Search

Abstract The cladding of fast reactor fuel rods, made of stainless steel, presents significant challenges in cutting due to its ductility, which leads to increased tool wear and poor cut quality with traditional mechanical methods. Laser cutting has emerged as a superior alternative, offering non-contact precision, high efficiency, and suitability for radioactive environments. This study systematically investigates the effects of laser cutting parameters—cutting speed, focal position, power, and gas pressure—on the cutting quality of simulated fast reactor fuel rods. The results show that optimal cutting is achieved with a cutting speed of 1 m/min, a focal position between − 20 and − 25 mm, a laser power between 7200 and 9600 W, and a gas pressure of 10 MPa. These parameters provide the best balance between cutting efficiency, surface roughness, and minimal slag formation. This study contributes valuable insights into optimizing laser cutting technology for nuclear fuel rod processing, with potential applications in fuel reprocessing and decommissioning.

Abstract Flue-curing and redrying are important processing stages before tobacco fermentation, closely linked to microbial actions that influence the fermentation process. It is necessary to investigate the effects of flue-curing and redrying on diversity and succession of tobacco fungal communities. It was shown that a total of 9 phyla, 33 classes, 94 orders, 266 families, 646 genera, and 6,396 amplicon sequence variants (ASVs) were identified in the fungi communities of 36 samples from different processing stages (before flue-curing, after flue-curing, before redrying and after redrying) based on high-throughput sequencing technology. Dominant genera shared by tobacco leaves at different stages were Alternaria and Sampaiozyma. About 80% of fungi in stored tobacco leaves after redrying originated from fresh tobacco leaves before flue-curing, while the rest were primarily enriched in the post-harvest processing environment. After flue-curing, major molds like Aspergillus and Penicillium were notably enriched. The distribution of fungal communities suggested that the flue-curing and redrying had a significant impact on fungal composition. Functional annotation of fungal communities at the guild level exhibited differences during processing stages. Main fungal functional groups were identified. In summary, our study elucidated dynamic changes in the composition of fungal communities and highlighted key stages in mold enrichment during tobacco leaf processing, laying groundwork for mildew prevention and control during tobacco leaf fermentation.

Abstract Per- and poly-fluoroalkyl substances (PFAS) have gained widespread attention due to their adverse effects on health and environment. Developing efficient technology to capture PFAS from contaminated sources remains a great challenge. In this study, we introduce a type of reusable polymeric sorbent (PFPE-IEX + ) for rapid, efficient, and selective removal of multiple PFAS impurities from various contaminated water sources. The resin achieves >98% removal efficiency ([PFPE-IEX + ] = 0.5–5 mg mL−1, [PFAS]0 = 1–10 ppb in potable water and landfill leachate) and >500 mg g−1 sorption capacity for the 11 types of examined PFAS. We achieve efficient PFAS removal without breakthrough and subsequent resin regeneration and demonstrate good PFAS recovery in a proof-of-concept cartridge setup. The outcomes of this study offer valuable guidance to the design of platforms for efficient and selective PFAS capture from contaminated water, such as drinking water and landfill leachate.

Data collection technologies or data sources are critical for highway network management. However, due to the limitations on available management resources, determining the importance of these data sources is necessary to allocate these resources reasonably. This study proposes a complex network based method for evaluating the importance of multiple data sources in highway networks. This method includes mainly three steps. First, the business-data source relation will be identified and formulated for the highway network. Second, a business data source complex network is built from the previously identified business-data relationship. Third, an entropy weight method is used to compute and rank the importance of data source nodes by combining three indexes of degree centrality (DC), closeness centrality (CC) and structural holes (SC) computed based on the complex network. The proposed method is applied and illustrated using the highway network of Xuzhou City, Jiangsu Province, China. The results show that among the data sources, the most important data source is the continuous traffic survey station, followed by an automatic gantry-based station and vehicle detectors-based system. Discussions on the limitations, applications and future studies are provided for the proposed approach.

Anammox granular sludge (AnGS) serves as an important platform for cost-effective nitrogen removal from wastewater. Different to the traditionally sphere-like granules, a novel type of AnGS in a unique ellipsoid-like shape was obtained through enhancing shear force. The ellipsoid-like AnGS significantly exhibited a smaller aspect ratio (-25.1 %) and granular size (-11.8 %), compared to traditional sphere-like AnGS (p < 0.01). Comprehensive comparisons showed that ellipsoid-like AnGS possessed a significantly higher extracellular polymeric substances (EPS) content and strength, as well as an enhanced mass transfer and a higher viable bacteria proportion due to the larger substrate permeable zone (p < 0.01). Additionally, the anammox bacterial abundance (Candidatus Kuenenia) was 12.2 % higher in ellipsoid-like AnGS than in sphere-like AnGS. All these characteristics of ellipsoid-like AnGS jointly increased the specific anammox activity by 29.0 % and nitrogen removal capacity by 22.6 %, compared to sphere-like AnGS. Further fluid field simulation suggested the enhanced flow shear on the side surface of AnGS likely drove the formation of ellipsoid-like AnGS. The higher shear force on the side surface led to an increase of EPS content (especially hydrophobic protein) and elastic modulus, thus constraining lateral expansion. This study sheds light on impacts of granular shape, an overlooked morphological factor, on anammox performance. The ellipsoid-like AnGS presented herein also offers a unique and promising aggregate to enhance anammox performance.

Abstract It is very important to clarify the reservoir damage characteristics and damage characteristics and damage mechanism of tight sandstone gas reservoirs in Jinhua-Zhongtai mountain area of central SiChuan Basin, and put forward the technical countermeasures of “Double protection” drilling fluid to protect the reservoir and the environment, which is very important for the efficient well construction in this area. Through X-ray diffraction, scanning electron microscopy, casting thin sections and other testing methods, the mineral composition and microstructure characteristics of the block were analyzed, and the potential damage factors of the reservoir were clarified. Based on the sensitivity evaluation, it was revealed that the overall sensitivity damage of the block was weak. The main damage type was salt-sensitive damage, and the critical salinity was 9472.5 mg/L. On the basis of the environmental protection drilling fluid system used in this block, the surfactant which can effectively prevent gas invasion and reduce surface tension is selected, and the “Double protection” drilling fluid system is constructed. Through comprehensive performance test and reservoir protection performance evaluation, the core permeability damage rate of the optimized drilling fluid system is reduced from 88.77 to 18.66%, and the cuttings recovery rate is increased to more than 66%, and the cuttings expansion rate is reduced to less than 3.2%, which can effectively solve the problem of reservoir damage in drilling in Jinhua-Zhongtai mountain block in central Sichuan.

Natural gas is easily soluble in oil-based muds (OBM), leading to complex flow behavior in wellbores, especially in horizontal wells. In this study, a new transient flow model considering wellbore-formation coupling and gas solubility on flow behavior is developed to simulate gas kicks during horizontal drilling with OBM. Furthermore, the effect of gas solubility on parameters such as bottom-hole pressure (BHP), gas void fraction and mixture velocity in the flow behavior is analyzed. Finally, several critical factors affecting flow behavior are investigated and compared to gas kicks in water-based muds (WBM) where the effect of solubility is neglected. The results show that the invading gas exists as dissolved gas in the OBM and as free gas in the WBM. Before the gas escapes from the OBM, the pit gain is zero and there is barely any change in the BHP, annulus return flow rate and mixture velocity, which means that detecting gas kicks through these warning signs can be challenging until they get very close to the surface and develop rapidly. However, in WBM drilling, these parameters change quickly with the increasing gas kick time. Additionally, for both cases, the longer the horizontal length and the greater reservoir permeability, the greater the decrease in BHP, and the shorter the time for gas to migrate from the bottom-hole to the wellhead. A larger flow rate contributes to a greater initial BHP and a lesser BHP reduction. This research is of value in characterizing gas kick behavior and identifying novel ways for early gas kick detection during horizontal drilling with OBM.

