Network Analysis Research Articles

Research on urban agglomeration spatial network structure in the middle reaches of the Yangtze River based on real-time traffic accessibility scenario analysis

ABSTRACT Investigating the spatial network structure of urban agglomerations based on traffic accessibility has an important practical significance in accelerating the process of regional integration. Taking urban agglomeration in the middle reaches of the Yangtze River (UAMRYR) as the case study, this study aims to examine the characteristics associated with the spatial network structure based on traffic accessibility and its changes under scenarios of different traffic accessibilities by adopting real-time traffic data, modified gravity model, and social network analysis (SNA). The main conclusions are as follows. Wuhan, Changsha, and Nanchang are the central cities in the spatial network; the spatial network structure of UAMRYR is imbalanced and in the agglomeration stage of regional economic development. With the development of traffic accessibility, resources first gather in the individual center cities and then spread to other cities, and the network tends toward equilibrium.

Typology of Terrorist Profiling Using Centrality Metrics: Hinge Figures, Influential Operatives and Trusted Assets

ABSTRACT The increase in terrorist activity worldwide has prompted the development of research tools and methodologies to study the phenomenon of terrorism. Among them, social network analysis (SNA) has found its way into the security studies discipline, which, despite its still timid presence, has increasingly been proven to be a useful tool for detecting underlying structures and key actors. This article seeks to contribute to the body of knowledge on the uses of SNA in the study of covert networks by testing the usefulness of metrics such as betweenness, closeness, and eigenvector centrality in identifying terrorist roles and functions in the cells that were behind the major terrorist attacks orchestrated by the Islamic State’s external operations apparatus. The study ends with the proposal of a new typology of terrorist profiling according to the results obtained from centrality measures: hinge figures, influential operatives and trusted assets.

비대면 온라인 수업에서의 학습 참여도와 학생 만족도의 관계에 관한 실증적 연구

Objectives The purpose of this study is to empirically analyze the relationship between learning engagement and student satisfaction in a contactless online class environment. Methods The study employed regression analysis and text-based network analysis as research methods. Regression analysis was used to quantitatively measure the direct impact of learning engagement factors on stu-dent satisfaction. Text-based network analysis was used to explore the indirect effects on satisfaction by identify-ing information flow and centrality within the learning community. Results The analysis revealed a positive correlation between course completion rates and the frequency of the keyword ‘hard work’ in lecture comments, as well as the number of completed quiz submissions. However, the number of lectures and viewing time did not have a significant impact. The network analysis indicated that key-words such as ‘fun,’ ‘informative,’ ‘quiz,’ and ‘completion’ were central, suggesting that learner interaction is a crucial factor in satisfaction. Conclusions In conclusion, this study suggests that promoting interaction among learners and encouraging their active participation in course design can improve the efficiency and satisfaction of virtual classes. The empirical data provided here is expected to contribute to the improvement of educational technology.

V4RIN: visual analysis of regional industry network with domain knowledge.

The regional industry network (RIN) is a type of financial network derived from industry networks that possess the capability to describe the connections between specific industries within a particular region. For most investors and financial analysts lacking extensive experience, the decision-support information provided by industry networks may be too vague. Conversely, RINs express more detailed and specific industry connections both within and outside the region. As RIN analysis is domain-specific and current financial network analysis tools are designed for generalized analytical tasks and cannot be directly applied to RINs, new visual analysis approaches are needed to enhance information exploration efficiency. In this study, we collaborated with domain experts and proposed V4RIN, an interactive visualization analysis system that integrates predefined domain knowledge and data processing methods to support users in uploading custom data. Through multiple views in the system panel, users can comprehensively explore the structure, geographical distribution, and spatiotemporal variations of the RIN. Two case studies were conducted and a set of expert interviews with five domain experts to validate the usability and reliability of our system.

