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Duplex stainless steel (DSS) is widely used in the marine, petroleum, chemical, automotive, and other fields owing to its excellent mechanical properties and corrosion resistance. However, the research on duplex stainless steel prepared by additive manufacturing is still limited. In this paper, high-density 2507 DSS was successfully prepared by selective laser melting (SLM) additive manufacturing. The effects of energy density on the formability, phase composition, microstructure and corrosion properties of SLM 2507 DSS were investigated. The results showed that with the decrease of the energy density, the density of the specimen increases first and then decreases, and the density achieves 99.18% with the energy density of 190.5 J/mm3. The types of phases are not affected by the energy density, i.e., all 2507 DSS samples prepared by SLM showed a ferrite phase. The YOZ (parallel to the building direction) plane of the SLM 2507 DSS samples showed predominantly columnar grains attributed to the high temperature gradient and epitaxial growth characteristics. With the increase of energy density, the average grain size decreases slightly from 16.97 μm to 15.78 μm, the KAM value decreases slightly from 1.15 to 1.05, and the low angle grain boundaries (LAGBs) increase significantly from 68.4% to 74.8%. The SLM 2507 DSS sample exhibited excellent corrosion resistance. The self-corrosion potential of the sample is 136 mV and the self-corrosion current density is 2.066 × 10−8 A/cm2 at the maximum density. This investigation provides a new approach for the preparation of super duplex stainless steel, which can provide a theoretical basis and guidance for industrialized application.

ABSTRACT: Salmonella is a globally prevalent foodborne pathogen, and adverse events caused by S. Enteritidis and S. Typhimurium are extremely common. With the emergence of drug resistance, there is an urgent need for efficient and specific lytic bacteriophages as alternative to antibiotics in clinical practice. In this study, phage P6 was isolated and screened from effluent and fecal samples from duck farm environments to specifically lyse the duck sources S. Typhimurium and S. Enteritidis. Phage P6 belongs to the genus Lederbergvirus, unclassified Lederbergvirus species. The phage P6 genome did not contained non-coding RNA, virulence genes and drug resistance genes, indicating that phage P6 was biologically safe for clinical applications. Phage P6 lysed 77.78% (28/36) of multidrug-resistant Salmonella and reduced biofilms formed by S. Enteritidis CVCC 3377, 4, and 24, and S. Typhimurium 44 by 44% to 75% within 3 h, and decreased Salmonella in duckling feces by up to 1.64 orders of magnitude. Prokaryotic expression of endolysin LysP6 lysed the chloroform-treated bacterial outer membrane from different serotypes of duck-derived Salmonella and E. coli standard strain ATCC 25922. The host range was expanded compared to phage P6, and the growth of Salmonella was effectively inhibited by LysP6 in conjunction with the membrane permeabilizer EDTA within 24 h. Therefore, phage P6 and phage-derived endolysins LysP6 are suitable for application as potent biocontrol agents to improve poultry health and food safety.

Pullulan is a kind of natural polymer, which is widely used in medicine and food because of its solubility, plasticity, edible, non-toxicity and good biocompatibility. It is of great significance to improve the yield of pullulan by genetic modification of microorganisms. It was previously reported that Aureobasidium melanogenum TN3-1 isolated from honey-comb could produce high-yield of pullulan, but the molecular mechanisms of its production of pullulan had not been completely solved. In this study, the reported strains of Aureobasidium spp. were further compared and analyzed at genome level. It was found that genome duplication and genome genetic variations might be the crucial factors for the high yield of pullulan and stress resistance. This particular phenotype may be the result of adaptive evolution, which can adapt to its environment through genetic variation and adaptive selection. In addition, the TN3-1 strain has a large genome, and the special regulatory sequences of its specific genes and promoters may ensure a unique characteristics. This study is a supplement of the previous studies, and provides basic data for the research of microbial genome modification in food and healthcare applications.

Disinfection by-products (DBPs), generated from the reaction of disinfectants with DBP precursors, have been found to pose unintentional risks to human health. Considering that the concentration and speciation of DBPs formed during disinfection will be affected by the content and composition of dissolved organic matter (DOM), widespread concern about the characteristics of DBP precursors in water sources have been prompted. Three-dimensional excitation–emission matrix (EEM) can quickly and efficiently determine the properties and composition of DOM in water, and thus is generally used to investigate the origin of DBP precursors in water sources. This study overviews the fluorescent properties of different DBP precursors, summarizes the application of different EEM interpretation methods in DBP precursors and analyses the key factors affecting the correlation between the fluorescent components and DBP precursors (e.g., natural organic matter, algal organic matter, effluent organic matter and organic matter derived from other sources). A series of factors, including composition of fluorophores, bromide concentration, spatio-temporal characteristics and disinfectant types, could impact the correlation between DBP formation potential and fluorescent components. As for future research needs, it is of significance to select suitable fluorescence analysis methods and investigate the combination of EEM with other characterization technologies based on different situations. HIGHLIGHTS The main substances and sources of DBP precursors in water are introduced.; Fluorescence analysis methods for DBP precursor are summarized.; The fluorescence properties of DBP precursors from different sources are analyzed.; The correlation between fluorescent substances and DBP precursors are discussed.;

Graph Pooling technology plays an important role in graph node classification tasks. Sorting pooling technologies maintain large-value units for pooling graphs of varying sizes. However, by analyzing the statistical characteristic of activated units after pooling, we found that a large number of units dropped by sorting pooling are negative-value units that contain representative information and can contribute considerably to the final decision. To maintain more representative information, we proposed a novel pooling technology, called Geometric Pooling (GP), containing the unique node features with negative values by measuring the similarity of all node features. We reveal the effectiveness of GP from the entropy reduction view. The experiments were conducted on TUdatasets to show the effectiveness of GP. The results showed that the proposed GP outperforms the SOTA graph pooling technologies by $1\%~\sim ~5\%$ with fewer parameters.

A better understanding of protein–protein interaction (PPI) networks representing physical interactions between proteins could be beneficial for evolutionary insights as well as for practical applications such as drug development. As a statistical model for PPI networks, duplication–divergence models have been proposed, but they suffer from resulting in either very sparse networks in which most of the proteins are isolated, or in networks which are much denser than what is usually observed, having almost no isolated proteins. Moreover, in real networks, where a gene codes a protein, gene loss may occur. The loss of nodes has not been captured in duplication–divergence models to date. Here, we introduce a new duplication–divergence model which includes node loss. This mechanism results in networks in which the proportion of isolated proteins can take on values which are strictly between 0 and 1. To understand this new model, we apply strong and weak attacks to networks from duplication–divergence models with and without node loss, and compare the results to those obtained when carrying out similar attacks on two real PPI networks of E. coli and of S. cerevisiae. We find that the new model more closely reflects the damage caused by strong and weak attacks found in the PPI networks.

