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Abstract Background With the widespread adoption of smartphones, mobile phone addiction has increasingly gained prominence among Chinese college students, exerting a profound and detrimental impact on their learning engagement. This study employs self-determination theory as a framework to examine the mechanisms through which mobile phone addiction affects students’ learning engagement. Specifically, it examines the mediating effects of physical activity and academic self-efficacy in this relationship. Methods This study was conducted from March to June 2024, using the Mobile Phone Addiction Scale, Learning Engagement Scale, Physical Activity Scale, and Academic Self-Efficacy Scale among college students from eight universities in Shaanxi Province. The survey was conducted using the Chinese online questionnaire platform “Questionnaire Star,”and 4,562 valid questionnaires were finally obtained. SPSS 29.0 and AMOS 29.0 were used for data analysis and structural equation model testing. Results The results revealed significant negative correlations between mobile phone addiction and learning engagement (r = -0.434, p

Abstract Accurate medical image segmentation plays a vital role in clinical practice. Convolutional Neural Network and Transformer are mainstream architectures for this task. However, convolutional neural network lacks the ability of modeling global dependency while Transformer cannot extract local details. In this paper, we propose DATTNet, D ual ATT ention Net work, an encoder-decoder deep learning model for medical image segmentation. DATTNet is exploited in hierarchical fashion with two novel components: (1) Dual Attention module is designed to model global dependency in spatial and channel dimensions. (2) Context Fusion Bridge is presented to remix the feature maps with multiple scales and construct their correlations. The experiments on ACDC, Synapse and Kvasir-SEG datasets are conducted to evaluate the performance of DATTNet. Our proposed model shows superior performance, effectiveness and robustness compared to SOTA methods, with mean Dice Similarity Coefficient scores of 92.2%, 84.5% and 89.1% on cardiac, abdominal organs and gastrointestinal poly segmentation tasks. The quantitative and qualitative results demonstrate that our proposed DATTNet attains favorable capability across different modalities (MRI, CT, and endoscopy) and can be generalized to various tasks. Therefore, it is envisaged as being potential for practicable clinical applications. The code has been released on https://github.com/MhZhang123/DATTNet/tree/main .

Abstract Purpose Good sleep is one of the necessary conditions to ensure the normal performance of the physiological and psychological functions of college students. This study aimed to explore the relationship between mobile phone addiction and bedtime procrastination among Chinese college students and the mediating mechanisms of physical exercise and anxiety between the two, with a view to seek ways to prevent and intervene in college students’ sleep procrastination and improve their sleep quality. Methods Using SPSS 29.0 analysis with Bootstrap’s method, 3,800 first-year students, sophomores, and juniors were given the Mobile Phone Addiction Tendency Scale, Bedtime Procrastination Scale, Physical Activity Scale, and Anxiety Scale. The results of the analyses included mediation tests and effect analyses of anxiety and physical activity. Results The correlation analysis revealed significant positive correlations between mobile phone addiction and bedtime procrastination (r = 0.149, p

Abstract Background High-cost medical consumables (HMCs) have emerged as significant economic and technological challenges for numerous national healthcare systems. Governmental hospitals play an indispensable role in many national health systems, closely linked to the evaluation of admissions and the management of procurement for HMCs. Nevertheless, many governmental hospitals face avoidable management risks due to the lack of a decision-making tool. In response, we conducted a systematic review to establishing a framework for the admission criteria of HMCs. This framework aims to enhance their effective utilization and maximize economic, clinical, and social benefits. Methods In accordance with a systematic review protocol developed for our study, we conducted comprehensive searches in the PubMed, Web of Science, and Embase databases to identify all correlation studies conducted prior to December 31, 2021. Subsequently, two independent reviewers performed a two-round screening process, resulting in the inclusion of 23 articles in our study. Finally, a third reviewer meticulously examined the selected indicators and contributed to the development of the final criterion framework. Results The criterion framework was established with 7 first-level indicators and 23 s-level indicators. Among the first-level indicators, "Clinical Benefit" held the highest significance, with a combined weight of 1.606, followed by "Economic Value" and "Organizational Impact" at 1.497 and 1.159, respectively. At the second level, "Safety" and "Efficacy" carried equal weight in the decision-making tool, with combined weights of approximately 1.300 each and a standard combined weight of 0.130. Conclusion This admission criteria framework serves as a vital decision-making tool for managing admissions and highlights several crucial evaluation indicators. Economic considerations emerge as the principal determinant in HMCs procurement decisions. Consequently, healthcare managers and decision-makers are recommended to give precedence to value-based healthcare and evidence-based procurement practices. In the long term, governmental hospitals must grapple with the challenge of judiciously allocating limited resources to maximize both social and economic benefits.