Assessing Residency and Site Fidelity in Bottlenose Dolphins: A Literature Review and Bibliometric Analysis

Residency and site fidelity are important parameters in population ecology for many species as they indicate the temporal and spatial use for individuals. Although both terms are clearly different, they are used interchangeably due to lack of clarity in their definitions and the ways to assess them, especially in bottlenose dolphins (Tursiops spp.). Individuals with well-defined patterns of residency and site fidelity may be more vulnerable to anthropogenic disturbances; thus, the study of these parameters may help to better assess such impacts. However, interspecific differences and logistical restrictions for the study of dolphins have prevented consensus. We set out to investigate the factors that have influenced measurements of residency and site fidelity in bottlenose and a set of other dolphin species through a retrospective (~30 y: 1990 to 2019) literature review. We found 117 scientific papers with a two-fold increasing trend approximately every 15 years, with 50% published in only four journals. Most of the studies were developed in the United States, followed by Australia and Europe, likely due to strict policies for marine mammal conservation. Author collaboration network analysis showed highly atomized national groups in which North American organizations formed the biggest cluster, followed by Australia, Africa, and Europe. However, large worldwide gaps still exist, possibly because of the heterogeneity in marine mammal sampling efforts and limited information availability in the North Pacific, Central and South America, Africa, Asia, and the Indian Ocean. We found 30 different classification methods in which 12 were based on defined categories. We provide conceptual aid to distinguish between the use of both terms, as well as guidance to tackle the challenge of defining patterns of temporal use due to the variability of thresholds for classifying individuals. A paradigm shift is needed to create comprehensive, standardized, and generalized assessments of residency and site fidelity, which can be compared based on their performance across different populations of bottlenose dolphins around the world.

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.

Global scholarly output on orthodontic temporary anchorage devices (TADs): A silver jublee scientometric analysis.

This study aimed to analyze the global scholarly production of articles related to temporary anchorage devices (TADs) from 1998-2023 in peer-reviewed dental journals indexed in the Web of Science. Adatabase of TADs-related articles was created via aWeb of Sciences structured search. The bibliometric characteristics of the studies, including the number of citations, publication year, journal title, journal impact factor (IF), authorship, contributing institutions and countries, thematic field, and study design, were extracted. Keyword co-occurrence network analyses and the correlation between the number of citations and the article age, journal IF, and journal quartile of each article were performed. The top50 cited articles were published from 1999-2016, and the total number of citations ranged from 82-602, with 160.36 citations/paper on average. Most of the articles originated from Japan (n = 12), with the most remarkable contributions from Nihon and Okayama Universities, Japan (n = 5, each). The American Journal of Orthodontics and Dentofacial Orthopedics had the most cited articles, with 196.57 citations/paper on average. Asignificant positive correlation occurred between the number of citations and publication age (rho = 0.392, P = 0.005). Our scientometric analysis reported the characteristics of TADs-related articles published over 25years. Most highly-cited articles were published between 2005 and 2008. The positive correlation between articles' publication date and the number of citations might impact the top50 within the next 5-10years.

Genome-wide association study and genomic selection of spike-related traits in bread wheat.

Identification of 337 stable MTAs for wheat spike-related traits improved model accuracy, and favorable alleles of MTA259 and MTA64 increased grain weight and yield per plant. Wheat (Triticum aestivum L.) is one of the three primary global, staple crops. Improving spike-related traits in wheat is crucial for optimizing spike and plant morphology, ultimately leading to increased grain yield. Here, we performed a genome-wide association study using a dataset of 24,889 high-quality unique single-nucleotide polymorphisms (SNPs) and phenotypic data from 314 wheat accessions across eight diverse environments. In total, 337 stable and significant marker-trait associations (MTAs) related to spike-related traits were identified. MTA259 and MTA64 were consistently detected in seven and six environments, respectively. The presence of favorable alleles associated with MTA259 and MTA64 significantly reduced wheat spike exsertion length and spike length, while enhancing thousand kernel weight and yield per plant. Combined gene expression and network analyses identified TraesCS6D03G0692300 and TraesCS6D03G0692700 as candidate genes for MTA259 and TraesCS2D03G0111700 and TraesCS2D03G0112500 for MTA64. The identified MTAs significantly improved the prediction accuracy of each model compared with using all the SNPs, and the random forest model was optimal for genome selection. Additionally, the eight stable and major MTAs, including MTA259, MTA64, MTA66, MTA94, MTA110, MTA165, MTA180, and MTA164, were converted into cost-effective and efficient detection markers. This study provided valuable genetic resources and reliable molecular markers for wheat breeding programs.

