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Abstract Circularly polarized room temperature phosphorescence materials represent a state-of-the-art frontier of optical materials and exhibit promising applications in various fields. Herein, we fabricate a series of full-color circularly polarized room temperature phosphorescence materials, based on anionic cellulose derivatives and achiral luminophores. The ionic achiral substituents promote the spontaneous formation of chiral helical structure of cellulose derivatives via the electrostatic repulsion effect. There are multiple interactions between anionic cellulose derivatives and the doped luminophores, thus the chirality is transferred to luminophores and the non-radiative transition is inhibited. The resultant materials can be easily processed into large-scale film and flexible 3D objects with repeatable folding and curling properties. In addition, their phosphorescence performance shows to be excitation-dependence, time-dependence, visible-light excitation, and multi-responsiveness to humidity, temperature as well as pH value. Importantly, they recognize many enantiomers in an instrument-free visual mode, including amino acids, hydroxyl acids, organic phosphate and hydrobenzoin. These results provide insights into design of advanced optical materials which can be applied in multilevel information handling and chiral sensing.

Abstract Background China has the third largest number of TB cases in the world, and the average annual floating population in China is more than 200 million, the increasing floating population across regions has a tremendous potential for spreading infectious diseases, however, the role of increasing massive floating population in tuberculosis transmission is yet unclear in China. Methods 29,667 tuberculosis flow data were derived from the new smear-positive pulmonary tuberculosis cases in China. Spatial variation of TB transmission was measured by geodetector q-statistic and spatial interaction model was used to model the tuberculosis flow and the regional socioeconomic factors. Results Tuberculosis transmission flow presented spatial heterogeneity. The Pearl River Delta in southern China and the Yangtze River Delta along China’s east coast presented as the largest destination and concentration areas of tuberculosis inflows. Socioeconomic factors were determinants of tuberculosis flow. Some impact factors showed different spatial associations with tuberculosis transmission flow. A 10% increase in per capita GDP was associated with 10.2% in 2010 or 2.1% in 2012 decrease in tuberculosis outflows from the provinces of origin, and 1.2% in 2010 or 0.5% increase in tuberculosis inflows to the destinations and 18.9% increase in intraprovincial flow in 2012. Per capita net income of rural households and per capita disposable income of urban households were positively associated with tuberculosis flows. A 10% increase in per capita net income corresponded to 14.0% in 2010 or 3.6% in 2012 increase in outflows from the origin, 44.2% in 2010 or 12.8% increase in inflows to the destinations and 47.9% increase in intraprovincial flows in 2012. Tuberculosis incidence had positive impacts on tuberculosis flows. A 10% increase in the number of tuberculosis cases corresponded to 2.2% in 2010 or 1.1% in 2012 increase in tuberculosis inflows to the destinations, 5.2% in 2010 or 2.0% in 2012 increase in outflows from the origins, 11.5% in 2010 or 2.2% in 2012 increase in intraprovincial flows. Conclusions Tuberculosis flows had clear spatial stratified heterogeneity and spatial autocorrelation, regional socio-economic characteristics had diverse and statistically significant effects on tuberculosis flows in the origin and destination, and income factor played an important role among the determinants.

Abstract While the anaerobic-anoxic-oxic (AAO) process is the most widely applied biological wastewater treatment process in municipal wastewater treatment plants (WWTPs), it struggles to meet the increasing demands on biological toxicity control of the treated effluent. To tackle this challenge, this study develops machine learning (ML)-based models for optimizing the AAO treatment process towards improving its toxicity reduction efficacy for the effluent. The water quality parameters, treatment process parameters, and biological toxicity information (based on the nematode bioassay) of the effluent collected from 122 WWTPs in China are used to train the models. The validated models accurately predict the effluent’s quality parameters (average R2 = 0.81) and the biological toxicity reduction ratio of treatment process (R2 = 0.86). To further improve the toxicity reduction, we developed a multiple objective optimization framework to optimize the AAO process via unit process recombination. In the short-range unit combination, the toxicity reduction ratio of the four-unit combined processes (up to 79.8% of anaerobic-aerobic-anaerobic-aerobic) is significantly higher than others. After optimization, it helps to improve the average toxicity reduction efficacy of 122 WWTPs from 48.6% to 70.7%, with a maximum of 87.5%. The methodologies and findings derived from this work are expected to provide the foundation for the optimization, expansion, and technical transformation of biological wastewater treatment in WWTPs.

Abstract Background Prostate cancer (PCa) is the second leading cause of tumor-related mortality in men. Metastasis from advanced tumors is the primary cause of death among patients. Identifying novel and effective biomarkers is essential for understanding the mechanisms of metastasis in PCa patients and developing successful interventions. Methods Using the GSE8511 and GSE27616 data sets, 21 metastasis-related genes were identified through the weighted gene co-expression network analysis (WGCNA) method. Subsequent functional analysis of these genes was conducted on the gene set cancer analysis (GSCA) website. Cluster analysis was utilized to explore the relationship between these genes, immune infiltration in PCa, and the efficacy of targeted drug IC50 scores. Machine learning algorithms were then employed to construct diagnostic and prognostic models, assessing their predictive accuracy. Additionally, multivariate COX regression analysis highlighted the significant role of POLD1 and examined its association with DNA methylation. Finally, molecular docking and immunohistochemistry experiments were carried out to assess the binding affinity of POLD1 to PCa drugs and its impact on PCa prognosis. Results The study identified 21 metastasis-related genes using the WGCNA method, which were found to be associated with DNA damage, hormone AR activation, and inhibition of the RTK pathway. Cluster analysis confirmed a significant correlation between these genes and PCa metastasis, particularly in the context of immunotherapy and targeted therapy drugs. A diagnostic model combining multiple machine learning algorithms showed strong predictive capabilities for PCa diagnosis, while a transfer model using the LASSO algorithm also yielded promising results. POLD1 emerged as a key prognostic gene among the metastatic genes, showing associations with DNA methylation. Molecular docking experiments supported its high affinity with PCa-targeted drugs. Immunohistochemistry experiments further validated that increased POLD1 expression is linked to poor prognosis in PCa patients. Conclusions The developed diagnostic and metastasis models provide substantial value for patients with prostate cancer. The discovery of POLD1 as a novel biomarker related to prostate cancer metastasis offers a promising avenue for enhancing treatment of prostate cancer metastasis.

Abstract This article proposes a line scanning chromatic confocal sensor to solve the problem of limited chromatic confocal measurement due to the small measurement range and low measurement efficiency in the industrial inspection process. To obtain an extensive dispersion range, the advantages of a simple single-axis structure are combined with the advantages of a large luminous flux of a biaxial structure. Considering large-scale measurement, our sensor uses off-axis rays to limit the illumination path and imaging path to the same optical path structure. At the same time, the field of view is expanded, and a symmetrical structure is adopted to provide a compact optical path and improve space utilization. The simulation and physical system test results shows that the sensor scanning line length is 12.5 mm, and the axial measurement range in the 450 nm to 750 nm band is better than 20 mm. The axial resolution of the detector is ±1 µm combined with the subpixel centroid extraction data processing method, and the maximum allowable tilt angle for specular reflection samples is ±7°. The thicknesses of transparent standard flat glass and the wet collagen membrane are measured. The maximum average error is 1.3 µm, and the relative error is within 0.7%. The constructed sensor is of great significance for rapidly measuring the three-dimensional profile, flatness, and thickness in the fields of transparent biological samples, optics, micromechanics, and semiconductors.

