome and the number of gene differentiation among species. The sequence and phylogenetic analysis of CaHDACs and CaHATs compared with other plant HDAC and HAT proteins revealed gene conserved and potential genus-specialized genes. Furthermore, fruit developmental trajectory expression profiles showed that CaHDAC and CaHAT genes were differentially expressed, suggesting that some are functionally divergent. The integrative analysis allowed us to propose CaHDAC and CaHAT candidates to be regulating fruit development and ripening-related phytohormone metabolism and signaling, which also accompanied capsaicinoid and carotenoid biosynthesis. This study provides new insights into the role of histone modification mediate development and ripening in non-climacteric fruits.

The long-term three-phase imbalance in distribution systems can lead to increased energy losses during transmission, reduced efficiency in energy utilization, and have serious implications for power supply security, power quality, and economic operations of the power system. The automatic load commutation device is an automatic device designed to address the issue of three-phase load imbalances in low-voltage distribution networks. By adjusting the phase of users without interrupting the power supply, this automatic device evenly distributes the load across all phases and effectively resolves the three-phase imbalance problem. Therefore, aiming at the above issue, a robust optimization method is adopted to address the control problem of automatic load commutation devices for a low-voltage distribution network. First, using historical data from photovoltaic and wind power generation systems as well as user load, a forecast analysis is conducted and uncertainty models for renewable energy and load demand are established. Then, a robust control strategy for the automatic load commutation device is proposed, which considers uncertainties of both source and load using the robust optimization method. The proposed model is then linearized using second-order cone technology and strong dual theory, and the column-and-constrained generation (C&CG) algorithm is employed to solve the problem iteratively. Finally, a modified IEEE 33-bus system is taken to verify the effectiveness of the proposed strategy. The simulation results show that the proposed load commutation device robust control model can enhance the ability of the distribution network to respond to load demand and renewable energy fluctuations while ensuring the economic operation of the distribution network. In addition, by adjusting the deviation amount and uncertainty parameters of load demand and renewable energy, a good balance between the robustness and economy of the proposed model can be achieved.