대학 강의평가 서술형 문항의 감정분석 및 의미연결망 분석

Objectives The purpose of this study was to derive directions and implications for quality of education through sentiment analysis and semantic network analysis of university descriptive course evaluations. Methods The analysis data consisted of 243,900 descriptive lecture evaluations from the first semester of 2020 to the first semester of 2023 at University A. Emotion words were classified in the order of positive, negative, and neutral, and the frequency and ratio of descriptive lecture evaluation contents by year, subject, and college were calculated. N-gram and clustering were analyzed using Textome, and network centrality between keywords was analyzed and visualized using Ucinet 6. Results First, in the sentiment analysis trend for descriptive lecture evaluation questions by year, course com-pleted, and university, positive opinions were found to be dominant. Second, as a result of the keyword frequency and N-gram analysis of the lecture evaluation contents, the frequency of ‘class’ and ‘thank you’ was high in pos-itive evaluations, and the frequency of ‘class’, ‘assignment’, and ‘unsatisfactory’ was high in negative descriptive course evaluations. In addition, ‘class’ was expanded around the keywords ‘content’, ‘progress’, ‘time’, and ‘regrettable’. Third, the results of semantic network analysis between keywords in the lecture evaluation contents showed that in the positive type, ‘gratitude’, ‘class’, ‘hard work’, ‘explanation’, ‘student’, ‘kindness’, ‘help’, ‘understanding’, ‘assignment’, ‘time’ were the most important and connected keywords. In the negative course evaluation, keywords including ‘class’, ‘lecture’, ‘professor’, ‘assignment’, ‘disappointing’, ‘difficult’, ‘anxiety of test’ were analyzed as the most connected. Conclusions This study showed the possibility of suggesting directions for education improvement through de-scriptive lecture evaluation using sentiment analysis and semantic network analysis.

Fear of monkeypox and intention to vaccinate against monkeypox: a network analysis

Fear of monkeypox and intention to vaccinate against monkeypox: a network analysis

Unveiling the influence of global innovation networks on corporate innovation: evidence from the international semiconductor industry

In this study, we investigate the influence of global innovation networks (GINs) on the innovation output of semiconductor firms. Utilizing negative binomial regression and network analysis, we assess how network positions, specifically degree, betweenness, and closeness centrality, affect firms’ innovation performance, revealing significant positive impacts. Moreover, our results identify a positive U-shaped relationship between structural holes in GINs and innovation performance, suggesting that while moderate network engagement aids innovation, too much can be detrimental. This research provides key insights into optimizing GIN participation for better innovation results in the competitive semiconductor sector.

Quantitative analysis of social influence and digital piracy contagion with differential equations on networks

Illegal file sharing of copyrighted contents through popular file sharing networks poses an enormous threat to providers of digital contents, such as, games, softwares, music and movies. Though empirical studies of network effects on piracy is a well-studied domain, the dynamics of peer effect in the context of evolving social contagion has not been enough explored using dynamical models. In this research, we methodically study the trends of online piracy with a continuous ODE approach and differential equations on graphs to have a clear comparative view. We first formulate a compartmental model to study bifurcations and thresholds mathematically. We later move on with a network-based analysis to illustrate the proliferation of online piracy dynamics with an epidemiological approach over a social network. We figure out a solution for this online piracy problem by developing awareness among individuals and introducing media campaigns, which could be a valuable factor in eradicating and controlling online piracy. Next, using degree-block approximation, network analysis has been performed to investigate the phenomena from a heterogeneous approach and to derive the threshold condition for the persistence of piracy in the population in a steady state. Considering the dual control of positive peer influence and media-driven awareness, we examine the system through realistic parameter selection to better understand the complexity of the dynamics and suggest policy implications.

CYTOR-NFAT1 feedback loop regulates epithelial-mesenchymal transition of retinal pigment epithelial cells.