Highlights The novel ionic cellulose derivative with cyano-imidazolium cation and chloride anion, designed from natural cellulose, promotes the crystallization process, grain growth, and orientation of perovskite in perovskite solar cells (PSCs). The use of ionic cellulose leads to the suppression of defect formation, reduction of grain boundaries, enhancement of carrier extraction, and inhibition of non-radiative recombination, resulting in a high power conversion efficiency of 24.71% in PSCs. The biopolymer-based approach enables excellent stability of PSCs, which maintain over 91.3% of their initial efficiencies after 3000 h in conventional air atmosphere.

BackgroundEarly childhood caries (ECC) are a prevalent chronic disease in young children. However, there has been limited research on the microbiota in different tissue levels of the same tooth in children with ECC. This study aimed to investigate the dynamic changes in bacterial diversity during the progression of Severe Early Childhood Caries (S-ECC) within the same tooth, from the tooth surface to the root canal, by collecting tissue samples from different areas of the affected tooth.MethodsTwenty primary teeth with periapical periodontitis were selected from 20 children aged 3–5 years, with 100 samples collected from the different layers: uncavitated buccal enamel surface without white spot lesion (surface), the outermost layer of the dentin carious lesion (superficial), the inner layer of carious dentin (deep), necrotic pulp tissue (pulp), and root exudate (exudate). The taxonomy of each OTU representative sequence was analyzed against the 16S rRNA database. Comparisons of alpha diversity between groups were performed. The number of shared and unique genera between groups counted. Beta diversity was contrasted to evaluate differences in bacterial community composition, and the relationships between the microbiota and samples were analyzed. The heatmap analysis of the 30 most abundant genera was used, which highlighted their relative distribution and abundance. The significantly abundant taxa (phylum to genera) of bacteria among the different groups were identified. The differences of relative abundance between bacterial genera among the five groups were analyzed. Significant Spearman correlations were noted, and visualization of the co-occurrence network was conducted.ResultsBacterial 16S rRNA gene sequencing showed that most genera were present in all layers, with the number of shared genera increasing as the disease advanced. The bacterial communities and core genera in the co-occurrence network changed with progression to severe ECC.ConclusionAn increase in both the quantity and complexity of bacterial interactions was observed. This study emphasized the importance of paying attention to the relationship between microbial species rather than just checking changes in bacterial species structure when investigating the role of bacteria in disease progression.

Coal spontaneous combustion (CSC) brings great danger to mine safety. Although traditional colloidal fire-fighting materials can reside at high fire source points, their permeability and fluidity are poor, and such materials focus on their water absorption, but pay less attention to water retention and resistance, which makes their fire-fighting effect not good. This paper proposed a new type of mining fire prevention colloid material (CPS-α), which had good solid water gel formation, viscosity, fluidity, and blocking properties to compensate for traditional colloids' shortcomings. According to the single-factor experiment, polymeric polyacrylamide (PAM) as the base material, sodium carboxymethyl cellulose (CMC) as the coagulant, modified starch (SS) as the flame retardant and reduced ascorbic acid were determined. After gel treatment, compared with raw coal, the critical temperature point of spontaneous combustion of coal was increased by about 28 °C, the time to reach the critical temperature point was delayed by 190s, and the characteristic temperature points were significantly increased; the overlap area of coal and water increases by about 20 % after adding gel, and the change slope of the diffusion coefficient of water decreases, which indicated that CPS-α had good flame retardant effect.

Specific leaf area (SLA) and leaf dry matter content (LDMC) are key leaf functional traits often used to reflect plant resource utilization strategies and predict plant responses to environmental changes. In general, grassland plants at different elevations exhibit varying survival strategies. However, it remains unclear how grassland plants adapt to changes in elevation and their driving factors. To address this issue, we utilized SLA and LDMC data of grassland plants from 223 study sites at different elevations in China, along with climate and soil data, to investigate variations in resource utilization strategies of grassland plants along different elevational gradients and their dominant influencing factors employing linear mixed-effects models, variance partitioning method, piecewise Structural Equation Modeling, etc. The results show that with increasing elevation, SLA significantly decreases, and LDMC significantly increases (P < 0.001). This indicates different resource utilization strategies of grassland plants across elevation gradients, transitioning from a “faster investment-return” at lower elevations to a “slower investment-return” at higher elevations. Across different elevation gradients, climatic factors are the main factors affecting grassland plant resource utilization strategies, with soil nutrient factors also playing a non-negligible coordinating role. Among these, mean annual precipitation and hottest month mean temperature are key climatic factors influencing SLA of grassland plants, explaining 28.94% and 23.88% of SLA variation, respectively. The key factors affecting LDMC of grassland plants are mainly hottest month mean temperature and soil phosphorus content, with relative importance of 24.24% and 20.27%, respectively. Additionally, the direct effect of elevation on grassland plant resource utilization strategies is greater than its indirect effect (through influencing climatic and soil nutrient factors). These findings emphasize the substantive impact of elevation on grassland plant resource utilization strategies and have important ecological value for grassland management and protection under global change.

The advancement of intelligent manufacturing technology in the era of Industry 5.0 has propelled the intelligence and automation of manufacturing production, while also exerting a significant impact on sustainable development of the manufacturing industry. However, the challenges and enablers faced by the transformation of intelligent manufacturing technology in the context of sustainable development of Industry 5.0 are still unclear. Based on literature review and expert opinions, this study uses the Likert scale to determine the challenges and enablers of the implementation of intelligent manufacturing technology in social, environmental and economic sustainability. The fuzzy-DEMETAL and AISM are used to analyze the logical relationship and hierarchical relationship between the above factors, and the MICMAC matrix is used to determine the key influencing factors. The research conclusions show that the most important challenges affecting the implementation of intelligent manufacturing technology are cost and funding, and the most important enabler is social benefits and public service improved. This research will provide insights for industry practitioners and decision makers in the management and decision-making process of implementing the transformation and upgrading of manufacturing intelligent manufacturing, thereby enhancing the sustainability of manufacturing development.

Spontaneous combustion of residual coal in the goaf is one of the main disasters in coal mines. Understanding the law of spontaneous combustion of residual coal can effectively prevent coal mine fires. This paper establishes a dynamic evolution model of overburden caving and porosity in the goaf using PFC numerical simulation software, and compares and analyzes the dynamic changes in porosity and the spontaneous combustion zone at advancing distances of 50 m, 70 m, and 100 m. The results show that when the working face advances 100 m, the porosity in the caving zone of the goaf decreases from 0–0.6 to 0.16–0.3. The range of the spontaneous combustion zone on the return air side expands from 42m-50 m to 39m–61 m, and on the inlet side, it expands from 0 to 22m–50 m. With increased exposure time, the spontaneous combustion zone range shifts slightly forward to 32m–55 m on the inlet side and 21m–49 m on the return side. This study reveals the dynamic evolution law of the spontaneous combustion zone in the goaf under the influence of different advancing distances and exposure times, which can assist in preventing goaf fires.