The accuracy of the control model is essential for the effectiveness of model-based control methods. However, factors such as model simplification, parameter variations, and environmental noise can introduce inaccuracies in vehicle state descriptions, thereby compromising the precision of path tracking. This study introduces data-driven enhancements for an MPC-based path tracking controller in autonomous vehicles (DD-PTC). The approach consists of two parts: firstly, Kolmogorov–Arnold Networks (KANs) are utilized to estimate tire lateral forces and correct tire cornering stiffness, thereby establishing a dynamic predictive model. Secondly, Gaussian Process Regression (GPR) is deployed to accurately capture the unmodeled dynamics of the vehicle to form a comprehensive control model. This enhanced model allows for precise path tracking through steering control. The superiority of DD-PTC is confirmed through extensive testing on the Simulink-CarSim simulation platform, where it consistently surpasses normal MPC and Linear Quadratic Regulator (LQR) strategies, especially in minimizing lateral distance errors under challenging driving conditions.

Short-term energy-consumption prediction is the basis of anomaly detection, real-time scheduling, and energy-saving control in manufacturing systems. Most existing methods focus on single-node energy-consumption prediction and suffer from difficult parameter collection and modelling. Although several methods have been presented for multinode energy-consumption prediction, their prediction performance needs to be improved owing to a lack of appropriate knowledge guidance and learning networks for complex spatiotemporal relationships. This study presents a symmetric spatiotemporal learning network (SSTLN) with a sparse meter graph (SMG) (SSTLN-SMG) that aims to predict multiple nodes based on energy-consumption time series and general process knowledge. The SMG expresses process knowledge by abstracting production nodes, material flows, and energy usage, and provides initial guidance for the SSTLN to extract spatial features. SSTLN, a symmetrical stack of graph convolutional networks (GCN) and gated linear units (GLU), is devised to achieve a trade-off not only between spatial and temporal feature extraction but also between detail capture and noise suppression. Extensive experiments were performed using datasets from an aluminium profile plant. The experimental results demonstrate that the proposed method allows multinode energy-consumption prediction with less prediction error than state-of-the-art methods, methods with deformed meter graphs, and methods with deformed learning networks.

The compression of coral concrete-filled aluminum alloy tube columns is a novel type of laterally restrained concrete element, with axial compressive load being the primary load type sustained by the laterally restrained concrete elements during their service life. In this study, square intermediate-length columns of coral concrete-filled aluminum alloy tubes were subjected to axial compression tests to investigate the influence of section width-to-thickness ratio (B/t), and aspect ratio of the column (L/B) on the failure mode, ultimate load-carrying capacity, and load-deformation relationship of the specimens. The research findings demonstrate that the intermediate-length columns of coral concrete-filled aluminum alloy tube exhibit good compressive performance, with a significant combined effect between the aluminum alloy tube and the core concrete. With an increase in the section width-to-thickness ratio (B/t), the compressive stiffness, ultimate load-carrying capacity, and deformation ductility of the specimens all decrease. As the aspect ratio of the column (L/B) increases, under the condition that end-zone failure does not occur, the ultimate load-carrying capacity and deformation ductility of the specimens gradually decrease, while the extent of flexural deformation significantly increases.

The ongoing evolution of SARS-CoV-2 is a significant concern, especially with the decrease in clinical sequencing efforts, which impedes the ability of public health sectors to prepare for the emergence of new variants and potential COVID-19 outbreaks. Wastewater-based epidemiology (WBE) has been proposed as a surveillance program to detect and monitor the SARS-CoV-2 variants being transmitted in communities. However, research is limited in evaluating the effectiveness of wastewater collection at sentinel sites for monitoring disease prevalence and variant dynamics, especially in terms of inferring the epidemic patterns on a broader scale, such as at the state/province level. This study utilized a multiplexed tiling amplicon-based sequencing (ATOPlex) to track the longitudinal dynamics of variant of concern (VOC) in wastewater collected from municipalities in Queensland, Australia, spanning from 2020 to 2022. We demonstrated that wastewater epidemiology measured by ATOPlex exhibited a strong and consistent correlation with the number of daily confirmed cases. The VOC dynamics observed in wastewater closely aligned with the dynamic profile reported by clinical sequencing. Wastewater sequencing has the potential to provide early warning information for emerging variants. These findings suggest that WBE at sentinel sites, coupled with sensitive sequencing methods, provides a reliable and long-term disease surveillance strategy.

Surface temperature is a key parameter in scientific studies, encompassing areas, such as resource environment, climate change, and terrestrial ecosystems. The moderate-resolution imaging spectroradiometer land surface temperature (MODIS LST) products play a critical role in research related to land surface temperature (LST). However, these products are often plagued with data loss or distortion, attributable to atmospheric conditions or technical impediments. Unfortunately, there is a shortage of fast LST reconstruction methods that consider both the temporal relationships between close images and the LST variation characteristics in complex, heterogeneous terrain. To address this, the present study proposed a novel method, the improved interpolation of the mean anomalies based on the digital elevation model (DEM-IMA), seeking to fill in missing temperature values. The model suggested in this research was evaluated by comparing it to conventional methods, such as interpolation of mean anomalies (IMA) and gap fill (GF), using a combination of simulation data and actual satellite data. The results suggest that the DEM-IMA model enhances LST reconstruction, particularly for heterogeneous landscapes. The approach effectively restored missing data, displaying a remarkable level of accuracy overall. It surpassed both the IMA and GF methods in the task of filling small, medium, and large cloud gaps in day and night LST data. It reduced the root-mean-square error by 17%, with its accuracy higher at night than during the day. The findings of this study have the potential to provide valuable technical support for enhancing the utilization of MODIS LST products and for conducting quantitative analysis and assessment of regional climate resources with greater effectiveness.

Fissures are an important factor to induce slope instability of expansive soil channel, which destroys the integrity of soil mass and deteriorates soil mass. Currently, the research is limited to the fissures in the plane direction, and it is very important to reveal the development mechanism of fissures in expansive soils along the depth direction by studying the development law of fissures in expansive soils with different thicknesses. In this study, taking expansive soil on channel slope of the Middle Route Project of South-to-North Water Transfer as an example, crack expansion tests with thickness of 10 mm, 20 mm, 30 mm and 40 mm are carried out based on self-designed crack expansion test device. An innovative test method for volumetric fracturing rate is proposed and the following conclusions are drawn: (1) the later the cracking time of soil body is, the lower the water content of cracking and the higher the water content after stabilization when the soil body is thicker; (2) When the fissures develop in soils of different thicknesses, their plane fissure rate changes with time in accordance with the logistic law; (3) Volumetric fracturing increases significantly with thickness; (4) The development of fissures is the form of stress release of soil mass, and the release along depth direction is the main form for soil mass with large thickness. (5) It is of great significance to study the law of fracture development in depth direction for further exploring the mechanism of fracture propagation.

