Basic Research Research Articles

Viral genome sequencing methods: benefits and pitfalls of current approaches.

Whole genome sequencing of viruses provides high-resolution molecular insights, enhancing our understanding of viral genome function and phylogeny. Beyond fundamental research, viral sequencing is increasingly vital for pathogen surveillance, epidemiology, and clinical applications. As sequencing methods rapidly evolve, the diversity of viral genomics applications and catalogued genomes continues to expand. Advances in long-read, single molecule, real-time sequencing methodologies present opportunities to sequence contiguous, haplotype resolved viral genomes in a range of research and applied settings. Here we present an overview of nucleic acid sequencing methods and their applications in studying viral genomes. We emphasise the advantages of different viral sequencing approaches, with a particular focus on the benefits of third-generation sequencing technologies in elucidating viral evolution, transmission networks, and pathogenesis.

Transglutaminase 2 serves as a pathogenic hub gene of KRAS mutant colon cancer based on integrated analysis

BACKGROUND Colon cancer is acknowledged as one of the most common malignancies worldwide, ranking third in United States regarding incidence and mortality. Notably, approximately 40% of colon cancer cases harbor oncogenic KRAS mutations, resulting in the continuous activation of epidermal growth factor receptor signaling. AIM To investigate the key pathogenic genes in KRAS mutant colon cancer holds considerable importance. METHODS Weighted gene co-expression network analysis, in combination with additional bioinformatics analysis, were conducted to screen the key factors driving the progression of KRAS mutant colon cancer. Meanwhile, various in vitro experiments were also conducted to explore the biological function of transglutaminase 2 (TGM2). RESULTS Integrated analysis demonstrated that TGM2 acted as an independent prognostic factor for progression-free survival. Immunohistochemical analysis on tissue microarrays revealed that TGM2 was associated with an elevated probability of perineural invasion in patients with KRAS mutant colon cancer. Additionally, biological roles of the key gene TGM2 was also assessed, suggesting that the downregulation of TGM2 attenuated the proliferation, invasion, and migration of the KRAS mutant colon cancer cell line. CONCLUSION This study underscores the potential significance of TGM2 in the progression of KRAS mutant colon cancer. This insight not only offers a theoretical foundation for therapeutic approaches but also highlights the need for additional clinical trials and fundamental research to support our preliminary findings.

Revolutionizing getaways: automation and artificial intelligence’s transformative journey in tourism and hospitality

PurposeThis theme issue aims to explore the depth and breadth of automation and artificial intelligence’s (AI’s) impact on the hospitality and tourism industry.Design/methodology/approachThe thematic examination of the articles presented in this theme issue highlights the central results concerning the strategic inquiry, especially regarding their addition to knowledge, which is vital for fostering idea creation and theoretical research beneficial to various stakeholders in the tourism and hospitality sector. Given the swift evolution of these technologies, grasping their utilization, advantages and obstacles is essential for industry experts, decision-makers and scholars.FindingsThis theme issue encapsulates the transformative impact of automation and AI in the tourism and hospitality industry, highlighting the juxtaposition of enhanced operational efficiency against employment security concerns. It emphasizes the need for ethical governance to address AI’s ethical dilemmas and security vulnerabilities. The exploration of consumer attitudes towards AI, particularly in service robots and facial emotion recognition technologies, is deemed crucial for leveraging AI’s full potential in service delivery. Furthermore, AI’s entry into gastronomy prompts a reevaluation of traditional culinary practices, advocating for a balance between technological innovation and the preservation of cultural heritage.Originality/valueThis theme issue stands out for its focused exploration of the transformative effects of automation and AI within the hospitality and tourism industry. Unlike broader discussions on technology in business, it delves into specific AI-driven innovations, operational changes and the resultant shifts in consumer behavior and industry standards. By curating a collection of empirical research, theoretical analyses and content analyses, this issue is providing important insights into how automation and AI are reshaping service delivery, management practices and strategic decision-making in an industry characterized by its intense customer focus and reliance on human-to-human interaction.

Single-cell sequencing advances in research on mesenchymal stem/stromal cells.

