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IntroductionPorcine viral diarrhea is a common clinical disease, which results in high mortality and economic losses in the pig industry. Porcine epidemic diarrhea virus (PEDV), porcine rotavirus (PoRV), and porcine deltacoronavirus (PDCoV) are important diarrhea viruses in pig herds. The similarities of their clinical symptoms and pathological changes make it difficult to distinguish these three viruses clinically. Therefore, there is a need for a highly sensitive and specific method to simultaneously detect and differentiate these viruses.MethodsA multiplex real-time PCR assay using TaqMan probes was developed to simultaneously detect PEDV, PoRV, and PDCoV. To assess the efficacy of the established assay, 30 clinical samples with diarrhea symptoms were used to compare the results obtained from the multiplex real-time PCR assay with those obtained from commercial singleplex real-time PCR kit. Importantly, a total of 4,800 diarrhea samples were tested and analyzed to validate the utility of the assay.ResultsThis multiplex real-time PCR assay showed high sensitivity, specificity, and excellent repeatability with a detection limit of 1 × 102 copies/μL. Comparing the results of the commercial singleplex real-time PCR kit and the multiplex real-time PCR method for detecting PEDV, PoRV, and PDCoV, there was complete agreement between the two approaches. Clinical data revealed single infection rates of 6.56% for PEDV, 21.69% for PoRV, and 6.65% for PDCoV. The co-infection rates were 11.83% for PEDV + PoRV, 0.29% for PEDV + PDCoV, 5.71% for PoRV + PDCoV, and 1.29% for PEDV + PDCoV + PoRV, respectively.DiscussionThe multiplex real-time PCR method established in this study is a valuable diagnostic tool for simultaneously differentiating PEDV, PoRV, and PDCoV. This method is expected to significantly contribute to prevent and control the spread of infectious diseases, as well as aid in conducting epidemiological investigations.

Abstract Introduction Locoregional recurrent breast cancers have a poor prognosis. Little is known about the prognostic impact of immune microenvironment, and tertiary lymphoid structures (TLSs) in particular have not been reported. Thus, we aimed to characterize the immune microenvironment in locoregional recurrent breast tumors and to investigate its relationship with prognosis. Methods We retrospectively included 112 patients with locoregional recurrent breast cancer, and hematoxylin–eosin staining and immunohistochemical staining (CD3, CD4, CD8, CD19, CD38, and CD68) were performed on locoregional recurrent tumor samples. The association of immune cells and TLSs with progression‐free survival (PFS) were analyzed by survival analysis. Results We found more immune cells in the peritumor than stroma. After grouping according to estrogen receptor (ER) status, a low level of peritumoral CD3+ cells in ER+ subgroup (p = 0.015) and a low level of stromal CD68+ cells in ER− subgroup (p = 0.047) were both associated with longer PFS. TLSs were present in 68% of recurrent tumors, and CD68+ cells within TLSs were significantly associated with PFS as an independent prognostic factor (p = 0.035). TLSs and immune cells (CD3, CD38, and CD68) within TLSs were associated with longer PFS in ER− recurrent tumors (p = 0.044, p = 0.012, p = 0.050, p

Abstract As a multi hop self-organizing network, wireless sensor network has the ability to cooperatively sense, collect and process the information of the sensed objects. The applications of WCN in 5G-based Internet of Vehicles (5G-IoV), using information fusion and intelligent information processing technologies, can obtain more reliable and accurate detection parameters, which has been widely concerned. However, the massive connectivity and information exchange in 5G-IoV pose great challenges to the bandwidth efficiency. In order to overcome these issues in 5G-IoV networks, a performance enhanced scheme based on non-orthogonal multiple access (NOMA) is proposed. In the proposed scheme, different vehicle locations are respectively discussed, i.e., whether in the overlap region of cluster head vehicles (CHVs). In particular, different to conventional works, each receiving node only decodes the desired signal to avoid performance loss provided from the poor channel quality limitation. On the other hand, all CHVs decode-and-forward new superposition coded signals with new power allocation factors, while that the maximum ratio combining is utilized at receivers to further improve the ergodic sum-rate (SR) and probability of conflict. The closed-form expressions of ergodic SR for our proposed scheme are analyzed under the independent Rayleigh fading channels. Numerical results corroborating our theoretical analysis show that the superposition coded signal transmission scheme applied to the proposed NOMA-IoV improves the ergodic SR performance significantly compared with the existing works, especially for the high signal-to-noise region.