Abstract Bladder cancer (BCa) is heterogeneous in the tumour microenvironment (TME). However, the role of the TME in BCa in modulating the response to immunotherapy has not been fully explored. We therefore analysed fractions of immune cells using CIBERSORTx and clustered BCa into subtypes. We also analyzed weighted correlation networks to generate immunotherapy-related hub genes that we used to construct a prediction model using multivariate Cox and LASSO regression analyses. We found that BCa comprised three subtypes (C1‒C3). The prognosis of the patients was the most favourable and the response rate to anti-programmed death ligand 1 (PD-L1) was the highest in C1 among the three subtypes. Immune cells, including CD8+, CD4+ memory activated, and follicular helper T cells, activated NK cells, and M1 macrophages infiltrated the C1 subtype. The C2 subtype was enriched in M0 macrophages and activated mast cells, and the C3 subtype was enriched in B and resting immune cells. Mechanistically, the enhanced immunogenicity of subtypes C1 and C2 correlated positively with a higher response rate, whereas the dysregulated ECM-related pathways in the C2 subtype and glycolytic and fatty acid metabolic pathways in the C3 subtype impaired the responses of patients to anti-PD-L1 therapy. We also constructed a TME-related signature based on 18 genes that performed well in terms of overall survival. In conclusion, we determined prognoses and anti-PD-L1 responses by analysing TME heterogeneity in BCa.

Abstract During the processing of tobacco leaves, flue-curing and redrying can affect the structure of bacterial community, having an effect on the aging quality of tobacco leaves. In order to characterize the effects of flue-curing and redrying on the bacterial community of tobacco leaves, the bacterial community of samples at different processing stages (before flue-curing, after flue-curing, before redrying and after redrying) was analyzed using Illumina sequencing. A total of 33 phyla, 79 classes, 195 orders, 344 families, 826 genera and 7922 ASVs were obtained from 36 samples. There was no significant difference in the core bacterial groups of tobacco leaf at four processing stages. Proteobacteria dominated at the phylum level. Sphingomonas, Pseudomonas and Methylobacterium were the main genera shared by all samples. The functional prediction by PICRUSt showed an increase in the relative abundance of pathway related to metabolism after flue-curing and pathway related to environmental information processing after redrying. This study, we analyzed the changes of bacterial community and structural composition of tobacco leaves from flue-curing to redrying, and found that flue-curing had a greater effect on the microbial community than redrying. This is conducive for the exploration of microbial resources and improvement of tobacco leaf quality.

Abstract During the multistage fracturing of shale gas horizontal wells, casing damage frequently occurs, making it essential to evaluate casing stress and deformation. This paper establishes a mathematical model of thermo‐hydro‐mechanical coupling and a finite element model of casing‐cement sheath‐formation (CCF). This paper examines the effects of temperature, casing thickness, nonuniform in situ stress, mechanical properties of cement sheath, and treating pressure on the stress and deformation of CCF. Finally, the study investigates the variation of local in situ stress at the heel and casing stress from toe to heel. The results show that the low temperature of CCF, high elastic modulus of cement sheath, small casing thickness, high treating pressure, and large nonuniform in situ stress can exacerbate casing stress. After pumping off, the local in situ stress and its nonuniformity near heel gradually increased, and the effective stress of casing increases compared with the pumping on the process. As the fracturing stages increase, the effective stress of casing at heel increases, and the casing at heel preferentially damages. The results provide a theoretical basis and guidance for maintaining wellbore integrity and preventing casing damage in the multistage fracturing of shale gas horizontal wells.

Abstract Several deficiencies exist in the present evaluation of land reclamation quality in mining areas. These include the absence of an established set of evaluation index systems and standard acceptance criteria, as well as the use of traditional sampling techniques, which are costly and in efficiency, and time-consuming. Compared with the traditional sampling survey methods, remote sensing has the advantages of a wide detection range, diverse information collection, multiple data-acquiring strategies, high speed, and short cycle. In this study, we used the Xinzhuang coal mining field in Yongcheng, Henan Province as an example to extract information and invert surface parameters using remote sensing techniques, based on national and local reclamation regulations and standards. Subsequently, using remote sensing, we constructed an index system for evaluating land reclamation quality in three aspects: reclaiming project quality, soil quality, and ecological benefits. Through the grading standards of evaluation indicators and quantitative remote sensing models, we determined the extracted information on the area of indicators, roads, ditches, soil moisture, organic matter, and ecological benefits after reclamation. Based on this, we established a quality evaluation model for mining land reclamation using an improved index and method. The evaluation units were divided, and the weight of the evaluation index was determined using the analytic hierarchy process and data envelopment analysis (AHP–DEA) method. The land reclamation quality in the study area was comprehensively evaluated, field accuracy was verified, and the results were analyzed. The results show that, except for the removal of roads, houses, and fishponds in the study area, all 13 evaluation units achieved a score of 60 points or higher. The quality of reclamation met the standards, and the evaluation results were consistent with the conclusions of the field investigation and project acceptance report, demonstrating the reliability and feasibility of the method developed in this study. The research results will provide technical support for the scientific evaluation of land reclamation quality.

Distributed drive electric vehicles improve steering response and enhance overall vehicle stability by independently controlling each motor. This paper introduces a control framework based on Adaptive Model Predictive Control (AMPC) for coordinating handling stability, consisting of three layers: the dynamic supervision layer, online optimization layer, and low-level control layer. The dynamic supervision layer considers the yaw rate and maneuverability limits when establishing the β−β˙ phase plane stability boundary and designs variable weight factors based on this stability boundary. The online optimization layer constructs the target weight-adaptive AMPC strategy, which can adjust the control weights for maneuverability and lateral stability in real time based on the variable weight factors provided by the dynamic supervision layer. The low-level control layer precisely allocates the driver’s requested driving force and additional yaw moment by using torque distribution error and tire utilization as the cost function. Finally, experiments are conducted on a Simulink-CarSim co-simulation platform to assess the performance of AMPC. Simulation results show that, compared to the traditional MPC strategy, this control strategy not only enhances maneuverability under normal conditions but also improves lateral stability control under extreme conditions.

The Middle Route of the South-to-North Water Diversion Project is a critical infrastructure that ensures optimal water resource distribution across river basins and safeguards the livelihood of people in China. This study investigated its effects on the land surface temperature (LST) and fractional vegetation coverage (FVC) in the Danjiang River Basin. Moreover, it examined the spatial and temporal patterns of this project, providing a scientific basis for the safe supply of water and ecological preservation. We used the improved interpolation of mean anomaly (IMA) method based on the digital elevation model (DEM) to reconstruct LST while FVC was estimated using the image element dichotomous model. Our findings indicated a general increase in the average LST in the Danjiang River Basin post-project implementation. During both wet and dry seasons, the cooling effect was primarily observed in the south-central region during the daytime, with extreme values of 6.1 °C and 5.9 °C. Conversely, during the nighttime, the cooling effect was more prevalent in the northern region, with extreme values of 3.0 °C and 2.3 °C. In contrast, the warming effect during both seasons was predominantly located in the northern region during the daytime, with extreme values of 5.3 °C and 5.5 °C. At night, the warming effect was chiefly observed in the south-central region, with extreme values of 5.8 °C and 5.9 °C. FVC displayed a seasonal trend, with higher values in the wet season and overall improvement over time. Statistical analysis revealed a negative correlation between vegetation change and daytime temperature variations in both periods (r = −0.184, r = −0.195). Furthermore, a significant positive correlation existed between vegetation change and nighttime temperature changes (r = 0.315, r = 0.328). Overall, the project contributed to regulating LST, fostering FVC development, and enhancing ecological stability in the Danjiang River Basin.

