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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Nutr.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Nutrition</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Nutr.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2296-861X</issn>
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<publisher-name>Frontiers Media S.A.</publisher-name>
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<article-meta>
<article-id pub-id-type="doi">10.3389/fnut.2026.1758832</article-id>
<article-version article-version-type="Version of Record" vocab="NISO-RP-8-2008"/>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Systematic Review</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Global research landscape and multisystem health mechanisms of luteolin: a comprehensive bibliometric and network pharmacology study</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes" equal-contrib="yes">
<name>
<surname>Guo</surname>
<given-names>Huina</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
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<surname>Tian</surname>
<given-names>Xiyan</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
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<surname>Wang</surname>
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<surname>Wang</surname>
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<surname>Guo</surname>
<given-names>Yujia</given-names>
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<surname>Guan</surname>
<given-names>Xiaoya</given-names>
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<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Zhongxun</given-names>
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<contrib contrib-type="author">
<name>
<surname>Wen</surname>
<given-names>Xin</given-names>
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<surname>Wu</surname>
<given-names>Bohui</given-names>
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<contrib contrib-type="author">
<name>
<surname>Zhao</surname>
<given-names>Liting</given-names>
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<surname>Wang</surname>
<given-names>Ying</given-names>
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<surname>Liu</surname>
<given-names>Hongliang</given-names>
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<surname>Zhang</surname>
<given-names>Chunming</given-names>
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<aff id="aff1"><label>1</label><institution>Shanxi Key Laboratory of Otorhinolaryngology Head and Neck Cancer, First Hospital of Shanxi Medical University</institution>, <city>Taiyuan</city>, <country country="cn">China</country></aff>
<aff id="aff2"><label>2</label><institution>Shanxi Province Clinical Medical Research Center for Precision Medicine of Head and Neck Cancer, First Hospital of Shanxi Medical University</institution>, <city>Taiyuan</city>, <country country="cn">China</country></aff>
<aff id="aff3"><label>3</label><institution>The First Clinical Medical College of Shanxi Medical University</institution>, <city>Taiyuan</city>, <country country="cn">China</country></aff>
<aff id="aff4"><label>4</label><institution>Department of Ultrasound Medicine, Jinyun People Hospital</institution>, <city>Lishui</city>, <country country="cn">China</country></aff>
<aff id="aff5"><label>5</label><institution>The Basic Medical Sciences College of Shanxi Medical University</institution>, <city>Taiyuan</city>, <country country="cn">China</country></aff>
<aff id="aff6"><label>6</label><institution>Department of Otolaryngology Head &#x0026; Neck Surgery, First Hospital of Shanxi Medical University</institution>, <city>Taiyuan</city>, <country country="cn">China</country></aff>
<author-notes>
<corresp id="c001"><label>&#x002A;</label>Correspondence: Chunming Zhang, <email xlink:href="mailto:zcmsxmu@sxent.org">zcmsxmu@sxent.org</email>; Huina Guo, <email xlink:href="mailto:guohuina@sxent.org">guohuina@sxent.org</email></corresp>
<fn fn-type="equal" id="fn1001"><p><sup>&#x2020;</sup>These authors have contributed equally to this work and share first authorship</p></fn>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-01-28">
<day>28</day>
<month>01</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2026</year>
</pub-date>
<volume>13</volume>
<elocation-id>1758832</elocation-id>
<history>
<date date-type="received">
<day>05</day>
<month>12</month>
<year>2025</year>
</date>
<date date-type="rev-recd">
<day>15</day>
<month>01</month>
<year>2026</year>
</date>
<date date-type="accepted">
<day>15</day>
<month>01</month>
<year>2026</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2026 Guo, Tian, Wang, Wang, Han, Guo, Guan, Li, Wen, Wu, Zhao, Wang, Liu and Zhang.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Guo, Tian, Wang, Wang, Han, Guo, Guan, Li, Wen, Wu, Zhao, Wang, Liu and Zhang</copyright-holder>
<license>
<ali:license_ref start_date="2026-01-28">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p>
</license>
</permissions>
<abstract>
<sec>
<title>Objective</title>
<p>This study employs bibliometric and network pharmacology methods to systematically analyze the development trends, knowledge structure, and potential biological mechanisms of luteolin research from 2000 to 2025, providing insights for its application in nutritional health and disease prevention.</p>
</sec>
<sec>
<title>Methods</title>
<p>Based on the Web of Science Core Collection (WoSCC), combined with Bibliometrix, VOSviewer, and citespace, we conducted analyses of publication characteristics, keywords, journals, and co-citation networks. Simultaneously, integrating TM-MC, string, and Cytoscape, we constructed a luteolin target-pathway-disease network and performed core target and KEGG enrichment analyses.</p>
</sec>
<sec>
<title>Results</title>
<p>Luteolin research exhibits sustained growth, with a significant increase after 2021. Research focus has expanded from early antioxidant and anti-inflammatory mechanisms to metabolic health, immune regulation, tumor suppression, and multisystem protection. Network pharmacology identified 239 potential targets, with core targets including TP53, TNF, STAT3, and EGFR, significantly enriched in p53, PI3K&#x2013;Akt, TNF, and IL-17 pathways. Disease association networks indicate luteolin&#x2019;s potential to intervene in neurological, circulatory, metabolic, immune, digestive, respiratory disorders, and multiple tumors, exhibiting typical multi-target comprehensive regulatory characteristics.</p>
</sec>
</abstract>
<kwd-group>
<kwd>bibliometric</kwd>
<kwd>dietary flavonoid</kwd>
<kwd>functional foods</kwd>
<kwd>luteolin</kwd>
<kwd>multisystem health effects</kwd>
<kwd>network pharmacology</kwd>
</kwd-group>
<funding-group>
<funding-statement>The author(s) declared that financial support was received for this work and/or its publication. This work was supported by the Basic Research Program of Shanxi Province (Free Exploration) (Nos. 202203021212045, 202203021212032, 202403021222446, and 202203021212029), Shanxi Provincial Health Commission Research Project (Guiding Science and Technology Special Project: No. 2025YD020), and the National Clinical Research Center for Otolaryngologic Diseases, Beijing, China, grant number 2024KF003.</funding-statement>
</funding-group>
<counts>
<fig-count count="9"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="74"/>
<page-count count="17"/>
<word-count count="9656"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Nutritional Immunology</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec1">
<label>1</label>
<title>Introduction</title>
<p>Natural products are regarded as vital resources bestowed upon humanity by nature, whose rich chemical diversity has long inspired novel drug development (<xref ref-type="bibr" rid="ref1">1</xref>, <xref ref-type="bibr" rid="ref2">2</xref>). They serve not only as the starting point for drug discovery but also as a crucial foundation for constructing lead compound structures (<xref ref-type="bibr" rid="ref3">3</xref>). Currently, approximately 60% of clinically used drugs can be traced back to direct extraction or structural inspiration from natural products. Classic drugs such as aspirin, digoxin, morphine, and artemisinin all originate from natural compounds. Historically, these natural molecules have been used to alleviate symptoms, prevent diseases, and promote recovery from various pathological states (<xref ref-type="bibr" rid="ref4">4</xref>). Flavonoids, as important natural products, have garnered extensive attention for their remarkable antioxidant, anti-tumor, and anti-inflammatory activities, as well as their ability to regulate multiple key cellular enzymes (<xref ref-type="bibr" rid="ref5">5</xref>). These properties confer broad application potential in drug development, functional foods, and nutritional health (<xref ref-type="bibr" rid="ref2">2</xref>).</p>