ABSTRACT: Since September 2018, serious meningitis has been found on some breeding-duck farms in Shandong Province, China. A large number of ducks exhibit severe neurological symptoms. The ducks were randomly selected for laboratory testing. Duck brain samples were collected using standard sterile techniques, and the staphylococci isolates were detected in 404 (70.14%) out of 576 brain samples. A total of 525 coagulase-negative staphylococci (CoNS) strains were isolated, including 6 species: Staphylococcus sciuri (S. sciuri) (67.24%, 353/525), Staphylococcus epidermidis (S. epidermidis) (9.71%, 51/525), Staphylococcus saprophyticus (S. saprophyticus) (8.38%, 44/525), Staphylococcus lentus (S. lentus) (7.62%, 40/525), Staphylococcus haemolyticus (S. haemolyticus) (2.48%, 13/525), and Staphylococcus xylosus (S. xylosus) (4.57%, 24/525). Mixed strain infections were detected in 121 (29.95%) infected presentations. The antimicrobial susceptibility testing indicated that 40.38% of the isolates exhibited multi-drug resistance, and 53.90% of the strains were methicillin-resistant strains by amplification of the methicillin resistance gene (mecA) gene. Through experimental reproduction of the disease, we determined that the CoNS strains were the leading pathogens causing bacterial meningitis in ducks. Although these CoNS strains does not directly cause the death of sick ducks, they still cause large economic losses due to the retarded growth and development of the sick ducks, lower feed returns, and lower grades of processed duck products. The results of this study will contribute to our understanding of the epidemiology and pathogenesis of CoNS and be helpful in the prevention and treatment of the infection.

Abstract Background Lignocellulose, the most abundant non-edible feedstock on Earth, holds substantial potential for eco-friendly chemicals, fuels, and pharmaceuticals production. Glucose, xylose, and arabinose are primary components in lignocellulose, and their efficient conversion into high-value products is vital for economic viability. While glucose and xylose have been explored for such purpose, arabinose has been relatively overlooked. Results This study demonstrates a microbial platform for producing 1,2,4-butanetriol (BTO) from arabinose, a versatile compound with diverse applications in military, polymer, rubber and pharmaceutical industries. The screening of the key pathway enzyme, keto acids decarboxylase, facilitated the production of 276.7 mg/L of BTO from arabinose in Escherichia coli. Through protein engineering of the rate-limiting enzyme KivD, which involved reducing the size of the binding pocket to accommodate a smaller substrate, its activity improved threefold, resulting in an increase in the BTO titer to 475.1 mg/L. Additionally, modular optimization was employed to adjust the expression levels of pathway genes, further enhancing BTO production to 705.1 mg/L. Conclusion The present study showcases a promising microbial platform for sustainable BTO production from arabinose. These works widen the spectrum of potential lignocellulosic products and lays the foundation for comprehensive utilization of lignocellulosic components.

Abstract The six species of lungfish possess both lungs and gills and are the closest extant relatives of tetrapods. Here, we report a single-cell transcriptome atlas of the West African lungfish (Protopterus annectens). This species manifests the most extreme form of terrestrialization, a life history strategy to survive dry periods that can last for years, characterized by dormancy and reversible adaptive changes of the gills and lungs. Our atlas highlights the cell type diversity of the West African lungfish, including gene expression consistent with phenotype changes of terrestrialization. Comparison with terrestrial tetrapods and ray-finned fishes reveals broad homology between the swim bladder and lung cell types as well as shared and idiosyncratic changes of the external gills of the West African lungfish and the internal gills of Atlantic salmon. The single-cell atlas presented here provides a valuable resource for further exploration of the respiratory system evolution in vertebrates and the diversity of lungfish terrestrialization.

Learning from multiclass imbalanced data streams with concept drift and variable class imbalance ratios under a limited label budget presents new challenges in the field of data mining. To address these challenges, this paper proposes an adaptive active learning method for multiclass imbalanced data streams with concept drift (AdaAL-MID). Firstly, a dynamic label budget strategy under concept drift scenarios is introduced, which allocates label budgets reasonably at different stages of the data stream to effectively handle concept drift. Secondly, an uncertainty-based label request strategy using a dual-margin dynamic threshold matrix is designed to enhance learning opportunities for minority class instances and those that are challenging to classify, and combined with a random strategy, it can estimate the current class imbalance distribution by accessing only a limited number of instance labels. Finally, an instance-adaptive sampling strategy is proposed, which comprehensively considers the imbalance ratio and classification difficulty of instances, and combined with a weighted ensemble strategy, improves the classification performance of the ensemble classifier in imbalanced data streams. Extensive experiments and analyses demonstrate that AdaAL-MID can handle various complex concept drifts and adapt to changes in class imbalance ratios, and it outperforms several state-of-the-art active learning algorithms.

The Yellow River Delta is considered one of the most water-stressed regions in China as the competition for water between various industrial sectors and agriculture is increasing. Since 2007, the regional governments have taken a leading role in agricultural water-saving planning by upgrading irrigation systems and constructing water-saving facilities. In this study, the effects of water-saving irrigation strategies on the groundwater table and quality were investigated in the Yellow River basin during the last two decades. The average phreatic water level of bore-wells was monitored as 13.47 m during 2011–2020 compared to the level of 12.09 m during 2011–2020. Besides, the depth of the deep confined aquifer dropped dramatically during 2001–2013 with a declining rate of 2.55 meters per annum (m/a) compared to the value of 0.385 m/a after 2014, suggesting the reduced exploitation of deep groundwater and increased availability of groundwater after the water-saving campaign. In addition, the physicochemical parameters of both phreatic water and deep confined aquifer indicated improved water quality. Consequently, understanding how the water-saving planning influences the groundwater availability is important, which would provide an insightful guidance for the water managers to protect the groundwater environment in the Yellow River Delta. HIGHLIGHTS Irrigation strategies affected the groundwater table in the Yellow River Delta.; The phreatic water could be more significantly affected by the water-saving irrigation planning than the deep confined aquifers.; Water-saving irrigation strategy improved the groundwater quality.;

The entity and relation extraction task, which is the technical source of constructing and updating large-scale knowledge graph, aims to identify the relationship between entities from unstructured text. Among the existing joint extraction methods of entity and relation, parallel decoding of tuples efficiently generates tuples by set prediction. However, this method ignores the interaction between entity and relationship, and entity subject and object, resulting in the generation of invalid tuples. To address this problem, this paper proposes a joint extraction model of entity and relation based on dual set prediction networks. To enhance the interaction between relationships and entities, a dual set prediction network is used to decode the tuples in parallel, and the entity information and relationship types in the tuples are generated sequentially. The first set prediction network models the set of tuples and decodes the subject-object information in the tuple. The second set prediction network models the set of tuples embedded with subject-object information and decodes the relationship type between subject and object. This paper designs an entity filter for entity subject-object, which predicts the subject-object correlation among entities in a sentence and filters out the tuples with lower subject-object correlation according to the result. Experiments on the NYT (New York Times) and WebNLG public datasets show that the proposed model performs better than the baseline model in terms of accuracy and F1 metrics when the encoder is BERT, which verifies the validity of the model.

