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Abstract Intense volcanic and geothermal activities characterize the Great Rift Valley of East Africa. Ground fissure disasters of the Great Rift Valley have garnered increasing attention in recent years. Through field investigations, trenching, geophysical exploration, gas sampling and analysis, we determined the distribution and origin of 22 ground fissures within the Kedong Basin of the Central Kenya Rift. These ground fissures caused varying degrees of damage to roads, culverts, railways, and communities. Trenching and geophysical exploration have shown that ground fissures in sediments are connected to rock fractures with gas escaping. The gases expelled from the rock fractures contained methane and SO2, which were absent in the normal atmosphere, and 3He/4He ratios in gases measured further indicated that the volatiles were derived from the mantle, suggesting that these rock fractures extended deep into the underlying bedrock. Spatial correlations with rock fractures demonstrate the deep origin of these ground fissures, which are associated with active rifting, plate separation, and volcanism. The ground fissures are formed due to movement on the deeper rock fractures, and then the gas escapes through the fissures. Determining the unusual origin of these ground fissures can not only guide infrastructure development and urban planning but also contribute to the safety of local communities.

At the moment of electric locomotive passing the neutral-section, the voltage and current of traction network may have low-frequency oscillation (LFO), which will seriously affect the safe operation of the railway. Aiming at eliminating the transient LFO, a modeling method of vehicle-grid coupling system based on flux-current theory is presented in this paper. In the model of electric locomotive, the transient current control strategy and magnetic saturation of on-board transformer are considered, and the equivalent model of excitation inductance of on-board transformer is established based on the flux-current theory. Using this model, based on the Middlebrook impedance ratio criterion, the stability region of vehicle-grid coupling system is analyzed under the influence of average saturation of on-board transformer and control parameters of electric locomotive. The simulation results are analyzed to evaluate and verify the proposed modeling method of LFO. This work has the benefits of defining the opening and closing phase angle region of system stability as well as providing guidance to adaptively modify the control parameters to suppress the LFO.

Effective agricultural management in maize production operations starts with the early quantification of seedlings. Accurately determining plant presence allows growers to optimize planting density, allocate resources, and detect potential growth issues early on. This study provides a comprehensive analysis of the performance of various object detection models in maize production, with a focus on the effects of planting density, growth stages, and flight altitudes. The findings of this study demonstrate that one-stage models, particularly YOLOv8n and YOLOv5n, demonstrated superior performance with AP50 scores of 0.976 and 0.951, respectively, outperforming two-stage models in terms of resource efficiency and seedling quantification accuracy. YOLOv8n, along with Deformable DETR, Faster R-CNN, and YOLOv3-tiny, were identified for further examination based on their performance metrics and architectural features. The study also highlights the significant impact of plant density and growth stage on detection accuracy. Increased planting density and advanced growth stages (particularly V6) were associated with decreased model accuracy due to increased leaf overlap and image complexity. The V2–V3 growth stages were identified as the optimal periods for detection. Additionally, flight altitude negatively affected image resolution and detection accuracy, with higher altitudes leading to poorer performance. In field applications, YOLOv8n proved highly effective, maintaining robust performance across different agricultural settings and consistently achieving rRMSEs below 1.64% in high-yield fields. The model also demonstrated high reliability, with Recall, Precision, and F1 scores exceeding 99.00%, affirming its suitability for practical agricultural use. These findings suggest that UAV-based image collection systems employing models like YOLOv8n can significantly enhance the accuracy and efficiency of seedling detection in maize production. The research elucidates the critical factors that impact the accuracy of deep learning detection models in the context of corn seedling detection and selects a model suited for this specific task in practical agricultural production. These findings offer valuable insights into the application of object detection technology and lay a foundation for the future development of precision agriculture, particularly in optimizing deep learning models for varying environmental conditions that affect corn seedling detection.