Mesenchymal stem/stromal cells (MSCs), originating from the mesoderm, represent a multifunctional stem cell population capable of differentiating into diverse cell types and exhibiting a wide range of biological functions. Despite more than half a century of research, MSCs continue to be among the most extensively studied cell types in clinical research projects globally. However, their significant heterogeneity and phenotypic instability have significantly hindered their exploration and application. Single-cell sequencing technology emerges as a powerful tool to address these challenges, offering precise dissection of complex cellular samples. It uncovers the genetic structure and gene expression status of individual contained cells on a massive scale and reveals the heterogeneity among these cells. It links the molecular characteristics of MSCs with their clinical applications, contributing to the advancement of regenerative medicine. With the development and cost reduction of single-cell analysis techniques, sequencing technology is now widely applied in fundamental research and clinical trials. This study aimed to review the application of single-cell sequencing in MSC research and assess its prospects.

Reporting Conflicts of Interest and Funding in Health Care Guidelines: The RIGHT-COI&F Checklist.

Conflicts of interest (COIs) of contributors to a guideline project and the funding of that project can influence the development of the guideline. Comprehensive reporting of information on COIs and funding is essential for the transparency and credibility of guidelines. To develop an extension of the Reporting Items for practice Guidelines in HealThcare (RIGHT) statement for the reporting of COIs and funding in policy documents of guideline organizations and in guidelines: the RIGHT-COI&F checklist. The recommendations of the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) network were followed. The process consisted of registration of the project and setting up working groups, generation of the initial list of items, achieving consensus on the items, and formulating and testing the final checklist. International collaboration. 44 experts. Consensus on checklist items. The checklist contains 27 items: 18 about the COIs of contributors and 9 about the funding of the guideline project. Of the 27 items, 16 are labeled as policy related because they address the reporting of COI and funding policies that apply across an organization's guideline projects. These items should be described ideally in the organization's policy documents, otherwise in the specific guideline. The remaining 11 items are labeled as implementation related and they address the reporting of COIs and funding of the specific guideline. The RIGHT-COI&F checklist requires testing in real-life use. The RIGHT-COI&F checklist can be used to guide the reporting of COIs and funding in guideline development and to assess the completeness of reporting in published guidelines and policy documents. The Fundamental Research Funds for the Central Universities of China.

Research on consumers' purchase intention of cultural and creative products-Metaphor design based on traditional cultural symbols.

Chinese traditional cultural symbols possess great aesthetic and cultural value, and are widely utilized in product design. In this study, we explore the relationship between metaphor design based on traditional cultural symbols, customer experience and cultural identity, and further estimate how these three variables stimulate consumers' perceived value to generate consumers' purchase intention. Based on existing traditional cultural literature and Stimulus-organism-response theory (SOR), we proposed a theoretical research model to characterize the relationship among metaphor design based on traditional cultural symbols, customer experience, cultural identity, perceived value and consumers' purchase intention. A research survey was conducted and 262 questionnaires were collected in total with 241 valid. We used Smart PLS graph version 3.0 for data analysis. Results indicate that the cognition of metaphor design based on traditional cultural symbols and customer experience has a direct and significant impact on the emotional value thereby, eliciting consumers' purchase intention, metaphor design based on traditional cultural symbols is directly and indirectly (i.e., through customer experience or perceived value) positively associated with consumers' purchase intention, also customer experience is directly and indirectly (i.e., through perceived value) associated with consumer purchase intention, cultural identity mediates the indirect effect of customer experience and perceived value on purchase intention, the moderating role of cultural identity between customer experience and perceived value is not significant. Our findings help to expand the existing literature on consumer purchase intentions by rationally using traditional cultural symbols in the product metaphor design.

The influence of rural tourism landscape perception on tourists’ revisit intentions—a case study in Nangou village, China

Rural tourism development has an important impact on optimizing the rural industrial structure and stimulating local economic growth. China’s Rural Revitalization Strategy has promoted the development of rural tourism nationwide and emphasized Chinese characteristics in the process of local development. Based on the theoretical analysis of landscape perception, this article uses the external Landscape Perception→Satisfaction→Revisit Intention influence path as a theoretical research framework to construct a structural equation model to analyze the willingness of tourists to revisit rural tourism destinations. We selected Nangou Village, Yan’an City, Shaanxi Province, as a key model village for rural revitalization, and conducted an empirical analysis. The empirical analysis results show that landscape perception has a significant positive impact on satisfaction and revisit intention. Tourist satisfaction has a significant positive impact on revisit intention and plays an intermediary role between landscape perception and revisit intention. The five dimensions of natural ecology, historical culture, leisure recreation, research experience, and integral route under landscape perception are all significantly positively correlated with revisit intention, with historical culture and integral route having the greatest impact on landscape perception. The survey about Nangou Village verifies the relationship between landscape perception, satisfaction, and tourists’ revisit intention. Based on the objective data analysis results, this study puts forward suggestions for optimizing Nangou Village’s tourism landscapes and improving tourists’ willingness to revisit from three aspects: deeply excavating rural historical and cultural resources, shaping the national red culture brand, and creating rural tourism boutique routes. It is hoped that the quantitative research method of landscape perception theory in Nangou Village can also provide a reference and inspiration for similar rural tourism planning.