<p>Luteolin (3&#x2032;,4&#x2032;,5,7-tetrahydroxyflavone) is a natural flavonoid compound (<xref ref-type="bibr" rid="ref2">2</xref>, <xref ref-type="bibr" rid="ref6 ref7 ref8">6&#x2013;8</xref>), found in numerous plants including many edible species such as celery, broccoli, green peppers, parsley, thyme, dandelion, perilla, chamomile tea, carrots, and olive oil (<xref ref-type="bibr" rid="ref1">1</xref>). Luteolin exhibits diverse biological activities including cytotoxic effects, anti-inflammatory activity (<xref ref-type="bibr" rid="ref9">9</xref>), antioxidant activity (<xref ref-type="bibr" rid="ref10">10</xref>), antitumor activity (<xref ref-type="bibr" rid="ref11">11</xref>), and antibacterial activity (<xref ref-type="bibr" rid="ref12">12</xref>, <xref ref-type="bibr" rid="ref13">13</xref>), leading to its widespread application in the food industry and biomedical fields (<xref ref-type="bibr" rid="ref14">14</xref>). Research indicates luteolin is an effective SARS-CoV-2 cell invasion inhibitor (<xref ref-type="bibr" rid="ref15">15</xref>) and has been recommended as a dietary supplement against COVID-19 (<xref ref-type="bibr" rid="ref16">16</xref>). Furthermore, Hou et al. (<xref ref-type="bibr" rid="ref17">17</xref>) demonstrated that luteolin alleviates pulmonary edema in acute respiratory distress syndrome, inhibits inflammatory responses to slow disease progression, and enhances the activity of multiple antioxidant enzymes by regulating oxidative stress levels (<xref ref-type="bibr" rid="ref18">18</xref>). As related research deepens, luteolin has gradually emerged as a significant research focus in natural drug development and disease prevention. However, the continuous growth in literature volume makes it challenging for researchers to systematically grasp the development trajectory and research frontiers in this field.</p>
<p>This study systematically reviews evolutionary trends, key target molecules, and associated diseases in luteolin research based on literature from 2000 to 2025 indexed in the WoSCC, integrating bibliometric and network pharmacology analyses. <xref ref-type="fig" rid="fig1">Figure 1</xref> illustrates the data retrieval process and an overall analytical framework. This study aims to comprehensively present the current state and structural characteristics of this field, identify potential research hotspots, and provide references and novel analytical perspectives for future research on luteolin in nutrition and health.</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Article strategy and analysis flowchart.</p>
</caption>
<graphic xlink:href="fnut-13-1758832-g001.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Flowchart depicting research on bibliometric and network pharmacology for luteolin. It starts with two databases: WoSCC and TM-MC. WoSCC processes titles such as "luteolin" for bibliometric analysis, yielding 2,287 results in English articles from 2000 to 2025. TM-MC analyzes luteolin target genes, herbs, and diseases for network pharmacology. The research examines global trends and health mechanisms, focusing on publication trends, journal analysis, reference co-citation and clustering, keyword clustering, and a luteolin-target-disease network.</alt-text>
</graphic>
</fig>
</sec>
<sec sec-type="materials|methods" id="sec2">
<label>2</label>
<title>Materials and methods</title>
<sec id="sec3">
<label>2.1</label>
<title>Data collection</title>
<p>The WoSCC is a major research platform spanning multiple fields including natural sciences, social sciences, arts, and humanities (<xref ref-type="bibr" rid="ref19">19</xref>), and one of the most widely cited comprehensive academic literature databases globally (<xref ref-type="bibr" rid="ref20">20</xref>). The literature extracted for this study originated from the WoSCC database. Searches were conducted using the terms TI&#x202F;=&#x202F;(&#x201C;luteolin&#x201D;) OR TI&#x202F;=&#x202F;(&#x201C;luteoline&#x201D;) OR TI&#x202F;=&#x202F;(&#x201C;luteolol&#x201D;) OR TI&#x202F;=&#x202F;(&#x201C;Digitoflavone&#x201D;), with the retrieval timeframe set from January 1, 2000, to September 30, 2025. The initial search yielded 2,587 documents. Subsequently, screening based on document type retained only Articles and Review Articles of high academic and citation values, resulting in 2,302 documents. Further restrictions on English-language documents ultimately included 2,287 documents for subsequent analysis. All documents were exported as complete records containing reference lists and saved as plain text files (download_.txt). It should be noted that due to ongoing updates to the WoSCC database and dynamic indexing status changes, the number of search results may exhibit slight variations. This is when applying the same search strategy at different points in time. The literature search and screening process for this study strictly adhered to the PRISMA 2020 checklist requirements (<xref rid="SM1" ref-type="supplementary-material">Supplementary Material S1</xref>) (<xref ref-type="bibr" rid="ref21">21</xref>).</p>
</sec>
<sec id="sec4">
<label>2.2</label>
<title>Grey prediction model</title>
<p>This study employs the Grey Model [GM (1.1)] (<xref ref-type="bibr" rid="ref22">22</xref>, <xref ref-type="bibr" rid="ref23">23</xref>) to analyze publication trends and future predictions. To predict publication volumes for the next 3 years using R 4.5.1 software (<xref rid="SM1" ref-type="supplementary-material">Supplementary Material S2</xref>), a time series forecasting model was constructed using annual publication volume data from 2000 to 2024.</p>
</sec>
<sec id="sec5">
<label>2.3</label>
<title>Bibliometric analysis and visualization</title>
<p>Import the articles retrieved in this study into bibliometrix, citespace, and VOSviewer for further bibliometric analysis. The bibliometrix software package captures and extracts relevant information from selected articles, including subject areas, journals, keywords, and country distribution. VOSviewer and citespace are two widely used visualization tools in current bibliometric research, each offering distinct advantages. VOSviewer excels at constructing keyword co-occurrence networks, offering intuitive visualizations that reflect clustering relationships and academic connections through node size, color, and edge thickness (<xref ref-type="bibr" rid="ref24">24</xref>). Citespace, meanwhile, focuses on revealing the developmental trajectories of research fields and the evolution of research hotspots. Through clustering information and burst term analysis, citespace effectively displays the temporal evolution of research themes, significant turning points within the field, and the citation paths of key publications. The integration of these two software tools facilitates multidimensional exploration of knowledge structures and developmental trends within luteolin research. This provides researchers with comprehensive and systematic theoretical references.</p>
</sec>
<sec id="sec6">
<label>2.4</label>
<title>Luteolin-target-disease network construction</title>
<p>This study screened luteolin-related targets, disease information, and herbal sources using the TM-MC database.<xref ref-type="fn" rid="fn0001"><sup>1</sup></xref> Subsequently, the string website<xref ref-type="fn" rid="fn0002"><sup>2</sup></xref> was utilized to construct a protein&#x2013;protein interaction (PPI) network, aiming to uncover functional connections between the targets. Building upon this, cytoscape 3.6.0 software was employed to construct a luteolin-target-disease network diagram. From this network, key targets potentially involved in luteolin&#x2019;s biological activity and their primary disease types were identified, providing a reference framework for subsequent research.</p>
</sec>
</sec>
<sec sec-type="results" id="sec7">
<label>3</label>
<title>Results</title>
<sec id="sec8">
<label>3.1</label>
<title>Publication trends and future prediction of luteolin research</title>
<p>In bibliometrics, publication volume serves as a key indicator for measuring research activity (<xref ref-type="bibr" rid="ref24">24</xref>). Based on the WOSCC, this study included 2,287 publications related to luteolin from January 2000 to September 2025. Statistics show that these articles were published in 840 journals, received 81,401 citations, and generated 43,698 cited references. The H-index stands at 114, with an average citation count of 35.59 per article.</p>