ABSTRACT: Duck hepatitis A virus type 1 (DHAV-1) can cause severe liver damage in infected ducklings and is a fatal and contagious pathogen that endangers the Chinese duck industry. The objective of this study was to explore the correlation mechanism of liver metabolism-gut microbiota in DHAV-1 infection. Briefly, liquid chromatography-mass spectrometry and 16S rDNA sequencing combined with multivariate statistical analysis were used to evaluate the effects of DHAV-1 infection on liver metabolism, gut microbiota regulation, and other potential mechanisms in ducklings. In DHAV-1-infected ducklings at 72 h postinfection, changes were found in metabolites associated with key metabolic pathways such as lipid metabolism, sugar metabolism, and nucleotide metabolism, which participated in signaling networks and ultimately affecting the function of the liver. The abundance and composition of gut microbiota were also changed, and gut microbiota is significantly involved in lipid metabolism in the liver. The evident correlation between gut microbiota and liver metabolites indicates that DHAV-host gut microbiome interactions play important roles in the development of duck viral hepatitis (DVH).

Abstract Background H9N2 virus is mainly transmitted through the respiratory mucosal pathway, so mucosal immunity is considered to play a good role in controlling avian influenza infection. It is commonly accepted that no adequate mucosal immunity is achieved by inactivated vaccines, which was widely used to prevent and control avian influenza virus infection. Thus, an improved vaccine to induce both mucosal immunity and systemic immunity is urgently required to control H9N2 avian influenza outbreaks in poultry farms. Methods In this study, we constructed a novel Lactococcus lactis (L. lactis) strain expressing a recombinant fusion protein consisting of the HA1 proteins derived from an endemic H9N2 virus strain and chicken IgY Fc fragment. We evaluated the immunogenicity and protective efficacy of this recombinant L. lactis HA1-Fc strain. Results Our data demonstrated that chickens immunized with L. lactis HA1-Fc strain showed significantly increased levels of serum antibodies, mucosal secretory IgA, T cell-mediated immune responses, and lymphocyte proliferation. Furthermore, following challenge with H9N2 avian influenza virus, chickens immunized with L. lactis HA1-Fc strain showed reduced the weight loss, relieved clinical symptoms, and decreased the viral titers and the pathological damage in the lung. Moreover, oropharyngeal and cloacal shedding of the H9N2 influenza virus was detected in chicken immunized with L. lactis HA1-Fc after infection, the results showed the titer was low and reduced quickly to reach undetectable levels at 7 days after infection. Conclusion Our data showed that the recombinant L. lactis HA1-Fc strain could induce protective mucosal and systemic immunity, and this study provides a theoretical basis for improving immune responses to prevent and control H9N2 virus infection.

Abstract Background This study aimed to construct a more accurate model to forecast the incidence of hand, foot, and mouth disease (HFMD) in mainland China from January 2008 to December 2019 and to provide a reference for the surveillance and early warning of HFMD. Methods We collected data on the incidence of HFMD in mainland China between January 2008 and December 2019. The SARIMA, SARIMA-BPNN, and SARIMA-PSO-BPNN hybrid models were used to predict the incidence of HFMD. The prediction performance was compared using the mean absolute error(MAE), mean squared error(MSE), root mean square error (RMSE), mean absolute percentage error (MAPE), and correlation analysis. Results The incidence of HFMD in mainland China from January 2008 to December 2019 showed fluctuating downward trends with clear seasonality and periodicity. The optimal SARIMA model was SARIMA(1,0,1)(2,1,2)[12], with Akaike information criterion (AIC) and Bayesian Schwarz information criterion (BIC) values of this model were 638.72, 661.02, respectively. The optimal SARIMA-BPNN hybrid model was a 3-layer BPNN neural network with nodes of 1, 10, and 1 in the input, hidden, and output layers, and the R-squared, MAE, and RMSE values were 0.78, 3.30, and 4.15, respectively. For the optimal SARIMA-PSO-BPNN hybrid model, the number of particles is 10, the acceleration coefficients c1 and c2 are both 1, the inertia weight is 1, the probability of change is 0.95, and the values of R-squared, MAE, and RMSE are 0.86, 2.89, and 3.57, respectively. Conclusions Compared with the SARIMA and SARIMA-BPNN hybrid models, the SARIMA-PSO-BPNN model can effectively forecast the change in observed HFMD incidence, which can serve as a reference for the prevention and control of HFMD.

Abstract Broadcasting more educating and language-reviving contents are ways radio stations can help revitalize the use of the English language in the Hunan province of China. The challenges faced in communicating in English in Chinese radio stations are majorly caused by the lack of language professionals and linguists in the broadcast stations. The absence of these professionals is a major constraint to the development of the community. The broadcast media can help manage multilingualism through the introduction of new words which would give little or no room for lexicon dearth but would expand the language lexicon. Using the English language during broadcast reduces language dearth, and helps reach a much larger audience, even those not in China. Programmes anchored in English in places where the language is barely spoken enhances the vocabulary, comprehension and language vitality of the listeners. This study examined the impact of the English language used in radio broadcasting using a descriptive Big Data survey research design. The study’s population comprises of the inhabitants of the Hunan province in China, from which a sample of 50 broadcast staff and 150 regular inhabitants was drawn using a stratified random sampling technique. The instrument of data collection was a structured questionnaire with closed questions and a self-structured interview. The sample employed frequency distribution tables, percentages, and charts in the presentation and analysis of data. The results revealed that majority of the respondents in Hunan listened to radio broadcast indicating that the use of English language can have massive impact on the people. The study also found that majority of the respondents use their indigenous languages in their day-to-day activities as well as their schools with English being used majorly only in schools with only English-speaking students. The study recommends, amongst others, that the Broadcasting Corporation of China (BCC) review their policy on the allocated time of broadcast in English languages, and that more English language experts and linguists should be incorporated into the broadcast system.

With the rapid advancement of flexible electronics, conventional rigid batteries, which serve as energy devices for flexible electronics, are no longer capable of meeting developmental requirements. In this context, solar cells, as an eco-friendly, low-carbon, and sustainable energy technology, have gained significant recognition. This paper aims to design a flexible solar energy harvester (FSEH) based on laser direct writing. The FSEH is comprised of commercial PET/PI films, flexible Cu circuits, and amorphous silicon solar cells which provide excellent flexibility and sustainability. The FSEH was formed by soldering the solar collection array to the laser direct-written flexible Cu circuit by using solder paste. The solar energy harvesting array consists of six sets of series-connected amorphous silicon solar cell arrays, with each set comprised of six amorphous silicon solar cells connected in parallel. It has a maximum light collection area of about 2772 mm2. The designed FSEH could generate energy by harvesting light energy from lights or solar radiation. The FSEH outputs 0.437 mW at the light intensity of 3000 Lux and 1.813 mW at the light intensity of 10,000 Lux. The FSEH maintains an output efficiency of over 92% with a bending angle of less than 45°. Based on laser direct writing technology which enables efficient, convenient, and large-scale production of FSEH, the FSEH is expected to form a flexible self-powered system with flexible supercapacitors and wearable electronics, and FSEH offers great advantages for the sustainable development of wearable electronics and flexible sensors.