Providing safe, smooth, and efficient trajectories for autonomous vehicles has long been a question of great interest in the field of autopiloting. In dynamic and ever-changing urban environments, safe and efficient trajectory planning is fundamental to achieving autonomous driving. Nevertheless, the complexity of environments with multiple constraints poses challenges for trajectory planning. It is possible that behavior planners may not successfully obtain collision-free trajectories in complex urban environments. Herein, this paper introduces spatio–temporal joint optimization-based trajectory planning (SJOTP) with multi-constraints for complex urban environments. The behavior planner generates initial trajectory clusters based on the current state of the vehicle, and a topology-guided hybrid A* algorithm applied to an inflated map is utilized to address the risk of collisions between the initial trajectories and static obstacles. Taking into consideration obstacles, road surface adhesion coefficients, and vehicle dynamics constraints, multi-constraint multi-objective coordinated trajectory planning is conducted, using both differential-flatness vehicle models and point-mass vehicle models. Taking into consideration longitudinal and lateral coupling in trajectory optimization, a spatio–temporal joint optimization solver is used to obtain the optimal trajectory. The simulation verification was conducted on a multi-agent simulation platform. The results demonstrate that this methodology can obtain optimal trajectories safely and efficiently in complex urban environments.

Canine mammary tumors (CMTs) are the most common type of tumor in female dogs. In this study, we obtained a metastatic key protein, Fascin-1, by comparing the proteomics data of in situ tumor and metastatic cell lines from the same individual. However, the role of Fascin-1 in the CMT cell line is still unclear. Firstly, proteomics was used to analyze the differential expression of Fascin-1 between the CMT cell lines CHMm and CHMp. Then, the overexpression (CHMm-OE and CHMp-OE) and knockdown (CHMm-KD and CHMp-KD) cell lines were established by lentivirus transduction. Finally, the differentially expressed proteins (DEPs) in CHMm and CHMm-OE cells were identified through proteomics. The results showed that the CHMm cells isolated from CMT abdominal metastases exhibited minimal expression of Fascin-1. The migration, adhesion, and invasion ability of CHMm-OE and CHMp-OE cells increased, while the migration, adhesion, and invasion ability of CHMm-KD and CHMp-KD cells decreased. The overexpression of Fascin-1 can upregulate the Tetraspanin 4 (TSPAN4) protein in CHMm cells and increase the number of migrations. In conclusion, re-expressed Fascin-1 could promote cell EMT and increase lamellipodia formation, resulting in the enhancement of CHMm cell migration, adhesion, and invasion in vitro. This may be beneficial to improve female dogs’ prognosis of CMT.

The regrowth and subsequent exposure of opportunistic pathogens (OPs) whilst reopening buildings that have been locked down due to the stay-at-home restrictions to limit the spread of COVID-19, is a public health concern. To better understand such microbiological risks due to lowered occupancy and water demand in buildings, first and post-flush water samples (n = 48) were sampled from 24 drinking water outlets from eight university buildings in two campuses (urban and rural), with various end-user occupancies. Both campuses were served with chlorinated water originating from a single drinking water distribution system in South-East Queensland, situated 14 km apart, where the rural campus had lower chlorine residuals. Culture-dependent and culture-independent methods (such as flow cytometry, qPCR and 16S rRNA gene amplicon sequencing) were used concurrently to comprehensively characterise the OPs of interest (Legionella spp., Pseudomonas aeruginosa, and nontuberculous mycobacteria (NTM)) and the premise plumbing microbiome. Results showed that buildings with extended levels of stagnation had higher and diverse levels of microbial growth, as observed in taxonomic structure and composition of the microbial communities. NTM were ubiquitous in all the outlets sampled, regardless of campus or end-user occupancy of the buildings. qPCR and culture demonstrated prevalent and higher concentrations of NTM in buildings (averaging 3.25 log10[estimated genomic copies/mL]) with extended stagnation in the urban campus. Furthermore, flushing the outlets for 30 minutes restored residual and total chlorine, and subsequently decreased the levels of Legionella by a reduction of 1 log. However, this approach was insufficient to restore total and residual chlorine levels for the outlets in the rural campus, where both Legionella and NTM levels detected by qPCR remained unchanged, regardless of building occupancy. Our findings highlight that regular monitoring of operational parameters such as residual chlorine levels, and the implementation of water risk management plans are important for non-healthcare public buildings, as the levels of OPs in these environments are typically not assessed.

ABSTRACTNon-caloric artificial sweeteners have been widely permitted as table sugar substitutes with high intensities of sweetness. They can pass through the intestinal tract without significant metabolization and frequently encounter the gut microbiome, which is composed of diverse bacterial species and is a pool of antibiotic resistance genes (ARGs). However, little is known about whether these sweeteners could accelerate the spread of ARGs in the gut microbiome. Here, we established an in vitro conjugation model by using Escherichia coli that carries chromosome-inserted Tn7 lacIq-pLpp-mCherry and plasmid-encoded gfpmut3b gene as the donor and murine fecal bacteria as the recipient. We found that four commonly used artificial sweeteners (saccharin, sucralose, aspartame, and acesulfame potassium) can increase reactive oxygen species (ROS) production and promote plasmid-mediated conjugative transfer to the gut microbiome. Cell sorting and 16S rRNA gene amplicon sequencing analysis of fecal samples reveal that the tested sweeteners can promote the broad-host-range plasmid permissiveness to both Gram-negative and Gram-positive gut bacteria. The increased plasmid permissiveness was also validated with a human pathogen Klebsiella pneumoniae. Collectively, our study demonstrates that non-caloric artificial sweeteners can induce oxidative stress and boost the plasmid-mediated conjugative transfer of ARGs among the gut microbiota and a human pathogen. Considering the soaring consumption of these sweeteners and the abundance of mobile ARGs in the human gut, our results highlight the necessity of performing a thorough risk assessment of antibiotic resistance associated with the usage of artificial sweeteners as food additives.

Abstract The microbial guild coupling anammox and nitrite/nitrate-dependent anaerobic methane oxidation (n-DAMO) is an innovative process to achieve energy-efficient nitrogen removal with the beneficial use of methane in biogas or in anaerobically treated wastewater. Here, metagenomics and metatranscriptomics were used to reveal the microbial ecology of two biofilm systems, which incorporate anammox and n-DAMO for high-level nitrogen removal in low-strength domestic sewage and high-strength sidestream wastewater, respectively. We find that different nitrogen loadings (i.e., 0.1 vs. 1.0 kg N/m3/d) lead to different combinations of anammox bacteria and anaerobic methanotrophs (“Candidatus Methanoperedens” and “Candidatus Methylomirabilis”), which play primary roles for carbon and nitrogen transformations therein. Despite methane being the only exogenous organic carbon supplied, heterotrophic populations (e.g., Verrucomicrobiota and Bacteroidota) co-exist and actively perform partial denitrification or dissimilatory nitrate reduction to ammonium (DNRA), likely using organic intermediates from the breakdown of methane and biomass as carbon sources. More importantly, two novel genomes belonging to “Ca. Methylomirabilis” are recovered, while one surprisingly expresses nitrate reductases, which we designate as “Ca. Methylomirabilis nitratireducens” representing its inferred capability in performing nitrate-dependent anaerobic methane oxidation. This finding not only suggests a previously neglected possibility of “Ca. Methylomirabilis” bacteria in performing methane-dependent nitrate reduction, and also challenges the previous understanding that the methane-dependent complete denitrification from nitrate to dinitrogen gas is carried out by the consortium of bacteria and archaea.