<p>The annual publication volume shows a steady upward trend in luteolin research from 2000 to 2024 (<xref ref-type="fig" rid="fig2">Figure 2</xref>). Early publications were relatively scarce with gradual growth; since 2010, annual output has steadily increased, particularly with a significant surge in 2021. To further explore future trends, this study employed GM(1.1) to predict publication volumes over the next 3 years. Results indicate that luteolin research will maintain an upward trajectory, with projected publications exceeding 390 by 2027. This predicts sustained growth in research activity in this field.</p>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption>
<p>Annual publication trends and future predictions of luteolin.</p>
</caption>
<graphic xlink:href="fnut-13-1758832-g002.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Bar and line graph showing publications and stimulation from 2000 to 2027. The graph displays an upward trend in both metrics, with publications in blue bars and stimulation in an orange line. Notable increases occur after 2014, peaking in 2024 for stimulation and predicting continued growth through 2027, with predicted values of 352 and 394 for 2025 and 2027, respectively.</alt-text>
</graphic>
</fig>
</sec>
<sec id="sec9">
<label>3.2</label>
<title>Country and institutional collaboration network analysis</title>
<p>To reveal the global distribution patterns and collaborative characteristics of luteolin research, this study conducted a systematic analysis of publication volumes across major countries. Results indicate that China consistently leads in annual publication output, followed by South Korea and the USA (<xref ref-type="fig" rid="fig3">Figure 3A</xref>). In terms of total citation counts, China also ranks first, with South Korea and the USA occupying the second and third positions, respectively (<xref rid="SM1" ref-type="supplementary-material">Supplementary Figure S1</xref>). Then, this study utilized VOSviewer and Scimago Graphica to visualize collaboration networks among the top 30 countries. The collaborative networks were clustered into three groups, with countries within the same cluster exhibiting close cooperation. China and the USA were the most closely connected countries across different clusters (<xref ref-type="fig" rid="fig3">Figure 3B</xref>). The institutional collaboration network (<xref ref-type="fig" rid="fig3">Figure 3C</xref>) revealed that Nanjing university of Chinese medicine and the Chinese academy of sciences occupied central positions, each forming close collaborations with multiple institutions.</p>
<fig position="float" id="fig3">
<label>Figure 3</label>
<caption>
<p>The distribution of collaborative publications and institutions by country. <bold>(A)</bold> Annual proportion of publications on luteolin contributed by major countries from 2000 to 2025. <bold>(B)</bold> Clusters of the country collaboration network. China and USA show the strongest collaboration intensity. <bold>(C)</bold> Institutional collaboration network clusters.</p>
</caption>
<graphic xlink:href="fnut-13-1758832-g003.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">A composite image with three panels: Panel A shows a stacked area chart depicting the percentage contributions of countries to a particular metric from 2000 to 2025. Dominant countries include China, USA, and India. Panel B is a chord diagram illustrating collaborations between countries, with notable links between China, USA, and South Korea. Panel C presents a network diagram of university collaborations, highlighting relationships among Chinese institutions such as Shanghai Jiao Tong University and Nanjing University.</alt-text>
</graphic>
</fig>
</sec>
<sec id="sec10">
<label>3.3</label>
<title>Journals and co-cited journals analysis</title>
<p>We utilized the Bibliometrix package to identify high-impact journals in the luteolin field and conducted visualization analysis using citespace. <xref ref-type="table" rid="tab1">Table 1</xref> presents the top 10 journals ranked by publication volume and citation performance. These journals are primarily distributed across JCR Q1 and Q2, with the <italic>Journal of Agricultural</italic> and <italic>Food Chemistry</italic> leading in both publication volume and citation count. Notably, among the top 10 journals by co-citation, high-impact journals such as <italic>Food Chemistry</italic> (IF&#x202F;=&#x202F;9.8, Q1) and <italic>Cancer Research</italic> (IF&#x202F;=&#x202F;16.6, Q1) are included.</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>The number of publications, IF, and JCR quartile of the top 10 and co-cited journals.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">No.</th>
<th align="left" valign="top">Journal</th>
<th align="center" valign="top">Publication</th>
<th align="center" valign="top">IF (JCR2025)</th>
<th align="left" valign="top">JCR quartile</th>
<th align="left" valign="top">Co-cited journal</th>
<th align="center" valign="top">Publication</th>
<th align="center" valign="top">IF (JCR2025)</th>
<th align="left" valign="top">JCR quartile</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">1</td>
<td align="left" valign="middle">J AGR FOOD CHEM</td>
<td align="center" valign="middle">35</td>
<td align="char" valign="middle" char=".">6.2</td>
<td align="left" valign="middle">Q1</td>
<td align="left" valign="middle">J AGR FOOD CHEM</td>
<td align="center" valign="middle">1,680</td>
<td align="char" valign="middle" char=".">6.2</td>
<td align="left" valign="middle">Q1</td>
</tr>
<tr>
<td align="left" valign="middle">2</td>
<td align="left" valign="middle">INT J MOL SCI</td>
<td align="center" valign="middle">33</td>
<td align="char" valign="middle" char=".">4.9</td>
<td align="left" valign="middle">Q1</td>
<td align="left" valign="middle">J BIOL CHEM</td>
<td align="center" valign="middle">1,316</td>
<td align="char" valign="middle" char=".">3.9</td>
<td align="left" valign="middle">Q2</td>
</tr>
<tr>
<td align="left" valign="middle">3</td>
<td align="left" valign="middle">FRONTIERS IN PHARMACOLOGY</td>
<td align="center" valign="middle">31</td>
<td align="char" valign="middle" char=".">4.8</td>
<td align="left" valign="middle">Q1</td>
<td align="left" valign="middle">INT J MOL SCI</td>
<td align="center" valign="middle">1,138</td>
<td align="char" valign="middle" char=".">4.9</td>
<td align="left" valign="middle">Q1</td>
</tr>
<tr>
<td align="left" valign="middle">4</td>
<td align="left" valign="middle">MOLECULES</td>
<td align="center" valign="middle">31</td>
<td align="char" valign="middle" char=".">4.6</td>
<td align="left" valign="middle">Q2</td>
<td align="left" valign="middle">PLOS ONE</td>
<td align="center" valign="middle">1,126</td>
<td align="char" valign="middle" char=".">2.6</td>
<td align="left" valign="middle">Q2</td>
</tr>
<tr>
<td align="left" valign="middle">5</td>
<td align="left" valign="middle">PLOS ONE</td>
<td align="center" valign="middle">30</td>
<td align="char" valign="middle" char=".">2.6</td>
<td align="left" valign="middle">Q2</td>
<td align="left" valign="middle">MOLECULES</td>
<td align="center" valign="middle">1,062</td>
<td align="char" valign="middle" char=".">4.6</td>
<td align="left" valign="middle">Q2</td>
</tr>
<tr>
<td align="left" valign="middle">6</td>
<td align="left" valign="middle">EUROPEAN JOURNAL OF PHARMACOLOGY</td>
<td align="center" valign="middle">27</td>
<td align="char" valign="middle" char=".">4.7</td>
<td align="left" valign="middle">Q1</td>
<td align="left" valign="middle">FOOD CHEM</td>
<td align="center" valign="middle">1,001</td>
<td align="char" valign="middle" char=".">9.8</td>
<td align="left" valign="middle">Q1</td>
</tr>
<tr>
<td align="left" valign="middle">7</td>
<td align="left" valign="middle">BIOMEDICINE &#x0026; PHARMACOTHERAPY</td>
<td align="center" valign="middle">24</td>
<td align="char" valign="middle" char=".">7.5</td>
<td align="left" valign="middle">Q1</td>
<td align="left" valign="middle">BIOMED PHARMACOTHER</td>
<td align="center" valign="middle">950</td>
<td align="char" valign="middle" char=".">7.5</td>
<td align="left" valign="middle">Q1</td>
</tr>
<tr>
<td align="left" valign="middle">8</td>
<td align="left" valign="middle">INTERNATIONAL IMMUNOPHARMACOLOGY</td>
<td align="center" valign="middle">23</td>
<td align="char" valign="middle" char=".">4.7</td>
<td align="left" valign="middle">Q1</td>
<td align="left" valign="middle">J ETHNOPHARMACOL</td>
<td align="center" valign="middle">885</td>
<td align="char" valign="middle" char=".">5.4</td>
<td align="left" valign="middle">Q1</td>
</tr>
<tr>
<td align="left" valign="middle">9</td>