Objective By assessing the genetic diversity and associated selective traits of Kirghiz sheep (KIR), we aim to uncover the mechanisms that contribute to sheep’s adaptability to the Pamir Plateau environment. Methods This study utilized Illumina Ovine SNP50 BeadChip data from KIR residing in the Pamir Plateau, Qira Black sheep (QBS) inhabiting the Taklamakan Desert, and commonly introduced breeds including Dorper sheep (DOR), Suffolk sheep (SUF), and Hu sheep (HU). The data was analyzed using principal component analysis, phylogenetic analysis, population admixture analysis, kinship matrix analysis, linkage disequilibrium analysis, and selective signature analysis. We employed four methods for selective signature analysis: fixation index (Fst), cross-population extended homozygosity (XP-EHH), integrated haplotype score (iHS), and nucleotide diversity (Pi). These methods aim to uncover the genetic mechanisms underlying the germplasm resources of Kirghiz sheep, enhance their production traits, and explore their adaptation to challenging environmental conditions. Results The test results unveiled potential selective signals associated with adaptive traits and growth characteristics in sheep under harsh environmental conditions, and annotated the corresponding genes accordingly. These genes encompass various functionalities such as adaptations associated with plateau, cold, and arid environment (ETAA1, UBE3D, TLE4, NXPH1, MAT2B, PPARGC1A, VEGFA, TBX15 and PLXNA4), wool traits (LMO3, TRPS1, EPHA5), body size traits (PLXNA2, EFNA5), reproductive traits (PPP3CA, PDHA2, NTRK2), and immunity (GATA3). Conclusion Our study identified candidate genes associated with the production traits and adaptation to the harsh environment of the Pamir Plateau in Kirghiz sheep. These findings provide valuable resources for local sheep breeding programs. The objective of this study is to offer valuable insights for the sustainable development of the Kirghiz sheep industry.

Climate change and anthropogenic activities have increased the complexity of hydrology–soil–vegetation interactions in arid-region irrigation areas. Therefore, studies on the spatiotemporal characteristics of these interactions can greatly benefit the sustainable development of arid areas. This study developed a spatially granular dataset of the key hydrology, soil, and vegetation elements for the Hetao Irrigation District (HID) for 2000–2020, recognized as the largest single-port artesian irrigation area in Asia, and explored the interactions between these elements by means of a geodetector, the analytic hierarchy process, and the Pearson correlation coefficient. The key results indicated the following: (1) a declining trend of 0.1–0.15 in the comprehensive influence of hydrology–soil–vegetation interactions; increasing significance of hydrologically driven soil and vegetation evolution, with feedback between soil and vegetation; (2) the maximization of the interactions between soil moisture and precipitation and groundwater, with evapotranspiration as the dominant factor regulating hydrology–vegetation interactions; (3) the interactions between hydrology, soil, and vegetation showing nonlinear synergism; (4) and the spatial distributions of the hydrology–soil–vegetation interactions showing significant band-like patterns with weak coupling between the elements.

