{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T02:53:15Z","timestamp":1781146395558,"version":"3.54.1"},"reference-count":49,"publisher":"The Royal Society","issue":"2011","license":[{"start":{"date-parts":[[2023,11,29]],"date-time":"2023-11-29T00:00:00Z","timestamp":1701216000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2023,11,29]],"date-time":"2023-11-29T00:00:00Z","timestamp":1701216000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Thomas M. and Joan C. 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R. Soc. B."],"published-print":{"date-parts":[[2023,11,29]]},"abstract":"<jats:p>\n                    Diverse and non-\n                    <jats:italic>Lactobacillus<\/jats:italic>\n                    -dominated vaginal microbial communities are associated with adverse health outcomes such as preterm birth and the acquisition of sexually transmitted infections. Despite the importance of recognizing and understanding the key risk-associated features of these communities, their heterogeneous structure and properties remain ill-defined. Clustering approaches are commonly used to characterize vaginal communities, but they lack sensitivity and robustness in resolving substructures and revealing transitions between potential sub-communities. Here, we address this need with an approach based on mixed membership topic models. Using longitudinal data from cohorts of pregnant and non-pregnant study participants, we show that topic models more accurately describe sample composition, longitudinal changes, and better predict the loss of\n                    <jats:italic>Lactobacillus<\/jats:italic>\n                    dominance. We identify several non-\n                    <jats:italic>Lactobacillus<\/jats:italic>\n                    -dominated sub-communities common to both cohorts and independent of reproductive status. In non-pregnant individuals, we find that the menstrual cycle modulates transitions between and within sub-communities, as well as the concentrations of half of the cytokines and 18% of metabolites. Overall, our analyses based on mixed membership models reveal substructures of vaginal ecosystems which may have important clinical and biological associations.\n                  <\/jats:p>","DOI":"10.1098\/rspb.2023.1461","type":"journal-article","created":{"date-parts":[[2023,11,29]],"date-time":"2023-11-29T03:11:33Z","timestamp":1701227493000},"update-policy":"https:\/\/doi.org\/10.1098\/crossmark-policy","source":"Crossref","is-referenced-by-count":17,"title":["Sub-communities of the vaginal microbiota in pregnant and non-pregnant women"],"prefix":"10.1098","volume":"290","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9286-0590","authenticated-orcid":true,"given":"Laura","family":"Symul","sequence":"first","affiliation":[{"name":"Department of Statistics, Stanford University, 390 Jane Stanford Way, Stanford, CA 94305, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6467-0180","authenticated-orcid":false,"given":"Pratheepa","family":"Jeganathan","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, McMaster University, 1280 Main Street, West Hamilton, Ontario, Canada L8S 4K1"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6441-2931","authenticated-orcid":false,"given":"Elizabeth K.","family":"Costello","sequence":"additional","affiliation":[{"name":"Department of Medicine, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, CA 94305, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6029-0201","authenticated-orcid":false,"given":"Michael","family":"France","sequence":"additional","affiliation":[{"name":"Institute for Genome Sciences, University of Maryland School of Medicine, 670 W. 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