<td align="left" valign="middle">FOOD &#x0026; FUNCTION</td>
<td align="center" valign="middle">22</td>
<td align="char" valign="middle" char=".">5.4</td>
<td align="left" valign="middle">Q1</td>
<td align="left" valign="middle">CANCER RES</td>
<td align="center" valign="middle">853</td>
<td align="char" valign="middle" char=".">16.6</td>
<td align="left" valign="middle">Q1</td>
</tr>
<tr>
<td align="left" valign="middle">10</td>
<td align="left" valign="middle">FOOD CHEMISTRY</td>
<td align="center" valign="middle">22</td>
<td align="char" valign="middle" char=".">9.8</td>
<td align="left" valign="middle">Q1</td>
<td align="left" valign="middle">P NATL ACAD SCI USA</td>
<td align="center" valign="middle">802</td>
<td align="char" valign="middle" char=".">9.1</td>
<td align="left" valign="middle">Q1</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>In addition, Bradford&#x2019;s Law analysis of journal sources (<xref ref-type="fig" rid="fig4">Figure 4A</xref>) reveals that research literature in this field exhibits a &#x201C;core-related-periphery&#x201D; distribution pattern. Journals such as <italic>Journal of Agricultural</italic> and <italic>Food Chemistry</italic>, International <italic>Journal of Molecular Sciences</italic>, <italic>Frontiers in Pharmacology</italic>, <italic>Molecules</italic>, and <italic>PLOS ONE</italic> occupy the core zone. They publish the highest volume of articles in this field and serve as primary knowledge output vehicles. Further journal dual-map overlay analysis (<xref ref-type="fig" rid="fig4">Figure 4B</xref>) reveals distinct interdisciplinary pathways in luteolin research knowledge flow. Citation sources on the left primarily focus on foundational disciplines like molecular biology/immunology, while cited works on the right concentrate on applied fields such as environmental toxicology and nutrition. These connecting pathways indicate a research shift from fundamental mechanism studies toward nutrition, toxicology, and related health effects.</p>
<fig position="float" id="fig4">
<label>Figure 4</label>
<caption>
<p>Journal source analysis and dual-map overlay visualization. <bold>(A)</bold> Core journals in luteolin research identified by Bradford&#x2019;s Law, displaying their distribution and ranking. <bold>(B)</bold> The dual-map overlay visualizes knowledge flow pathways between citing and cited journals.</p>
</caption>
<graphic xlink:href="fnut-13-1758832-g004.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Part A shows a plot illustrating Bradford's Law, highlighting core sources in scientific research, with specific journals such as "J AGR FOOD CHEM" and "FOOD CHEMISTRY" listed. Part B presents a colorful network map of citing and cited journals, showing connections between fields like "MOLECULAR BIOLOGY, IMMUNOLOGY" and "ENVIRONMENTAL TOXICOLOGY, NUTRITION" with highlighted pathways.</alt-text>
</graphic>
</fig>
</sec>
<sec id="sec11">
<label>3.4</label>
<title>Co-citation and cluster analysis of literature</title>
<p>To identify the knowledge base and core research trajectories within the luteolin field, this study conducted a co-citation analysis of the literature. Co-citation relationships reveal underlying logical connections between different publications, aiding in clarifying the theoretical underpinnings and developmental trends of research.</p>
<p><xref ref-type="fig" rid="fig5">Figure 5A</xref> displays the top 10 most cited articles and constructs their co-citation network using citespace, with nodes possessing high betweenness centrality values marked by purple outer rings. Additionally, <xref ref-type="fig" rid="fig5">Figure 5B</xref> highlights seven articles exhibiting significant citation bursts related to luteolin when the minimum duration was set to 6. These articles were clustered into 18 groups (<xref ref-type="fig" rid="fig5">Figure 5C</xref>), with the most prominent being #0 gastric cancer cell. Clusters such as #1 oral administration, #2 novel approach, and #3 lead acetate pertain to formulation innovation, toxicological assessment, and administration methods. In contrast, earlier clusters like &#x201C;#16 bioflavonoid inhibitor,&#x201D; &#x201C;#15 flavonoid,&#x201D; and &#x201C;#14 contractile function&#x201D; indicate that luteolin&#x2019;s traditional pharmacological effects, structural studies, and chemical mechanisms remain crucial components of the knowledge base.</p>
<fig position="float" id="fig5">
<label>Figure 5</label>
<caption>
<p>Literature co-citation and cluster analysis. <bold>(A)</bold> Literature co-citation reference network. Nodes with high betweenness centrality values are marked with purple outer rings. <bold>(B)</bold> Top seven references with the strongest citation bursts between 2000 and 2025. <bold>(C)</bold> Thematic evolution map of luteolin-related research based on literature co-occurrence clustering.</p>
</caption>
<graphic xlink:href="fnut-13-1758832-g005.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Illustration highlighting keyword clusters and citation bursts related to scientific research from 2000 to 2025. Panel A shows a network map with clusters labeled by author name and publication year. Panel B lists the top 7 references with strong citation bursts, detailing year, strength, begin and end dates, and a bar chart showing citation trends. Panel C provides another network view with thematic clusters labeled by research topic, such as "oral administration" and "gastric cancer cell." Both network maps display interconnected nodes representing the flow and influence of academic citations.</alt-text>
</graphic>
</fig>
</sec>
<sec id="sec12">
<label>3.5</label>
<title>Keywords co-occurrence and clustering analysis</title>
<p>Keyword co-occurrence analysis helps reveal connections between different research topics, identifying core research hotspots and potential mechanisms in the luteolin field. This study visualized author keywords using VOSviewer, setting the minimum number of occurrences to 5. After excluding irrelevant or meaningless keywords such as &#x2018;luteolin&#x2019;, &#x2018;cells&#x2019;, &#x201C;expression,&#x201D; &#x2018;I&#x2019;, and &#x2018;assay&#x2019;, a total of 212 keywords were obtained. <xref ref-type="fig" rid="fig6">Figure 6A</xref> shows distinct high-frequency clusters. Keywords such as apoptosis, inflammation, oxidative stress, and flavonoids exhibit elevated co-occurrence frequencies and brightness, indicating their centrality in the research landscape of luteolin.</p>
<fig position="float" id="fig6">
<label>Figure 6</label>
<caption>
<p>Heatmap of research themes, keyword burst analysis, and keyword clustering in luteolin studies. <bold>(A)</bold> Keyword co-occurrence heatmap highlighting major research themes in the luteolin field. <bold>(B)</bold> Reference co-citation network. Red nodes represent references with strong citation bursts, purple nodes denote high betweenness centrality references. <bold>(C)</bold> The panel shows the top7 references with the strongest citation bursts. <bold>(D)</bold> Keyword clustering network showing major thematic clusters.</p>
</caption>
<graphic xlink:href="fnut-13-1758832-g006.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">A multi-part scientific visualization displays data and analysis related to bibliometrics. Panel A features a heat map of keywords with highlights on terms like "oxidative stress" and "apoptosis." Panel B shows a network graph with nodes representing citations, where larger nodes indicate higher importance or frequency. Panel C lists seven references with strong citation bursts from 2000 to 2025, shown in a timeline bar graph. Panel D consists of clusters labeled with research topics, indicating connections and influences within scientific literature. A color scale is provided for citation strength representation.</alt-text>
</graphic>
</fig>
<p>We further performed burst analyses to identify keyword bursts related to luteolin research. The results (<xref ref-type="fig" rid="fig6">Figures 6B</xref>,<xref ref-type="fig" rid="fig6">C</xref>) show that keyword bursts in the early stages primarily included flavonoids, free radicals, and dietary flavonoids, reflecting a focus on nutritional antioxidant mechanisms and free radical scavenging. Subsequently, terms such as tyrosine kinase, cell cycle, induced apoptosis, necrosis factor alpha, and kinase appeared. These terms indicated a gradual shift in research emphasis toward molecular signaling pathway regulation and cellular-level mechanisms. In recent years, keywords such as reactive oxygen species, cycle arrest, and combination reflect a growing research focus on luteolin&#x2019;s role in oxidative stress, cell cycle arrest, and multi-component combination applications.</p>