Portable, wearable electronic devices have spurred the rapid development of flexible and stretchable energy harvesting/storage devices with high energy density, superior mechanical stability, and long cycle life. Micro-supercapacitor (MSC) has attracted wide interest due to their advantages of high power density, rapid charge and discharge, and long cycle life. Fabrication of flexible supercapacitors based on laser induced graphene (LIG) has shown strong advantages and potential for flexible sensor power supply. The purpose of this paper is to propose and develop a laser induced flexible micro-supercapacitor (FMSC) for pressure sensors. FMSC is manufactured from a planar forked finger electrode made of graphene induced by CO2 laser radiation commercial Polyimide (PI) film and PVA polymer gel electrolyte. The FMSCs prepared by this method exhibit good electrochemical properties and excellent mechanical properties. The microscopic morphology of LIG was investigated using SEM, and the optimal laser-induced power was determined to be 12.5%. In this paper, a novel fork-finger electrode pattern was applied to improve the performance of FMSCs by optimizing the structure of planar interdigital electrodes, and the FMSCs prepared at 12.5% power showed excellent supercapacitance performance at a voltage window of 0.8 V with a specific capacitance of 2.21 mF/cm2. The FMSCs were made by assembling commercial PI films, PVA, and H3PO4 simple materials, which makes it possible to prepare FMSCs at low cost and high efficiency based on laser direct writing technology. FMSCs provide energy to the flexible sensors and continuously collect energy to charge FMSCs through an integrated flexible energy harvester, which makes FMSCs promising for flexible self-powered wireless sensing platforms.

Abstract Background Salmonella as an important food-borne zoonotic bacterial pathogen, infection in ducks is a recessive infection, however, it can also cause high mortality and threat to food safety. Preventing and controlling the infection and transmission of Salmonella in ducks critically require rapid and sensitive detection method. Full-length Salmonella-specific protein PagN was induced and expressed in E.coil BL21 and was purified as an antigen to establish an indirect enzyme-linked immunosorbent assays (iELSA) detection kit. Results The recombinant PagN protein has a molecular weight of 43 kDa containing a His-tag, was recognized by an anti-Salmonella positive serum by Western blot assay. The optimal concentration of PagN as a coating antigen in the iELISA was 1 μg/mL, and the optimal dilution of enzyme-labeled secondary antibody was 1:4000 (0.025 μg/mL). The cutoff OD450 value was established at 0.268. The iELISA kit showed high selectivity since no cross-reaction with E. coli, Staphylococcus aureus and Streptococcus was observed. iELISA method and Dot-blot test were performed on 100 clinical sera samples collected from duck farms, and the actual coincidence rate was 89% (89/100). 613 duck serum samples from 3 different farms were tested using established method and commercial ELISA kit. The concordance between the two methods was 94.1%. Conclusion Anti-PagN based iELISA can serve as a useful tool for diagnosis of Salmonella infection.

As part of city planning and urban studies, it is customary to use the phrase urban density to describe people and other human activity and development throughout a certain area of land. Urban regions in affluent nations are not only more densely populated (DPUA), but they also have a greater population density per unit of land area than rural areas do as well. In densely populated urban areas, public transportation is more plentiful, reducing travel times making them more efficient. Greater affluent residents in metropolitan areas can also benefit from modern high-rise structures, which offer more breathing room. An energy-efficient design and features provide great living standards and comfort while using little energy and releasing minimal carbon dioxide in this sort of housing. In the absence of or rare usage of conventional active and passive heating and cooling systems, Smart sensors and other IoT devices make up the Internet of Things (IoT). IoT presents cities with new potential for using data from sensors in their infrastructure to improve traffic flow and reduce pollution. The more crowded and congested a city is, the more dissatisfied its residents are. There are numerous negatives to urban life, including high living costs, congestion, pollution, crime, and traffic, yet the benefits exceed the risks. Clean up the air by reducing the amount of energy used and using alternate modes of transportation. Provide services like garbage disposal and housing through private–public partnerships. Urban planning should include planting trees and the maintenance of municipal green areas. There are many advantages to living in densely populated places, such as better healthcare, better amenities, and faster emergency response times. The innovative DPUA-IoT approach proposed in this study is only one example of these advantages. Rapid population expansion is harmful to achieving economic and social progress and sustainably managing the natural resource base. However, there is still a large disparity between the interests of the commercial and public sectors when it comes to reducing fertility.

Abstract Globally, since the outbreak of the Omicron variant in November 2021, the number of confirmed cases of COVID-19 has continued to increase, posing a tremendous challenge to the prevention and control of this infectious disease in many countries. The global daily confirmed cases of COVID-19 between November 1, 2021, and February 17, 2022, were used as a database for modeling, and the ARIMA, MLR, and Prophet models were developed and compared. The prediction performance was evaluated using mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE). The study showed that ARIMA (7, 1, 0) was the optimum model, and the MAE, MAPE, and RMSE values were lower than those of the MLR and Prophet models in terms of fitting performance and forecasting performance. The ARIMA model had superior prediction performance compared to the MLR and Prophet models. In real-world research, an appropriate prediction model should be selected based on the characteristics of the data and the sample size, which is essential for obtaining more accurate predictions of infectious disease incidence.

Abstract This study investigates the possibility of supporting tourists in a foreign land intelligently by using the Tourism Cloud Management System (TCMS) to enhance and better their tourism experience. Some technologies allow tourists to highlight popular tourist routes and circuits through the visualisation of data and sensor clustering approaches. With this, a tourist can access the shared data on a specific location to know the sites of famous local attractions, how other tourists feel about them, and how to participate in local festivities through a smart tourism model. This study surveyed the potential of smart tourism among tourists and how such technologies have developed over time while proposing a TCMS. Its goals were to make physical/paper tickets redundant via the introduction of a mobile app with eTickets that can be validated using camera and QR code technologies and to enhance the transport network using Bluetooth and GPS for real-time identification of tourists’ presence. The results show that a significant number of participants engage in tourist travels, hence the need for smart tourism and tourist management. It was concluded that smart tourism is very appealing to tourists and can improve the appeal of the destination if smart solutions are implemented. This study gives a first-hand review of the preference of tourists and the potential of smart tourism.