Within the context of CO2 emission peaking and carbon neutrality, the study of CO2 emissions at the provincial level is few. Sichuan Province in China has not only superior clean energy resources endowment but also great potential for the reduction of CO2 emissions. Therefore, using logarithmic mean Divisia index (LMDI) model to analysis the influence degree of different influencing factors on CO2 emissions from final energy consumption in Sichuan Province, so as to formulate corresponding emission reduction countermeasures from different paths according to the influencing factors. Based on the data of final energy consumption in Sichuan Province from 2010 to 2019, we calculated CO2 emission by the indirect emission calculation method. The influencing factors of CO2 emissions originating from final energy consumption in Sichuan Province were decomposed into population size, economic development, industrial structure, energy consumption intensity, and energy consumption structure by the Kaya–logarithmic mean Divisia index (LMDI) decomposition model. At the same time, grey correlation analysis was used to identify the correlation between CO2 emissions originating from final energy consumption and the influencing factors in Sichuan Province. The results showed that population size, economic development and energy consumption structure have positive contributions to CO2 emissions from final energy consumption in Sichuan Province, and economic development has a significant contribution to CO2 emissions from final energy consumption, with a contribution rate of 519.11%. The industrial structure and energy consumption intensity have negative contributions to CO2 emissions in Sichuan Province, and both of them have significant contributions, among which the contribution rate of energy consumption structure was 325.96%. From the perspective of industrial structure, secondary industry makes significant contributions and will maintain a restraining effect; from the perspective of energy consumption structure, industry sector has a significant contribution. The results of this paper are conducive to the implementation of carbon emission reduction policies in Sichuan Province.

The Kenya Rift valley is located in the middle section of the eastern branch of the Great Rift valley in East Africa. Modern tectonic movement and volcanic activity are intense, and it is a hotspot in current geological research.The rift zone has developed ground fissure disasters due to its unique geological structure background, rock and soil characteristics, and meteorological and hydrological conditions. In this paper, we have studied the geological environment background, plane characteristics and shallow section structure characteristics of ground fissures in rift valley area through data collection, detailed field geological surveytrenching, drilling and indoor geotechnical tests. Internal dynamic geological processes such as rift extension and volcanic activity are the controlling factors for the formation of ground fissures in this area; the loose and easily eroded soil on the shallow surface is the material basis for the formation of ground fissures; strong rainfall provides hydraulic power for the formation of ground fissure Conditions: The "soft-hard-soft" stratum structure provides a favorable accumulation place for water-erosive substances. Finally, we divide the formation and evolution process of ground fissures in the Kenya Rift Valley into three stages, the incubation stage, the expansion stage and the disaster stage.

Abstract Earth fissures caused by tectonic forces, human activities, or both seriously threaten the safety of people’s lives and properties. The Taiyuan Basin, a Cenozoic downfaulted basin located in the centre of the Fen-Wei Basin tectonic belt, in northwestern China, presents the ideal study area for a hazard assessment of earth fissures. A total of 104 earth fissures have been observed in the Taiyuan Basin, with a total length of approximately 128 km. In this paper, we proposed a probabilistic method for mapping earth fissure hazards by integrating the analytic hierarchy process (AHP), the area under the curve (AUC), and the certainty factor model (CFM). Geomorphic units, geologic formations, active faults and land subsidence zones of the Taiyuan Basin were mapped in detail. Correlations between these factors and earth fissures were evaluated through spatial modelling in ArcGIS. The AUC was introduced into the AHP to weight each factor and thus, to derive an earth fissure susceptibility map. Finally, the modelled earth fissure susceptibility was compared with a digital inventory of earth fissures to develop a probability function and map the spatial variability in failure probability through the CFM. The study indicates that active faults have the greatest contribution to the generation of earth fissures. Earth fissures are prone to develop in the piedmont alluvial-diluvial clinoplain and the transitional zone near the geomorphic boundary. This mapping procedure can assist in making rational decisions regarding urban planning and infrastructure development in areas susceptible to earth fissures.

Abstract Carbon tax and some other policies are designed to reduce emissions; resource tax can raise the energy price from the supply side to achieve the purpose of emission mitigation. Based on previous studies, this paper abstracts mitigation policies into supply-control (resource tax as an example) and demand-control (carbon tax as an example). The effects of these policies have been divided into the direct and the indirect effects. A dynamic recursive computable general equilibrium model is applied to simulate different impact path of the two policies. The research shows that if there is no foreign trade and the market is completely market-oriented, the effect of the demand control and the supply control may be equivalent. But this is not the real case. Under the same level of CO2 emission, carbon tax can significantly reduce the energy demand of enterprises and restrain energy imports. However, resource tax can significantly increase domestic energy prices firstly, and then enterprises will be more willing to use cheaper imported energy. Regardless of energy security, relatively low energy use costs ease the economic costs of emission mitigation. Therefore, if every country in the world is required to reduce emissions compulsorily, resource tax may be a better policy of reducing emissions while obtaining “excess profits”.