<p>Keyword cluster analysis results indicate that luteolin related research focuses primarily on themes such as antitumor effects, inflammation and immune regulation, metabolic improvement, and cardiovascular and neuroprotection (<xref ref-type="fig" rid="fig6">Figure 6D</xref>). The largest cluster, #0 trail sensitivity, represents research hotspots for inducing tumor cell apoptosis; clusters such as #7 kinase activity and #16 cell cycle suggest that molecular mechanism studies remain predominant. Simultaneously, clusters such as #4 insulin sensitivity, #13 cardioprotective effect, and #8 neuroprotective role reflect the gradual expansion of luteolin research into nutrition and chronic disease prevention.</p>
</sec>
<sec id="sec13">
<label>3.6</label>
<title>Luteolin target and signaling pathway enrichment</title>
<p>Based on bibliometric analysis, we can clearly observe that luteolin has garnered extensive attention in fields such as anti-inflammatory effects, anti-tumor activity, and immunomodulation, occupying a significant position in research into various diseases. However, as a naturally occurring flavonoid widely present in food sources, luteolin&#x2019;s health benefits often depend on its comprehensive regulation through multiple targets and pathways. Its underlying mechanisms still require systematic elucidation.</p>
<p>In order to understand luteolin&#x2019;s biological actions, this study constructed a network pharmacology model to analyze its sources, targets, and potential functional pathways. First, the TM-MC database identified 113 plant sources containing luteolin (<xref rid="SM1" ref-type="supplementary-material">Supplementary Table S1</xref>), covering traditional efficacy categories such as clearing heat and detoxifying, promoting blood circulation and removing blood stasis, and dispelling wind-dampness (<xref ref-type="fig" rid="fig7">Figures 7A</xref>,<xref ref-type="fig" rid="fig7">B</xref>). This also suggested diverse dietary intake pathways for luteolin.</p>
<fig position="float" id="fig7">
<label>Figure 7</label>
<caption>
<p>Network pharmacology analysis of the multi-target mechanisms and key signaling pathway enrichment of luteolin. <bold>(A,B)</bold> Distribution of luteolin-containing herbs by efficacy category. Yellow represents luteolin, purple represents herbs, green represents herbs efficacy classification. <bold>(C)</bold> Luteolin target-associated KEGG signaling pathway enrichment. <bold>(D)</bold> PPI network map of luteolin&#x2019;s targets. Green represents luteolin targets and purple represents 10 core targets.</p>
</caption>
<graphic xlink:href="fnut-13-1758832-g007.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Diagram with four panels related to luteolin in Chinese herbal medicine. Panel A: Luteolin at the center connected to six categories. Panel B: Table with Chinese herbal medicine classification, from invigorating blood circulation to miscellaneous. Panel C: Dot plot showing gene involvement in various signaling pathways, with dot size indicating gene number and color representing statistical significance. Panel D: Network diagram with central cluster connected to outer nodes like TNF and CASP3, indicating interactions.</alt-text>
</graphic>
</fig>
<p>Further screening identified 239 potential targets associated with luteolin (<xref rid="SM1" ref-type="supplementary-material">Supplementary Table S2</xref>). After constructing a PPI network using the string platform and performing KEGG enrichment analysis, the top 20 pathways were selected based on the false discovery rate (<xref ref-type="fig" rid="fig7">Figure 7C</xref>). Results revealed multiple pathways associated with tumorigenesis and progression, significantly enriched in key biological processes including inflammatory regulation, immune control, and metabolic homeostasis&#x2014;particularly signaling pathways such as p53, PI3K&#x2013;Akt, IL-17, and TNF. These pathways play central roles in nutrition-related diseases characterized by chronic inflammation, immune dysregulation, and metabolic disorders.</p>
<p>We conducted a topological parameter analysis of the compound-target interaction network by cytoscape software. Employing degree as the primary screening criterion, we identified the top 10 core targets ranked by degree value: TP53, TNF, IL1B, STAT3, EGFR, JUN, CASP3, FN1, HSP90AA1, and ERBB2 (<xref ref-type="fig" rid="fig7">Figure 7D</xref>). These targets participate in critical pathways such as the inflammatory response, cell cycle regulation, apoptosis, and cellular stress responses. This suggests that luteolin may exert synergistic biological regulatory effects in nutrition-related diseases by modulating multiple signaling axes.</p>
<p>In summary, luteolin modulates inflammation, immune responses, and metabolic processes through coordinated regulation of multiple molecular targets and signaling pathways, providing theoretical support for its application in nutritional interventions, disease prevention, and functional food development.</p>
</sec>
<sec id="sec14">
<label>3.7</label>
<title>Network analysis of diseases associated with core luteolin targets</title>
<p>Based on the TM-MC database, we identified the top 10 target-related diseases and obtained 91 common diseases through intersection analysis (<xref ref-type="fig" rid="fig8">Figures 8A</xref>&#x2013;<xref ref-type="fig" rid="fig8">C</xref>). Subsequently, we systematically categorized disease types and constructed a luteolin-cored target&#x2013;disease association network (<xref ref-type="fig" rid="fig8">Figure 8D</xref> and <xref rid="SM1" ref-type="supplementary-material">Supplementary Table S3</xref>). Results revealed widespread distribution across neurological, circulatory, respiratory, digestive, immune, and metabolic disorders, alongside multiple tumor types (e.g., breast cancer, head and neck tumors, bone and soft tissue tumors). This pattern suggests that luteolin may exert cross-systemic anti-inflammatory, anti-tumor, immunomodulatory, and tissue-protective effects by acting on diverse molecular nodes involved in key biological processes.</p>
<fig position="float" id="fig8">
<label>Figure 8</label>
<caption>
<p>Network construction and classification analysis of diseases associated with core targets of Luteolin. <bold>(A&#x2013;C)</bold> 10 core target-associated diseases Venn analysis. <bold>(A)</bold> TNF, TP53, IL-1B, STAT3, and EGFR associated diseases Venn analysis acquired 330 diseases. <bold>(B)</bold> CASP3, FN1, HSP90AA1, ERBB2, and JUN associated diseases Venn analysis acquired 102 diseases. <bold>(C)</bold> 330 diseases and 102 diseases Venn analysis acquired 91 diseases. <bold>(D)</bold> Luteolin-core target-diseases network map. Purple represents luteolin, green represents core target, blue represents diseases, yellow represents diseases classification.</p>
</caption>
<graphic xlink:href="fnut-13-1758832-g008.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Venn diagrams and a network diagram illustrating gene interactions and associations with diseases. Panels A and B show overlap among genes (TP53, TNF, etc.). Panel C displays overlaps between two specific gene groups. Panel D presents a circular network linking Luteolin with genes (TP53, IL1B) and various diseases, such as tumors and immune system disorders.</alt-text>
</graphic>
</fig>
<p>As a whole, luteolin&#x2019;s broad coverage across diseases and the concentrated distribution of its core targets in key biological processes reflect its potential value as a natural dietary flavonoid for intervening in multisystem diseases. This network characteristic not only supports its potential application to promoting nutritional health and preventing chronic diseases. It also provides crucial evidence for subsequent mechanism studies and multi-indication drug development.</p>
</sec>
</sec>
<sec sec-type="discussion" id="sec15">
<label>4</label>
<title>Discussion</title>
<p>This study comprehensively reveals the knowledge structure, research hotspots, and future development trends of luteolin research from 2000 to 2025 through systematic bibliometric and network pharmacology analyses. Overall, luteolin research exhibits sustained growth, with expanding research themes and significantly deepening mechanistic investigations. Its dual status as both a food and a medicinal substance grants it unique advantages in nutrition science, functional foods, and chronic disease prevention. This aligns closely with recent trends in nutritional health research emphasizing natural bioactive compounds, diet interventions, and precision nutrition.</p>