Grouted Sleeve Connections (GSC) play an important role in assembly of structural members for precast concrete structures. With many experimental work and parametric study have been done on the tension load-slip behavior of GSC, the mechanical behavior for the tension load-slip responses of GSC should also be studied and explained. The failure modes for GSC in tensile tests with different material properties are firstly analyzed here by investigations on 326 GSC specimens. To study the mechanism of the failure modes, a partial-interaction numerical model is introduced to simulate the load-slip responses of GSC with provided bond-slip characteristics. The different boundary conditions for long and short embedment lengths are described respectively. More than 400 data points in load-slip responses are collected from tensile tests of GSC. The verification between theoretical results with test results shows good agreement. Hence, with the partial-interaction numerical model, the corresponding GSC load-slip responses could be obtained by given material and dimensional properties. Furthermore, parametric study shows that load-slip responses of GSC in tensile behavior change with embedment lengths of reinforcing bars. The CT scan results also show that embedment lengths for reinforcement are suggested to be longer than the designed size by considering the original defects of the sleeves and the eccentricity of reinforcement in construction.

Abstract Background Southwest China is one of the largest karst regions in the world. Karst environment is relatively fragile and vulnerable to human activities. Due to the discharge of sewage and domestic garbage, the karst system may be polluted by pathogenic bacteria. The detection of bacterial distribution and identification of phage capable of infecting them is an important approach for environmental assessment and resource acquisition. Methods Bacteria and phages were isolated from karst water in southwest China using the plate scribing and double plate method, respectively. Isolated phage was defined by transmission electron microscopy, one-step growth curve and optimal multiplicity of infection (MOI). Genomic sequencing, phylogenetic analysis, comparative genomic and proteomic analysis were performed. Results A Klebsiella quasipneumoniae phage was isolated from 32 isolates and named KL01. KL01 is morphologically identified as Caudoviricetes with an optimal MOI of 0.1, an incubation period of 10 min, and a lysis period of 60 min. The genome length of KL01 is about 45 kb, the GC content is 42.5%, and it contains 59 open reading frames. The highest average nucleotide similarity between KL01 and a known Klebsiella phage 6939 was 83.04%. Conclusions KL01 is a novel phage, belonging to the Autophagoviridae, which has strong lytic ability. This study indicates that there were not only some potential potentially pathogenic bacteria in the karst environment, but also phage resources for exploration and application.

Abstract Ulcerative colitis (UC) is a chronic, recurrent inflammatory bowel disease. UC confronts with severe challenges including the unclear pathogenesis and lack of specific diagnostic markers, demanding for identifying predictive biomarkers for UC diagnosis and treatment. We perform immune infiltration and weighted gene co-expression network analysis on gene expression profiles of active UC, inactive UC, and normal controls to identify UC related immune cell and hub genes. Neutrophils, M1 macrophages, activated dendritic cells, and activated mast cells are significantly enriched in active UC. MMP-9, CHI3L1, CXCL9, CXCL10, CXCR2 and S100A9 are identified as hub genes in active UC. Specifically, S100A9 is significantly overexpressed in mice with colitis. The receiver operating characteristic curve demonstrates the excellent performance of S100A9 expression in diagnosing active UC. Inhibition of S100A9 expression reduces DSS-induced colonic inflammation. These identified biomarkers associated with activity in UC patients enlighten the new insights of UC diagnosis and treatment.

Abstract Spatial clustering is an essential method for the comprehensive understanding of a region. Spatial clustering divides all spatial units into different clusters. The attributes of each cluster of the spatial units are similar, and simultaneously, they are as continuous as spatially possible. In spatial clustering, the handling of spatial outliers is important. It is necessary to improve spatial integration so that each cluster is connected as much as possible, while protecting spatial outliers can help avoid the excessive masking of attribute differences This paper proposes a new spatial clustering method for raster data robust to spatial outliers. The method employs a sliding window to scan the entire region to determine spatial outliers. Additionally, a mechanism based on the range and standard deviation of the spatial units in each window is designed to judge whether the spatial integration should be further improved or the spatial outliers should be protected. To demonstrate the usefulness of the proposed method, we applied it in two case study areas, namely, Changping District and Pinggu District in Beijing. The results show that the proposed method can retain the spatial outliers while ensuring that the clusters are roughly contiguous. This method can be used as a simple but powerful and easy-to-interpret alternative to existing geographical spatial clustering methods.

Temperature superconducting (HTS) synchronous condenser is a reactive power compensation device with the advantages of low loss, high efficiency and wide reactive power range. Therefore, it has a very good application prospect in power grid. To solve the problems of low power factor and low conduction angle of constant excitation function for a long time due to single power supply excitation system, this paper proposes a high-low voltage switching excitation system, which separates the forced excitation and constant excitation modes of the excitation system into two power supplies. Based on the introduction of principle of excitation system, the design of its parameters and simulation analysis are completed, and a set of 400kW device is designed. On this basis, a series of corresponding superconducting experiment are carried out. The experimental results verify the principle of the power supply topology, and also show the feasibility and reliability of the proposed excitation system.

Abstract Background Acetyl-CoA acetyltransferase 2 (ACAT2) is a lipid metabolism enzyme and rarely was researched in epithelial ovarian cancer (EOC). Methods ACAT2 expressions were confirmed in two pairs of cell lines (A2780 and A2780/DDP, OVCAR8 and OVCAR8/DDP) from Gene Expression Omnibus database by bioinformatics analysis, and in A2780 and A2780/DDP cell lines by quantitative real-time polymerase chain reaction and western blotting. Tissue samples were stained by immunohistochemistry and scored for ACAT2 expression. The relationships between ACAT2 expression and clinicopathological characteristics were analyzed by χ2 test. The prognosis of ACAT2 was analyzed by the log-rank tests and Cox regression models. Results ACAT2 was remarkably upregulated in the above drug-resistant cell lines by mRNA (all P

In this article, a second-order time discrete algorithm with a shifted parameter $ \theta $ combined with a fast time two-mesh (TT-M) mixed finite element (MFE) scheme was considered to look for the numerical solution of the nonlinear fractional hyperbolic wave model. The second-order backward difference formula including a shifted parameter $ \theta $ (BDF2-$ \theta $) with the weighted and shifted Grünwald difference (WSGD) approximation for fractional derivative was used to discretize time direction at time $ t_{n-\theta} $, the $ H^1 $-Galerkin MFE method was applied to approximate the spatial direction, and the fast TT-M method was used to save computing time of the developed MFE system. A priori error estimates for the fully discrete TT-M MFE system were analyzed and proved in detail, where the second-order space-time convergence rate in both $ L^2 $-norm and $ H^1 $-norm were derived. Detailed numerical algorithms with smooth and weakly regular solutions were provided. Finally, some numerical examples were provided to illustrate the feasibility and effectiveness for our scheme.

Abstract Recently, advanced adenoma (AA) has been recognized as a target for colorectal cancer (CRC) screening. However, the fecal occult blood test (FOBT), the primary non-invasive screening method, shows limited sensitivity in detecting AA. This study investigates the relationship between adenoma characteristics and FOBT false-negative results. In a retrospective cohort study conducted from 2015 to 2022, we examined 342 inpatients with AA who underwent colonoscopy and received qualitative FOBT. FOBT sensitivity was analyzed about various adenoma characteristics, and logistic regression models were employed to investigate the relationship between adenoma features and FOBT false-negative outcomes. FOBT sensitivity in AA inpatients was 52.63%. Significant differences in sensitivity were observed based on adenoma location (left vs. right), morphology (with or without pedunculation), and size (≤ 10 mm vs. > 10 mm). After adjusting for several potential confounders, FOBT showed a reduced false-negative rate in AA with large-sized (OR, 0.49; 95% CI 0.31–0.77), left-sided location (OR, 0.53; 95% CI 0.31–0.89), and pedunculated morphology (OR, 0.73; 95% CI 0.43–1.24). AA with large size, left-sided location, and pedunculated morphology independently contribute to a decreased rate of FOBT false-negative results. However, these adenoma characteristics are not actively modifiable. Therefore, novel non-invasive methods are needed to improve AA detection accuracy.