Background: For pediatric patients with solid abdominal tumors, early diagnosis can guide clinical treatment decisions, and comprehensive preoperative evaluation is essential to reduce surgical risk. The aim of this study was to explore the feasibility of multiphase enhanced CT-based transformer in the early diagnosis of tumors and prediction of surgical risk events (SRE). Methods: A total of 496 pediatric patients with solid abdominal tumors were enrolled in the study. With Swin transformer, we constructed and trained two Swin-T models based on preoperative multiphase enhanced CT for personalized prediction of tumor type and SRE status. Subsequently, we comprehensively evaluated the performance of each model and constructed four benchmark models for performance comparison. Results: There was no significant difference in SRE status between tumor types. In the diagnostic task, areas under the receiver operating characteristic curves (AUC) of the Swin-T model were 0.987 (95 % CI, 0.973–0.997) and 0.844 (95 % CI, 0.730–0.940) in the training and validation cohorts, respectively. In predicting SRE, AUCs of the Swin-T model were 0.920 (95 % CI, 0.885–0.948) and 0.741 (95 % CI, 0.632–0.838) in the training and test cohorts, respectively. The Swin-T model achieved the best performance in both classification tasks compared to benchmark models. Conclusion: The Swin-T model is a promising tool to assist pediatricians in the differential diagnosis of abdominal tumors and in comprehensive preoperative evaluation.

Background: Even with significant advancements, treating multiple myeloma (MM) remains difficult. At present, the main treatment methods include combined treatment of stem cell transplantation, drug treatment, etc. With the clarification of the molecular biological mechanism of MM, as well as the in-depth study of the internal signal of myeloma cells and the microenvironment of MM patients, more and more new drugs targeting myeloma and microenvironment are gradually used in clinical maintenance treatment, such as inhibit the proteosome: ixazomib, bortezomib and carfilzomib, immune - modulators: thalidomide and lenalidomide, monoclonal antibodies, etc. have made great progress in MM maintenance treatment. With the continuous development of proteasome inhibitor maintenance treatment in MM, the prognosis of the disease has been significantly improved. Our aim is to evaluate the effectiveness and adverse reactions of proteasome inhibitors in maintenance therapy for multiple myeloma, providing new ideas for clinical medication. Methods: Four databases containing randomized controlled studies on the effectiveness and safety of proteasome inhibitors in the maintenance therapy of multiple myeloma are retrieved by the computer. Once the quality of the literature has been thoroughly evaluated, run the data via the RevMan 5.3 software. Results: Eventually 8 studies were added in this systematic review. Compared with the placebo group, proteasome inhibitor in maintenance treatment of multiple myeloma patients with prolonged the survival without progression and overall existence. 5 studies reported the peripheral neuropathy of multiple myeloma in the treatment group compared to placebo group, which was remarkably greater (OR: 1.98; 95 % Cl: 1.35, 2.92; P

The objective of this study is to analyze environmental genetic selection signals in large-scale sheep populations with conflicting environmental adaptations, aiming to identify and isolate genes associated with environmental adaptations in sheep populations. Kirghiz sheep, which inhabit high-altitude environments year-round, demonstrate the ability to adapt to extreme conditions. In this study, 42 Kirghiz sheep, 24 Tien-Shan in Kyrgyzstan sheep, 189 Qira black sheep, and 160 Chinese Merino sheep were genotyped using Illumina Ovine SNP50K chip. Regions exhibiting a selection signal threshold of 5%, as well as PI analysis and haplotype statistical scanning gene data were annotated, and intersecting genes were identified as candidate genes. Through Fst and haplotype statistical analysis revealed the key gene PDGFD and its vicinity’s impact on fat deposition in sheep tails. Additionally, Fst and PI analysis uncovered genes related to high-altitude adaptation as well as those linked to animal growth and reproduction.Further GO and KEGG enrichment pathway analyses unveiled pathways associated with high-altitude adaptation such as negative regulation of peptidyl-tyrosine phosphorylation and xenobiotic metabolism processes.This investigation into the adaptability of Kirghiz sheep provides theoretical support and practical guidance for the conservation and genetic enhancement of Kirghiz sheep germplasm resources.