Skyline query under multidimensional incomplete data based on classification tree

A method for skyline query of multidimensional incomplete data based on a classification tree has been proposed to address the problem of a large amount of useless data in existing skyline queries with multidimensional incomplete data, which leads to low query efficiency and algorithm performance. This method consists of two main parts. The first part is the proposed incomplete data weighted classification tree algorithm. In the first part, an incomplete data weighted classification tree is proposed, and the incomplete data set is classified using this tree. The data classified in the first part serves as the basis for the second step of the query. The second part proposes a skyline query algorithm for multidimensional incomplete data. The concept of optimal virtual points has been recently introduced, effectively reducing the number of comparisons of a large amount of data, thereby improving the query efficiency for incomplete data. Theoretical research and experimental analysis have shown that the proposed method can perform skyline queries for multidimensional incomplete data well, with high query efficiency and accuracy of the algorithm.

Does internal control improve enterprise environmental, social, and governance information disclosure? Evidence from China

AbstractEnvironmental, social, and governance (ESG) is a relatively new concept that emphasizes how to contribute to creating sustainable businesses. However, research on factors that influence ESG development is insufficient. This study explores how internal control influence enterprise ESG information disclosure, using 2009–2021 data from China's A‐share listed companies. The findings show a substantial positive correlation between internal control quality and corporate ESG information disclosure. Particularly, the internal control quality significantly affects corporate governance information disclosure. Moreover, the connection between internal control quality and enterprise ESG information disclosure is significantly and positively moderated by media attention. Specifically, negative media evaluations have significant impacts on enterprises. The main findings remain valid even after conducting multiple robustness tests, such as the lag test, propensity score matching, instrumental variable method, and alternative measurements for the key variables. This study widens the theoretical research frontier of internal and external supervision mechanisms.

For the greater good: modern China’s struggle on housing shortage

The examination of housing shortages in China presents a fascinating subject that is rarely directly addressed. This topic not only captures our interest due to the irony in a communist country but also in light of the profound transformation of Chinese society, evolving from an agrarian civilization to a modern industrialized state. The objective of this essay is to establish a comprehensive framework that encompasses economic, social, and architectural narratives as an integrated whole. This essay delves into the historical trajectory of housing shortages in modern China, tracing the evolution of this issue within Chinese society since the founding of the communist regime in 1949. Given China’s unique industrial and residential policy framework, housing provision is intrinsically linked to state-owned factories and residential certification, commonly referred to as hukou. As the political and economic foundations have shifted over time, so too has the root cause of housing shortages. In addition to general historical and theoretical research, we have undertaken an in-depth examination of Lanxi City, one of the industrial clusters established in China. The case study of Lanxi City involves a series of visits and interviews conducted within local factories and communities. Our analysis identifies two distinct phases in this evolution: the “fundamentalist communist era” and the transitional period toward a market economy. Each of these eras can be further subdivided into four distinct phases, providing a more nuanced perspective. Our findings reveal that various housing distribution mechanisms have contributed to the issue of housing shortages. During the first era, housing shortages were primarily a result of hukou restrictions, industrial disparities, sluggish construction processes, and corporate profit considerations. In the latter phase, spanning the 1980s and 1990s, housing shortages were exacerbated by escalating costs and a slow rate of housing unit replenishment. As the new millennium unfolded, real estate bubbles compounded the housing crisis, with older neighborhoods ill-suited for modern living. Our interviews and visits complemented our literature research, offering valuable insights into the systemic exploitation of specific groups in pursuit of broader goals, hence the title. This paper underscores the housing shortage in China as a consequence of economic disparities between urban and rural regions, as well as between the prosperous East coast and the underdeveloped West hinterland.