Abstract The quality assurance of higher education in China is an issue of vital international interest. To improve the international reputation of the nation’s universities, steps must be taken to ensure a sustained focus on the quality assurance within its ranks. This paper is primarily focused on the quality assurance models operational in Chinese universities, the Big data challenges and the legal framework backing them. The paper also discusses the implementation of the models, the extent to which they meet international standards, and how they adhere to prevailing laws. The degree of success in attaining and maintaining quality and evaluation of quality improvement opportunities are also discussed. Some of the solutions recommended in this study are the participation of more teachers and students in quality management, more emphasis of Higher Education Institution (HEI) quality assurance on self-regulation and a learning-oriented approach and conducting sessions to collect anonymous feedback from students to reward staff with best practices. Some of the Quality Assurance practices/models adopted in Chinese Universities are the Ministry of Education (MOE) reviews; the Academic Degree Committee oversight; Higher Education Evaluation Center (HEEC) overview, University self-evaluation according to HEEC Indicators, and the Webometric Ranking Model.

Conventional rigid optical-electronic systems need to be improved to adapt to the current food quality monitoring. This paper aims to propose and develop a flexible wearable optical wireless sensing system (FWOS) by laser ablation of polyethylene terephthalate/polyimide/copper (PET/PI/Cu) film. The FWOS can consist of different sensor arrays to suit different fruit sizes. FWOS can acquire the spectral data of the fruit and transmit it by Bluetooth (BT) to smartphones or personal computers (PCs). Simulations are used to determine the most suitable ablation power and speed and to measure the surface characteristics of the flexible Cu circuit using a stereomicroscope. FWOS has the characteristics of a simple process, simple operation, low cost, low power consumption, real-time monitoring, and small physical size. The soluble solids content (SSC) of apples, grapes, peaches, and cherries was evaluated. The results show the potential application of FWOS for quality monitoring of a wide range of fruits. It can significantly reduce fruit waste rates and ensure food quality and safety.

With the deepening understanding of the nutritional value of oysters by consumers, oysters as high-quality seafood are gradually entering the market. Raw edible oyster production lines mainly rely on manual sorting and packaging, which hinders the improvement of oyster packaging efficiency and quality, and it is easy to cause secondary oyster pollution and cross-contamination, which results in the waste of oysters. To enhance the production efficiency, technical level, and hygiene safety of the raw aquatic products production line, this study proposes and constructs a deep learning-based oyster packaging system. The system achieves intelligence and automation of the oyster packaging production line by integrating the deep learning algorithm, machine vision technology, and mechanical arm control technology. The oyster visual perception model is established by deep learning object detection techniques to realize fast and real-time detection of oysters. Using a simple online real-time tracking (SORT) algorithm, the grasping position of the oyster can be predicted, which enables dynamic grasping. Utilizing mechanical arm control technology, an automatic oyster packaging production line was designed and constructed to realize the automated grasping and packaging of raw edible oysters, which improves the efficiency and quality of oyster packaging. System tests showed that the absolute error in oyster pose estimation was less than 7 mm, which allowed the mechanical claw to consistently grasp and transport oysters. The static grasping and packing of a single oyster took about 7.8 s, and the success rate of grasping was 94.44%. The success rate of grasping under different transportation speeds was above 68%.

Studying the stress propagation and damage mechanism for the mechanical environment of the gun bore is an important way to popularize and apply the new propellant. Taking rosette 19-hole gun propellant as the research object, transverse drop hammer impact tests for the propellant under low temperature were carried out. Electron microscope tests for the propellant interface were conducted before and after the drop hammer tests. Then, a simulation mechanical model of the propellant was established by using the discrete element method with the rosette shape and 19 inner holes taken into consideration. And a simulation of the transverse drop hammer impact on the propellant was carried out. Research results show that the discrepancy between the simulation and test results of the maximum drop hammer force is 3.16%; the amplitude and pulse width of the drop hammer force-time curves and the fracture damage in the simulation and test studies are also in good agreement. The results reveal that the established simulation model is able to well describe the stress propagation and fracture process of the rosette 19-hole gun propellant under low temperature when affected by transverse drop hammer impact, providing an effective theoretical model basis for studying the damage mechanism of the new propellant.

IntroductionPseudorabies virus (PRV) is a herpesvirus that can infect domestic animals, such as pigs, cattle and sheep, and cause fever, itching (except pigs), and encephalomyelitis. In particular, the emergence of PRV variants in 2011 have resulted in serious economic losses to the Chinese pig industry. However, the signaling pathways mediated by PRV variants and their related mechanisms are not fully understood.MethodsHere, we performed RNA-seq to compare the gene expression profiling between PRV virulent SD2017-infected PK15 cells and Bartha-K/61-infected PK15 cells.ResultsThe results showed that 5,030 genes had significantly different expression levels, with 2,239 upregulated and 2,791 downregulated. GO enrichment analysis showed that SD2017 significantly up-regulated differentially expressed genes (DEGs) were mainly enriched in the binding of cell cycle, protein and chromatin, while down-regulated DEGs were mainly enriched in ribosomes. KEGG enrichment analysis revealed that the pathways most enriched for upregulated DEGs were pathways in cancer, cell cycle, microRNAs in cancer, mTOR signaling pathway and autophagy-animal. The most down-regulated pathways of DEGs enrichment were ribosome, oxidative phosphorylation, and thermogenesis. These KEGG pathways were involved in cell cycle, signal transduction, autophagy, and virus-host cell interactions.DiscussionOur study provides a general overview of host cell responses to PRV virulent infection and lays a foundation for further study of the infection mechanism of PRV variant strain.

The primary constraints hindering the widespread adoption of laser powder bed fusion (LPBF) are expensive raw materials, internal defects, difficulty in controlling the quality and stability, and lack of consistency in the powder feedstock. The spatters induced by the violent interaction between the laser and powder can be deposited on the unmelted powder bed, and if not effectively separated by sieving, they would pose a significant detriment to the characteristics and consistency of the recycled powders. In this work, a systematic investigation of the evolution mechanism of 316L powders after 10 and 30 successive recycling in the LPBF process was presented. Firstly, the variation mechanism of particle size distribution and morphology of 316L powder and the generation mechanism of heterogeneous particles were studied. Then, changes in microstructure and hardness trends were characterized. Finally, we emphasized the changes of chemical composition, phase composition, magnetic properties, and the formation mechanism of oxide spots. The results show that the circulation had significant effects on the physical properties, phase transformation, mechanical properties, and magnetic properties of the 316L powders, but had minor effects on the chemical composition, surface and cross-sectional microstructure. In addition, a large number of oddly shaped, large-diameter spatters were identified in the recycled powders, which could not be separated effectively by sieving, and the formation mechanism of the spatters were elaborated. Based on the comprehensive high-temperature oxidation thermodynamics and experimental results, it was concluded that the circular oxide spots on the spatter surface were a composite of multiple oxides of Mn and Si. Further, it was also shown that the ferrite content, XRD peak characteristics, and magnetic properties in the recycled powders were governed by the droplet solidification modes, which in turn is determined by the chemical composition and cooling rates.