BackgroundPrevious studies have indicated a potential link between the gut microbiota and lymphoma. However, the exact causal interplay between the two remains an area of ambiguity.MethodsWe performed a two-sample Mendelian randomization (MR) analysis to elucidate the causal relationship between gut microbiota and five types of lymphoma. The research drew upon microbiome data from a research project of 14,306 participants and lymphoma data encompassing 324,650 cases. Single-nucleotide polymorphisms were meticulously chosen as instrumental variables according to multiple stringent criteria. Five MR methodologies, including the inverse variance weighted approach, were utilized to assess the direct causal impact between the microbial exposures and lymphoma outcomes. Moreover, sensitivity analyses were carried out to robustly scrutinize and validate the potential presence of heterogeneity and pleiotropy, thereby ensuring the reliability and accuracy.ResultsWe discerned 38 potential causal associations linking genetic predispositions within the gut microbiome to the development of lymphoma. A few of the more significant results are as follows: Genus Coprobacter (OR = 0.619, 95% CI 0.438–0.873, P = 0.006) demonstrated a potentially protective effect against Hodgkin’s lymphoma (HL). Genus Alistipes (OR = 0.473, 95% CI 0.278–0.807, P = 0.006) was a protective factor for diffuse large B-cell lymphoma. Genus Ruminococcaceae (OR = 0.541, 95% CI 0.341–0.857, P = 0.009) exhibited suggestive protective effects against follicular lymphoma. Genus LachnospiraceaeUCG001 (OR = 0.354, 95% CI 0.198–0.631, P = 0.0004) showed protective properties against T/NK cell lymphoma. The Q test indicated an absence of heterogeneity, and the MR-Egger test did not show significant horizontal polytropy. Furthermore, the leave-one-out analysis failed to identify any SNP that exerted a substantial influence on the overall results.ConclusionOur study elucidates a definitive causal link between gut microbiota and lymphoma development, pinpointing specific microbial taxa with potential causative roles in lymphomagenesis, as well as identifying probiotic candidates that may impact disease progression, which provide new ideas for possible therapeutic approaches to lymphoma and clues to the pathogenesis of lymphoma.

Abstract The purpose of click-through rate (CTR) prediction is to anticipate how likely a person is to click on an advertisement or item. It's required for a lot of internet applications, such online advertising and recommendation systems. The previous click-through rate estimation approach suffered from the following two flaws. On the one hand, input characteristics (such as user id, user age, user age, item id, item category) are usually sparse and multidimensional, making them effective. High-level combination characteristics are used for prediction. Obtaining it manually by domain experts takes a long time and is difficult to finish; also, customer interests are not all the same. The accuracy of the model findings will significantly increase if this immediately recognized component is incorporated in the prediction model. As a consequence, this study creates an IARM (interactive attention rate estimation model) that incorporates user interest as well as a multi-head self-attention mechanism. The deep learning network is used in the model to determine the user's interest expression based on user attributes. The multi-head self-attention mechanism with residual network is then employed to get feature interaction, which enhances the degree of effect of significant characteristics on the estimation result as well as its accuracy. The IARM model outperforms other recent prediction models in the assessment metrics AUC and LOSS, and it has superior accuracy, according to the results from the public experimental data set.

CTR prediction is an important task in recommender systems, which is used to estimate the likelihood of a user clicking on an advertisement.In the past, the CTR prediction model based on the deep neural network mainly obtains the implicit feature combination of the model at the bit-wise level, and the interpretability and generalization of the model are poor. At the same time, the prediction accuracy of the model is poor. For the above problems, We propose a click-through rate prediction model (DTM) with double matrix-level cross-features. The model integrates various components such as multi-head self-attention, residual network and interaction network into an end-to-end model, and automatically obtains explicit feature combinations at the vector-wise level and bit-wise level, which not only has better interpretability, generalization and memory, and reduce the inherent flaws and engineering complexity of multi-modules. The experimental results show that on the datasets Criteo and Avazu, compared with other state-of-the-art CTR prediction models, the AUC values of the DTM model are increased by 4% and 3% on average, and the loss values are decreased by 3.5% and 2.8% on average, respectively.