ABSTRACT: A 2-dimensional (2D) egg-shape equation can be used to construct a 3D egg geometry based on the hypothesis that an egg is a solid of revolution, which helps to calculate egg volume and surface area. The parameters in the 2D egg-shape equation are potentially valuable for providing a clue to the ecology and evolution of avian eggs. In this study, the 5-parameter Preston equation (PE), the 4-parameter Troscianko equation (TE), and another 2 egg-shape equations, were compared in describing real 2D egg-shape data of 300 Gallus gallus domesticus eggs and additional 50 eggs that represented the variation in avian egg geometries. Adjusted root-mean-square error was used to quantify each equation's prediction error. Given that the 4 equations are nonlinear, relative curvature measures of nonlinearity were used to assess the extent of nonlinearity in each equation. PE was found to be the best among the 4 equations in terms of adjusted root-mean-square error and minimizing nonlinearity. The empirically determined egg volumes using a graduated cylinder were compared with the predicted egg volumes using the formula for a solid of revolution based on 2D predictions from the 4 egg-shape equations. There were negligible differences in the predicted egg volumes and surface areas among the 4 equations, indicating that these equations are all valid in calculating egg volume and surface area. In addition, we proposed a 5-parameter TE and found that it outperformed the above 4 equations in describing the 2D egg shape of G. gallus, but was less general than PE for other egg shapes. This work provides statistical evidence to show which equation is the best for describing the geometry of avian eggs and nondestructively calculating their volume and surface area, helping to classify poultry eggs into different grades according to the morphological characteristics of the eggs.

With large-scale access to distributed new energy, the power flow form of the distribution network tends to be complex. The distribution loop network rate increases, resulting in serious circulation of the distribution network, which places significant pressure on the loss of the distribution network. The problem of network loss change caused by distributed new energy grid connection, coupled with the inconsistency between load fluctuation and output power change of distributed new energy, will have a significant impact on the safety, reliability, and economic operation of the distribution network. Therefore, it is urgent to have good economic and technical means of power flow control. This paper proposes a minimum network loss optimization control strategy for active distribution networks based on a distributed power flow controller. First, according to the characteristics of the distribution network load and the new energy power supply along the distribution line, the multiple sub-modules of the distributed power flow controller are arranged in sections in the distribution loop network line. The regulation effect of the distributed power flow controller on the voltage and power flow of the distribution loop network is analyzed. The loop network current equation and power loss equation after the distributed power flow controller are constructed, and the power equation with the minimum active loss of the active distribution loop network is derived. Second, the control strategy for minimum network loss of the active distribution network based on the distributed power flow controller is proposed. Finally, the simulation model of the active distribution loop network is constructed by PSCAD/EMTDC. The loss of the loop network before and after the distributed power flow controller is simulated and analyzed, and the effectiveness of the proposed strategy is verified.

Introduction: In recent research, the expansion in the use of Mg alloys for biomedical applications has been approached by modifying their surfaces in conjunction with micro-arc oxidation (MAO) techniques which enhance their abrasion and corrosion resistance.Methods: In this study, combining laser texturing and MAO techniques to produce the dense ceramic coatings with microstructures. On the surface of the AZ31 Mg alloy, a micro-raised annulus array texture has been designed in order to increase the surface friction under liquid lubrication and to improve the operator’s grip when holding the tool. For this work, the micro-morphology of the coatings was characterised, and the friction properties of the commonly used scalpel shank material 316 L, the untextured surface and the textured surface were comparatively analysed against disposable surgical gloves.Results and discussion: The results show that the Laser-MAO ceramic coating grows homogenous, the porosity decreases from 14.3% to 7.8%, and the morphology after friction indicates that the coating has good wear resistance. More specifically, the average coefficient of friction (COF) of the three types of gloves coated with Laser-MAO ceramic was higher than that of the 316 L and MAO ceramic coatings under the action of the annulus-integrated texture under the lubrication conditions of physiological saline and defatted sheep blood, which achieved the goal of increasing friction for the purpose of helping to prevent the problem of tool slippage from the hand.

Quorum-sensing bacteria (QSB) are crucial factors for microbial communication, yet their ecological role in wastewater treatment plants (WWTPs) remains unclear. Here, we developed a method to identify QSB by comparing 16S rRNA gene sequences. QSB in 388 activated sludge samples collected from 130 WWTPs across China primarily were identified as rare taxa and conditionally rare taxa. A co-occurrence network shared by all sludge communities revealed that QSB exhibited higher average clustering coefficient (0.46) than non-QSB (0.15). Individual sludge networks demonstrated that quorum sensing microbiomes were positively correlated with network robustness and network complexity, including average clustering coefficient and link density. We confirmed that QSB keystones and QSB nodes have a positive impact on network complexity by influencing network modularity through a structural equation model. Meanwhile, QSB communities directly contributed to maintaining network robustness (r = 0.29, P

Tomato spotted wilt virus (TSWV) is ranked among the top 10 most destructive viruses globally. It results in abnormal leaf growth, stunting, and even death, significantly affecting crop yield and quality. Phytohormones play a crucial role in regulating plant-virus interactions. However, there is still limited research on the effect of TSWV on phytohormone levels, particularly growth hormones and genes involved in the phytohormone pathway. In our study, we combined phytohormone metabolomics and transcriptomics to examine the impact of TSWV infection on phytohormone content and gene expression profile. Metabolomic results showed that 41 metabolites, including major phytohormones and their precursors and derivatives were significantly altered after 14 days of TSWV inoculation tobacco plants cvK326, with 31 being significantly increased and 10 significantly reduced. Specifically, the levels of abscisic acid (ABA) and jasmonoyl-isoleucine (JA-Ile) were significantly reduced. The levels of indole-3-acetic acid (IAA) have remained unchanged. However, the levels of cytokinin isopentenyladenine (iP) and salicylic acid (SA) significantly increased. The transcriptome analysis revealed 2,746 genes with significant changes in expression. Out of these, 1,072 genes were significantly downregulated, while 1,674 genes were significantly upregulated. Among them, genes involved in ABA synthesis and signaling pathways, such as 9-cis-epoxycarotenoid dioxygenase (NCED), protein phosphatase 2C (PP2C), serine/threonine-protein kinase (SnRK2), and abscisic acid responsive element binding factor (ABF), exhibited significant downregulation. Additionally, expression of the lipoxygenase gene LOX, Jasmonate ZIM domain-containing protein gene JAZ, and transcription factor gene MYC were significantly down-regulated. In the cytokinin pathway, while there were no significant changes in the expression of the cytokinin synthesis genes, a significant downregulation of transcriptionally active factor type-B response regulators (type-B RRs) was observed. In terms of SA synthesis and signaling pathways, the isochorismate synthase gene ICS1 and the pathogenesis-related gene PR1 were significantly upregulated. These results can strengthen the theoretical foundation for understanding the interaction between TSWV and tobacco and provide new insights for the future prevention and control of TSWV.