Prestressed anchor cables are active reinforcement to improve slope stability. However, the anchoring is not a permanent guarantee of stability, and the slope retains a potential risk of instability. From the perspective of the internal force of anchor cables, a new early warning method for the safety of the slope is provided, and a slope analysis model is established. With the increase in the strength reduction factor, the internal force increment curves of anchor cables under different prestresses are obtained. The point corresponding to strength reduction factors λ1 and λ2 represents a warning point. Key conclusions are drawn as follows: (1) The internal force of an anchor cable can be used to judge the stability of the slope strengthened by a prestressed anchor cable. (2) A warning index based on the internal force increment ratio of anchor cables is established. (3) The internal force increment ratio of anchor cables eliminates the influence of the initial prestress and is convenient for engineering applications.

Cloud detection is a fundamental step for optical satellite image applications. Existing deep learning methods can provide more accurate cloud detection results. However, the performance of these methods relies on a large number of label samples, whose collection is time-consuming and high-cost. In addition, cloud detection is challenging in high-brightness scenes due to cloud and high-brightness objects having a similar spectral features. In this study, we propose a cloud index driven spectral-spatial-context attention network (SSCA-net) for cloud detection, which relies on no effort to manually collect label samples and can improve the accuracy of cloud detection in high-brightness scenes. The label samples are automatically generated from the cloud index by using dual-threshold, which is then expanded to improve the completeness of cloud mask labels. We designed SSCA-net with the spectral-spatial-context aware module and spectral-spatial-context information aggregation module, aimed to improve the accuracy of cloud detection in high-brightness scenes. The results show that the proposed SSCA-net achieved good performance with an average overall accuracy of 97.69% and an average kappa coefficient of 92.71% on the Sentinel-2 and Landsat-8 datasets. This article provides fresh insight into how advanced deep attention networks and cloud indexes can be integrated to obtain high accuracy of cloud detection on high-brightness scenes.

Abstract Background Porcine circovirus type 2 (PCV2) is one of the major pathogens commonly found in pigs, which causes immunosuppression and apoptosis. Vaccination and a single drug cannot totally prevent and treat PCV2 infection. Our previous in vitro study reported that the synergistic anti-PCV2 effect of Matrine and Osthole was better than that of Matrine or Osthole alone, This study was aimed to evaluate the synergistic anti-PCV2 effect as well as the underline molecular mechanism of Matrine and Osthole in Kunming (KM) mice model infected with PCV2. KM mice were randomly divided into 8 groups namely control group, PCV2 infected, Matrine combined with Osthole high dose treatment (40 mg/kg + 12 mg/kg), medium dose treatment (20 mg/kg + 6 mg/kg), low dose treatment (10 mg/kg + 3 mg/kg), Matrine treatment (40 mg/kg), Osthole treatment (12 mg/kg) and Ribavirin positive control (40 mg/kg) groups. PCV2 was intraperitoneally (i.p.) injected in all mice except the control group. 5 days of post-infection (dpi), mice in different treatment groups were injected i.p. with various doses of Matrine, Osthole and Ribavirin once daily for the next 5 consecutive days. Results The synergistic inhibitory effect of Matrine and Osthole on PCV2 replication in mouse liver was significantly heigher than that of Matrine and Osthole alone. The expression of GRP78, p-PERK, p-eIF2α, ATF4, CHOP, cleaved caspase-3 and Bax proteins were significantly reduced, while that of Bcl-2 was significantly increased in Matrine combined with Osthole groups, which alleviated the pathological changes caused by PCV2, such as interstitial pneumonia, loss of spleen lymphocytes, infiltration of macrophages and eosinophils. Conclusions The synergistic anti-apoptotic effect of Matrine and Osthole was better than their alone effect, Both Matrine and Osthole had directly inhibited the expression of PCV2 Cap and the apoptosis of spleen cells induced by PCV2 Cap through the PERK pathway activated by endoplasmic reticulum (ER) GRP78. These results provided a new insight to control PCV2 infection and provide good component prescription candidate for the development of novel anti-PCV2 drugs.

Abstract Background Zedoary turmeric oil extracted from the roots of curcuma (Curcuma aeruginosa Roxb.) is used for the treatment of myocarditis in China. EMCV infection causes abortion in pregnant sows and myocarditis in piglets. Our previous studies demonstrated that curcumol significantly increased the expression of IFN-β in EMCV infected HEK-293T cells. The present results showed that curcumol inhibits EMCV replication by interfering the host cell cholesterol homeostasis and reducing ROs production through activation of the JAK/STAT signaling pathway. Method This study was designed to explore whether curcumol can inhibit the replication of encephalomyocarditis viruses (EMCV) in cell culture. The expression level of JAK1, IRF9, STAT2, P-STAT2, CH25H, PI4KA and OSBP in EMCV-infected HEK-293T cells treated with curcumol, ribavirin or hydroxypropyl-β-CD (HPCD) were determined by Western blotting (WB). The cholesterol level in EMCV infected HEK-293T cells treated with curcumol and HPCD were detected using Amplex™ Red Cholesterol Assay Kit. The antiviral effects of curcumol and HPCD on EMCV were also quantitatively detected by real-time fluorescence quantitative PCR (q-PCR). The amount and morphology of ROs were observed by transmission electron microscopy (TEM). Results The results demonstrated that curcumol significantly (P < 0.05) increased the expression of JAK1, IRF9, P-STAT2 and CH25H proteins, while that of STAT2, PI4KA and OSBP were remained unchanged. Compared with virus group (0.134 μg.μg-1 proteins), the total cholesterol level was significantly (P < 0.05) reduced by curcumol (0.108 μg.μg-1 proteins) and HPCD (0.089 μg.μg-1 proteins). Compared with virus group (88237 copies), curcumol (41802 copies) and HPCD (53 copies) significantly (P < 0.05) reduced EMCV load. Curcumol significantly reduced the production of ROs in EMCV-infected HEK-293T cells and activated CH25H through the JAK/STAT signaling pathway. Conclusion Curcumol inhibited EMCV replication by affecting the cholesterol homeostasis and the production of ROs in HEK-293T cell.

Anaerobic microorganisms can oxidize short-chain gaseous alkanes such as ethane, propane and butane using sulfate as electron acceptor. Here, the authors show that a bioreactor enrichment of a wastewater microbial community can perform anaerobic propane oxidation coupled to nitrate reduction.

Abstract Antibiotic resistance genes are often carried by plasmids, which spread intra- and inter genera bacterial populations, and also play a critical role in bacteria conferring phage resistance. However, it remains unknown about the influence of plasmids present in bacterial hosts on phage isolation and subsequent infectivity. In this study, using both Escherichia coli and Pseudomonas putida bacteria containing different plasmids, eight phages were isolated and characterized in terms of phage morphology and host range analysis, in conjunction with DNA and protein sequencing. We found that plasmids can influence both the phage isolation process and phage infectivity. In particular, the isolated phages exhibited different phage plaquing infectivity towards the same bacterial species containing different plasmids. Furthermore, the presence of plasmids was found to alter the expression of bacteria membrane protein, which correlates with bacterial cell surface receptors recognized by phages, thus affecting phage isolation and infectivity. Given the diverse and ubiquitous nature of plasmids, our findings highlight the need to consider plasmids as factors that can influence both phage isolation and infectivity.