In order to accurately describe and explore the relationship characteristics between the faults of the numerical control equipment and identify weak links in reliability, a new method for associated fault analysis of CNC equipment based on social network analysis (SNA) are proposed. First, an associated fault directed graph is established based on the statistical analysis on the associated faults of CNC equipment; then, a social network analysis method is introduced in consideration of the network attribute, the relationship between faults and the key subsystem affecting the reliability of CNC equipment are analyzed from three levels of association analysis, element analysis and matrix analysis, and then weak links in reliability of CNC equipment are identified; and finally, a series of fault records of a machining center production site are used as research objects for empirical research ,thereby verifying the scientific validity of the method. Abbreviations: CNC: Computer Numerical Control; FMECA: Failure Mode Effect and Criticality Analysis; SNA: Social Network Analysis; LAN: Local Area Network

Abstract Background Studies have demonstrated that BBX (B-BOX) genes play crucial roles in regulatory networks controlling plant growth, developmental processes and stress response. Nevertheless, comprehensive study of BBX genes in orchids (Orchidaceae) is not well studied. The newly released genome sequences of Dendrobium officinale and Phalaenopsis equestris have allowed a systematic analysis of these important BBX genes in orchids. Results Here we identified 19 (DoBBX01–19) and 16 (PeBBX01–16) BBX genes from D. officinale and P. equestris, respectively, and clustered into five clades (I-V) according to phylogenetic analysis. Thirteen orthologous, two DoBBXs paralogous and two PeBBXs paralogous gene pairs were validated. This gene family mainly underwent purifying selection, but five domains experienced positive selection during evolution. Noteworthy, the expression patterns of root, root_tips, stem, leaf, speal, column, lip, and flower_buds revealed that they might contribution to the formation of these tissues. According to the cis-regulatory elements analysis of BBX genes, qRT-PCR experiments were carried out using D. officinale PLBs (protocorm-like bodies) and displayed that these BBX genes were differentially regulated under AgNO3, MeJA (Methyl Jasmonate), ABA (abscisic acid) and SA (salicylic acid) treatments. Conclusions Our analysis exposed that DoBBX genes play significant roles in plant growth and development, and response to different environmental stress conditions of D. officinale, which provide aid in the selection of appropriate candidate genes for further functional characterization of BBX genes in plants.

Abstract Background The B-BOX (BBX) proteins have important functions in regulating plant growth and development. In plants, the BBX gene family has been identified in several plants, such as rice, Arabidopsis and tomato. However, there still lack a genome-wide survey of BBX genes in pear. Results In the present study, a total of 25 BBX genes were identified in pear (Pyrus bretschneideri Rehd.). Subsequently, phylogenetic relationship, gene structure, gene duplication, transcriptome data and qRT-PCR were conducted on these BBX gene members. The transcript analysis revealed that twelve PbBBX genes (48%) were specifically expressed in pear pollen tubes. Furthermore, qRT-PCR analysis indicated that both PbBBX4 and PbBBX13 have potential role in pear fruit development, while PbBBX5 should be involved in the senescence of pear pollen tube. Conclusions This study provided a genome-wide survey of BBX gene family in pear, and highlighted its roles in both pear fruits and pollen tubes. The results will be useful in improving our understanding of the complexity of BBX gene family and functional characteristics of its members in future study.