Disturbances to the power system may lead to relative swing between synchronous generator rotors, causing low-frequency oscillation problems in the absence of damping. In this article, based on the single-machine infinity system containing flexible distribution transformer and synchronous generator, the linearized state equations of the system is deduced by the small-signal modeling. The mechanism of flexible distribution transformer on the rotor speed of synchronous generator is analyzed. The influence factors of flexible distribution transformer on the rotor speed of synchronous generator are analyzed. The equation of the additional damping provided by the flexible distribution transformer to this system is constructed. It was concluded that by controlling the output voltage of the regulating converter in the flexible distribution transformer, the rotor speed of the synchronous generator can be varied to increase the system damping. An additional damping control strategy for flexible distribution transformer is proposed. The simulation verifies that the proposed control strategy can effectively suppress the oscillation amplitude of each electrical quantity and shorten the oscillation duration when the system is subjected to large and small perturbations. The proposed additional damping control strategy of flexible distribution transformer can effectively improve the damping of the system and alleviate the problem of low frequency oscillation.

Abstract Plaque accumulation and microbial community changes are important causes of periodontal disease. Cleaned plaque microorganisms will reattach to form biofilms, but the recovery and outcome of plaque microbial communities in different periodontal health states remain unknown. In this study, we tracked the biofilm remodeling process in 206 dental plaque samples from 40 healthy periodontal, gingivitis and periodontitis volunteers at 6 time points before and after supragingival scaling. We found that microbial communities of different periodontal states changed asynchronously during the process, and the more severe the periodontal disease condition, the more lagged the recovery of plaque microorganisms to their original state after cleaning; this reflected a higher degree of plaque development in periodontitis samples. The plaque index and bleeding index were significantly correlated with plaque recovery, especially the recovery of bacteria such as Abiotrophia and Capnocytophaga. Meanwhile, we found that the microbial community structure of different periodontal health states was most similar at the Day 3 after plaque cleaning, and the communities gradually differentiated and developed in different directions. Abiotrophia and other bacteria might play an important role in determining the development trend of plaque biofilms. The discovery of specific time points and bacteria was of great value in clarifying the pathogenesis of periodontal disease and in seeking targets for prevention and treatment.

Abstract Background The gut microbiota play important roles in host adaptation and evolution, but are understudied in natural population of wild mammals. To address host adaptive evolution and improve conservation efforts of threatened mammals from a metagenomic perspective, we established a high-quality gut microbiome catalog of the giant panda (pandaGUT) to resolve the microbiome diversity, functional, and resistome landscapes using approximately 7 Tbp of long- and short-read sequencing data from 439 stool samples. Results The pandaGUT catalog comprises 820 metagenome-assembled genomes, including 40 complete closed genomes, and 64.5% of which belong to species that have not been previously reported, greatly expanding the coverage of most prokaryotic lineages. The catalog contains 2.37 million unique genes, with 74.8% possessing complete open read frames, facilitating future mining of microbial functional potential. We identified three microbial enterotypes across wild and captive panda populations characterized by Clostridium, Pseudomonas, and Escherichia, respectively. We found that wild pandas exhibited host genetic-specific microbial structures and functions, suggesting host-gut microbiota phylosymbiosis, while the captive cohorts encoded more multi-drug resistance genes. Conclusions Our study provides largely untapped resources for biochemical and biotechnological applications as well as potential intervention avenues via the rational manipulation of microbial diversity and reducing antibiotic usage for future conservation management of wildlife. Video Abstract

The “leafing intensity premium” hypothesis proposes that leaf size results from natural selection acting on different leafing intensities, i.e., the number of leaves per unit shoot volume or mass. The scaling relationships among various above-ground functional traits in the context of this hypothesis are important for understanding plant growth and ecology. Yet, they have not been sufficiently studied. In this study, we selected four bamboo species of the genus Indocalamus Nakai and measured the total leaf fresh mass per culm, total non-leaf above-ground fresh mass, total number of leaves per culm, and above-ground culm height of 90 culms from each species. These data were used to calculate leafing intensity (i.e., the total number of leaves per culm divided by the total non-leaf above-ground fresh mass) and mean leaf fresh mass per culm (i.e., the total leaf fresh mass per culm divided by the total number of leaves per culm). Reduced major axis regression protocols were then used to determine the scaling relationships among the various above-ground functional traits and leafing intensity. Among the four species, three exhibited an isometric (one-to-one) relationship between the total leaf fresh mass per culm and the total non-leaf above-ground fresh mass, whereas one species (Indocalamus pumilus) exhibited an allometric (not one-to-one) relationship. A negative isometric relationship was found between the mean leaf fresh mass per culm and the leafing intensity for one species (Indocalamus pedalis), whereas three negative allometric relationships between mean leaf fresh mass per culm and leafing intensity were observed for the other three species and the pooled data. An exploration of the alternative definitions of “leafing intensity” showed that the total number of leaves per culm divided by the above-ground culm height is superior because it facilitates the non-destructive calculation of leafing intensity for Indocalamus species. These results not only confirm the leafing intensity premium hypothesis for bamboo species but also highlight the interconnected scaling relationships among different functional traits, thereby contributing to our understanding of the ecological and evolutionary significance of leaf size variation and biomass investment strategies.

Abstract The inequality in leaf and fruit size distribution per plant can be quantified using the Gini index, which is linked to the Lorenz curve depicting the cumulative proportion of leaf (or fruit) size against the cumulative proportion of the number of leaves (or fruits). Prior researches have predominantly employed empirical models—specifically the original performance equation (PE‐1) and its generalized counterpart (GPE‐1)—to fit rotated and right‐shifted Lorenz curves. Notably, another potential performance equation (PE‐2), capable of generating similar curves to PE‐1, has been overlooked and not systematically compared with PE‐1 and GPE‐1. Furthermore, PE‐2 has been extended into a generalized version (GPE‐2). In the present study, we conducted a comparative analysis of these four performance equations, evaluating their applicability in describing Lorenz curves related to plant organ (leaf and fruit) size. Leaf area was measured on 240 culms of dwarf bamboo (Shibataea chinensis Nakai), and fruit volume was measured on 31 field muskmelon plants (Cucumis melo L. var. agrestis Naud.). Across both datasets, the root‐mean‐square errors of all four performance models were consistently smaller than 0.05. Paired t‐tests indicated that GPE‐1 exhibited the lowest root‐mean‐square error and Akaike information criterion value among the four performance equations. However, PE‐2 gave the best close‐to‐linear behavior based on relative curvature measures. This study presents a valuable tool for assessing the inequality of plant organ size distribution.

The vascular veins in photosynthetic leaves play an important role in transporting water and sugars throughout the plant body, and their venation pattern and vein density determine the hydraulic efficiency of the leaf. Likewise, stomatal density (SD) can influence photosynthetic gas exchange. However, the correlation between leaf vein density and SD is seldom reported. Herein, we examined 16 leaves from the hybrid Photinia × fraseri and 16 leaves from one of its parents, P. serratifolia, to explore the correlation between leaf vein density and SD. For each leaf, equidistant lamina quadrats were excised along two longitudinal transects (one along the midrib and another along the leaf margin). For each quadrat, micrographs of 1.2 mm × 0.9 mm stomatal imprints, and 2.51 mm × 1.88 mm micrographs of leaf veins were used to measure total vein area per leaf unit area (VAA) and total vein length per unit area (VLA), as indicators of leaf vein density, to determine the correlation between SD and leaf vein density. For each taxon, there was no significant correlation between SD and VAA, but there was a significant correlation between SD and VLA. The data indicate that SD is not positively correlated with VAA but positively correlated with VLA for both the hybrid and the parent species. This study indicates that future work should focus on the relationships between SD and total vein length per unit area rather than on total leaf vein area per unit area within and across species.