<sec id="sec16">
<label>4.1</label>
<title>Luteolin research on the rise: extending from basic pharmacology to nutritional science</title>
<p>Luteolin, as a vital dietary compound, has seen a sustained increase in the number of published papers, indicating growing recognition of its potential value in nutrition, metabolic health, and chronic disease prevention. The accelerated growth in publications since 2010, particularly the significant surge in 2021, may be closely linked to the recent research boom on natural bioactive substances and food-medicine dual-use substances for health promotion. Studies indicate that oral luteolin administration reduces bone loss in ovariectomized rats (<xref ref-type="bibr" rid="ref25">25</xref>). In Wistar rats, oral luteolin protects the kidneys from lead acetate-induced nephrotoxicity through antioxidant, anti-inflammatory, and anti-apoptotic mechanisms (<xref ref-type="bibr" rid="ref26">26</xref>). Furthermore, luteolin has been demonstrated to alleviate mucosal tissue damage caused by enterocolitis during cancer treatment (<xref ref-type="bibr" rid="ref27">27</xref>). The gray prediction model predicts a sustained rapid upward trend in this field over the next 3 years. This predicts sustained research interest in luteolin and highlights its long-term potential in nutrition and health sciences.</p>
</sec>
<sec id="sec17">
<label>4.2</label>
<title>Research themes have expanded from fundamental mechanisms to multisystem health effects</title>
<p>Journal and co-citation analysis suggests that core journals for luteolin research are predominantly concentrated in the food science and life sciences, maintaining substantial academic influence. This aligns with existing studies emphasizing luteolin&#x2019;s prominence in food chemistry, pharmacology, and biomedicine (<xref ref-type="bibr" rid="ref28">28</xref>, <xref ref-type="bibr" rid="ref29">29</xref>). The co-citation structure further revealed a distinctly multidisciplinary research foundation for luteolin. Mechanistic studies on its anti-inflammatory effects (<xref ref-type="bibr" rid="ref30">30</xref>), immunomodulation (<xref ref-type="bibr" rid="ref31">31</xref>), and antitumor activity (<xref ref-type="bibr" rid="ref32">32</xref>) have reached relative maturity, providing robust molecular-level evidence for its biological activity. Bradford&#x2019;s zoning analysis suggests that journals in food science and nutrition constitute the core knowledge output platforms in this field. This reflects a transition in luteolin research from basic exploration at the single-compound level toward application-oriented nutritional science (<xref ref-type="bibr" rid="ref31">31</xref>).</p>
<p>Meanwhile, the knowledge flow pathways revealed by the journal dual-map overlay indicate that the research focus is expanding beyond traditional molecular biology and immunology into more applied fields such as nutrition, metabolic health, and environmental toxicology. Existing studies demonstrate that luteolin can improve insulin sensitivity, regulate lipid metabolism, and restore energy homeostasis (<xref ref-type="bibr" rid="ref33">33</xref>). Furthermore, it plays a significant role in protecting the intestinal barrier (<xref ref-type="bibr" rid="ref34">34</xref>), reducing food-induced oxidative damage (<xref ref-type="bibr" rid="ref35">35</xref>), and alleviating toxin-induced inflammation (<xref ref-type="bibr" rid="ref36">36</xref>). Overall, luteolin research has entered a critical phase of transitioning from fundamental mechanisms to multi-system health effects. It is increasingly recognized as a key dietary bioactive compound with potential for nutritional intervention. This lays a solid scientific foundation for functional food development, prevention of inflammation-related diseases, and nutritional regulation of metabolic disorders.</p>
</sec>
<sec id="sec18">
<label>4.3</label>
<title>Deepening of molecular mechanism research: inflammation, apoptosis, and metabolic regulation as key axes</title>
<p>Keyword co-occurrence and burst analyses indicate that apoptosis, oxidative stress, and inflammation remain core mechanisms in luteolin research, consistent with extensive <italic>in vivo</italic> and <italic>in vitro</italic> evidence (<xref ref-type="bibr" rid="ref37">37</xref>). Research indicates that luteolin may exerts synergistic anti-inflammatory and cytoprotective effects by regulating multiple key signaling pathways, including AMPK-PPAR&#x03B3; (<xref ref-type="bibr" rid="ref38">38</xref>), IL-33-ST2 (<xref ref-type="bibr" rid="ref39">39</xref>), and TLR4/NF-&#x03BA;B (<xref ref-type="bibr" rid="ref40">40</xref>), thereby improving immune responses, inflammatory progression and related functional barriers (<xref ref-type="bibr" rid="ref41">41</xref>). A study indicates that luteolin prevents colon cancer development by inhibiting macrophage polarization toward the M1 phenotype. Specifically, it suppresses M1 macrophage polarization by acting on the IL-6/STAT3 signaling pathway, thereby inhibiting the proliferation, migration, and invasive capabilities of colon cancer cells (<xref ref-type="bibr" rid="ref42">42</xref>). Further research indicates that luteolin significantly enhances mitochondrial membrane potential depolarization in bladder cancer cells. The promotes the release of cytochrome C and SMAC/DIABLO from the mitochondria into the cytoplasm. This activates the mitochondrial-mediated intrinsic apoptosis pathway. Concurrently, it markedly downregulates the expression of anti-apoptotic proteins Bcl-xl and Mcl-1 while inducing endoplasmic reticulum stress responses, ultimately suppressing bladder cancer cell activity and promoting apoptosis (<xref ref-type="bibr" rid="ref43">43</xref>). These consistently emerging keywords not only suggest a high degree of consensus among researchers regarding fundamental molecular mechanisms but also reinforce luteolin&#x2019;s potential value as a dietary flavonoid in preventing nutrition-related diseases and promoting health.</p>
<p>Notably, recent keyword bursts of terms such as reactive oxygen species, cycle arrest, and combinations in recent years indicate that research is increasingly extending toward more refined regulation of cellular fate and information networks. Existing studies demonstrate that luteolin can induce cell cycle arrest by modulating key nodes including CDK2, p21, and p53 (<xref ref-type="bibr" rid="ref44">44</xref>, <xref ref-type="bibr" rid="ref45">45</xref>), thereby inhibiting abnormally proliferating cells, including tumor cells and inflammation-associated cell subpopulations. Concurrently, the potential synergistic effects of luteolin combined with other drugs or nutritional factors in metabolic disorders and tumor therapy are gaining increasing attention (<xref ref-type="bibr" rid="ref46 ref47 ref48">46&#x2013;48</xref>).</p>
<p>Cluster analysis further highlights this trend. For instance, the &#x201C;#0 TRAIL sensitivity,&#x201D; &#x201C;#7 kinase activity,&#x201D; and &#x201C;#16 cell cycle&#x201D; clusters all point to anti-tumor mechanisms involving apoptosis regulation, TRAIL pathway activation, and protein kinase signaling networks. Luteolin enhances pancreatic cancer cells&#x2019; sensitivity to TRAIL-mediated apoptosis and inhibits cell proliferation by downregulating miR-301-3p expression in pancreatic ductal adenocarcinoma cells, thereby upregulating its target gene caspase-8 (<xref ref-type="bibr" rid="ref49">49</xref>). Wu et al. (<xref ref-type="bibr" rid="ref50">50</xref>) further demonstrated that luteolin enhances non-small cell lung cancer sensitivity to TRAIL-induced apoptosis by upregulating death receptor DR5, inducing Drp1-dependent mitochondrial fission, and activating the JNK signaling pathway. These findings collectively highlight luteolin&#x2019;s significant role in anti-tumor nutritional research.</p>
<p>Meanwhile, clusters such as &#x201C;#4 insulin sensitivity,&#x201D; &#x201C;#13 cardioprotective effect,&#x201D; and &#x201C;#8 neuroprotective role&#x201D; highlight its potential for nutrition-related chronic diseases. Evidence suggests that luteolin improves insulin signaling pathways, reduces myocardial oxidative damage, and modulates neuroinflammation, thereby demonstrating significant effects on metabolic syndrome (<xref ref-type="bibr" rid="ref51">51</xref>), cardiovascular diseases, and neurodegenerative disorders (<xref ref-type="bibr" rid="ref52">52</xref>). Huang&#x2019;s research indicates that luteolin improves metabolic disorders and alleviates diabetic nephropathy progression by inhibiting NLRP3-TGF-&#x03B2;-mediated inflammatory and fibrotic signaling through AMPK (<xref ref-type="bibr" rid="ref51">51</xref>). Furthermore, luteolin effectively ameliorates cognitive deficits in Alzheimer&#x2019;s disease by suppressing A&#x03B2;-induced oxidative stress through a PPAR&#x03B3;-dependent mechanism, thereby repairing mitochondrial damage and reducing neuronal apoptosis (<xref ref-type="bibr" rid="ref10">10</xref>). These findings are indicative of a gradual expansion of luteolin&#x2019;s sphere of action from localized cellular effects to broader systemic regulation, paralleling the current research shift from &#x201C;single-target pharmacology&#x201D; to &#x201C;multisystem nutritional modulation.&#x201D;</p>