Abstract Background Horizontal gene transfer (HGT) plays a critical role in the spread of antibiotic resistance and the evolutionary shaping of bacterial communities. Conjugation is the most well characterized pathway for the spread of antibiotic resistance, compared to transformation and transduction. While antibiotics have been found to induce HGT, it remains unknown whether non-antibiotic pharmaceuticals can facilitate conjugation at a microbial community-wide level. Results In this study, we demonstrate that several commonly consumed non-antibiotic pharmaceuticals (including carbamazepine, ibuprofen, naproxen and propranolol), at environmentally relevant concentrations (0.5 mg/L), can promote the conjugative transfer of IncP1-α plasmid-borne antibiotic resistance across entire microbial communities. The over-generation of reactive oxygen species in response to these non-antibiotic pharmaceuticals may contribute to the enhanced conjugation ratios. Cell sorting and 16S rRNA gene amplicon sequencing analyses indicated that non-antibiotic pharmaceuticals modulate transconjugant microbial communities at both phylum and genus levels. Moreover, microbial uptake ability of the IncP1-α plasmid was also upregulated under non-antibiotic pharmaceutical exposure. Several opportunistic pathogens, such as Acinetobacter and Legionella, were more likely to acquire the plasmid conferring multidrug resistance. Conclusions Considering the high possibility of co-occurrence of pathogenic bacteria, conjugative IncP1-α plasmids and non-antibiotic pharmaceuticals in various environments (e.g., activated sludge systems), our findings illustrate the potential risk associated with increased dissemination of antibiotic resistance promoted by non-antibiotic pharmaceuticals in complex environmental settings. Video abstract

BackgroundWith the development of early diagnosis and treatment, the second primary malignancy (SPM) attracts increasing attention. The second primary prostate cancer (spPCa) is an important class of SPM, but remains poorly understood.MethodsWe retrospectively analyzed 3,322 patients with spPCa diagnosed between 2004 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database. Chi-square test was applied to compare demographic and clinical variables and analyze causes of death. Multivariate competitive risk regression model was used to identify risk factors associated with prostate-cancer-specific mortality (PCSM), and these factors were enrolled to build a nomogram of competitive risk. The C-index, calibration curve, and decision curve analysis (DCA) were employed to evaluate the discrimination ability of our nomogram.ResultsThe median follow-up (interquartile range, IQR) time was 47 (24–75) months, and the median (IQR) diagnosis interval between the first primary cancer (FPC) and spPCa was 32 (16–57) months. We found that the three most common sites of SPM were the urinary system, digestive system, and skin. Through multivariate competitive risk analysis, we enrolled race (p < 0.05), tumor–node–metastasis (TNM) stage (p < 0.001), Gleason score (p < 0.05), surgery (p = 0.002), and radiotherapy (p = 0.032) to construct the model to predict the outcomes of spPCa. The C-index was 0.856 (95% CI, 0.813–0.899) and 0.905 (95% CI, 0.941–0.868) in the training and validation set, respectively. Moreover, both the calibration curve and DCA illustrated that our nomogram performed well in predicting PCSM.ConclusionIn conclusion, we identified four risk factors associated with the prognosis of spPCa and construct a competing risk nomogram, which performed well in predicting the 3-, 5-, and 10-year PCSM.

In the present study, the optimization design of the cubic nonlinear damping is conducted for a floating raft isolation system, which can be simplified as a multiple degree-of-freedom system with double parallel freedom inputs. The direct relationship between the power transmissibility and cubic nonlinear damping parameters is derived by taking advantage of the output frequency response function (OFRF) approach. The design requirements are proposed in order to achieve low resonant peak values, low power transmissibility over the high frequency range. The detailed step-by-step design process of the floating raft isolation system applied in a practical vessel is provided. A polynomial function, in terms of the required frequency range, is developed and validated from the simulation data. The case application indicates that the design method determined by the OFRF approach can effectively realize the design requirements of a floating raft isolation system, which can deal with the relationship of the power transmissibility and nonlinear damping parameters.

Mainstream nitrogen removal via anammox is widely recognized as a promising wastewater treatment process. However, its application is challenging at large scale due to unstable suppression of nitrite-oxidizing bacteria (NOB). In this study, a pilot-scale mainstream anammox process was implemented in an Integrated Fixed-film Activated Sludge (IFAS) configuration. Stable operation with robust NOB suppression was maintained for over one year. This was achieved through integration of three key control strategies: i) low dissolved oxygen (DO = 0.4 ± 0.2 mg O2/L), ii) regular free nitrous acid (FNA)-based sludge treatment, and iii) residual ammonium concentration control (NH4+ with a setpoint of ∼8 mg N/L). Activity tests and FISH demonstrated that NOB barely survived in sludge flocs and were inhibited in biofilms. Despite receiving organic-deficient wastewater from a pilot-scale High-Rate Activated Sludge (HRAS) system as the feed, the system maintained a stable effluent total nitrogen concentration mostly below 10 mg N/L, which was attributed to the successful retention of anammox bacteria. This study successfully demonstrated large-scale long-term mainstream anammox application and generated new practical knowledge for NOB control and anammox retention.

Abstract The development of antibiotic resistance as an unavoidable consequence of the application of antimicrobials is a significant concern for human health. Antidepressants are being increasingly consumed globally. Human gut microbial communities are frequently exposed to antidepressants, yet little is known about the interaction between antidepressants and antibiotic resistance. This study aimed to investigate whether antidepressants can accelerate the dissemination of antibiotic resistance by increasing the rate of the horizontal transfer of antibiotic resistance genes (ARGs). Results demonstrated that some of the commonly-prescribed antidepressants (Duloxetine, Sertraline, Fluoxetine and Bupropion) at clinically relevant concentrations can significantly (n = 9; p adj

Abstract Background Porcine Reproductive and Respiratory Syndrome (PRRS) is one of the most important porcine viral diseases which have been threatening the pig industry in China. At present, most commercial vaccines fail to provide complete protection because of highly genetic diversity of PRRSV strains. This study aimed to optimize a component formula from traditional Chinese medicine(TCM)compounds with defined chemical characteristics and clear mechanism of action against PRRSV. Methods A total of 13 natural compounds were screened for the anti-PRRSV activity using porcine alveolar macrophages (PAMs). Three compounds with strong anti-PRRSV activity were selected to identify their potential protein targets by proteomic analysis. The optimal compound formula was determined by orthogonal design based on the results of proteomics. MTT assay was used to determine the maximum non-cytotoxic concentration (MNTC) of each compound using PAMs. QPCR and western blot were used to investigate the PRRSV N gene and protein expression, respectively. The Tandem Mass Tag (TMT) technique of relative quantitative proteomics was used to detect the differential protein expression of PAMs treated with PRRSV, matrine (MT), glycyrrhizic acid (GA) and tea saponin (TS), respectively. The three concentrations of these compounds with anti-PRRSV activity were used for orthogonal design. Four formulas with high safety were screened by MTT assay and their anti-PRRSV effects were evaluated. Results MT, GA and TS inhibited PRRSV replication in a dose-dependent manner. CCL8, IFIT3, IFIH1 and ISG15 were the top four proteins in expression level change in cells treated with MT, GA or TS. The relative expression of IFIT3, IFIH1, ISG15 and IFN-β mRNAs were consistent with the results of proteomics. The component formula (0.4 mg/mL MT + 0.25 mg/mL GA + 1.95 μg/mL TS) showed synergistic anti-PRRSV effect. Conclusions The component formula possessed anti-PRRSV activity in vitro, in which the optimal dosage on PAMs was 0.4 mg/mL MT + 0.25 mg/mL GA + 1.95 μg/mL TS. Compatibility of the formula was superposition of the same target with GA and TS, while different targets of MT. IFN-β may be one of the targets of the component formula possessed anti-PRRSV activity.