Endoplasmic reticulum (ER) stress-related genes are closely related to the occurrence, development, and immunotherapy response of tumors. This study provides a comprehensive assessment of HSPA5 from a pan-cancer perspective using multi-omics data. We analyzed the function of HSPA5 in multiple tumor types using multiple databases. Finally, immunohistochemistry was used to examine the relationship between HSPA5 expression in tissue microarrays from 100 patients with bladder cancer and the prognosis of patients with bladder cancer. Using the TCGA database, we were able to determine that HSPA5 is significantly elevated in a number of common malignancies and is linked with a bad prognosis. Cox regression analysis showed that the high expression of HSPA5 was correlated with OS, progression free survival (PFS), disease free survival (DFS), and disease special survival (DSS) of adrenocortical carcinoma (ACC). In addition, we discovered significant disparities in HSPA5 methylation and phosphorylation levels between various malignancies and normal tissues. HSPA5 expression was significantly correlated with the levels of infiltrating cells and immune checkpoint genes. HSPA5 is highly expressed in bladder cancer and patients with high HSPA5 expression have a poor prognosis. Our study provides a basis for further understanding of the role of ER stress-related gene HSPA5 in different tumor genesis and development. HSPA5 has also been shown to be a prognostic biomarker for bladder cancer patients.

In order to solve the problem of the power quality caused by distributed power access to the distribution network, this paper proposes a coordinated control strategy of reactive power compensation based on a flexible distribution transformer. First, the working principle of the flexible distribution transformer is analyzed, and the mathematical model of energy acquisition and the regulation converter of the flexible distribution transformer are studied as well. The device-level control strategies of energy acquisition and regulation converters are proposed, respectively. Then, in order to maintain the stability of the bus voltage and quickly respond to the reactive power changes of the system, a coordinated control strategy for the reactive power compensation of flexible distribution transformers is proposed. The priority herein is to maximize the reactive power compensation capacity of the energy harvesting converter. When the energy harvesting converter reaches the compensation upper limit, the control converter is used for reactive power compensation to further suppress the grid voltage fluctuation. Finally, it is verified through simulations that the flexible distribution transformer can realize the reactive power compensation of the distribution network and effectively improve the power quality of the distribution network.

Due to nutrient stress, which is an important constraint to the development of the global agricultural sector, it is now vital to timely evaluate plant health. Remote sensing technology, especially hyperspectral imaging technology, has evolved from spectral response modes to pattern recognition and vegetation monitoring. This study established a hyperspectral library of 14 NPK (nitrogen, phosphorus, potassium) nutrient stress conditions in rice. The terrestrial hyperspectral camera (SPECIM-IQ) collected 420 rice stress images and extracted as well as analyzed representative spectral reflectance curves under 14 stress modes. The canopy spectral profile characteristics, vegetation index, and principal component analysis demonstrated the differences in rice under different nutrient stresses. A transformer-based deep learning network SHCFTT (SuperPCA-HybridSN-CBAM-Feature tokenization transformer) was established for identifying nutrient stress patterns from hyperspectral images while being compared with classic support vector machines, 1D-CNN (1D-Convolutional Neural Network), and 3D-CNN. The total accuracy of the SHCFTT model under different modeling strategies and different years ranged from 93.92% to 100%, indicating the positive effect of the proposed method on improving the accuracy of identifying nutrient stress in rice.

Product innovation is a robust approach for enterprises to acquire and maintain a competitive edge. In order to support the development of enterprise product innovation, it is essential to establish an innovation pathway. Grounded in a modular perspective and considering the product innovation process, this study segments the process into product demand analysis, product module partitioning, product innovation opportunity recognition, and product innovation design. Consequently, an integrated product innovation pathway is constructed by incorporating relevant innovation theories and methodologies, encompassing the innovation process, theory, and methods. The feasibility and efficacy of this research are validated through a case study of a large aircraft assembly line, indicating that this approach effectively bolsters product innovation development and holds practical significance.

ABSTRACT: Eggs rich in polyunsaturated fatty acids (PUFA), known as functional eggs, are animal products deemed beneficial to human health and possess high economic value. The production of functional eggs involves supplementing exogenous additives with the ability to regulate lipid metabolism. As N-Carbamylglutamate (NCG) serves as an endogenous arginine synthesizer, and arginine acts as the substrate for the formation of nitric oxide (NO), the biological function of NCG is partially mediated by NO. NO is a key regulatory molecule in lipid metabolism, suggesting that NCG may also have the ability to modulate lipid metabolism. In order to assess the capacity of NCG in regulating liver lipid metabolism and its potential application in producing functional eggs, we conducted a study to investigate the effects of dietary supplementation of NCG on production performance, serum, and liver NO levels, yolk fatty acid composition, and the liver transcriptome of layers. In this study, we utilized 30 layers of the Jinghong No.1 breed, all aged 45 wk. All the birds were randomly divided into 2 groups. Each group had 5 replicates, and each replicate had 3 birds. We provided them with different diets: one group received the basic diet, and the other group's diet was supplemented with 0.08% NCG. The experiment lasted for 14 wk. The results did not reveal any positive impact of NCG on production performance. However, NCG supplementation elevated NO levels in serum and liver, along with an increase in yolk PUFA, ω-3, and ω-6 fatty acids. Liver transcriptome analysis identified 124 upregulated differentially expressed genes (DEGs) and 43 downregulated DEGs due to NCG supplementation. Functional annotation using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database highlighted 3 upregulated DEGs (CPT1A, MOGAT1, and CHKA) and 2 downregulated DEGs (FASN and ETNPPL) associated with lipid metabolism. Pathway enrichment analysis revealed that CPT1A was enriched in the AMPK signaling pathway and the PPAR signaling pathway, while FASN was enriched in the AMPK signaling pathway. Thus, CPT1A and FASN are potential functional genes related to lipid metabolism facilitated by NCG supplementation. In summary, our study suggests that NCG supplementation modulates liver lipid metabolism, leading to the production of functional eggs in layers.

Abstract Existing methods for fine-scale air quality assessment have significant gaps in their reliability. Purely data-driven methods lack any physically-based mechanisms to simulate the interactive process of air pollution, potentially leading to physically inconsistent or implausible results. Here, we report a hybrid multilevel graph neural network that encodes fluid physics to capture spatial and temporal dynamic characteristics of air pollutants. On a multi-air pollutant test in China, our method consistently improved extrapolation accuracy by an average of 11–22% compared to several baseline machine learning methods, and generated physically consistent spatiotemporal trends of air pollutants at fine spatial and temporal scales.