The process of carbon neutrality does have economic costs; however, few studies have measured the cost and the economic neutral opportunities. This paper uses a dynamic computable general equilibrium (CGE) model to simulate China’s carbon neutrality path from 2020 to 2060 and analyzes its economic impact. This paper innovatively adjusts the CGE modeling technology and simulates the boundary of the Porter hypothesis on the premise of economic neutrality. The results show that the carbon neutrality target may reduce the annual GDP growth rate by about 0.8% in 2020–2060. To make the carbon pricing method under the carbon neutrality framework meet the strong version of the Porter hypothesis (or economic neutrality), China must increase its annual total factor productivity by 0.56–0.57% in 2020–2060; this is hard to achieve. In addition, the study finds that China’s 2030 carbon target has little impact on the economy, but the achievement of the 2060 carbon neutrality target will have a significant effect. Therefore, the paper believes that the key to carbon neutrality lies in the coexistence of technological innovation and carbon pricing to ensure that we can cope with global warming with the lowest cost and resistance.

Abstract Background To investigate corneal densitometry values obtained using Scheimpflug tomography in normal and highly myopic (HM) eyes and to assess the differences in densitometry values between them. Methods Highly myopic and normal corneas were examined using the Pentacam Scheimpflug imaging system. Corneal densitometry was automatically performed over a 12-mm diameter area, which was divided on the basis of annular concentric zones (0–2 mm, 2–6 mm, 6–10 mm, 10–12 mm, total diameter) and depth (anterior layer: inner 120 μm; center layer: from 120 μm to the last 60 μm; posterior layer: last 60 μm; total corneal thickness). Results A total of 100 normal and 100 HM eyes were enrolled in this study. Upon total corneal thickness densitometry, the HM group was found to have significantly lower values compared with the normal group in 4 annuli, including the 2 mm central zone, 2-6 mm zone, 6–10 mm zone, and 0–12 mm total diameter. Upon anterior layer densitometry, the HM group demonstrated statistically lower values in the 2-6 mm and 6–10 mm zones. Upon densitometry of the central and posterior layers, the HM group was found to have lower values in all annuli. Conclusions The densitometry map reveals that light backscatter was lower in most portions of the HM cornea than in the normal cornea.

Abstract Background To investigate the anterior lens capsule and epithelium thickness (defined as anterior lens capsular complex: ALCC) in normal Chinese subjects using spectral-domian optical coherence tomography (SD-OCT) and examine the factors that may influence the ALCC, such as age, gender, pupil diameter (PD) and signal strength index (SSI). Methods A prospective observational case series. One-hundred-thirty-four normal subjects (134 eyes) were included. The ALCCs were determined manually via SD-OCT. Using the pupil center as a reference position, the central ALCC (CALCC), nasal 1-mm ALCC (NALCC), temporal 1-mm ALCC (TALCC) and PD were measured manually. Results The mean CALCC, NALCC and TALCC were 33 ± 6 μm, 36 ± 7 μm and 34 ± 6 μm, respectively. The NALCC was significantly thicker than the CALCC (P

With the rapid development of high-precision road network maps, low-precision road network maps (basic data unrelated to hardware) will need to be directly produced for traditional navigation software from high-precision maps. To do so, large amounts of vector data representing road networks must be simplified and spatial directional similarity in road networks must be maintained while reducing precision. In this study, an elite strategy genetic algorithm based on the grid model is applied to spatial directional adjustment in road networks for producing road network maps for traditional navigation. Firstly, semantic features and critical vertices are extracted from the road network with high precision. Secondly, some high-precision vertices are eliminated under constraints of the digital navigation map. During this process, the local shape maintenance of the road is considered, and the destruction of the spatial topological relationships is avoided. Thirdly, a genetic algorithm for minimizing the total changes in road azimuths at nodes of road networks is developed to maintain spatial directional relationships while reducing precision. Experimental results and visualization effects on the test data of different cities show that this method is suitable for generating road network maps for traditional navigation software from high-precision ones.