Epithelial mesenchymal transition (EMT) occurring in retinal pigment epithelial cells (RPE) is a crucial mechanism that contributes to the development of age-related macular degeneration (AMD), a pivotal factor leading topermanent vision impairment. Long non-coding RNAs (lncRNAs) have emerged as critical regulators orchestrating EMT in RPE cells. In this study, we explored the function of the lncRNA CYTOR (cytoskeleton regulator RNA) in EMT of RPE cells and its underlying mechanisms. Through weighted correlation network analysis, we identified CYTOR as an EMT-related lncRNA associated with AMD. Experimental validation revealed that CYTOR orchestrates TGF-β1-induced EMT, as well as proliferation and migration of ARPE-19 cells. Further investigation demonstrated the involvement of CYTOR in regulating the WNT5A/NFAT1 pathway and NFAT1 intranuclear translocation in the ARPE-19 cell EMT model. Mechanistically, CHIP, EMSA and dual luciferase reporter assays confirmed NFAT1's direct binding to CYTOR's promoter, promoting transcription. Reciprocally, CYTOR overexpression promoted NFAT1 expression, while NFAT1 overexpression increased CYTOR transcription. These findings highlight a mutual promotion between CYTOR and NFAT1, forming a positive feedback loop that triggers the EMT phenotype in ARPE-19 cells. These discoveries provide valuable insights into the molecular mechanisms of EMT and its association with AMD, offering potential avenues for targeted therapies in EMT-related conditions, including AMD.

Anti-chitinase-3-like 1 antibody attenuated atopic dermatitis-like skin inflammation through inhibition of STAT3-dependent CXCL8 expression.

Chitinase-3-like 1 (CHI3L1) causes skin inflammation in the progression of atopic dermatitis. We investigated if anti-CHI3L1 antibody could prevent the development of atopic dermatitis and its mechanisms of action. The effect of CHI3L1 antibody on phthalic anhydride-induced atopic dermatitis animal model and in vitro reconstructed human skin (RHS) model were investigated. Expression and release of atopic dermatitis-related cytokines were determined using an enzyme-linked immunosorbent assay, and RT-qPCR, STAT3 and CXCL8 signalling were measured by western blotting. Anti-CHI3L1 antibody suppressed phthalic anhydride-induced epidermal thickening, clinical score, IgE level and infiltration of inflammatory cells, and reduced phthalic anhydride-induced inflammatory cytokines concentration. In addition, CHI3L1 antibody treatment inhibited the expression of STAT3 activity in phthalic anhydride-treated skin. It was also confirmed that CHI3L1 antibody treatment alleviated atopic dermatitis-related inflammation in the RHS model. The inhibitory effects of CHI3L1 antibody was similar or more effective compared with that of the IL-4 antibody. We further found that CHI3L1 is associated with CXCL8 by protein-association network analysis. siRNA of CHI3L1 blocked the mRNA levels of CHI3L1, IL-1β, IL-4, CXCL8, TSLP, and the expression of CHI3L1 and p-STAT, and the level of CXCL8, whereas recombinant level of CXCL8 was elevated. Moreover, siRNA of STAT3 reduced the mRNA level of these cytokines. CHI3L1 and p-STAT3 expression correlated with the reduced CXCL8 level in the RHS in vitro model. Our data demonstrated that CHI3L1 antibody could be a promising effective therapeutic drug for atopic dermatitis.

Salivary metabolites are promising noninvasive biomarkers of drug-induced liver injury

BACKGROUND Drug-induced liver injury (DILI) is one of the most common adverse events of medication use, and its incidence is increasing. However, early detection of DILI is a crucial challenge due to a lack of biomarkers and noninvasive tests. AIM To identify salivary metabolic biomarkers of DILI for the future development of noninvasive diagnostic tools. METHODS Saliva samples from 31 DILI patients and 35 healthy controls (HCs) were subjected to untargeted metabolomics using ultrahigh-pressure liquid chromatography coupled with tandem mass spectrometry. Subsequent analyses, including partial least squares-discriminant analysis modeling, t tests and weighted metabolite coexpression network analysis (WMCNA), were conducted to identify key differentially expressed metabolites (DEMs) and metabolite sets. Furthermore, we utilized least absolute shrinkage and selection operato and random fores analyses for biomarker prediction. The use of each metabolite and metabolite set to detect DILI was evaluated with area under the receiver operating characteristic curves. RESULTS We found 247 differentially expressed salivary metabolites between the DILI group and the HC group. Using WMCNA, we identified a set of 8 DEMs closely related to liver injury for further prediction testing. Interestingly, the distinct separation of DILI patients and HCs was achieved with five metabolites, namely, 12-hydroxydodecanoic acid, 3-hydroxydecanoic acid, tetradecanedioic acid, hypoxanthine, and inosine (area under the curve: 0.733-1). CONCLUSION Salivary metabolomics revealed previously unreported metabolic alterations and diagnostic biomarkers in the saliva of DILI patients. Our study may provide a potentially feasible and noninvasive diagnostic method for DILI, but further validation is needed.