In plants, plant fructokinases (FRKs) are considered to be the main gateway of fructose metabolism as they can phosphorylate fructose to fructose-6-phosphate. Chinese white pears (Pyrus bretschneideri) are one of the popular fruits in the world market; sugar content is an important factor affecting the quality of the fruit. We identified 49 FRKs from four Rosaceae species; 20 of these sequences were from Chinese white pear. Subsequently, phylogenic relationship, gene structure and micro-collinearity were analysed. Phylogenetic and exon–intron analysis classified these FRKs into 10 subfamilies, and it was aimed to further reveal the variation of the gene structure and the evolutionary relationship of this gene family. Remarkably, gene expression patterns in different tissues or different development stages of the pear fruit suggested functional redundancy for PbFRKs derived from segmental duplication or genome-wide duplication and sub-functionalization for some of them. Additionally, PbFRK11, PbFRK13 and PbFRK16 were found to play important roles in regulating the sugar content in the fruit. Overall, this study provided important insights into the evolution of the FRK gene family in four Rosaceae species, and highlighted its roles in both pear tissue and fruits. Results presented here provide the appropriate candidate of PbFRKs that might contribute to fructose efflux in the pear fruit.

WUSCHEL-related homeobox (WOX) family is one of the largest group of transcription factors (TFs) specifically found in plant kingdom. WOX TFs play an important role in plant development processes and evolutionary novelties. Although the roles of WOXs in Arabidopsis and rice have been well-studied, however, little are known about the relationships among the main clades in the molecular evolution of these genes in Rosaceae. Here, we carried out a genome-wide analysis and identified 14, 10, 10, and 9 of WOX genes from four Rosaceae species (Fragaria vesca, Prunus persica, Prunus mume, and Pyrus bretschneideri, respectively). According to evolutionary analysis, as well as amino acid sequences of their homodomains, these genes were divided into three clades with nine subgroups. Furthermore, due to the conserved structural patterns among these WOX genes, it was proposed that there should exist some highly conserved regions of microsynteny in the four Rosaceae species. Moreover, most of WOX gene pairs were presented with the conserved orientation among syntenic genome regions. In addition, according to substitution models analysis using PMAL software, no significant positive selection was detected, but type I functional divergence was identified among certain amino acids in WOX protein. These results revealed that the relaxed purifying selection might be the main driving force during the evolution of WOX genes in the tested Rosaceae species. Our result will be useful for further precise research on evolution of the WOX genes in family Rosaceae.

The ethylene-insensitive3/ethylene-insensitive3-like (EIN3/EIL) proteins are a type of nuclear-localized protein with DNA-binding activity in plants. Although the EIN3/EIL gene family has been studied in several plant species, little is known about comprehensive study of the EIN3/EIL gene family in Rosaceae. In this study, ten, five, four, and five EIN3/EIL genes were identified in the genomes of pear (Pyrus bretschneideri), mei (Prunus mume), peach (Prunus persica) and strawberry (Fragaria vesca), respectively. Twenty-eight chromosomal segments of EIL/EIN3 gene family were found in four Rosaceae species, and these segments could form seven orthologous or paralogous groups based on interspecies or intraspecies gene colinearity (microsynteny) analysis. Moreover, the highly conserved regions of microsynteny were found in four Rosaceae species. Subsequently it was found that both whole genome duplication and tandem duplication events significantly contributed to the EIL/EIN3 gene family expansion. Gene expression analysis of the EIL/EIN3 genes in the pear revealed subfunctionalization for several PbEIL genes derived from whole genome duplication. It is noteworthy that according to environmental selection pressure analysis, the strong purifying selection should dominate the maintenance of the EIL/EIN3 gene family in four Rosaceae species. These results provided useful information on Rosaceae EIL/EIN3 genes, as well as insights into the evolution of this gene family in four Rosaceae species. Furthermore, high level of microsynteny in the four Rosaceae plants suggested that a large-scale genome duplication event in the EIL/EIN3 gene family was predated to speciation.