Abstract Recently, the application and development of flexible microwave-absorption composites based on silicone rubber have gradually become a research hot spot. In this study, methyl vinyl phenyl silicone rubber (MPVQ)/carbonyl iron particles (CIPs)/graphene (GR) composites were prepared by mechanical blending, and the effects of thermal-ageing temperature on the microwave-absorption properties of the composites were investigated. The mechanism of the thermal-ageing temperature’s effects on microwave-absorption behaviour was identified. The results show that unaged composites have superior microwave-absorption properties, with a minimum reflection loss (RL min ) of − 87.73 dB, a lowest thickness of 1.46 mm, and an effective absorption bandwidth (EAB, RL

【Objective】The study was carried out to explore the effect of chemical stress on the colonization ability of biocontrol bacteria on cucumber plants.【Method】By setting a greenhouse experiment and two field experiments, biocontrol bacteria were inoculated on cucumber plants without fungicides and pathogens, with fungicides and without pathogens, with fungicides and pathogens, respectively.【Result】The six biocontrol strains tested had good colonization effects on cucumber leaves and roots. Under the greenhouse conditions without fungicides and pathogens, the colonization of each biocontrol strain showed a trend of decrease-increase-stability, strains 1BS4 and 3BY4 had strong colonization ability in cucumber leaves and roots. The colonization quantity of strains 1BS4 and 3BY4 was close to 106 CFU/g(FW) at 30 days post inoculation(dpi) about 104 CFU/g(FW); Under the field conditions without fungicides and with pathogens, there were significant differences in the colonization quantities of various biocontrol strains in leaves and roots, and they all showed a trend of decrease-increase-decrease-stability. Strain 5BJN1 had the strongest colonization ability. The colonization quantity of cucumber leaves and roots at 30 dpi was 105.92 CFU/g(FW) and 104.95 CFU/g(FW), respectively; Under the field conditions with both fungicides and pathogens, there were differences in the colonization quantity of biocontrol bacteria in leaves and roots, but the difference was not significant, and all showed a trend of decrease-increase-decrease-stability, and the colonization quantities of strains 3BJN7 and 5BJN1 in cucumber leaves at 30 dpi were relatively high, which were 103.88 CFU/g(FW) and 104.23 CFU/g(FW), respectively. The colonization quantity of other strains was about 103 CFU/g(FW).【Conclusion】The effect of chemicals on the colonization ability of biocontrol bacteria depends on the types of strains. Some strains (3BJN7 and 5BJN1) have good compatibility with chemicals. In the presence of cucumber downy mildew, they can still maintain a certain amount of colonization after using chemicals, therefore, they can be used as potential biocontrol agents; In the absence of fungicide stress, the emergence of downy mildew pathogen can induce the improvement of colonization ability of strain 3BJN7 so that it can colonize stably on cucumber plants.

Globally, brucellosis is a widespread zoonotic disease. It is prevalent in more than 170 countries and regions. It mostly damages an animal’s reproductive system and causes extreme economic losses to the animal husbandry industry. Once inside cells, Brucella resides in a vacuole, designated the BCV, which interacts with components of the endocytic and secretory pathways to ensure bacterial survival. Numerous studies conducted recently have revealed that Brucella’s ability to cause a chronic infection depends on how it interacts with the host. This paper describes the immune system, apoptosis, and metabolic control of host cells as part of the mechanism of Brucella survival in host cells. Brucella contributes to both the body’s non-specific and specific immunity during chronic infection, and it can aid in its survival by causing the body’s immune system to become suppressed. In addition, Brucella regulates apoptosis to avoid being detected by the host immune system. The BvrR/BvrS, VjbR, BlxR, and BPE123 proteins enable Brucella to fine-tune its metabolism while also ensuring its survival and replication and improving its ability to adapt to the intracellular environment.

The limited driving range and the unavailability or insufficiency of battery charging/swapping stations cause the so-called range anxiety issue for traffic assignment involving battery electric vehicle (BEV) users. In addition, expected utility theory-based stochastic user equilibrium (EUT-SUE) model generates the perfectly rational issue when the travellers make route choice decisions. To tackle these two problems, this article improves the cumulative prospect theory-based stochastic user equilibrium (CPT-SUE) model in a degradable transport network through incorporating the constraints of multiple user classes and distance limit. In this degradable network, the travellers experience stochastic travel times due to network link capacity degradations. For this improved CPT-SUE model, the equivalent variational inequality (VI) model and associated method of successive averages (MSA) based solution are provided. The improved CPT-SUE model is tested and compared with the EUT-SUE model with distance limit, with results showing that the improved CPT-SUE model can handle jointly the range anxiety issue and the perfectly rational issue.

Asymmetric transamination of α-keto amides could provide an efficient strategy to synthesise peptides, but has not been well developed yet. Here, the authors design chiral pyridoxamine catalyst and realize the asymmetric biomimetic transamination of α-keto amides, providing access to various peptides with excellent enantiopurities.

Abstract In this paper, a novel energy management strategy with the improved adaptability to various conditions for plug‐in hybrid electric vehicle (PHEV) is proposed. The control parameters, derived from the benchmark test, are optimized offline for different driving conditions. The optimized parameters are implemented according to different driving behaviours identified online. The offline and online cooperation improves performance of energy management strategy in different driving conditions. Three main efforts have been made: Firstly, the valuable features that describe different driving conditions are extracted by random forest (RF) and the features are used for determining driving condition categories, utilized for online driving condition identification by support vector machine (SVM). Secondly, the control thresholds in the developed control strategy are optimized by whale optimization algorithm (WOA) under different driving conditions. The optimal control thresholds for different driving conditions will be called online after certain traffic condition is categorized. At last, simulation‐based evaluation is performed, validating the enhanced performance of the proposed methods in energy‐saving in different driving conditions.

Abstract Porcine reproductive and respiratory syndrome (PRRS) induces respiratory disease and reproductive failure accompanied by gastroenteritis-like symptoms. The mechanism of intestinal barrier injury caused by PRRSV infection in piglets has yet to be investigated. An in vivo PRRSV-induced model was established in 30-day-old piglets by the intramuscular injection of 2 mL of 104 TCID50/mL PRRSV for 15 days. Observations of PRRSV replication and histology were conducted in the lungs and intestine, and goblet cell counts, relative MUC2 mRNA expression, and tight junction protein, proinflammatory cytokine, TLR4, MyD88, IκB and p-IκB expression were measured. PRRSV replicated in the lungs and small intestine, as demonstrated by absolute RT-qPCR quantification, and the PRRSV N protein was detected in the lung interstitium and jejunal mucosa. PRRSV infection induced both lung and gut injury, markedly decreased villus height and the villus to crypt ratio in the small intestine, and obviously increased the number of goblet cells and the relative expression of MUC2 mRNA in the jejunum. PRRSV infection aggravated the morphological depletion of tight junction proteins and increased IL-1β, IL-6, IL-8 and TNF-α expression by activating the NF-κB signalling pathway in the jejunum. PRRSV infection impaired intestinal integrity by damaging physical and immune barriers in the intestine by inducing inflammation, which may be related to the regulation of the gut-lung axis. This study also provides a new hypothesis regarding the pathogenesis of PRRSV-induced diarrhoea.

Under the trend of vehicle intelligentization, many electrical control functions and control methods have been proposed to improve vehicle comfort and safety, among which the Adaptive Cruise Control (ACC) system is a typical example. However, the tracking performance, comfort and control robustness of the ACC system need more attention under uncertain environments and changing motion states. Therefore, this paper proposes a hierarchical control strategy, including a dynamic normal wheel load observer, a Fuzzy Model Predictive Controller and an integral-separate PID executive layer controller. Firstly, a deep learning-based dynamic normal wheel load observer is added to the perception layer of the conventional ACC system and the observer output is used as a prerequisite for brake torque allocation. Secondly, a Fuzzy Model Predictive Control (fuzzy-MPC) method is adopted in the ACC system controller design, which establishes performance indicators, including tracking performance and comfort, as objective functions, dynamically adjusts their weights and determines constraint conditions based on safety indicators to adapt to continuously changing driving scenarios. Finally, the executive controller adopts the integral-separate PID method to follow the vehicle’s longitudinal motion commands, thus improving the system’s response speed and execution accuracy. A rule-based ABS control method was also developed to further improve the driving safety of vehicles under different road conditions. The proposed strategy has been simulated and validated in different typical driving scenarios and the results show that the proposed method provides better tracking accuracy and stability than traditional techniques.