Organosulfur Cathodes in Lithium Metal Batteries: Bridging the Gap between Fundamentals and Practical Applications

AbstractHigh‐specific energy sulfur‐based cathodes have attracted considerable interest in lithium batteries. Organosulfur cathodes offer inherent advantages of high element abundance and an extended cycling life, aligning with the evolving requirements of future energy storage devices. Over the past decade, research efforts have been devoted to optimizing electrochemical performance through the rich and tunable molecular structures of organosulfur compounds. To further advance the fundamental research and practical application of lithium‐organosulfur batteries, a systematical analysis of the correlation between the molecular structures and electrochemical mechanisms of organosulfur cathodes is imperative. This involves deriving the key parameters at the cell level and investigating the feasibility. In this review, the thermodynamics, reaction processes, and electrochemical kinetics of organosulfur cathodes, grounded in fundamental theories of electrochemistry and materials science are discussed. Expanding the insights, comparisons among elemental sulfur, organosulfur, and n‐type organic cathodes (e.g., carbonyl cathodes) are drawn. The gap between fundamentals and practical applications targeting 500 Wh kg−1 lithium organosulfur batteries is highlighted through energy density calculations and identification of key factors affecting pouch cells. Finally, potential strategies and prospects for the overall design of advanced lithium‐organosulfur batteries are proposed, considering both theoretical foundations and practical implementations.

Quantum sensing with tunable superconducting qubits: optimization and speed-up

Abstract Sensing and metrology are crucial in both fundamental science and practical applications. They meet the constant demand for precise data, enabling more dependable assessments of theoretical models’ validity. Sensors, now a common feature in many fields, play a vital role in applications like gravity imaging, geology, navigation, security, timekeeping, spectroscopy, chemistry, magnetometry, healthcare, and medicine. The advancements in quantum technologies have sparked interest in employing quantum systems as sensors, offering enhanced capabilities and new possibilities. This article describes the optimization of the quantum-enhanced sensing
of magnetic fluxes with a Kitaev phase estimation algorithm based on frequency tunable transmon qubits. It provides the optimal flux biasing point for sensors with different qubit transition frequencies and gives an estimation of decoherence rates and achievable sensitivity. The use of 2- and 3-qubit entangled states are compared in simulation with the single-qubit case. The flux sensing accuracy reaches 10-8·Φ0 and scales inversely with time, which proves the speed-up of sensing with high ultimate accuracy.

Customs services and ways to improve their quality in the context of digitalisation

This article is devoted to problems of the process of rendering services in the field of customs during digitalisation of the economy. The observed mechanism of rendering state customs services, as well as improving their quality, naturally affect the entire service sector and the development of the country’s economy as a whole. The main purposes of the article are to analyse the mechanism of rendering services in the field of customs and to search for effective methods of assessing their quality. The relevance of the article is determined by the need to improve the operations performed to be able to manage the quality of provided customs services. The main objective of this article is to propose possible ways to reduce time costs without losing the quality of customs control in the process of providing the services. The article used both theoretical (analysis of the current legislation) and empirical research methods (giving practical examples of improving the efficiency of customs operations and the quality of customs services). The results of the study are the following: development of sequential operations performed by customs authorities in the process of rendering services in the field of customs; proposal of possible criteria for assessing their quality; formulation of options for managing this quality.

Uncovering the molecular mechanism of Mume Fructus in treatment of Sjögren's syndrome.

Modern medicine has no cure for the xerostomia caused by the early onset of Sjögren's syndrome. Mume Fructus is a common Chinese herbal medicine used to relieve xerostomia. However, the molecular mechanisms of the effects of Mume Fructus are unknown. In this study, network pharmacology and molecular docking were used to investigate the mechanisms of action of Mume Fructus on Sjögren's syndrome. The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database was used to identify the active components and targets of Mume Fructus, and the UniProt database was used to identify the genes encoding these targets. SS-related targets were also identified from the GeneCards and OMIM databases. By finding the intersection of the targets of the compounds and the targets of Sjögren's syndrome, the predicted targets of Mume Fructus in the treatment of Sjögren's syndrome were obtained. Further investigation of the active compounds and their targets was carried out by constructing a network of "medicine-candidate compound-target-disease" using Cytoscape 3.7.2, the Protein-Protein Interaction network using the STRING database and Cytoscape 3.7.2, and key targets were identified by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis on R software. Finally, molecular docking was used to verify the affinity of the candidate compounds to the key targets. Quercetin, beta-sitosterol, and kaempferol in Mume Fructus interact with AKT1, IL-6, IL-1B, JUN, CASP3, and MAPK8. These results suggest that Mume Fructus exerts its therapeutic effects on the peripheral gland injury of Sjögren's syndrome and its secondary cardiovascular disease and tumorigenesis through anti-inflammatory, anti-oxidant, and anti-tumor pathways. With network pharmacology, this study systematically identified the main active components, targets, and specific mechanisms of the therapeutic effects of Mume Fructus on Sjögren's syndrome, providing both a theoretical basis and research direction for further investigations on Mume Fructus.