Objective: Effects of phycobiliprotein and phycocyanin from artifically raised Nostoc sphaeroides Kützing on the growth of tumor in S180 tumor-bearing mice and its mechanism. Methods: The in vivo antitumor activity of phycobiliprotein and phycocyanin from Nostoc sphaeroides Kützing was evaluated by examining the tumor volume of S180 tumor-bearing mice, mouse organ indices and tumor tissue section observation, and its mechanism of action was initially studied. Results: The results of in vivo antitumor effect showed that the tumor inhibition rates of phycobiliprotein 12.5, 25 and 50 mg/kg dose groups were 11.19%, 20.14% and 37.65%, respectively, against mouse sarcoma S180. The tumor inhibition rates of phycocyanin 12.5, 25 and 50 mg/kg dose groups were 19.74%, 35.00% and 52.06%, respectively, against mouse sarcoma S180. Phycocyanin significantly promoted the expression of oncoprotein P53 and pro-apoptotic protein Bax, and inhibited the expression of apoptosis suppressor protein Bcl2. Conclusion: Phycocyanin high dose group significantly reduced the proliferation of S180 sarcoma cells. Phycocyanin low and medium doses and phycocyanin high doses also had some inhibitory effects. Phycobiliprotein and phycocyanin from artifically raised Nostoc sphaeroides Kützing have better in vivo antitumor activity.

Automaticidentification and prevention of leaf diseases and insect pests on fruit crops represent a key trend in the development of smart agriculture. In order to address the limitations of existing models with low identification rates of apple leaf diseases and insect pests, a novel identification model based on an improved ResNet-50 architecture was proposed, which incorporated the coordinate attention (CA) module and weight-adaptive multi-scale feature fusion (WAMFF) to enhance the ResNet-50’s image feature extraction capabilities. Transfer learning and online data enhancement are employed to boost the model’s generalization ability. The proposed model achieved a top-1 accuracy rate of 98.32% on the basis of AppleLeaf9 datasets, which is 4.58% higher than the value from the original model, and the improved model can effectively improve the localization of lesion features. Furthermore, compared with mainstream deep networks, such as AlexNet, VGG16, DenseNet, MNASNet, and GoogLeNet on the same dataset, the top-1 accuracy rate increased by 7.3%, 3.19%, 4.98%, 6.04% and 3.87%, respectively. The experimental results demonstrate that the improved model is effective in improving the identification accuracy of apple leaf diseases and insect pests and enhancing the model’s effective feature extraction capabilities.

Syphilis is a sexually transmitted disease caused by treponema pallidum infection. It is mainly transmitted through mucous membrane or injured skin. Its clinical manifestations are complex and diverse, and almost all organs of the whole body can be affected. The process of immune response to treponema pallidum is very complex, and innate immunity, cellular immunity and humoral immunity all participate in this process. The mechanisms of immune escape of treponema pallidum are not clear yet. The studies on the immune response and mechanisms of immune escape in treponema pallidum infection can lay a foundation for further clarification of the pathogenesis of syphilis and the development of vaccine. This paper reviews the research progress in syphilis immunity.

Urechis unicinctus can utilize the ability of large deformation to advance in sands by radial expansion, just using a small force. However, the large deformation of U. unicinctus skin and the discrete nature of the sands make it hard to analyze this process quantitatively. In this study, we aim to uncover the burrowing mechanism of U. unicinctus in granular sediments by combining discrete and finite elements. We observe that U. unicinctus will expand radially at the head, and then the head will shrink to move forward. The radial expansion will collapse the sands and let them flow, making it easy to advance. U. unicinctus mainly relies on the skin’s large deformation and sufficient pressure to achieve radial expansion. Thus, we first establish the large deformation constitutive model of the skin. The stress–strain relationship can be expressed by the Yeoh model. Meanwhile, the pressure required for radial expansion is indirectly measured by the balloon experiment. To study the effect of radial expansion on the burrowing behavior, we use the finite element method–discrete element method (FEM–DEM) coupling model to simulate the expansion process of burrowing. The simulated pressure for radial expansion is very close to the experimental data, verifying the reliability of the simulation. The results show that the expansion can drastically reduce the pressure of sand particles on the head front face by 97.1% ± 0.6%, significantly decreasing the difficulty of burrowing. This unique underwater burrow method of U. unicinctus can provide new ideas for engineering burrowing devices in soft soil, especially for granular sediments.

SpCas9 has a NGG PAM requirement that limits its DNA target range. Here the authors present a PAM-expanded SpdCas9 variant SpdNG-LWQT to target NRN PAMs.

Objective: To determine the therapeutic effect of pulmonary arterial hypertension (PAH) agents for portal pulmonary hypertension (POPH).Design: Systematic review and meta-analysis.Background: POPH is a serious complication of end-stage liver disease with a low survival rate. Liver transplantation (LT) is an effective treatment. Due to the presence of POPH, some patients cannot undergo LT. After PAH treatment, patients with POPH can obtain good hemodynamics and cardiac function for LT, but there are no standard guidelines.Methods: Two independent researchers searched PubMed, EMBASE, Cochrane Library, and Web of Science for studies published from inception to 27 September 2022, focusing on the changes in hemodynamics and cardiac function in all patients with POPH to understand the effect of PAH treatment on the entire population of POPH patients. Among these, we specifically analyzed the changes in hemodynamics and cardiac function in moderate and severe POPH patients. After collecting the relevant data, a meta-analysis was carried out using the R program meta-package.Results: A total of 2,775 literatures were retrieved, and 24 literatures were included. The results showed that in all POPH patients (n = 1,046), the following indicators were significantly improved with PAH agents: mPAP: (MD = −9.11 mmHg, p < 0.0001); PVR: (MD = −239.33 dyn·s·cm−5, p < 0.0001); CO: (MD = 1.71 L/min, p < 0.0001); cardiac index: (MD = 0.87 L/(min·m2), p < 0.0001); 6MWD: (MD = 43.41 m, p < 0.0001). In patients with moderate to severe POPH (n = 235), the following indicators improved significantly with PAH agents: mPAP (MD = −9.63 mmHg, p < 0.0001); PVR (MD = −259.78 dyn·s·cm−5, p < 0.0001); CO (MD = 1.76 L/min, p < 0.0001); Cardiac index: (MD = 1.01 L/(min·m2), p = 0.0027); 6MWD: (MD = 61.30 m, p < 0.0001).Conclusion: The application of PAH agents can improve cardiopulmonary hemodynamics and cardiac function in patients with POPH, especially in patients with moderate to severe POPH, and the above changes are more positive.Systematic Review Registration:https://inplasy.com, identifier INPLASY202250034.