Abstract Callerya speciosa (Champ. ex Benth.) Schot is a traditional Chinese medicine characterized by tuberous roots as the main organ of isoflavonoid accumulation. Root thickening and isoflavonoid accumulation are two major factors for yield and quality of C. speciosa. However, the underlying mechanisms of root thickening and isoflavonoid biosynthesis have not yet been elucidated. Here, integrated morphological, hormonal and transcriptomic analyses of C. speciosa tuberous roots at four different ages (6, 12, 18, 30 months after germination) were performed. The growth cycle of C. speciosa could be divided into three stages: initiation, rapid-thickening and stable-thickening stage, which cued by the activity of vascular cambia. Endogenous changes in phytohormones were associated with developmental changes during root thickening. Jasmonic acid might be linked to the initial development of tuberous roots. Abscisic acid seemed to be essential for tuber maturation, whereas IAA, cis-zeatin and gibberellin 3 were considered essential for rapid thickening of tuberous roots. A total of 4337 differentially expressed genes (DEGs) were identified during root thickening, including 15 DEGs participated in isoflavonoid biosynthesis, and 153 DEGs involved in starch/sucrose metabolism, hormonal signaling, transcriptional regulation and cell wall metabolism. A hypothetical model of genetic regulation associated with root thickening and isoflavonoid biosynthesis in C. speciosa is proposed, which will help in understanding the underlying mechanisms of tuberous root formation and isoflavonoid biosynthesis.

Pseudorabies (PR) is a disease that is seriously endangering the pig industry in China. To understand the current prevalence of pseudorabies virus (PRV) in Shandong Province, China, 19,292 serum samples were collected from 16 locations in Shandong from 2018 to 2020. The gE antibody was detected by enzyme-linked immunosorbent assay. Ninety-seven suspected cases of PRV infection were collected from sick pigs vaccinated with Bartha-K61 to isolate PRV. The results showed that the average positive rate of the PRV gE antibody decreased from 38.20% in 2018 to 18.12% in 2020, but there was a high positive rate in sows. The isolation rate of PRV was 13.40% (13/97), and four strains were purified through plaque assay (named PRV-SD1, PRV-SD2, PRV-SD3, and PRV-SD4). The homology and genetic evolution of four PRV strains based on gE, gC, gI, and TK genes were analyzed and showed that these four strains shared more than 99.0% nucleotide homology with the variant PRV XJ5 strain, and they clustered in the same sub-branch with the domestic variant PRV strains, including JS-2012 and XJ5. Furthermore, the pathogenicity of the isolated variant strain was assessed by intranasal infection of 16-week-old pigs with 1 mL PRV-SD1 strain. The results of the animal experiment demonstrated that the PRV-SD1–infected pigs exhibited obvious clinical symptoms as early as 2 days post inoculation (dpi), and all infected pigs died within 1 week. The severe hyperemia of meninges and swelling of lungs and tonsils were observed. Histopathology analysis showed the obvious lymphocytes necrosis of tonsils, interstitial pneumonia, and viral encephalitis. Many positive staining cells were observed in tonsils and brains through immunohistochemistry staining assay. Viral shedding in oropharyngeal and rectal swabs were detected at 2 dpi, reached a peak at 3 dpi, and then gradually decreased. The detection of viral loads in the tissues showed that tonsils had the highest virus titer, further proving it may be the target organ of variant PRV infection. In conclusion, variant PRV strains were still highly prevalent in Shandong Province, and they had a strong pathogenicity in pigs.