<p>In general, molecular mechanisms of luteolin are being studied more deeply from classical anti-inflammatory pathways to integrated signaling pathways and systemic metabolic improvement. This trend not only reinforces its biological value as a dietary flavonoid for health promotion. It also provides a solid theoretical foundation for its application in nutritional interventions for chronic diseases.</p>
</sec>
<sec id="sec19">
<label>4.4</label>
<title>Multi-target, multi-pathway, multi-system effects reveal the nutraceutical essence of luteolin</title>
<p>Network pharmacology analysis further reveals that luteolin exhibits typical nutraceutical characteristics, characterized by extensive target coverage and coordinated regulation across multiple signaling networks, thereby conferring robust systemic modulatory capacity. For instance, in the mechanism of luteolin&#x2019;s anti-non-small cell lung cancer activity, network pharmacology analysis identified 47 potential targets, including core genes such as TP53, EGFR, AKT1, and TNF (<xref ref-type="bibr" rid="ref53">53</xref>). Furthermore, in an osteoporosis model, combined network pharmacology and experimental validation studies revealed that luteolin targets TP53, AKT1, STAT3, and others, regulating signaling pathways such as PI3K&#x2013;Akt, TNF, and p53 to promote osteogenesis and inhibit bone resorption (<xref ref-type="bibr" rid="ref25">25</xref>). Another study on dry age-related macular degeneration revealed that through protein&#x2013;protein interaction network analysis, TP53, TNF, STAT3, IL6, and others were identified as key targets for luteolin, supporting its role in anti-inflammation, anti-stress, and metabolic homeostasis (<xref ref-type="bibr" rid="ref54">54</xref>). In oncology, a network pharmacology and transcriptomics study on hepatocellular carcinoma identified luteolin-regulated targets associated with inflammation, cell migration, cell cycle, and apoptosis, involving pathways such as EGFR, STAT3, and TP53 (<xref ref-type="bibr" rid="ref55">55</xref>).</p>
<p>It is noteworthy that although the core targets identified by network pharmacology analysis share certain commonalities across multiple tumors, their specific modes of action may exhibit variability depending on the molecular context of the tumor. In non-small cell lung cancer driven primarily by EGFR, luteolin can inhibit cancer cell progression by targeting the HGF-MET-AKT pathway (<xref ref-type="bibr" rid="ref56">56</xref>). Conversely, in glioblastoma, luteolin combined with erlotinib binds to the ATP-binding site of the EGFR receptor to suppress its expression, thereby reducing the phosphorylation levels of downstream molecules AKT, NF-&#x03BA;B, and STAT3, effectively inhibiting malignant cell proliferation (<xref ref-type="bibr" rid="ref57">57</xref>). In contrast, within the context of inflammation-associated tumors such as colorectal cancer, luteolin not only improves the tumor microenvironment by inhibiting pro-inflammatory signaling pathways and modulating T-cell and macrophage function, but also induces ferroptosis by targeting GPX4, thereby exerting unique anti-cancer effects (<xref ref-type="bibr" rid="ref13">13</xref>, <xref ref-type="bibr" rid="ref32">32</xref>). Furthermore, in tumors with frequent TP53 mutations, luteolin assembles in structural clefts in the TP53 Y220C mutation region. This stabilizes the binding domain of mutant TP53 Y220C and restores it to wild-type levels (<xref ref-type="bibr" rid="ref58">58</xref>).</p>
<p>From an immunoregulatory perspective, luteolin alleviates inflammatory responses in acute pneumonia and colitis by targeting pro-inflammatory factors such as IL-1&#x03B2;, IL-6, and TNF. It accomplishes this by inhibiting the EGFR/MAPK/PI3K-AKT and NF-&#x03BA;B signaling pathways, while inducing macrophage polarization from M1 to M2 (<xref ref-type="bibr" rid="ref9">9</xref>, <xref ref-type="bibr" rid="ref30">30</xref>). Lu et al. (<xref ref-type="bibr" rid="ref59">59</xref>) further demonstrated that luteolin effectively mitigates TNF-&#x03B1;-induced inflammation damage in human microvascular endothelial cells via the Akt/MAPK/NF-&#x03BA;B pathway. Similarly, the STAT3 and IL-17 signaling axes play pivotal regulatory roles in macrophage inflammatory responses and M1/M2 polarization (<xref ref-type="bibr" rid="ref59">59</xref>, <xref ref-type="bibr" rid="ref60">60</xref>), and are beneficial for regulating T cell subset imbalances (<xref ref-type="bibr" rid="ref61">61</xref>) and maintaining Treg-related immune tolerance states (<xref ref-type="bibr" rid="ref62">62</xref>). This comprehensive regulatory mechanism governs immune cell function and immune cytokine production. It provides substantial theoretical support for the potential application of luteolin in nutrition-immunity-related diseases such as inflammation-related conditions.</p>
<p>Furthermore, from a bibliometric perspective, luteolin research keywords have evolved from early macro-level descriptions such as &#x201C;antioxidant&#x201D; and &#x201C;free radicals&#x201D; toward mechanism-oriented terms like &#x201C;apoptosis,&#x201D; &#x201C;inflammation,&#x201D; and &#x201C;kinase activity.&#x201D; This shift reflects the deepening research paradigm within the field, transitioning from macro-functional observations toward molecular mechanism analysis. Neurodegenerative diseases trigger oxidative stress and inflammation triggered by ROS accumulation. Instead, they are amplified through the activation of a cascade of MAPK/JNK, PI3K&#x2013;Akt, and NF-&#x03BA;B kinase signaling pathways, thereby regulating neuroinflammation, programmed cell death, and protein homeostasis imbalances (<xref ref-type="bibr" rid="ref52">52</xref>). Consequently, the earlier research focused on &#x2018;free radicals&#x2019; and antioxidant imbalances may be regarded as a phenotypic description of upstream stress signals. In contrast, current studies centered on kinase activity and signaling networks reveal downstream molecular regulatory essence.</p>
<p>Collectively, these findings highlight the recurrent involvement of core nodes including TP53, TNF, IL1B/IL6, STAT3, and EGFR across diverse disease models, underscoring their central roles within luteolin regulated signaling networks. This suggests their pivotal roles in luteolin&#x2019;s regulation of chronic inflammation, metabolic imbalance, and tumorigenesis. Additionally, pathway analysis encompasses the p53 pathway (<xref ref-type="bibr" rid="ref63">63</xref>), the PI3K&#x2013;Akt pathway (<xref ref-type="bibr" rid="ref64">64</xref>, <xref ref-type="bibr" rid="ref65">65</xref>), and the TNF signaling pathway (<xref ref-type="bibr" rid="ref59">59</xref>). These pathways are closely associated with inflammation, immunity, apoptosis, and metabolic homeostasis (<xref ref-type="bibr" rid="ref11">11</xref>, <xref ref-type="bibr" rid="ref66">66</xref>, <xref ref-type="bibr" rid="ref67">67</xref>).</p>
<p>Disease network analysis further suggests that luteolin may potentially intervene in neurological disorders, circulatory system diseases, digestive system diseases, respiratory system diseases, and multiple tumor types, highlighting its potential as a nutritional compound capable of coordinated regulation across multiple biological systems. Collectively, these findings support luteolin&#x2019;s nutraceutical properties.</p>
</sec>
<sec id="sec20">
<label>4.5</label>
<title>Application prospects: from functional nutrition to advanced delivery and synergistic strategies</title>