Rhein suppresses esophageal cancer development by regulating cell cycle through DNMT3B gene.

The mechanism by which DNMT3B facilitates esophageal cancer (ESCA) progression is currently unknown, despite its association with adverse prognoses in several cancer types. To investigate the potential therapeutic effects of the Chinese herbal medicine rhubarb on esophageal cancer (ESCA), we adopted an integrated bioinformatics approach. Gene Set Enrichment Analysis (GSEA) was first utilized to screen active anti-ESCA components in rhubarb. We then employed Weighted Gene Co-expression Network Analysis (WGCNA) to identify key molecular modules and targets related to the active components and ESCA pathogenesis. This system-level strategy integrating multi-omics data provides a powerful means to unravel the molecular mechanisms underlying the anticancer activities of natural products, like rhubarb. To investigate module gene functional enrichment, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. In addition, we evaluated the predictive impact of DNMT3B expression on ESCA patients utilizing the Kaplan-Meier method. Finally, we conducted experiments on cell proliferation and the cell cycle to explore the biological roles of DNMT3B. In this study, we identified Rhein as the main active ingredient of rhubarb that exhibited significant anti-ESCA activity. Rhein markedly suppressed ESCA cell proliferation. Utilizing Weighted Gene Co-expression Network Analysis (WGCNA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, we determined that the blue module was associated with Rhein target genes and the cell cycle. Additionally, DNMT3B was identified as a Rhein target gene. Analysis of The Cancer Genome Atlas (TCGA) database revealed that higher DNMT3B levels were associated with poor prognosis in ESCA patients. Furthermore, Rhein partially reversed the overexpression of DNMT3B to inhibit ESCA cell proliferation. In vitro studies demonstrated that Rhein and DNMT3B inhibition disrupted the S phase of the cell cycle and affected the production of cell cycle-related proteins. In this study, we found that Rhein exerts its anti-proliferative effects in ESCA cells by targeting DNMT3B and regulating the cell cycle.

Deciphering infected cell types, hub gene networks and cell-cell communication in infectious bronchitis virus via single-cell RNA sequencing.

Infectious bronchitis virus (IBV) is a coronavirus that infects chickens, which exhibits a broad tropism for epithelial cells, infecting the tracheal mucosal epithelium, intestinal mucosal epithelium, and renal tubular epithelial cells. Utilizing single-cell RNA sequencing (scRNA-seq), we systematically examined cells in renal, bursal, and tracheal tissues following IBV infection and identified tissue-specific molecular markers expressed in distinct cell types. We evaluated the expression of viral RNA in diverse cellular populations and subsequently ascertained that distal tubules and collecting ducts within the kidney, bursal mucosal epithelial cells, and follicle-associated epithelial cells exhibit susceptibility to IBV infection through immunofluorescence. Furthermore, our findings revealed an upregulation in the transcription of proinflammatory cytokines IL18 and IL1B in renal macrophages as well as increased expression of apoptosis-related gene STAT in distal tubules and collecting duct cells upon IBV infection leading to renal damage. Cell-to-cell communication unveiled potential interactions between diverse cell types, as well as upregulated signaling pathways and key sender-receiver cell populations after IBV infection. Integrating single-cell data from all tissues, we applied weighted gene co-expression network analysis (WGCNA) to identify gene modules that are specifically expressed in different cell populations. Based on the WGCNA results, we identified seven immune-related gene modules and determined the differential expression pattern of module genes, as well as the hub genes within these modules. Our comprehensive data provides valuable insights into the pathogenesis of IBV as well as avian antiviral immunology.

Understanding Work Ability in Employees with Pain and Stress-Related Ill-Health: An Explorative Network Analysis of Individual Characteristics and Psychosocial Work Environment.