The R2R3-MYB family is one of the largest plant transcription factor (TF) families playing vital roles in defense, plant growth, and secondary metabolism biosynthesis. Although this gene family has been studied in many species, isoflavonoid biosynthesis-related R2R3-MYB TFs in Callerya speciosa (Champ. ex Benth.) Schot, a traditional Chinese medicinal herb, are poorly understood. Here, a total of 101 R2R3-MYB TFs were identified from C. speciosa transcriptome dataset. 25 clades divided into five functional groups were clustered based on the sequence similarity and phylogenetic tree. Conserved motifs and domain distribution, expression patterns, and coexpression networks were also employed to identify the potential R2R3-MYB TFs in the regulation of isoflavonoid biosynthesis. In silico evaluation showed that the deduced R2R3-CsMYB proteins contain highly conserved R2R3 repeat domain at the N-terminal region, that is the signature motif of R2R3-type MYB TFs. Eight potential TFs (CsMYB17, CsMYB36, CsMYB41, CsMYB44, CsMYB45, CsMYB46, CsMYB72, and CsMYB81) had high degrees of coexpression with four key isoflavonoid biosynthetic genes (CsIFS, CsCHS7, CsHID-1, and CsCHI3), in which CsMYB36 as a potential regulator possessed the highest degree. HPLC analysis showed that formononetin and maackiain contents were significantly increased during the development of tuberous roots, which might be controlled by both related R2R3-CsMYBs and structural genes involved in the isoflavonoid biosynthesis pathway. The transcriptome data were further validated by reverse transcription real-time PCR (RT-qPCR) analysis, and similar expression profiles between TFs and key structural genes were identified. This study was the first step toward the understanding of the R2R3-MYB TFs regulating isoflavonoid biosynthesis in C. speciosa. The results will provide information for further functional analysis and quality improvement through genetic manipulation of these potential R2R3-CsMYB genes in C. speciosa.

Highly pathogenic (HP) H7N9 avian influenza virus (AIV) emerged in China in 2016. HP H7N9 AIV caused at least 33 human infections and has been circulating in poultry farms continuously since wave 5. The genetic divergence, geographic patterns, and hemagglutinin adaptive and parallel molecular evolution of HP H7N9 AIV in China since 2017 are still unclear. Here, 10 new strains of HP H7N9 AIVs from October 2019 to April 2021 were sequenced. We found that HP H7N9 was primarily circulating in Northern China, particularly in the provinces surrounding the Bohai Sea (Liaoning, Hebei, and Shandong) since wave 6. Of note, HP H7N9 AIV phylogenies exhibit a geographical structure compatible with high levels of local transmission after unidirectional rapid geographical expansion towards the north of China in 2017. In addition, we showed that two major subclades were continually expanding with the viral population size undergoing a sharp increase after 2018 with an obvious seasonal tendency. Notably, the hemagglutinin gene showed signs of parallel evolution and positive selection. Our research sheds light on the current epidemiology, evolution, and diversity of HP H7N9 AIV that can help prevent and control the spreading of HP H7N9 AIV.

Abstract Quickly identifying and classifying lightning waveforms is the foundation of lightning forecasting and early warning. In this paper, based on the electric field observation of the Beijing lightning location website of the Institute of Atmospheric Physics, Chinese Academy of Sciences, a recognition and classification method of pulse signal waveform based on Convolutional Neural Network(CNN) algorithm is designed and implemented. The CNN network model and its parameters were optimized from three aspects: dataset, model parameters, and network structure, achieving a recognition rate of over 90%. The effects of various optimization terms and their different optimization orders on the training time of the model were studied. The results indicate that the CNN algorithm is suitable for the classification and recognition of lightning electric field (LEF) waveforms. Optimization can significantly improve recognition rate. The optimization method of fitting idealized waveforms can reduce noise in the dataset and significantly improve recognition rate, indicating that noise has a significant impact on waveform recognition. Therefore, it is necessary to perform noise preprocessing before recognition. The optimization has a huge impact on training efficiency, increasing training time by about 51% after optimization, but the influence of optimization order on it can be ignored.

Change detection (CD) in satellite time series is one of the hot research topics in the field of remote sensing (RS). Recently, graph convolutional network (GCN)-based CD methods have garnered significant attention from numerous researchers, as GCN can perform convolutional operations on irregular graphs using superpixels. However, these methods still face two challenges, i.e., inaccurate superpixel segmentation may lead to detection errors, and temporal information is ignored in the GCN-based CD methods. To this end, we propose a temporal information enhanced GCN with superpixel-pixel gated knowledge dynamic selection for CD (TSCD) in satellite time series. This method fully leverages the strengths of both GCN and convolutional neural network (CNN) frameworks to accurately identify changes in satellite time series. It is composed of three parts: First, a superpixel-level temporal information enhanced GCN (STIG) subnetwork, which is designed to capture the large-scale discriminative features of land surfaces, in which temporal information enhanced GCN (TIGCN) not only extracts spatial-spectral features of images, but also captures temporal correlations within satellite time series, thereby reducing the pseudochanges caused by temporal dynamics; second, a pixel-level 3D-CNN (P3DC) subnetwork, which is proposed to focus on subtle features by extracting temporal-spatial-spectral information to correct detection errors caused by superpixel segmentation; third, a gated knowledge dynamic selection module, which is designed to dynamically select the optimal features in the spectral dimension from the superpixel-level, pixel-level, and their combined features, thereby reducing the impact of redundant information on the detection performance. TSCD not only extracts large-scale and subtle features simultaneously, but also captures the temporal correlations among images. Comparative experimental results with eight state-of-the-art CD methods on nine publicly available satellite time series scenes demonstrate the effectiveness of the TSCD method.