To compare the axial length (AL), anterior chamber depth (ACD) and intraocular lens power (IOLP) of IOLMaster and Ultrasound in normal, long and short eyes.Seventy-four normal eyes (≥ 22 mm and ≤ 25 mm), 74 long eyes (> 25 mm) and 78 short eyes (< 22 mm) underwent AL and ACD measurements with both devices in the order of IOLMaster followed by Ultrasound. The IOLP were calculated using a free online LADAS IOL formula calculator.The difference in AL and IOLP between IOLMaster and Ultrasound was statistically significant when all three groups were combined. The difference in ACD between IOLMaster and Ultrasound was statistically significant in the normal group (P

When electric multiple units (EMU) pass the neutral zone, the traction transformer may generate sympathetic inrush, which will cause a malfunction in the transformer differential protection. In order to study the mechanism of the sympathetic inrush of the cascaded traction transformer, the flux−current model of the transformer, line impedance, power system voltage source, and other loads was established. On the basis of the flux−current circuit model, the influence of different factors on the sympathetic inrush of the traction transformer was analyzed. The analysis results were verified by simulation. Research results show that the remanence, closing angle, line impedance, and load will affect the duration and amplitude of the sympathetic inrush.

To compare the anterior chamber depth (ACD), keratometry (K) and astigmatism measurements taken by IOLMaster and Pentacam HR in normal and high myopic (HM) eyes.A prospective observational case series.Sixty-six normal eyes and 59 HM eyes underwent ACD, keratometry and astigmatism measurements with both devices. Axial length (AL) was measured on IOLMaster. The interdevice agreement was evaluated using the Bland-Altman analysis and paired t-test. The correlations between age and AL & ACD were analyzed. Vector analysis was used to compare astigmatism measurements.The ACD from IOLMaster and Pentacam HR was different for the normal group (P = 0.003) but not for the HM group (P = 0.280). IOLMaster demonstrated higher steep K and mean K values than Pentacam HR for both normal and HM groups (P

In recent years, the epidemiological profile of Getah virus (GETV) has become increasingly serious, posing a huge threat to animal and public health in China. GETV can cause multi-species infection, including horses, pigs, rats, cattle, kangaroos, reptiles and birds. However, there were few reports on the efficiency of the virus entering the host via routes of different systems. In the present study, a GETV strain (SC201807) was obtained from a piglet's blood in 2018 in Sichuan, China. First, we established a quantitative real-time polymerase chain reaction (qRT-PCR) SYBR assay specific to GETV. Then, we evaluated the infection efficiency of different routes using mouse animal model. 108 male mice were randomly divided into four groups as follows: intramuscular, intraoral and intranasal infection routes, and negative control. All mice in the experimental group were inoculated with 4 × 102.85 TCID50 GETV virus. Tissue tropism experiments show that GETV has a wide range of tissue distribution, and intramuscular infection is the first to infect all tissues of the body, and suggest that oral infection may be a new GETV transmission route. Histopathological examination results showed that intramuscular injection of GETV mainly caused different degrees of pathological damage to the tissues, and could rapidly induce a large amount of inflammatory regulatory factors such as IL-6 and TNF-α. Our data may help us to evaluate the risk of transmission of Porcine Getah virus and provide an experimental basis for the prevention and control of Porcine Getah virus.

Bacterial exonuclease III (ExoIII), widely acknowledged for specifically targeting double-stranded DNA (dsDNA), has been documented as a DNA repair-associated nuclease with apurinic/apyrimidinic (AP)-endonuclease and 3′→5′ exonuclease activities. Due to these enzymatic properties, ExoIII has been broadly applied in molecular biosensors. Here, we demonstrate that ExoIII (Escherichia coli) possesses highly active enzymatic activities on ssDNA. By using a range of ssDNA fluorescence-quenching reporters and fluorophore-labeled probes coupled with mass spectrometry analysis, we found ExoIII cleaved the ssDNA at 5′-bond of phosphodiester from 3′ to 5′ end by both exonuclease and endonuclease activities. Additional point mutation analysis identified the critical residues for the ssDNase action of ExoIII and suggested the activity shared the same active center with the dsDNA-targeted activities of ExoIII. Notably, ExoIII could also digest the dsDNA structures containing 3′-end ssDNA. Considering most ExoIII-assisted molecular biosensors require the involvement of single-stranded DNA (ssDNA) or nucleic acid aptamer containing ssDNA, the activity will lead to low efficiency or false positive outcome. Our study revealed the multi-enzymatic activity and the underlying molecular mechanism of ExoIII on ssDNA, illuminating novel insights for understanding its biological roles in DNA repair and the rational design of ExoIII-ssDNA involved diagnostics.