Peroxidases (PRXs) are widely existed in various organisms and could be divided into different types according to their structures and functions. Specifically, the Class III Peroxidase, a plant-specific multi-gene family, involves in many physiological processes, such as the metabolism of auxin, the extension and thickening of cell wall, as well as the formation of lignin. By searching the pear genome database, 94 non-redundant PRXs from Pyrus bretschneideri (PbPRXs) were identified. Subsequently, analysis of phylogenetic relationships, gene structures, conserved motifs, and microsynteny was performed. These PbPRXs were unevenly distributed among 17 chromosomes of pear. In addition, 26 segmental duplication events but only one tandem duplication were occurred in these PbPRXs, implying segmental duplication was the main contributor to the expansion of the PbPRX family. By the Ka/Ks analysis, 26 out of 27 duplicated PbPRXs has experienced purifying selection. Twenty motifs were identified in PbPRXs based on the MEME analysis, eleven of which were enriched in pear. A total of 41 expressed genes were identified from ESTs of pear fruit. According to qRT-PCR, the expression trends of five PbPRXs in subgroup C were consistent with the change of lignin content during pear fruit development. So we inferred that the five PbPRXs were candidate genes involved in the lignin synthesis pathway. These results provided useful information for further researches of PRX genes in pear.

Growth-regulating factors (GRFs) are plant-specific transcription factors that have important functions in regulating plant growth and development. Previous studies on GRF family members focused either on a single or a small set of genes. Here, a comparative genomic analysis of the GRF gene family was performed in poplar (a model tree species), Arabidopsis (a model plant for annual herbaceous dicots), grape (one model plant for perennial dicots), rice (a model plant for monocots) and Chinese pear (one of the economical fruit crops). In total, 58 GRF genes were identified, 12 genes in rice (Oryza sativa), 8 genes in grape (Vitis vinifera), 9 genes in Arabidopsis thaliana, 19 genes in poplar (Populus trichocarpa) and 10 genes in Chinese pear (Pyrus bretschneideri). The GRF genes were divided into five subfamilies based on the phylogenetic analysis, which was supported by their structural analysis. Furthermore, microsynteny analysis indicated that highly conserved regions of microsynteny were identified in all of the five species tested. And Ka/Ks analysis revealed that purifying selection play an important role in the maintenance of GRF genes. Our results provide basic information on GRF genes in five plant species and lay the foundation for future research on the functions of these genes.

The Chinese giant salamander iridovirus (CGSIV), belonging to the genus Ranavirus in the family Iridoviridae, is the causative agent of an emerging infectious disease causing high mortality of more than 90% and economic losses in Chinese giant salamanders in China. In this study, a recombinant baculovirus-based vaccine expressing the CGSIV major capsid protein (MCP) was developed and its protective immunity in Chinese giant salamanders was evaluated. The recombinant Autographa californica nucleopolyhedrosis virus (AcNPV), expressing CGSIV MCP, designated as AcNPV-MCP, was generated with the highest titers of 1 × 108 plaque forming units/mL (PFU/mL) and confirmed by Western blot and indirect immunofluorescence (IIF) assays. Western blot analysis revealed that the expressed MCP reacted with mouse anti-MCP monoclonal antibodies at the band of about 53 kDa. The results of IIF indicated that the MCP was expressed in the infected Spodoptera frugiperda 9 (Sf9) cells with the recombinant baculovirus, and the Chinese giant salamander muscle cells also transduced with the AcNPV-MCP. Immunization with the recombinant baculovirus of AcNPV-MCP elicited robust specific humoral immune responses detected by ELISA and neutralization assays and potent cellular immune responses in Chinese giant salamanders. Importantly, the effective immunization conferred highly protective immunity for Chinese giant salamanders against CGSIV challenge and produced a relative percent of survival rate of 84%. Thus, the recombinant baculovirus expressing CGSIV MCP can induce significant immune responses involving both humoral and cell-mediated immunity in Chinese giant salamanders and might represent a potential baculovirus based vaccine candidate for Chinese giant salamanders against CGSIV.