Array
(
    [0] => stdClass Object
        (
            [journal] => stdClass Object
                (
                    [id_jnl] => 87
                )

        )

    [1] => stdClass Object
        (
            [section] => stdClass Object
                (
                    [section] => 281
                )

        )

    [2] => stdClass Object
        (
            [title] => Array
                (
                    [0] => Metabolomics in arbovirus research: A scientometric analysis of its scientific production, collaboration networks, and thematic evolution@en
                )

        )

    [3] => stdClass Object
        (
            [abstract] => Array
                (
                    [0] => Objective. Metabolomics is increasingly used to characterize host-virus interactions, metabolic remodeling linked to viral pathogenesis, and vector biology that shapes arbovirus transmission. However, research at the arbovirus-metabolomics interface is fragmented across viruses, hosts, vectors, analytical platforms, and disciplinary communities, which limits a consolidated understanding. To summarize the available literature on this topic, we conducted a scientometric review using Web of Science and Scopus.
Design/Methodology/Approach. We retrieved records and cited references from 2000 to 2024 and curated them using transparent deduplication and data-cleaning procedures. We quantified production and impact (e.g., annual output, citations), mapped geographic and journal landscapes, and built co-authorship, co-citation, and keyword co-occurrence networks. Community detection and thematic evolution analyses were complemented by a Tree of Science approach to prioritize seminal, structural, and frontier literature for qualitative synthesis (60 articles).
Results/Discussion. Our findings indicate that the field exhibits sustained growth and a multi-community structure. Activity is concentrated in the United States, Brazil, and France, with core venues spanning virology, tropical medicine, and multidisciplinary journals. Three dominant thematic clusters emerged: (1) host metabolic remodeling and immunometabolism during arboviral infection, (2) vector metabolism and microbiome-related mechanisms that influence transmission, and (3) translational directions, including biomarker discovery, therapeutic target identification, and multi-omics integration.
Conclusions. While recent work emphasizes lipidomics, multi-omics, and single-cell approaches, as well as vector-microbiome interactions, gaps persist in standardization and cross-study comparability.This mapping clarifies the intellectual structure of arbovirus metabolomics, identifies influential figures and outlets, and outlines priorities to improve reproducibility and integrative synthesis.@en
                )

        )

    [4] => stdClass Object
        (
            [author] => Array
                (
                    [0] => Keneth Stiven Garcia Cifuentes
                    [1] => Zuly Dayanna Villanueva
                    [2] => Sindy J. Escobar-Luján
                    [3] => Jaime A. Cardona-Ospina
                    [4] => Martha Zuluaga
                )

        )

    [5] => stdClass Object
        (
            [subject] => Array
                (
                    [0] => Arboviruses@en
                    [1] => Metabolomics@en
                    [2] => Scientometric analysis@en
                    [3] => Bibliometric mapping@en
                    [4] => Co-citation analysis@en
                    [5] => Research trends@en
                    [6] => Tree of science@en
                )

        )

    [6] => stdClass Object
        (
            [source] => stdClass Object
                (
                    [vol] => 6
                    [nr] => 
                    [year] => 2026
                    [theme] => 
                )

        )

    [7] => stdClass Object
        (
            [datePub] => Array
                (
                    [0] => 2026-06-12
                )

        )

    [8] => stdClass Object
        (
            [DOI] => Array
                (
                    [0] => stdClass Object
                        (
                            [type] => DOI
                            [value] => Array
                                (
                                    [0] => 10.47909/ijsmc.386
                                )

                        )

                )

        )

    [9] => stdClass Object
        (
            [http] => Array
                (
                    [0] => stdClass Object
                        (
                            [type] => HTTP
                            [value] => Array
                                (
                                    [0] => https://ijsmc.pro-metrics.org/index.php/i/article/view/386
                                )

                        )

                    [1] => stdClass Object
                        (
                            [type] => HTTP
                            [value] => Array
                                (
                                    [0] => https://ijsmc.pro-metrics.org/index.php/i/article/view/386/221
                                )

                        )

                )

        )

    [10] => stdClass Object
        (
            [language] => Array
                (
                    [0] => en
                )

        )

    [11] => stdClass Object
        (
            [license] => Array
                (
                    [0] => Copr
                    [1] => by-nc/4.0
                )

        )

)