Stacking-dependent interlayer magnetic interactions in CrSe2.

Recently, CrSe2, a new ferromagnetic van der Waals two-dimensional material, was discovered to be highly stable under ambient conditions, making it an attractive candidate for fundamental research and potential device applications. Here, we study the interlayer interactions of bilayer CrSe2using first-principles calculations. We demonstrate that the interlayer interaction depends on the stacking structure. The AA and AB stackings exhibit antiferromagnetic (AFM) interlayer interactions, while the AC stacking exhibits ferromagnetic (FM) interlayer interaction. Furthermore, the interlayer interaction can be further tuned by tensile strain and charge doping. Specifically, under large tensile strain, most stacking structures exhibit FM interlayer interactions. Conversely, under heavy electron doping, all stacking structures exhibit AFM interlayer interactions. These findings are useful for designing spintronic devices based on CrSe2.

Assessing the impact of Medical Education's Innovation & Entrepreneurship Program in China

ObjectiveA growing number of clinical undergraduates are chosen to enter institutions for higher education biotechnology and industry workforce, though most need more laboratory experience training and business practice. Innovation and Entrepreneurship Program (I&E Program) can benefit from biological experiment and commercialization training largely absent from standard clinical medical educational curricula. Our study investigates the impact and status of the I&E Program in enhancing medical students’ research and entrepreneurial abilities and provides recommendations for improving this program.MethodsA cross-sectional study was applied by delivering a questionnaire to survey medical students from Central South University who participated in the I&E Program. The questionnaire consisted of three parts: basic information, the impact of the I&E Program on medical students’ research and entrepreneurial abilities, and attitudes and recommendations regarding the I&E Program.ResultsMany students participating in the I&E Program have received competition awards and improved their academic experience, article writing, and application patents. Their research-related abilities have been enhanced, including in-lab techniques, theoretical research skills, data analysis knowledge, clinical research skills, experimental research skills, entrepreneurship, data analysis ability, teamwork, and communication. While 73.93% of students express satisfaction with the I&E Program, there are still several areas of improvement, including more robust practical components, increased support, and enhanced teamwork.ConclusionThe scale of the I&E Program is rapidly expanding to address scientific research or business skills needed by college students in the new era. However, more programs still need to be discontinued during their further study. The I&E Program significantly enhances research abilities and fosters confidence in their study. This analysis emphasizes the importance of research-oriented and interdisciplinary education for students’ holistic development in medical schools compared with formal medical education.

Knowledge mapping of graph neural networks for drug discovery: a bibliometric and visualized analysis

IntroductionIn recent years, graph neural network has been extensively applied to drug discovery research. Although researchers have made significant progress in this field, there is less research on bibliometrics. The purpose of this study is to conduct a comprehensive bibliometric analysis of graph neural network applications in drug discovery in order to identify current research hotspots and trends, as well as serve as a reference for future research.MethodsPublications from 2017 to 2023 about the application of graph neural network in drug discovery were collected from the Web of Science Core Collection. Bibliometrix, VOSviewer, and Citespace were mainly used for bibliometric studies.Results and DiscussionIn this paper, a total of 652 papers from 48 countries/regions were included. Research interest in this field is continuously increasing. China and the United States have a significant advantage in terms of funding, the number of publications, and collaborations with other institutions and countries. Although some cooperation networks have been formed in this field, extensive worldwide cooperation still needs to be strengthened. The results of the keyword analysis clarified that graph neural network has primarily been applied to drug-target interaction, drug repurposing, and drug-drug interaction, while graph convolutional neural network and its related optimization methods are currently the core algorithms in this field. Data availability and ethical supervision, balancing computing resources, and developing novel graph neural network models with better interpretability are the key technical issues currently faced. This paper analyzes the current state, hot spots, and trends of graph neural network applications in drug discovery through bibliometric approaches, as well as the current issues and challenges in this field. These findings provide researchers with valuable insights on the current status and future directions of this field.