There is a wide range of individual and work environment factors that influence work ability among workers with pain and stress-related ill-health. The multiple interactions and overlap between these factors are insufficiently understood, and a network approach could mitigate limitations of previous research. This pilot study aimed to explore interactions between individual characteristics and psychosocial work environment and potential links to long-term work ability. Prospective data from a prevention project was used. Individuals (N = 147) with pain and/or stress-related ill-health (95% women) at public sector workplaces filled out baseline questionnaires about a collection of individual and work environment factors, which were used for constructing undirected networks. The model was run in three subsamples of workplaces. Finally, a separate model was established with work ability at 6-month follow-up as outcome variable. A shortest pathway analysis was calculated to identify mediators of work ability. Symptom catastrophizing and perceived stress were the most influential factors in all network models. Symptom catastrophizing and pain-disability risk were found to mediate the relation between perceived stress and long-term work ability. Further, demand-control-support factors were interrelated, and patterns of interaction differed between different types of workplaces. The findings support the importance of individual factors, specifically symptom catastrophizing in an individual's coping with pain or stress-problems and its influence on long-term work ability. Catastrophizing might play a role in stress-related disorders which should be further investigated. Individual and work environment factors interact and vary across context, which needs to be taken into consideration to prevent pain and stress-related ill-health at work.

Evolutionary relationship of moso bamboo forms and a multihormone regulatory cascade involving culm shape variation.

Moso bamboo (Phyllostachys edulis) known as Mao Zhu (MZ) in Chinese exhibits various forms with distinct morphological characteristics. However, the evolutionary relationship among MZ forms and the mechanisms of culm shape variation are still lacking. Here, the main differences among MZ forms were identified as culm shape variation, which were confirmed by analysing MZ forms (799 bamboo culms) and MZ (458 bamboo culms) populations. To unravel the genetic basis underlying the morphological variations, 20 MZ forms were subjected to whole-genome resequencing. Further analysis yielded 3 230 107 high-quality SNPs and uncovered low genetic diversity and high genotype heterozygosity associated with MZ forms' formation. By integrating the SNP data of 427 MZ individuals representing 15 geographic regions, the origins of eight MZ forms were successfully traced using the phylogenetic tree and the identified common heterozygous loci. Meanwhile, transcriptomic analysis was performed using shoots from MZ and its two forms with culm shape variation. The results, combined with genomic analyses, demonstrated that hormone signalling related genes played crucial roles in culm variation. Co-expression network analysis uncovered genes associated with multiple plant hormone signal transduction, especially auxin and cytokinin were involved in culm shape variation. Furthermore, the regulatory relationships of a specific transcription factor and their target genes associated with auxin and ethylene signalling were validated by yeast one-hybrid, electrophoretic mobility shift assays, and dual-luciferase reporter. Overall, this study provides important insights into the culm shape variation formation in bamboo, which facilitates to breed new varieties with novel culms.

EP4-induced mitochondrial localization and cell migration mediated by CALML6 in human oral squamous cell carcinoma

Lymph node metastasis, primarily caused by the migration of oral squamous cell carcinoma (OSCC) cells, stands as a crucial prognostic marker. We have previously demonstrated that EP4, a subtype of the prostaglandin E2 (PGE2) receptor, orchestrates OSCC cell migration via Ca2+ signaling. The exact mechanisms by which EP4 influences cell migration through Ca2+ signaling, however, is unclear. Our study aims to clarify how EP4 controls OSCC cell migration through this pathway. We find that activating EP4 with an agonist (ONO-AE1-473) increased intracellular Ca2+ levels and the migration of human oral cancer cells (HSC-3), but not human gingival fibroblasts (HGnF). Further RNA sequencing linked EP4 to calmodulin-like protein 6 (CALML6), whose role remains undefined in OSCC. Through protein-protein interaction network analysis, a strong connection is identified between CALML6 and calcium/calmodulin-dependent protein kinase kinase 2 (CaMKK2), with EP4 activation also boosting mitochondrial function. Overexpressing EP4 in HSC-3 cells increases experimental lung metastasis in mice, whereas inhibiting CaMKK2 with STO-609 markedly lowers these metastases. This positions CaMKK2 as a potential new target for treating OSCC metastasis. Our findings highlight CALML6 as a pivotal regulator in EP4-driven mitochondrial respiration, affecting cell migration and metastasis via the CaMKK2 pathway.