Rationale and objectives: To investigate the relationship between the pericoronary adipose tissue CT mean attenuation (PCATMA) measurement and image reconstruction parameters (adaptive statistical iterative reconstruction-veo (ASIR-V) percentage, kernel, and slice thickness). Materials and methods: One hundred and ninety-eight consecutive patients underwent CT coronary angiography at 100 kilovoltage peak (kVp) (n = 102) and 120 kVp (n = 96) were included. All scans were reconstructed by three means: 1. with 11 different ASIR-V percentages, standard kernel and 0.625 mm; 2. with soft, standard, detail, and bone kernels, 60 % ASIR-V, and 0.625 mm; 3. at 0.625 mm and 1.25 mm slice thickness, standard kernel and 60 % ASIR-V. PCATMA of the three main coronary arteries was calculated using a dedicated software. Linear regression, analysis of variance (ANOVA), Friedman test, and paired t-test were used for statistical analysis. Results: Linear regression of pooled average data showed that the PCATMA was positively and linearly correlated with the ASIR-V percentage (all R squared >0.99). Regression analysis of individual data showed that most R squared were greater than 0.8 or 0.9, but their slope consisted of a relatively wide range. The difference of PCATMA among different kernels for each coronary artery reached statistically significant levels (P

Abstract Infectious disease outbreaks transcend the medical and public health realms, triggering widespread panic and impeding socio-economic development. Considering that self-limiting diarrhoea of sporadic cases is usually underreported, the Salmonella outbreak (SO) study offers a unique opportunity for source tracing, spatiotemporal correlation, and outbreak prediction. To summarize the pattern of SO and estimate observational epidemiological indicators, 1,134 qualitative reports screened from 1949 to 2023 were included in the systematic review dataset, which contained a 506-study meta-analysis dataset. In addition to the dataset comprising over 50 columns with a total of 46,494 entries eligible for inclusion in systematic reviews or input into prediction models, we also provide initial literature collection datasets and datasets containing socio-economic and climate information for relevant regions. This study has a broad impact on advancing knowledge regarding epidemic trends and prevention priorities in diverse salmonellosis outbreaks and guiding rational policy-making or predictive modeling to mitigate the infringement upon the right to life imposed by significant epidemics.

The climate effects caused by greenhouse gases represented by CO2 are increasingly prominent, and global carbon reduction is urgent. Plasma technology has unique advantages in converting CO2 and it shows good prospects in achieving CO2-resource conversion. This paper reviewed the research results of plasma technology for CO2-resource conversion in recent years, mainly introduced the main process parameters and evaluation indicators of plasma converting CO2, summarized the effects of process parameters, active species and background gases on CO2 conversion, and focused on analyzing the synergistic effect of dielectric barrier dischange (DBD) plasma synergistic catalysis on CO2 conversion. Finally, in view of the problems and challenges faced by plasma synergistic catalysis for CO2-resource conversion, several key research directions in the future were proposed: 1) furtherly reveal the reaction mechanism of plasma converting CO2; 2) systematically explore the synergistic mechanism of plasma and catalyst; 3) from the perspective of practical engineering applications, more attention should be paid on the engineering amplification, safety risks in use, economic benefits of reactors, and so on.