Error analysis and estimation of thunder source location results is a prerequisite for obtaining accurate location results of thunder sources, which is of great significance for a deeper understanding of the physical process of lightning channel discharges. Most of the thunder source location algorithms are based on the simplified model of the straight-line propagation of acoustic waves to determine the location of the thunder source; however, the acoustic wave is affected by the inhomogeneity of the atmosphere medium in the propagation process and its acoustic ray will be bent. Temperature and humidity are the main factors affecting the vertical distribution of the velocity of sound in the atmosphere, therefore, it is necessary to study the changes in location errors under the models of uniform vertical distribution of temperature only and uniform vertical distribution of humidity only. This paper focuses on the theory of acoustic ray-tracing in neglecting the presence of the wind and the acoustic attenuation and the theoretical derivation of the location error of thunder source inversion for the three models is carried out by using MATLAB R2019b programming. Then, simulation analysis and comparative study on the variation law of thunder source location error with the height of the source, ground temperature, ground humidity, and array position under the three models are carried out. The results of the study show that the maximum location error can be obtained from the straight-line propagation model, the location error obtained from the model of uniform vertical distribution of temperature only is the second, and the location error obtained from the model of uniform vertical distribution of humidity only is the least and can be negligible compared to the first two models. In the trend of error variation, the variation of location error with temperature and humidity is relatively flat in the first two models; however, the variation of location error with the height of the thunder source is more drastic, which can be more than 80%. The location error obtained from the array inversion closer to the thunder source increases linearly with the height of the thunder source, the location error obtained from the more distant array inversion shows a fast-decreasing trend at the height of the thunder source from 500 to 3500 m, and a flat trend above 3500 m. The location error varies relatively smoothly with the height of the thunder source, the ground temperature, and the ground humidity in the model of uniform vertical distribution of humidity only. In addition, the position of the array also has an important effect on lightning location. The further the horizontal distance from the source, the greater the location error will be obtained in the first two models, and when the thunder source is at a low height and detected at a long distance, the location error will be very large, so relevant data should be modified in actual observation.

Exposure scenario and receptor behavior significantly affect PM2.5 exposure quantity of persons and resident groups, which in turn influenced indoor or outdoor air quality & health management. An Internet of Things (IoT) system, EnvironMax+, was developed to accurately and conveniently assess residential dynamic PM2.5 exposure state. A university community “QC”, as the application area, was divided into four exposure scenarios and five groups of residents. Low-cost mobile sensors and indoor/outdoor pollution migration (IOP) models jointly estimated multi-scenario real-time PM2.5 concentrations. Questionnaire was used to investigate residents' indoor activity characteristics. Mobile application (app) “Air health management (AHM)” could automatic collect residents' activity trajectory. At last, multi-scenario daily exposure concentrations of each residents-group were obtained. The results showed that residential exposure scenario was the most important one, where residents spend about 60 % of their daily time. Closing window was the most significant behavior affecting indoor contamination. The annual average PM2.5 concentration in the studied scenarios: residential scenario (RS) outdoor workers > indoor workers > students > the elderly, related to their daily activity time proportion in different exposure scenario.