Abstract Causal inference in complex systems has been largely promoted by the proposal of some advanced temporal causation models. However, temporal models have serious limitations when time series data are not available or present insignificant variations, which causes a common challenge for earth system science. Meanwhile, there are few spatial causation models for fully exploring the rich spatial cross-sectional data in Earth systems. The generalized embedding theorem proves that observations can be combined together to construct the state space of the dynamic system, and if two variables are from the same dynamic system, they are causally linked. Inspired by this, here we show a Geographical Convergent Cross Mapping (GCCM) model for spatial causal inference with spatial cross-sectional data-based cross-mapping prediction in reconstructed state space. Three typical cases, where clearly existing causations cannot be measured through temporal models, demonstrate that GCCM could detect weak-moderate causations when the correlation is not significant. When the coupling between two variables is significant and strong, GCCM is advantageous in identifying the primary causation direction and better revealing the bidirectional asymmetric causation, overcoming the mirroring effect.

Abstract Background Rectal neuroendocrine neoplasms (NENs) are rare neoplasms with limited understanding of its genomic alterations and molecular typing. Methods The paraffin‐embedded tissue specimens of 38 patients with rectal NENs after surgery were subjected to whole gene sequencing (WGS), and mutation profilings were drawn to identify high‐frequency mutation genes, copy‐number variations (CNVs), tumor mutation burden (TMB), signal pathways, mutation signatures, DNA damage repair (DDR) genes, and molecular types. The differences of mutated genes and signaling pathways in different pathological grades and metastatic/non‐metastatic groups were compared. It helped to search for potential targets. Results C > T and T > C transitions are the most common base substitutions in rectal NENs. DNA mismatch repair deficiency, DNA base modifications, smoking and exposure to ultraviolet light might play a role in the occurrence of rectal NENs. DAXX, KMT2C, BCL2L1, LTK, MERTK, SPEN, PKN1, FAT3, and LRP2 mutations were found in only low‐grade rectal NETs, whereas APC, TP53, NF1, SOX9, and BRCA1 mutations were common in high‐grade rectal NECs/MiNENs. These genes helped in distinguishing poorly‐differentiated or well‐differentiated rectal NENs. Alterations in P53, Wnt and TGFβ signaling pathways were more pronounced in rectal NECs and MiNENs. Alterations in Wnt, MAPK and PI3K/AKT signaling pathways promoted metastases. Rectal NENs were classified into two molecular subtypes by cluster analysis based on the mutant genes and signaling pathways combined with clinicopathological features. Patients with mutations in the LRP2, DAXX, and PKN1 gene showed a trend of well‐differentiated and early‐stage tumors with less metastasis (p = 0.000). Conclusions This study evaluated risk factors for regional lymphatic and/or distant metastases, identified high‐frequency mutated genes, mutation signatures, altered signaling pathways through NGS. Rectal NENs were divided into two molecular types. This helps to evaluate the likelihood of metastasis, formulate follow‐up strategies for patients and provide a target for future research on precision treatment of rectal NENs. PARP inhibitors, MEK inhibitors, mTOR/AKT/PI3K and Wnt signaling pathway inhibitors may be effective drugs for the treatment of metastatic rectal NENs.

To easily control distributed photovoltaic power stations and provide fast responses for their regulation, this paper proposes an optimal cluster partitioning method based on a graph-based genetic algorithm (GA). In this approach, a novel structure utilizing a graph model is designed for chromosomes, and enhancements are made to the selection, crossover, and mutation models of the evolutionary to generate a search population for dividing distributed photovoltaic (PV) power grids into clusters. Moreover, the modularity and active power balance degree of the classic Girvan–Newman algorithm are employed as optimal objectives to establish a basis and evaluation system for cluster partitioning. Additionally, a Simulink simulation platform is established for the IEEE 33-bus time-varying scenario to validate its performance. A comparative analysis with some classic PV cluster partitioning algorithms demonstrates that the proposed method can achieve a more accurate and stable division of distributed PV units.

With the continuous expansion of the scale of power generated by grid-connected renewable energy, the form and operation characteristics of power grids have undergone significant changes, and the power electronic characteristics of power systems are prominent, resulting in the frequent occurrence of wide-band oscillation problems when renewable energy power generation equipment is connected to a power grid. Oscillation has the characteristics of nonlinearity and has an oscillation frequency ranging from a few hertz to several thousand hertz or more, which seriously threatens the stable operation of power grids. This paper summarizes the wide-band oscillation events that occur worldwide under the background of renewable energy access to power grids, classifies the wide-band oscillation events according to the distribution of oscillation frequency bands, and sorts out the characteristics of various oscillations. From the perspectives of the source side and network side, the existing oscillation suppression measures are classified and prospected.

Abstract Backgrounds Tuberculosis (TB) remains a serious public health and human development problem, especially in developing countries. Despite the effectiveness of directly observed therapy, short course programs in reducing transmission and progression of TB, poverty reduction and socioeconomic development remain crucial factors in decreasing TB incidence. However, the geographical pathway on the planet is not yet clear. Objectives This study was to reconstruct the geographical evolutionary process of TB in 173 countries and territories from 2010 to 2019 to analyze the socioeconomic determinants that impact the global TB epidemic. In addition, the TB incidence in 2030 was predicted. Methods This study analyses TB incidence data from 173 countries and territories between 2010 and 2019. The Geotree model would be used to reconstruct the geographical evolutionary process of TB, which provides a simplified schema for geo-visualizing the trajectories of TB incidence and their socioeconomic drivers. Additionally, to estimate the future TB incidence in 2030, a multilevel model was utilized in conjunction with the hierarchical nature of the Geotree based on a stratified heterogeneity analysis. Results Global TB incidence was found to be associated with the country type and development stages. Between 2010 and 2019, the average TB incidence rate in 173 countries and territories was -27.48%, with marked spatially stratified heterogeneity by country type and development stage. Low-income and lower-middle-income countries were most vulnerable to TB. Upper-middle-income countries experienced a faster decline in TB incidence than high-income countries, and TB incidence generally decreased as the development stage increased, except for the lower-middle development stage in 2019.The highest average rate of decline in TB incidence was observed in the upper-middle development stage of high-income countries, with a reduction of 45.24%. Meanwhile, 37 high-income countries in the high development stage demonstrated an average rate of change of -13.93%. Socioeconomic determinants, including gross domestic product per capita, urbanization rate, and sociodemographic index, were found to inhibit TB incidence. Based on current trends, the predicted average global TB incidence in 2030 is 91.581 per 100,000 population. Conclusions The trajectories of the global TB incidence have been reconstructed to formulate targeted public health responses. To eliminate TB, countries at similar development stage can draw on the experiences of countries at higher development stages that are tailored to their unique characteristics. By learning from successful TB control strategies, countries can take strategic steps toward eradicating TB and improving public health outcomes.

Summary: Cytotoxin-associated gene A (CagA) of Helicobacter pylori (Hp) may promote immune evasion of Hp-infected gastric cancer (GC), but potential mechanisms are still under explored. In this study, the positive rates of CagA and PD-L1 protein in tumor tissues and the high level of exosomal PD-L1 protein in plasma exosomes were significantly associated with the elevated stages of tumor node metastasis (TNM) in Hp-infected GC. Moreover, the positive rate of CagA was positively correlated with the positive rate of PD-L1 in tumor tissues and the level of PD-L1 protein in plasma exosomes, and high level of exosomal PD-L1 might indicate poor prognosis of Hp-infected GC. Mechanically, CagA increased PD-L1 level in exosomes derived from GC cells by inhibiting p53 and miRNA-34a, suppressing proliferation and anticancer effect of CD8+ T cells. This study provides sights for understanding immune evasion mediated by PD-L1. Targeting CagA and exosomal PD-L1 may improve immunotherapy efficacy of Hp-infected GC.

