{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T06:04:48Z","timestamp":1780639488462,"version":"3.54.1"},"reference-count":59,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T00:00:00Z","timestamp":1780617600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000060","name":"National Institute of Allergy and Infectious Diseases","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000060","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Cell. Infect. Microbiol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Vaccine adjuvants enhance immune responses by boosting vaccine efficacy, reducing required doses, and improving long-term immunity. The Vaxjo database is a web-based resource that stores information on vaccine adjuvants, including their names, storage conditions, structures, preparation methods, components, functions, safety, and references. The original version of Vaxjo, released in 2012 with 103 vaccine adjuvants, has been expanded and modernized as Vaxjo 2.0, a significantly enhanced version.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In Vaxjo 2.0, newly identified adjuvants from biomedical literature retrieved through PubMed searches, as well as from the Vaccine Adjuvant Compendium (VAC) and AdjuvareDB, were added. To accelerate data collection and curation, we developed a vaccine adjuvant large language model (Vaxjo-LLM) system that automatically identifies and annotates new vaccine adjuvants and characterizes their mechanisms. The LLM-mined results were manually evaluated, annotated, and selectively included in the database to ensure quality.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Overall, Vaxjo 2.0 includes 448 vaccine adjuvants, organized into 16 distinct categories (e.g., mineral salt, emulsion, cytokine, peptide, and toll-like receptor (TLR) agonist vaccine adjuvants), all of which are represented in the Vaccine Ontology (VO) to streamline information storage and exchange. From 817 PubMed abstracts, Vaxjo-LLM identified mechanisms for 323 unique vaccine adjuvants across 16 mechanism families, including T cell activation\/polarization, dendritic cell activation, TLR signaling, inflammasome activation, cytokine signaling, B cell\/antibody production, and pattern recognition receptor (PRR) sensing. The mined information was subsequently manually reviewed to ensure consistency and accuracy. Based on this analysis, the mechanism profiles and clustering of the top 20 adjuvants were generated, revealing shared and distinct mechanistic signatures. For deeper mechanistic understanding, Vaxjo 2.0 further classified adjuvants based on PRR families, including TLRs, C-type lectin receptors, NOD-like receptors, and RIG-I-like receptors. Vaccine adjuvants were also categorized based on host immune response profiles, such as Th1\/Th2\/Th17-biased, Th1\/Th2-mixed, and Treg-biased immune profiles.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>\n                      The newly designed Vaxjo 2.0 web interface (\n                      <jats:ext-link>https:\/\/violinet.org\/vaxjo<\/jats:ext-link>\n                      ) provides an openly available and user-friendly platform for querying, visualizing, and analyzing vaccine adjuvant data.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fcimb.2026.1763384","type":"journal-article","created":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T05:40:29Z","timestamp":1780638029000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Vaxjo 2.0: An ontology- and large language model-powered knowledge base of vaccine adjuvants and mechanisms"],"prefix":"10.3389","volume":"16","author":[{"given":"Joshua","family":"Monickaraj","sequence":"first","affiliation":[{"name":"College of Literature, Science, and the Arts, University of Michigan","place":["Ann Arbor, MI, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hasin","family":"Rehana","sequence":"additional","affiliation":[{"name":"Department of Biomedical Sciences, University of North Dakota, School of Medicine and Health Sciences","place":["Grand Forks, ND, United States"]},{"name":"School of Electrical Engineering & Computer Science, University of North Dakota","place":["Grand Forks, ND, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ani","family":"Bernardi","sequence":"additional","affiliation":[{"name":"College of Literature, Science, and the Arts, University of Michigan","place":["Ann Arbor, MI, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuping","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Data Science, Chinese University of Hong Kong","place":["Shenzhen, Guangdong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Taiyu","family":"Lin","sequence":"additional","affiliation":[{"name":"Division of Life Science, The Hong Kong University of Science and Technology","place":["Hong Kong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Le","family":"Liu","sequence":"additional","affiliation":[{"name":"Marine College, Shandong University","place":["Weihai, Shandong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amogh","family":"Madireddi","sequence":"additional","affiliation":[{"name":"College of Engineering, University of Michigan","place":["Ann Arbor, MI, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leo","family":"Yeh","sequence":"additional","affiliation":[{"name":"Unit for Laboratory Animal Medicine, University of Michigan","place":["Ann Arbor, MI, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Zheng","sequence":"additional","affiliation":[{"name":"Unit for Laboratory Animal Medicine, University of Michigan","place":["Ann Arbor, MI, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junguk","family":"Hur","sequence":"additional","affiliation":[{"name":"Department of Biomedical Sciences, University of North Dakota, School of Medicine and Health Sciences","place":["Grand Forks, ND, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongqun","family":"He","sequence":"additional","affiliation":[{"name":"Unit for Laboratory Animal Medicine, University of Michigan","place":["Ann Arbor, MI, United States"]},{"name":"Department of Learning Health Sciences, University of Michigan Medical School","place":["Ann Arbor, MI, United States"]},{"name":"Center of Computational Medicine and Bioinformatics, University of Michigan Medical School","place":["Ann Arbor, MI, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,6,5]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1093\/narcan\/zcad060","article-title":"CanVaxKB: a web-based cancer vaccine knowledgebase","volume":"6","author":"Asfaw","year":"2024","journal-title":"NAR Cancer"},{"key":"B2","volume-title":"The description logic handbook: Theory, implementation and applications","author":"Baader","year":"2003"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1172\/jci202216","article-title":"The 2025 Nobel Prize in Physiology or Medicine - a bridge to peripheral immune tolerance","volume":"135","author":"Bluestone","year":"2025","journal-title":"J. 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