IntroductionWith the promulgation of air pollution control policies, there are still many cities where the PM2.5 concentration exceeds 35 μg/m3, and O3 pollution is increasingly apparent.MethodsThe spatio-temporal evolution and differentiation characteristics of PM2.5 and O3 pollution were explored, and then compound pollution hotspot urban agglomerations were screened out. A weather normalization technique was used to identify the driving amount, the influence of meteorological factors, and the anthropogenic emissions quantitatively, on pollution in hotspot urban agglomeration. Furthermore, the health and economic losses due to PM2.5 and O3 in hot cities in 2015–2020 were quantified. Finally, a natural break-point classification method was used to establish the health loss rating systems for PM2.5 and O3.Results and DiscussionThe results showed the following: (1) From 2015 to 2020, 78%, 72%, 69%, 58%, 50%, and 41% of the annual mean PM2.5 concentration had exceeded 35 μg/m3, respectively, and 17%, 18%, 31%, 33%, 30%, and 17% of the annual mean O3 concentration exceeded 160 μg/m3, respectively, in 337 cities in China. (2) From 2015 to 2020, the health losses caused by PM2.5 and O3 were ranked as follows: Beijing–Tianjin–Hebei (BTH; 1968, 482 people) > Shandong Peninsula (SDP; 1,396, 480 people) > Central Plains (CP; 1,302, 314 people) > Yangtze River Delta (YRD; 987, 306 people) > Triangle of Central China (TC; 932, 275 people) > Guanzhong Plain (GZP; 869, 189 people). (3) The average economic losses associated with public health of the PM2.5 and O3 were ranked as follows: BTH (2.321 billion, 3.218 billion RMB, 1 RMB = 0.0.1474 USD on 20 January 2023) > SDP (1.607, 2.962 billion RMB) > YRD (1.075, 1.902 billion RMB) > TC (1.016 billion, 1.495 billion RMB) > CP (1.095, 1.453 billion RMB) > GZP (0.69, 0.828 billion RMB). Therefore, combining hot pollution factors, the regional characteristics of the priority control areas, and the national 14th 5-Year Plan, targeted control countermeasures were proposed.

[Objectives] This study aimed to investigate the pathogenicity, growth characteristics and drug resistance of Streptococcus suis type 2. [Methods] Bacterial isolation and identification, biochemical experiments, determination of growth curve and correlation curve between 0D(ai values and viable counts, drug susceptibility tests, pathogenicity analysis, and histopalhological observations were carried out. [Results] The Streptococcus strain isolated from infected pigs was identified as Streptococcus suis type 2, which was named TA01 strain. TA01 strain reached die growth peak at 6 -8 h post-incubation, and viable counts gradually declined after 8 li of inculwtion. The correlation equation between ODm values and viable counts is y =24.659x - 1.076 1, R2 =0.996 7. TA01 strain was sensitive to penicillin, erythromycin, florfenicol and oxacillin, and resistant to ciprofloxacin, polymyxin B and clindamycin. According to the results of pathogenicity analysis, all the mice in 3.6x109 c-fu/mouse group died within 48, and these dead mice exhibited acute pyaemia septiea. Based on the Heed-Muench formula, it was calculated that LD50 of TA01 strain was 1.137x108 cfu/mouse. Pathological examination showed obvious blue-stained bacteria clusters, accompanied by neutrophil infiltration. [Conclusions] TA01 strain was a virulent strain of Streptoa>ccus suis type 2. Compared with Streptococcus strains which were isolated and reported in China, TA01 strain exhibited strong virulence and rapid proliferation. [ABSTRACT FROM AUTHOR]

Human respiratory syncytial virus (HRSV) poses a significant disease burden on global health. To date, two vaccines that primarily induce humoral immunity to prevent HRSV infection have been approved, whereas vaccines that primarily induce T-cell immunity have not yet been well-represented. To address this gap, 25 predicted T-cell epitope peptides derived from the HRSV fusion protein with high human leukocyte antigen (HLA) binding potential were synthesized, and their ability to be recognized by PBMC from previously infected HRSV cases was assessed using an ELISpot assay. Finally, nine T-cell epitope peptides were selected, each of which was recognized by at least 20% of different donors’ PBMC as potential vaccine candidates to prevent HRSV infection. The protective efficacy of F-9PV, a combination of nine peptides along with CpG-ODN and aluminum phosphate (Al) adjuvants, was validated in both HLA-humanized mice (DR1-TCR transgenic mice, Tg mice) and wild-type (WT) mice. The results show that F-9PV significantly enhanced protection against viral challenge as evidenced by reductions in viral load and pathological lesions in mice lungs. In addition, F-9PV elicits robust Th1-biased response, thereby mitigating the potential safety risk of Th2-induced respiratory disease during HRSV infection. Compared to WT mice, the F-9PV mice exhibited superior protection and immunogenicity in Tg mice, underscoring the specificity for human HLA. Overall, our results demonstrate that T-cell epitope peptides provide protection against HRSV infection in animal models even in the absence of neutralizing antibodies, indicating the feasibility of developing an HRSV T-cell epitope peptide-based vaccine.

