A Description of the THRIVE (The Study of Host-Bacterial Relationships and Immune Function in Different Vaginal Environments) Bacterial Vaginosis Observational Study
Bibliographic record
Abstract
Objectives Bacterial vaginosis (BV) contributes to poor reproductive health and is characterized by a displacement of Lactobacillus in the vaginal microbiome. However, treatment for BV is limited to antibiotics and half of the women treated experience recurrence within a year. THRIVE (The Study of Host-Bacterial Relationships and Immune Function in Different Vaginal Environments) is a prospective study in Winnipeg, Manitoba, Canada, which is designed to capture the daily variation of the microbiome and host mucosal immunity during treatment. The objective of this study is to identify host and bacterial factors that associate with vaginal microbiome stability to better inform therapeutic interventions. Methods Women treated for BV, and controls, are followed for 6 months collecting daily vaginal swabs and monthly questionnaires. Comprehensive mucosal sampling, including swabs, cytobrushes, biopsies, and blood are collected at baseline, months 1 and 6 post-enrolment. Results We performed analysis on the first 52 participants, (19 BV+, 33 BV–). Molecular profiling by 16s RNA sequencing showed 20 women with non- Lactobacillus- dominant microbiomes and 32 with Lactobacillus- dominant microbiomes, with increased microbial diversity in non- Lactobacillus- dominant microbiomes ( P = 3.1E-05). A pilot analysis in 2 participants demonstrates that multi-omics profiling of self-collected daily swabs provides high-quality data identifying 73 bacterial species, 1773 mucosal proteins and 117 metabolites. Initial flow cytometry analysis showed an increased cluster of differentiation (CD)4+ T cells and neutrophil activation (CD11b+CD62L neg/dim ) in the positive participant at baseline, while after treatment these shifted and resembled the control participant. Conclusions This study provides a framework to comprehensively investigate the kinetics of vaginal mucosal microbiome alterations, providing further insight into host and molecular features predicting BV recurrence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".