Nanotechnology is revolutionizing the efficient production and sustainable development of modern agriculture. Understanding the pesticide activity of both nano- and conventional methods is useful for developing new pesticide formulations. In this study, three solid fluopyram formulations with varying particle sizes were developed, and the mechanisms underlying the difference in the antifungal activity among these formulations were investigated. Wet media milling combined with freeze drying was used to prepare fluopyram nanoparticles (FLU-NS) and a micron-sized solid formulation (FLU-MS), and a jet grinding mill was employed to fabricate fluopyram wettable powder (FLU-WP). The mean particle sizes of FLU-NS, FLU-MS, and FLU-WP were 366.8 nm, 2.99 μm, and 10.16 μm, respectively. Notably, FLU-NS displayed a toxicity index against Botrytis cinerea (gray mold) that was approximately double those of FLU-MS and FLU-WP. Similar trends were noticed in the antifungal tests on Alternaria solani. The uptake of FLU-NS by B. cinerea was approximately twice that of FLU-MS and FLU-WP, indicating that fluopyram nanoparticles are more easily taken up by the pathogen (B. cinerea), and display better bioactivity than the larger fluopyram particles. Therefore, the nanosizing of pesticides appears to be a viable strategy to enhance efficiency without increasing the amount of pesticide used.

Emotion analysis is currently a popular research direction in the field of natural language processing. However, existing research focuses primarily on tasks such as emotion classification, emotion extraction, and emotion cause analysis, while there are few investigations into the relationship between emotions and their impacts. To address these limitations, this paper introduces the emotion-driven behavior extraction (EDBE) task, which addresses these limitations by separately extracting emotions and behaviors to filter emotion-driven behaviors described in text. EDBE comprises three sub-tasks: emotion extraction, behavior extraction, and emotion–behavior pair filtering. To facilitate research in this domain, we have created a new dataset, which is accessible to the research community. To address the EDBE task, we propose a pipeline approach that incorporates the causal relationship between emotions and driven behaviors. Additionally, we adopt the prompt paradigm to improve the model’s representation of cause-and-effect relationships. In comparison to state-of-the-art methods, our approach demonstrates notable improvements, achieving a 1.32% improvement at the clause level and a 1.55% improvement at the span level on our newly curated dataset in terms of the F1 score, which is a commonly used metric to measure the performance of models. These results underscore the effectiveness and superiority of our approach in relation to existing methods.

ABSTRACT: Duck salmonellosis is a common acute septic infectious disease that spreads rapidly, with serious harm to the duck breeding industry and public health. To date, there are few reports about the epidemiological characteristics of drug resistance in Salmonella from ducks. In this study, an epidemiological investigation was conducted on drug resistance of 110 Salmonella strains isolated from multiple duck farms in Shandong Province and surrounding areas, China. The multidrug-resistant (MDR) rate for 110 Salmonella strains was up to 71.82% (79/110), and 12 types of drug resistance genes were detected in all isolates, including β-lactams, aminoglycosides, tetracycline, macrolides, and quinolones resistance genes. Using the multilocus sequence typing (MLST) based on 7 housekeeping genes, 13 various ST types were identified among all strains, and ST19 (32/110, 29.09%) was the primary type. As the dominant serotypes, S. Kottbus and S. Typhimurium were divided into multiple ST types. A total of 6 kinds of plasmid incompatibility groups were carried in the Salmonella strains, of which IncFIIs (29/110, 26.36%) was most prevalent, and the class I integrons were detected in 78.18% (86/110) of strains. Furthermore, we found that some drug resistance genes, plasmid incompatibility groups, and class I integrons coexist in the same strain. This phenomenon indicates that class I integrons and plasmids are important ways for the spread of drug resistance genes. Therefore, the spread of antibiotic resistance in Salmonella had been facilitated, especially erythromycin (108/110, 98.18%), streptomycin (93/110, 84.54%), and tetracycline (53/110, 48.18%). The above research results broadened ideas and provided directions for the transmission mechanism of Salmonella resistance.

Abstract. Hepatitis B virus infection is a major global public health concern. This study explored the epidemic characteristics and tendency of hepatitis B in 31 provinces of mainland China, constructed a SARIMA model for prediction, and provided corresponding preventive measures. Monthly hepatitis B case data from mainland China from 2013 to 2020 were obtained from the website of the National Health Commission of the People's Republic of China. Monthly data from 2013 to 2020 were used to build the SARIMA model and data from 2021 were used to test the model. Between 2013 and 2020, 9,177,313 hepatitis B cases were reported in mainland China. SARIMA(1,0,0)(0,1,1)12 was the optimal model and its residual was white noise. It was used to predict the number of hepatitis B cases from January to December 2021, and the predicted values for 2021 were within the 95% confidence interval. This study suggests that the SARIMA model simulated well based on epidemiological trends of hepatitis B in mainland China. The SARIMA model is a feasible tool for monitoring hepatitis B virus infections in mainland China.

Abstract Background H9N2 influenza virus, a subtype of influenza A virus, can spread across different species and induce the respiratory infectious disease in humans, leading to a severe public health risk and a huge economic loss to poultry production. Increasing studies have shown that polymerase acidic (PA) subunit of RNA polymerase in ribonucleoproteins complex of H9N2 virus involves in crossing the host species barriers, the replication and airborne transmission of H9N2 virus. Methods Here, to further investigate the role of PA subunit during the infection of H9N2 influenza virus, we employed mass spectrometry (MS) to search the potential binding proteins of PA subunit of H9N2 virus. Our MS results showed that programmed cell death protein 7 (PDCD7) is a binding target of PA subunit. Co-immunoprecipitation and pull-down assays further confirmed the interaction between PDCD7 and PA subunit. Overexpression of PA subunit in A549 lung cells greatly increased the levels of PDCD7 in the nuclear and induced cell death assayed by MTT assay. Results Flow cytometry analysis and Western blot results showed that PA subunit overexpression significantly increased the expression of pro-apoptotic protein, bax and caspase 3, and induced cell apoptosis. However, knockout of PDCD7 effectively attenuated the effects of PA overexpression in cell apoptosis. Conclusions In conclusion, the PA subunit of H9N2 virus bind with PDCD7 and regulated cell apoptosis, which provide new insights in the role of PA subunit during H9N2 influenza virus infection.

Sarin is a potent organophosphorus nerve agent that causes cognitive dysfunction, but its underlying molecular mechanisms are poorly understood. In this study, a rat model of repeated low-level sarin exposure was established using the subcutaneous injection of 0.4 × LD50 for 21 consecutive days. Sarin-exposed rats showed persistent learning and memory impairment and reduced hippocampal dendritic spine density. A whole-transcriptome analysis was applied to study the mechanism of sarin-induced cognitive impairment, and a total of 1035 differentially expressed mRNA (DEmRNA), including 44 DEmiRNA, 305 DElncRNA, and 412 DEcircRNA, were found in the hippocampus of sarin-treated rats. According to Gene Ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and Protein–Protein Interaction (PPI) analysis, these DERNAs were mainly involved in neuronal synaptic plasticity and were related to the pathogenesis of neurodegenerative diseases. The circRNA/lncRNA–miRNA–mRNA ceRNA network was constructed, in which Circ_Fmn1, miR-741-3p, miR-764-3p, miR-871-3p, KIF1A, PTPN11, SYN1, and MT-CO3 formed one circuit, and Circ_Cacna1c, miR-10b-5p, miR-18a-5p, CACNA1C, PRKCD, and RASGRP1 constituted another circuit. The balance between the two circuits was crucial for maintaining synaptic plasticity and may be the regulatory mechanism by which sarin causes cognitive impairment. Our study reveals the ceRNA regulation mechanism of sarin exposure for the first time and provides new insights into the molecular mechanisms of other organophosphorus toxicants.