Abstract The SARS-CoV-2 pandemic has raised concerns in the identification of the hosts of the virus since the early stages of the outbreak. To address this problem, we proposed a deep learning method, DeepHoF, based on extracting viral genomic features automatically, to predict the host likelihood scores on five host types, including plant, germ, invertebrate, non-human vertebrate and human, for novel viruses. DeepHoF made up for the lack of an accurate tool, reaching a satisfactory AUC of 0.975 in the five-classification, and could make a reliable prediction for the novel viruses without close neighbors in phylogeny. Additionally, to fill the gap in the efficient inference of host species for SARS-CoV-2 using existing tools, we conducted a deep analysis on the host likelihood profile calculated by DeepHoF. Using the isolates sequenced in the earliest stage of the COVID-19 pandemic, we inferred that minks, bats, dogs and cats were potential hosts of SARS-CoV-2, while minks might be one of the most noteworthy hosts. Several genes of SARS-CoV-2 demonstrated their significance in determining the host range. Furthermore, a large-scale genome analysis, based on DeepHoF’s computation for the later pandemic in 2020, disclosed the uniformity of host range among SARS-CoV-2 samples and the strong association of SARS-CoV-2 between humans and minks.

Viruses are increasingly viewed as vital components of the human gut microbiota, while their roles in health and diseases remain incompletely understood. Here, we first sequenced and analyzed the 37 metagenomic and 18 host metabolomic samples related to irritable bowel syndrome (IBS) and found that some shifted viruses between IBS and controls covaried with shifted bacteria and metabolites. Especially, phages that infect beneficial lactic acid bacteria depleted in IBS covaried with their hosts. We also retrieved public whole-genome metagenomic datasets of another four diseases (type 2 diabetes, Crohn’s disease, colorectal cancer, and liver cirrhosis), totaling 438 samples including IBS, and performed uniform analysis of the gut viruses in diseases. By constructing disease-specific co-occurrence networks, we found viruses actively interacting with bacteria, negatively correlated with possible dysbiosis-related and inflammation-mediating bacteria, increasing the connectivity between bacteria modules, and contributing to the robustness of the networks. Functional enrichment analysis showed that phages interact with bacteria through predation or expressing genes involved in the transporter and secretion system, metabolic enzymes, etc. We further built a viral database to facilitate systematic functional classification and explored the functions of viral genes on interacting with bacteria. Our analyses provided a systematic view of the gut virome in the disease-related microbial community and suggested possible positive roles of viruses concerning gut health.

The popularity of social media, such as WeChat and Weibo in China, has provided an opportunity to develop social commerce. Although shopping through social commerce platforms is widely favored by consumers, the factors affecting consumers’ decision-making behavior in the social commerce environment remain unclear. Therefore, from the perspective of the stimulus–organism–response (SOR) theory, we construct a consumer repurchase decision model in the social commerce environment and analyze the influencing mechanism of social commerce features (interactivity, recommendations, and feedback) on perceived value (utilitarian value and hedonic value) and consumers’ repurchase intention. The empirical results found that social commerce features are positively related to the generation of perceived value, which in turn drives consumers to form repurchase intentions. We also found some mediating effects of perceived value. The study’s conclusions clarify the intrinsic influence mechanism of social commerce features on consumers’ perceived value and repurchase intentions. In addition, it can provide some theoretical guidance for future research and business.