<p>Integrated results from bibliometrics and network pharmacology, future research and applications on luteolin exhibit multidimensional expansion trends. Its widespread presence in dietary sources and prominent anti-inflammatory and antioxidant activities make it an ideal natural ingredient for functional food and dietary supplement development (<xref ref-type="bibr" rid="ref68">68</xref>). Regarding chronic inflammation and metabolic-related diseases, network pharmacology analysis reveals luteolin&#x2019;s broad regulatory capacity across multiple molecular pathways in enhancing insulin sensitivity, regulating lipid metabolism, and alleviating inflammation, demonstrating its significant potential as a nutritional intervention strategy for diabetes and metabolic syndrome (<xref ref-type="bibr" rid="ref35">35</xref>). Furthermore, luteolin&#x2019;s strong association with apoptosis and cell cycle arrest targets offers novel directions for nutritional regulation and adjuvant therapy in tumorigenesis and progression (<xref ref-type="bibr" rid="ref69">69</xref>). Concurrently, the latest keyword evolution and disease association networks indicate rising research interest in luteolin&#x2019;s role in neurodegenerative diseases and cardiovascular health (<xref ref-type="bibr" rid="ref70">70</xref>).</p>
<p>Despite extensive research revealing luteolin&#x2019;s multifaceted biological actions in the anti-inflammatory, immunomodulatory, and anti-tumor contexts, its clinical translation remains constrained by inadequate bioavailability. Luteolin&#x2019;s poor water solubility, low oral absorption rate, and limited <italic>in vivo</italic> stability prevent it from achieving effective concentrations comparable to those observed in experimental settings (<xref ref-type="bibr" rid="ref71">71</xref>). This significantly constrains its potential for nutritional intervention, co-creation and translation. Furthermore, current mechanistic studies on luteolin focus on cellular models or animal experiments. These studies have dosage ranges that differ from human dietary intake or functional food applications. This underscores that isolated target and pathway predictions alone cannot substantiate their clinical or nutritional value. Consequently, there is an urgent need to integrate delivery systems and formulation optimization to bridge the gap between mechanistic research and practice application. Notably, synergistic and composite delivery systems are emerging as a key trend to enhance its bioavailability and therapeutic efficacy. This includes constructing nanocomposites with multiple drugs or materials (<xref ref-type="bibr" rid="ref72">72</xref>), hydrogel delivery systems (<xref ref-type="bibr" rid="ref73">73</xref>), and synergistic antitumor effects with paclitaxel (<xref ref-type="bibr" rid="ref74">74</xref>). These approaches open broader avenues for its deepening application in precision nutrition and nutritional therapy.</p>
</sec>
<sec id="sec21">
<label>4.6</label>
<title>Limitations and future prospects</title>
<p>Although this study is relatively comprehensive, certain limitations remain: the bibliometric findings are constrained by database scope and may omit some grey literature; the network pharmacology analysis is predictive in nature, and its results require validation through additional <italic>in vitro</italic> and <italic>in vivo</italic> experiments; furthermore, this study has not yet conducted an in-depth exploration of key nutritional evaluation issues such as dose&#x2013;response relationships, safety, and bioavailability&#x2014;all of which represent crucial directions for future translational research on luteolin. Looking ahead, future research should integrate clinical nutrition, gut microbiome studies, metabolomics, and precision nutrition models to elucidate luteolin&#x2019;s biological mechanisms and optimize dosage strategies at the system level. This will advance its practical application to functional food development and nutritional interventions for chronic diseases.</p>
</sec>
</sec>
<sec sec-type="conclusions" id="sec22">
<label>5</label>
<title>Conclusion</title>
<p>This study systematically reveals the growth trends, knowledge structure, and key biological mechanisms of luteolin research from 2000 to 2025 through bibliometrics and network pharmacology. Results indicate that luteolin research continues to gain momentum, with themes expanding into multi-system health domains such as metabolic homeostasis, immune regulation, and tumor prevention and treatment. Luteolin modulates inflammation, apoptosis, oxidative stress, and metabolism-related pathways through coordinated regulation of key molecular nodes, including TP53, TNF, STAT3, EGFR, and others, thereby influencing neurological, cardiovascular, metabolic, and oncological diseases (<xref ref-type="fig" rid="fig9">Figure 9</xref>). Overall, luteolin exhibits broad and integrated regulatory effects across multiple signaling networks, demonstrating broad application potential in functional food development and nutritional interventions for chronic diseases. Future research should further advance in dosage, bioavailability, and clinical evidence to facilitate translational applications.</p>
<fig position="float" id="fig9">
<label>Figure 9</label>
<caption>
<p>Conceptual model of potential mechanisms of action of luteolin.</p>
</caption>
<graphic xlink:href="fnut-13-1758832-g009.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">Diagram showing the relationship between bibliometric hotspots, predicted molecular mechanisms, and multisystem effects of luteolin. Bibliometric hotspots include apoptosis and metabolism. Core targets such as TP53 and TNF are linked to key pathways like p53 signaling. Multisystem effects include tumor-related mechanisms and immune system diseases. A silhouetted male and female figure is centrally placed between these elements.</alt-text>
</graphic>
</fig>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="sec23">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref rid="SM1" ref-type="supplementary-material">Supplementary material</xref>, further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec sec-type="author-contributions" id="sec24">
<title>Author contributions</title>
<p>HG: Writing &#x2013; review &#x0026; editing, Conceptualization, Investigation, Writing &#x2013; original draft, Project administration. XT: Software, Data curation, Visualization, Writing &#x2013; original draft. HW: Methodology, Writing &#x2013; original draft, Software. KW: Software, Visualization, Writing &#x2013; original draft. QH: Formal analysis, Writing &#x2013; review &#x0026; editing. YG: Visualization, Software, Writing &#x2013; original draft. XG: Investigation, Writing &#x2013; original draft, Validation, Funding acquisition. ZL: Conceptualization, Funding acquisition, Writing &#x2013; review &#x0026; editing. XW: Writing &#x2013; original draft, Resources. BW: Methodology, Writing &#x2013; original draft, Data curation. LZ: Investigation, Funding acquisition, Writing &#x2013; review &#x0026; editing. YW: Funding acquisition, Writing &#x2013; original draft. HL: Writing &#x2013; review &#x0026; editing, Supervision, Formal analysis. CZ: Writing &#x2013; review &#x0026; editing, Investigation, Writing &#x2013; original draft.</p>
</sec>
<ack>
<title>Acknowledgments</title>
<p>We sincerely thank all individuals and organizations whose support and contributions made this review possible. First and foremost, we are deeply grateful to all team members involved in the research and analysis&#x2014;their dedication and expertise were fundamental to the completion of this study. We also extend our heartfelt appreciation to our colleagues and friends for their valuable support and constructive feedback throughout the research process. Their insights greatly enhanced the quality of this work. Finally, we gratefully acknowledge the foundations and institutions that provided funding for this study; their support was indispensable to its successful completion.</p>
</ack>
<sec sec-type="COI-statement" id="sec25">
<title>Conflict of interest</title>
<p>The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="ai-statement" id="sec26">
<title>Generative AI statement</title>
<p>The author(s) declared that Generative AI was not used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p>
</sec>
<sec sec-type="disclaimer" id="sec27">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec sec-type="supplementary-material" id="sec28">
<title>Supplementary material</title>
<p>The Supplementary material for this article can be found online at: <ext-link xlink:href="https://www.frontiersin.org/articles/10.3389/fnut.2026.1758832/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/fnut.2026.1758832/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Data_Sheet_1.ZIP" id="SM1" mimetype="application/zip" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
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<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/3011828/overview">Koushik Sen</ext-link>, Government of West Bengal, India</p>
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