Chronic pain is one of the most prevalent health problems worldwide. An alternative to suppress or alleviate chronic pain is the use of peptide drugs that block N-type Ca2+ channels (Cav2.2), such as ω-conotoxin MVIIA. Nevertheless, the narrow therapeutic window, severe neurological side effects and low stability associated with peptide MVIIA have restricted its widespread use. Fortunately, self-assembly endows the peptide with high stability and multiple functions, which can effectively control its release to prolong its duration of action. Inspired by this, MVIIA was modified with appropriate fatty acid chains to render it amphiphilic and easier to self-assemble. In this paper, an N-terminal myristoylated MVIIA (Myr-MVIIA, medium carbon chain length) was designed and prepared to undergo self-assembly. The present results indicated that Myr-MVIIA can self-assemble into micelles. Self-assembled micelles formed by Myr-MVIIA at higher concentrations than MVIIA can prolong the duration of the analgesic effect and significantly reduce or even eliminate the side effects of tremor and coordinated motor dysfunction in mice.

Attention is an important field to explore the importance of each convolutional kernel channel/weight. The existing attention methods mostly use the Squeeze-and-Excitation (SE) technology to extract the global nonlinear feature vectors as the weights of corresponding feature maps. However, the pooling operators and fully-connected layers used in SE technology extract global features at the cost of much valuable information loss and the parameter amount increase. Actually, the feature map containing full information is a ready-made and better attention for other feature maps in the same layer. Simultaneously the products of feature maps will bring powerful non-linearity. Seeing this, Kernel Product (KP) technology is proposed to simply get useful nonlinear attention. To verify the effectiveness of KP, the proposed KP module is employed on Selective Kernel Networks (SKNets) to take the place of the original SE technology. The variety of SKNets is called Kernel Product Networks (KPNets) in this paper. In addition, identity mapping is used to solve the non-convergence problem in very deep neural networks. The KPNets are evaluated on ImageNet-1k, CIFAR-10, and CIFAR-100. The experiment results show that KPNets outperform many state-of-the-art methods and get a similar but more efficient performance than its SKNets with counterpart.

Duck hepatitis A virus type 1 (DHAV-1) is a highly lethal virus that severely affects the duck industry worldwide. Long noncoding RNAs (lncRNAs) exert crucial roles in pathogen attacks. Here, we conducted deep transcriptome analysis to investigate the dynamic changes of host lncRNAs profiles in DHAV-1-infected duck embryo fibroblasts. We identified 16,589 lncRNAs in total and characterized their genomic features. Moreover, 772 and 616 differentially expressed lncRNAs (DELs) were screened at 12 and 24 h post-infection. Additionally, we predicted the DELs’ cis- and trans-target genes and constructed lncRNA-target genes regulatory networks. Functional annotation analyses indicated that the putative target genes of DELs participated in diverse vital biological processed, including immune responses, cellular metabolism, and autophagy. For example, we confirmed the dysregulation of pattern recognition receptors (TLR3, RIG-I, MDA5, LGP2, cGAS), signal transducers (STAT1), transcription factors (IRF7), immune response mediators (IL6, IL10, TRIM25, TRIM35, TRIM60, IFITM1, IFITM3, IFITM5), and autophagy-related genes (ULK1, ULK2, EIF4EBP2) using RT-qPCR. Finally, we confirmed that one DHAV-1 induced lncRNA-XR_003496198 is likely to inhibit DHAV-1 replication in DEFs. Our study comprehensively analyzed the lncRNA profiles upon DHAV-1 infection and screened the target genes involved in the innate immune response and autophagy signaling pathway, thereby revealing the essential roles of duck lncRNAs and broadening our understanding of host-virus interactions.

ABSTRACT: The plasmid-borne fosfomycin resistance gene fosA3 has been identified in Escherichia coli (E. coli) from various animals but has rarely been reported in ducks. In this study, we investigated the fosA3 prevalence and molecular characteristics of fosA3-harboring E. coli strains from ducks in Shandong province of China. In 416 E. coli isolates, 91 (21.88%) were identified as fosA3-bearing strains, and the fosfomycin-resistant phenotype of 88 of the 91 fosA3-harboring strains was successfully transferred to the recipient strains. Seven different genetic structures surrounding the fosA3 gene were detected and 2 new contexts were discovered among the fosA3-carrying E. coli. Twenty fosA3-harboring isolates and their trans-conjugants were randomly selected for pulsed-field gel electrophoresis (PFGE) typing and S1-nuclease PFGE, respectively. The PFGE patterns revealed that the 20 randomly selected fosA3-bearing isolates were not a result of clonal dissemination. S1-PFGE showed that 15 of the 20 randomly selected trans-conjugants carried a single plasmid, and these 15 plasmids that harbored fosA3 (55–190 kb) were distributed into the following replicon types: IncF (n = 11), IncI1 (n = 1), IncN (n = 1), untypable (n = 1), and W-FIC (n = 1). Additionally, as vectors for fosA3 in E. coli, F-:A1:B6, N/ST1, IncI1/ST2, W-FIC, and one untypable plasmid had never been reported before. These observations highlighted the importance of ducks as a reservoir for multidrug-resistant fosA3-carrying E. coli.

Since 2017, an infectious disease, named feather shedding syndrome (FSS), has consistently broken out in Cherry Valley ducks in East China. The sick ducks showed the new clinical symptoms of feather shedding and being plucked off with difficulty after slaughter. The high incidence rate of 20 to 70% predominantly happened in ducks of 4 to 5 wk of age, and nearly 40% mortality rate was observed in infected ducks. To explore the possible role of novel goose parvovirus–associated virus (NGPV) and duck circovirus (DuCV) in this disease, a total of 540 feather sac samples were collected from sick ducks with FSS. The infection rates of NGPV and DuCV in samples were 82.78 and 78.89%, respectively, and the coinfection rate of the 2 viruses was 70.00%. Notably, ducks of 4 to 5 wk of age usually presented obvious and severe FSS in the flocks with high codetection rate of NGPV and DuCV. Furthermore, 9 NGPV strains were isolated from feather sacs and 5 synchronous amino acid mutations were demonstrated in VP3 protein. These results indicated that coinfection of NGPV and DuCV might play an important role in duck FSS disease.