From 2013 to 2017, progress has been made by implementing the Air Pollution Prevention and Control Action Plan. Under the background of the 3 Year Action Plan to Fight Air Pollution (2018–2020), the pollution status of PM2.5, a typical air pollutant, has been the focus of continuous attention. The spatiotemporal specificity of PM2.5 pollution in the Chinese urban atmospheric environment from 2018 to 2020 can be summarized to help conclude and evaluate the phased results of the battle against air pollution, and further, contemplate the governance measures during the period of the 14th Five-Year Plan (2021–2025). Based on PM2.5 data from 2018 to 2020 and taking 366 cities across China as research objects, this study found that PM2.5 pollution has improved year by year from 2018 to 2020, and that the heavily polluted areas were southwest Xinjiang and North China. The number of cities with a PM2.5 concentration in the range of 25–35 μg/m3 increased from 34 in 2018 to 86 in 2019 and 99 in 2020. Moreover, the spatial variation of the PM2.5 gravity center was not significant. Concretely, PM2.5 pollution in 2018 was more serious in the first and fourth quarters, and the shift of the pollution's gravity center from the first quarter to the fourth quarter was small. Global autocorrelation indicated that the space was positively correlated and had strong spatial aggregation. Local Moran's I and Local Geti's G were applied to identify hotspots with a high degree of aggregation. Integrating national population density, hotspots were classified into four areas: the Beijing–Tianjin–Hebei region, the Fenwei Plain, the Yangtze River Delta, and the surrounding areas were selected as the key hotspots for further geographic weighted regression analysis in 2018. The influence degree of each factor on the average annual PM2.5 concentration declined in the following order: (1) the proportion of secondary industry in the GDP, (2) the ownership of civilian vehicles, (3) the annual grain planting area, (4) the annual average population, (5) the urban construction land area, (6) the green space area, and (7) the per capita GDP. Finally, combined with the spatiotemporal distribution of PM2.5, specific suggestions were provided for the classified key hotspots (Areas A, B, and C), to provide preliminary ideas and countermeasures for PM2.5 control in deep-water areas in the 14th Five-Year Plan.

Classical swine fever virus (CSFV) causes an economically important and highly contagious disease of pigs worldwide. C-strain vaccination is one of the most effective ways to contain this disease. Since 2014, sporadic CSF outbreaks have been occurring in some C-strain vaccinated provinces of China. To decipher the disease etiology, 25 CSFV E2 genes from 169 clinical samples were cloned and sequenced. Phylogenetic analyses revealed that all 25 isolates belonged to subgenotype 2.1. Twenty-three of the 25 isolates were clustered in a newly defined subgenotype, 2.1d, and shared some consistent molecular characteristics. To determine whether the complete E2 gene was under positive selection pressure, we used a site-by-site analysis to identify specific codons that underwent evolutionary selection, and seven positively selected codons were found. Three positively selected sites (amino acids 17, 34, and 72) were identified in antigenicity-relevant domains B/C of the amino-terminal half of the E2 protein. In addition, another positively selected site (amino acid 200) exhibited a polarity change from hydrophilic to hydrophobic, which may change the antigenicity and virulence of CSFV. The results indicate that the circulating CSFV strains in Shandong province were mostly clustered in subgenotype 2.1d. Moreover, the identification of these positively selected sites could help to reveal molecular determinants of virulence or pathogenesis, and to clarify the driving force of CSFV evolution in East China. [ABSTRACT FROM AUTHOR]

The main seasonal characteristics in the tropics include both spatial patterns and temporal parameters of onset, cessation, duration, and the number of wet and dry seasons. Previous studies showed that wet seasons shortened and dry seasons extended with global warming, but the changes in spatial distribution and the number of wet and dry seasons are still unclear. Here, we analyze the climatic characteristics of once wet and dry season a year (annual regime) and twice wet and dry seasons a year (biannual regime), and find that regimes of wet and dry seasons have changed from 1935 to 2014. Across the equator and the Tropic of Cancer and Capricorn, some regions where there used to be an annual regime have become a biannual regime; instead, other regions have shifted from a biannual regime into an annual regime. With seasonal regimes shifting, areas of the biannual regime have expanded at a rate of 31 000 km ^2 /decade. Meanwhile, in annual regime regions, wet seasons have been shortened in 60.3% of regions, with an average of 7 d; the onset dates of wet seasons have been delayed in 64.8%, with an average of 6 d. Besides, wet seasons have become wetter in 51.1% of regions, and dry seasons have become drier in 59.9%. In biannual regime regions, the shortened wet seasons have occurred in 83.7% of regions, with an average shortening of 8 d, and precipitation has decreased in both wet and dry seasons. Moreover, the shorter wet seasons will amplify further by the end of the 21st century. The continuous seasonal changes will threaten agricultural, ecological security, and even human well-being.