Christopher Tam: Brief history and accomplishments

This introduction provides a brief personal background and highlights the scientific accomplishments of Professor Christopher Tam. He has maintained extremely high standards of research and an enviable track record for productivity, spanning more than five decades. The depth and breadth of his technical output are truly breathtaking, and he has inspired scores of researchers and graduate students. When the first author was an Acoustics Engineer at Lockheed, Georgia, he started collaborating with Chris in the early 1990s. There were several joint projects when the author moved to Boeing, which encompassed both fundamental research and applications. The second author has an even longer association with Chris, initially as a PhD advisee in the late 1980s and then as a co-researcher. In this special volume we pay tribute to Chris’s many achievements, an endeavor that provides us with great satisfaction and which is long overdue.

Incorporation of adaptive compression into a GPU parallel computing framework for analyzing large-scale vessel trajectories

Automatic Identification System (AIS) offers a wealth of vessel navigation data, which underpins research in maritime data mining, situational awareness, and knowledge discovery within the realm of intelligent transportation systems. The flourishing marine industry has prompted AIS satellites and base stations to generate massive amounts of vessel trajectory data, escalating both data storage and calculation costs. The conventional Douglas-Peucker (DP) algorithm used for trajectory compression sets a uniform threshold, which hampers effective compression. Additionally, compressing and accelerating the computation of large datasets poses a significant challenge in real-world applications. To address these limitations, this paper aims to develop a new Graphics Processing Unit (GPU) parallel computing and compression framework that enables the acceleration of the optimal threshold calculation for each trajectory automatically in maritime big data mining. It achieves this by incorporating a new Adaptive DP with Speed and Course (ADPSC) algorithm, which utilizes the dynamic navigation characteristics of different vessels. It can effectively solve the associated computational time cost concern when using the ADPSC algorithm to compress vast trajectory datasets in the real world. Additionally, this paper proposes a novel evaluation metric for assessing compression efficacy based on the Dynamic Time Warping (DTW) method. Comprehensive experiments encompass vessel trajectory datasets from three representative research areas: Tianjin Port, Chengshan Jiao Promontory, and Caofeidian Port. The experimental results demonstrate that 1) the newly developed ADPSC method outperforms in terms of compression, and 2) the designed GPU parallel computing framework can significantly shorten the compression time for extensive datasets. The GPU-accelerated compression methodology not only minimizes storage and transmission costs for data from both manned and unmanned vessels but also enhances data processing speed, supporting real-time decision-making. From a theoretical perspective, it provides the key to the puzzle of realizing the real-time anti-collision of manned and unmanned ships, particularly in complex waters. It hence makes significant contributions to maritime safety in the autonomous shipping era.

Empowering pro-environmental behavior in tourists through digital media: the influence of eco-guilt and empathy with nature

In the digital economy era, leveraging digital media to foster tourists’ pro-environmental behavioral intention (TPEBI) has become crucial in the field of sustainable tourism. While existing studies have mainly focused on the driving mechanism of TPEBI within physical tourism contexts, the correlation between digital media information sharing and TPEBI remains unclear. Our study employs the cognitive-affective-conative framework to construct a theoretical model, considering eco-guilt and empathy with nature as mediating variables. It aims to explore the influencing mechanism of destination environmental information sharing through digital media on TPEBI from a presence perspective. Thereby, two scenario experiments were designed: Study 1 examined the impact of different formats of destination environmental threat information presentation on digital media on the sense of presence, while Study 2 explored the influencing mechanism of presence on TPEBI based on the conclusions of Study 1. Results indicate that (1) vivid and visible presentation formats of destination environmental threat information on digital media enhance individuals’ sense of presence; (2) sense of presence positively influences TPEBI; and (3) eco-guilt and empathy with nature mediate between presence and TPEBI. These findings not only contribute to theoretical and empirical research on digital media information sharing in sustainable tourism but also offer guidance for governments and tourism destinations to effectively stimulate TPEBI through digital media, achieve the sustainable development of destinations.