ABSTRACTPorcine reproductive and respiratory syndrome virus (PRRSV) causes significant economic losses in the swine industry. Frequent mutations and recombinations account for PRRSV immune evasion and the emergence of novel strains. In this study, we isolated and characterized two novel PRRSV-2 strains from Southwest China exhibiting distinct recombination patterns. They were designated SCABTC-202305 and SCABTC-202309. Phylogenetic results indicated that SCABTC-202305 was classified as lineage 8, and SCABTC-202309 was classified as lineage 1.8. Amino acid mutation analysis identified unique amino acid substitutions and deletions in ORF5 and Nsp2 genes. The results of the recombination analysis revealed that SCABTC-202305 is a recombinant with JXA1 as the major parental strain and NADC30 as the minor parental strain. At the same time, SCABTC-202309 is identified as a recombinant with NADC30 as the major parental strain and JXA1 as the minor parental strain. In this study, we infected piglets with SCABTC-202305, SCABTC-202309, or mock inoculum (control) to study the pathogenicity of these isolates. Although both isolated strains were pathogenic, SCABTC-202305-infected piglets exhibited more severe clinical signs and higher mortality, viral load, and antibody response than SCABTC-202309-infected piglets. SCABTC-202305 also caused more extensive lung lesions based on histopathology. Our findings suggest that the divergent pathogenicity observed between the two novel PRRSV isolates may be attributed to variations in the genetic information encoded by specific genomic regions. Elucidating the genetic determinants governing PRRSV virulence and transmissibility will inform efforts to control this devastating swine pathogen.IMPORTANCEPorcine reproductive and respiratory syndrome virus (PRRSV) is one of the most critical pathogens impacting the global swine industry. Frequent mutations and recombinations have made the control of PRRSV increasingly difficult. Following the NADC30-like PRRSV pandemic, recombination events involving PRRSV strains have further increased. We isolated two novel field PRRSV recombinant strains, SCABTC-202305 and SCABTC-202309, exhibiting different recombination patterns and compared their pathogenicity in animal experiments. The isolates caused higher viral loads, persistent fever, marked weight loss, moderate respiratory clinical signs, and severe histopathologic lung lesions in piglets. Elucidating correlations between recombinant regions and pathogenicity in these isolates can inform epidemiologic tracking of emerging strains and investigations into viral adaptive mechanisms underlying PRRSV immunity evasion. Our findings underscore the importance of continued genomic surveillance to curb this economically damaging pathogen.

Abstract Porcine deltacoronavirus (PDCoV) is a novel coronavirus that causes enteric diseases in pigs leading to substantial financial losses within the industry. The absence of commercial vaccines and limited research on PDCoV vaccines presents significant challenges. Therefore, we evaluated the safety and immunogenicity of recombinant pseudorabies virus (PRV) rPRVXJ-delgE/gI/TK-S through intranasal mucosal immunization in weaned piglets and SPF mice. Results indicated that rPRVXJ-delgE/gI/TK-S safely induced PDCoV S-specific and PRV gB-specific antibodies in piglets, with levels increasing 7 days after immunization. Virus challenge tests demonstrated that rPRVXJ-delgE/gI/TK-S effectively improved piglet survival rates, reduced virus shedding, and alleviated clinical symptoms and pathological damage. Notably, the recombinant virus reduced anti-inflammatory and pro-inflammatory responses by regulating IFN-γ, TNF-α, and IL-1β secretion after infection. Additionally, rPRVXJ-delgE/gI/TK-S colonized target intestinal segments infected with PDCoV, stimulated the secretion of cytokines by MLVS in mice, stimulated sIgA secretion in different intestinal segments of mice, and improved mucosal immune function. HE and AB/PAS staining confirmed a more complete intestinal mucosal barrier and a significant increase in goblet cell numbers after immunization. In conclusion, rPRVXJ-delgE/gI/TK-S exhibits good immunogenicity and safety in mice and piglets, making it a promising candidate vaccine for PDCoV.

Pseudorabies virus can cause inflammation in the central nervous system and neurological symptoms. To further investigate the protective mechanism of PRV XJ delgE/gI/TK in the central nervous system, an intracranial PRV-infection mice model was developed. The results demonstrated that immunization with PRV XJ delgE/gI/TK successfully prevented death caused by PRV-intracranial infection. Subsequently, the brains were collected for transcriptome and metabolome analysis. GO and KEGG enrichment analysis indicated that the differentially expressed genes were primarily enriched in pathways such as TNF, NOD-like receptor, JAK–STAT, MAPK, IL-17 and apoptosis signaling. Metabolomics analysis revealed that the differential metabolites were mainly associated with pathways such as fatty acid degradation, arachidonic acid metabolism, linoleic acid metabolism and unsaturated fatty acid biosynthesis. The combined analysis of metabolites and differentially expressed genes revealed a strong correlation between the differential metabolites and TNF, PI3K, and MAPK signaling pathways. Anti-inflammatory metabolites have been shown to inhibit the inflammatory response and prevent mouse death caused by PRV infection. Notably, when glutathione was injected intracranially and dihydroartemisinin was injected intraperitoneally, complete protection against PRV-induced death in mice was observed. Moreover, PRV activates the PI3K/AKT signaling pathway. In conclusion, our study demonstrates that PRV XJ delgE/gI/TK can protects intracranially infected mice from death by regulating various metabolites with anti-inflammatory functions post-immunization.