BackgroundPre-mRNA processing factor 19 (PRPF19) is an E3 ligase that plays a crucial role in repairing tumor-damaged cells and promoting cell survival. However, the predictive value and biological function of PRPF19 in bladder urothelial carcinoma (BLCA) require further investigation.MethodsIn this study, we utilized transcriptomic data and bladder cancer tissue microarrays to identify the high expression of PRPF19 in BLCA, suggesting its potential as a prognostic biomarker. To gain a better understanding of the role of PRPF19 in the immune microenvironment of BLCA, we performed single cell analysis and employed the LASSO method. Additionally, we examined the methylation profiles of PRPF19 using the SMART website. Our investigation confirmed the correlation between PRPF19 and BLCA cell senescence and stemness. Furthermore, we constructed a PRPF19-miR-125a-5p-LINC02693-MIR4435-2HG ceRNA network using the ENCORI and miRWALK databases.ResultsOur comprehensive analysis reveals that PRPF19 can serve as a prognostic marker for BLCA and is significantly associated with various immune-infiltrating cells in BLCA. Moreover, our findings suggest that PRPF19 influences cellular senescence through the regulation of stemness. Finally, we developed a ceRNA network that has the potential to predict the prognosis of BLCA patients.ConclusionWe confirmed the prognostic value and multiple biological functions of PRPF19 in BLCA. Furthermore, the specific ceRNA network can be used as a potential therapeutic target for BLCA.

As a zoonotic parasite, Cryptosporidium spp. could cause severe diarrhea mainly in calves and children globally. Monitoring and prevention of Cryptosporidium spp.’s prevalence is of great significance in both economy and public health aspects. In this study, specific primers and probes were designed within the conserved region of 18S rRNA gene for Cryptosporidium spp. and recombinase polymerase amplification assays based on the fluorescence monitoring (real-time RPA) as well as combined with a lateral flow strip (LFS RPA) were developed. Both of the two RPA assays allowed the exponential amplification of the target fragment within 20 min. After incubation on a metal bath at 42 °C, the LFS RPA results were displayed on the lateral flow strip within 5 min while real-time RPA allowed the real-time observation of the results in Genie III at 39 °C. The RPA assays showed high specificity for Cryptosporidium spp. without any cross-reaction with other tested pathogens causing diarrhea in cattle. With the recombinant plasmid DNA containing the 18S rRNA gene of Cryptosporidium spp. serving as a template, the limit of detection for real-time RPA and LFS RPA assays were 14.6 and 12.7 copies/reaction, respectively. Moreover, the RPA assays were validated by testing diarrheic cattle fecal samples and compared with a real-time PCR. The positive ratio of Cryptosporidium spp. was 24.04 % (44/183) and 26.23 % (48/183) in both RPA assays and real-time PCR assay, respectively, and the kappa coefficient value was 0.942. The diagnostic specificity and diagnostic sensitivity of both RPA assays were 100 % and 91.67 %, respectively. Forty-one of 48 positive samples were successfully sequenced and four Cryptosporidium species were detected, including C. parvum (n = 20), C. andersoni (n = 17), C. bovis (n = 3) and C. ryanae (n = 1). The developed RPA assays are easy to operate and faster to obtain the detection results, and they are suiting for the point-of-care detection and facilitating the prevention and control of Cryptosporidium spp. infections.

Soil erosion is the leading cause of global environmental degradation that accelerates soil degradation through climate and land use/land cover changes. The eastern sandy region of China is located at vast arid and semi-arid desert areas, and is characterized by arid climate, extreme rainfall events, vegetation degradation and poor farming practices, with serious land desertification, sandstorm disaster and soil erosion. Soil protection is the primary way to suppress soil erosion, including windbreak and sand fixation (WSF) and soil conservation (SC) service. The spatio-temporal patterns, spatial relationships and driving factors of soil protection services (WSF and SC) in eastern sandy region of China were investigated using National Wind Erosion Survey Model of China (NWESMC) and Revised Universal Soil Loss Equation (RUSLE). The results indicated that: (1) In eastern sandy region, the total soil erosion was 17.31 × 107 t from 2000 to 2020, of which wind and water erosion was 15.8 × 107 t and 1.51 × 107 t, respectively. (2) The total amount of soil protection was 45.5 × 107 t, with WSF and SC showing opposite spatio-temporal pattern. (3) Climate factors played dominant role for the change of soil protection service, with wind speed weakening being the main reason for the weakening of WSF service, the increase of precipitation enhancing SC service. Human activities (such as ecological engineering) may play a significant part in the future. The study has implications for soil protection in arid and semiarid regions worldwide, and can offer scientific recommendations for land management and soil remediation in sandy areas of China.

A conductive ceramic composite (CCC) based on carbonized phenolic resin is fabricated via a facile and scalable dry-pressing method. A conductive carbonaceous precursor solution is homogeneously mixed with a ceramic precursor. Subsequently, carbonization and ceramicization are achieved simultaneously in a single heating process. The carbonized materials endow the composites with excellent electrical conductivity and reliable cyclic heating properties. The temperature of the obtained composites is approximately 386 °C at 12 V after 10 min and 400 °C at 20 V after 48 s, and their energy consumption is low. Thermal images show that an even heat distribution is achieved on the composite surface, and that the electro-thermal performance can be adjusted by changing the electrical circuit arrangement (series or parallel circuits). In addition, the ceramic composites exhibit favorable electromagnetic interference (EMI) shielding performance of 26.2 dB at 8.2 GHz and improved photothermal conversion effect compared with the pristine ceramic. More importantly, this single-step heating provides a convenient and cost-effective approach for producing CCCs, thereby enabling the scalable production of conductive ceramics for electro-thermal applications. The excellent electrical performance facilitates the application of ceramic composites in Joule heating (e.g., deicing, boiling water, and cooking) and EMI shielding.

Abstract Background A sudden increase in heart rate (HR) during ablation of the right superior pulmonary venous vestibule (RSPVV) is often detected in patients undergoing circumferential pulmonary vein isolation (CPVI). In our clinical practices, we observed that some patients had few complaints of pain during the procedures under conscious sedation. Aim We aimed to investigate whether there is a correlation between a sudden increase in HR during AF ablation of the RSPVV and pain relief under conscious sedation. Methods We prospectively enrolled 161 consecutive paroxysmal AF patients who underwent the first ablation from July 1, 2018, to November 30, 2021. Patients were assigned to the R group when they had a sudden increase in HR during the ablation of the RSPVV, and the others were assigned to the NR group. Atrial effective refractory period and HR were measured before and after the procedure. Visual Analogue Scale (VAS) scores, vagal response (VR) during ablation, and the amount of fentanyl used were also documented. Results Eighty-one patients were assigned to the R group, and the remaining 80 were assigned to the NR group. The post-ablation HR (86.3 ± 8.8 vs. 70.0 ± 9.4 b/min; p ≤ 0.001) was higher in the R group than in pre-ablation. Ten patients in the R group had VRs during CPVI, as well as 52 patients in the NR group. The VAS score [2.3 (1.3–3.4) vs. 6.0 (4.4–6.9); p ≤ 0.001)] and the amount of fentanyl used (107 ± 12 vs. 172 ± 26 ug; p ≤ 0.001) were significantly lower in the R group. Conclusion A sudden increase in HR during the ablation of the RSPVV was correlated with pain relief in patients undergoing AF ablation under conscious sedation.