Aroma is a crucial quality attribute of apple fruit, which significantly impacts its commercial value and consumer choice. Despite its importance the volatile aroma substances produced by the new variety ‘Ruixue’ after harvest remain unclear. In this study, we utilized headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) to investigate the changes in volatile substances, fruit hardness, crispness, and related aroma synthase activity of commercially mature ‘Ruixue’ apples during cold storage. Our findings revealed a gradual decline in fruit firmness and brittleness of ‘Ruixue’ apples during cold storage, with hexyl acetate, hexyl caproate, and hexyl thiocyanate being the main hexyl esters detected. To gain a better understanding of the metabolic pathway of esters, we identified 42 MdCXE gene members that are associated with ester degradation. Through RT-qPCR analysis, we discovered that carboxylesterase MdCXE20 exhibited higher expression levels compared to other MdCXE genes during cold storage. To confirm the role of MdCXE20, we conducted a transient injection of apple fruits and observed that overexpression of MdCXE20 led to the degradation of esters such as hexyl hexanoate, butyl hexanoate, butyl 2-methylbutyrate, hexyl butyrate, and hexyl 2-methylbutyrate. The results of the study showed that the virus-induced gene silencing of MdCXE20 found the opposite results. Additionally, the esters of OE-MdCXE20 callus showed a lower content of ester VOC than the control callus, according to the homologous stable transformation of ‘Wanglin’ callus. Overall, these findings suggest that the MdCXE20 gene plays a crucial role in the decrease of esters in ‘Ruixue’ apples, which ultimately affects their flavor.

BackgroundNumerous studies have found that infiltrating M2 macrophages play an important role in the tumor progression of lung adenocarcinoma (LUAD). However, the roles of M2 macrophage infiltration and M2 macrophage-related genes in immunotherapy and clinical outcomes remain obscure.MethodsSample information was extracted from TCGA and GEO databases. The TIME landscape was revealed using the CIBERSORT algorithm. Weighted gene co-expression network analysis (WGCNA) was used to find M2 macrophage-related gene modules. Through univariate Cox regression, lasso regression analysis, and multivariate Cox regression, the genes strongly associated with the prognosis of LUAD were screened out. Risk score (RS) was calculated, and all samples were divided into high-risk group (HRG) and low-risk group (LRG) according to the median RS. External validation of RS was performed using GSE68571 data information. Prognostic nomogram based on risk signatures and other clinical information were constructed and validated with calibration curves. Potential associations of tumor mutational burden (TMB) and risk signatures were analyzed. Finally, the potential association of risk signatures with chemotherapy efficacy was investigated using the pRRophetic algorithm.ResultsBased on 504 samples extracted from TCGA database, 183 core genes were identified using WGCNA. Through a series of screening, two M2 macrophage-related genes (GRIA1 and CLEC3B) strongly correlated with LUAD prognosis were finally selected. RS was calculated, and prognostic risk nomogram including gender, age, T, N, M stage, clinical stage, and RS were constructed. The calibration curve shows that our constructed model has good performance. HRG patients were suitable for new ICI immunotherapy, while LRG was more suitable for CTLA4-immunosuppressive therapy alone. The half-maximal inhibitory concentrations (IC50) of the four chemotherapeutic drugs (metformin, cisplatin, paclitaxel, and gemcitabine) showed significant differences in HRG/LRG.ConclusionsIn conclusion, a comprehensive analysis of the role of M2 macrophages in tumor progression will help predict prognosis and facilitate the advancement of therapeutic techniques.

Background: Numerous studies have shown that infiltrating eosinophils play a key role in the tumor progression of bladder urothelial carcinoma (BLCA). However, the roles of eosinophils and associated hub genes in clinical outcomes and immunotherapy are not well known.Methods: BLCA patient data were extracted from the TCGA database. The tumor immune microenvironment (TIME) was revealed by the CIBERSORT algorithm. Candidate modules and hub genes associated with eosinophils were identified by weighted gene co-expression network analysis (WGCNA). The external GEO database was applied to validate the above results. TIME-related genes with prognostic significance were screened by univariate Cox regression analysis, lasso regression, and multivariate Cox regression analysis. The patient’s risk score (RS) was calculated and divided subjects into high-risk group (HRG) and low-risk group (LRG). The nomogram was developed based on the risk signature. Models were validated via receiver operating characteristic (ROC) curves and calibration curves. Differences between HRG and LRG in clinical features and tumor mutational burden (TMB) were compared. The Immune Phenomenon Score (IPS) was calculated to estimate the immunotherapeutic significance of RS. Half-maximal inhibitory concentrations (IC50s) of chemotherapeutic drugs were predicted by the pRRophetic algorithm.Results: 313 eosinophil-related genes were identified by WGCNA. Subsequently, a risk signature containing 9 eosinophil-related genes (AGXT, B3GALT2, CCDC62, CLEC1B, CLEC2D, CYP19A1, DNM3, SLC5A9, SLC26A8) was finally developed via multiplex analysis and screening. Age (p < 0.001), grade (p < 0.001), and RS (p < 0.001) were independent predictors of survival in BLCA patients. Based on the calibration curve, our risk signature nomogram was confirmed as a good predictor of BLCA patients’ prognosis at 1, 3, and 5 years. The association analysis of RS and immunotherapy indicated that low-risk patients were more credible for novel immune checkpoint inhibitors (ICI) immunotherapy. The chemotherapeutic drug model suggests that RS has an effect on the drug sensitivity of patients.Conclusions: In conclusion, the eosinophil-based RS can be used as a reliable clinical predictor and provide insights into the precise treatment of BLCA.

BackgroundThe tumor microenvironment (TME) is a complex and evolving environment, and the tumor immune microenvironment in kidney renal clear cell carcinoma (KIRC) has a strong suppressive profile. This study investigates the potential prognostic role and value of genes of the tumor microenvironment in KIRC.MethodsThe transcriptome sequencing data of 530 cases and 39 cases of KIRC and the corresponding clinical prognosis information were downloaded from TCGA data and GEO data, respectively, and TME-related gene expression profiles were extracted. A prognostic signature was constructed and evaluated using univariate Cox regression analysis and LASSO regression analysis. Gene set enrichment analysis (GSEA) was used to obtain the biological process of gene enrichment in patients with high and low-risk groups.ResultsA prognostic signature consisting of eight TME-related genes (LRFN1, CSF1, UCN, TUBB2B, SERPINF1, ADAM8, ABCB4, CCL22) was constructed. Kaplan-Meier survival analysis yielded significantly lower survival times for patients in the high-risk group than in the low-risk group, and the AUC values for the ROC curves of this prognostic signature were essentially greater than 0.7, and univariate and multifactorial Cox regression analyses indicated that the risk score was independent risk factors for KIRC prognosis. GSEA analysis showed that immune-related biological processes were enriched in the high-risk group and that risk values were strongly associated with multiple immune cell scores and immune checkpoint-related genes (PDCD1, CTLA4).ConclusionsThe prognostic signature can accurately predict the prognosis of KIRC patients, which may provide new ideas for future precision immunotherapy of KIRC.