Additional file 1 of Quantitative profiling of the vaginal microbiota improves resolution of the microbiota-immune axisLink copied to clipboard!
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- Description:
- Supplementary Material 1: Supplementary methods. Figure S1: Variation in total bacterial load and vaginal soluble immune factors across CST-IV subgroups. Figure S2: BV-associated bacteria drive the association between total bacterial load and immune factors within CST-III. Figure S3: Genital immune milieu cluster tightly with vaginal microbiota composition. Figure S4: Genital immune milieu is closely tied to vaginal microbiota composition in an independent, Uganda-based confirmatory cohort. Table S1: Association between vaginal CST and sociodemographic variables. Table S2: The absolute abundance of BV-associated bacteria, including G. vaginalis and F. vaginae, but not L. iners, were positively associated with sE-cad and IL-1α. Table S3: Nugent scores of women misclassified by the logistic regression model predicting Nugent BV with bacterial load in the SWOP cohort. Table S4: CST subgroups of women misclassified by the logistic regression model predicting molecular BV with bacterial load in the SWOP cohort. Table S5: Comparison of linear regression models predicting soluble immune factors with different vaginal microbiota characterization metrics. Table S6: Comparison of sociodemographic characteristics based on availability of complete immune data in the SWOP cohort. Table S7: Association between PAM immune cluster and sociodemographic variables. Table S8: Sociodemographic factors for Uganda-based confirmatory cohort. N = 61. Table S9: Nugent scores of women misclassified by the logistic regression model predicting Nugent BV with bacterial load in the Uganda-based confirmatory cohort. Table S10: Comparison of linear regression models predicting soluble immune factors with different vaginal microbiota characterization metrics in the confirmatory Uganda-based confirmatory cohort. Table S11: Primer and probe sequences for qPCR assays quantifying total bacterial load.
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- Author(s):
- Armstrong, Eric, Liu, RachelUniversity of Toronto Toronto General Hospital, Pollock, JamesUniversity of Toronto, Huibner, SanjaUniversity of Toronto, Udayakumar, SujiUniversity of Toronto, Irungu, ErastusUniversity of Toronto, Ngurukiri, PaulinePartners for Health and Development in Africa, Muthoga, PeterPartners for Health and Development in Africa, Adhiambo, WendyPartners for Health and Development in Africa, Yegorov, SergeyPartners for Health and Development in Africa, Kimani, JoshuaMcMaster University, Beattie, TaraPartners for Health and Development in Africa, Coburn, BryanLondon School of Hygiene & Tropical Medicine, and Kaul, RupertUniversity of Toronto Toronto General HospitalUniversity of Toronto Toronto General Hospital
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- Source Repository:
- Figshare
- Publisher(s):
- figshare
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- License:
- Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode
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- URL:
- https://springernature.figshare.com/articles/dataset/Additional_file_1_of_Quantitative_profiling_of_the_vaginal_microbiota_improves_resolution_of_the_microbiota-immune_axis/28348685
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- Publication date:
- 2025
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- Subjects:
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- Identifier:
- https://doi.org/10.6084/m9.figshare.28348685
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Citation
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- APA Citation:
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Armstrong, E., Liu, R., Pollock, J., Huibner, S., Udayakumar, S., Irungu, E., Ngurukiri, P., Muthoga, P., Adhiambo, W., Yegorov, S., Kimani, J., Beattie, T., Coburn, B., & Kaul, R. (2025). Additional file 1 of Quantitative profiling of the vaginal microbiota improves resolution of the microbiota-immune axis [Data set]. Figshare. https://springernature.figshare.com/articles/dataset/Additional_file_1_of_Quantitative_profiling_of_the_vaginal_microbiota_improves_resolution_of_the_microbiota-immune_axis/28348685Citation copied to clipboard
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