Vaginal Lactobacillus crispatus persistence following application of a live biotherapeutic product: colonization phenotypes and genital immune impact
Bibliographic record
Abstract
Abstract Background Bacterial vaginosis (BV) increases HIV acquisition risk, potentially by eliciting genital inflammation. After BV treatment, the vaginal administration of LACTIN-V, a live biotherapeutic containing the Lactobacillus crispatus strain CTV-05, reduced BV recurrence and vaginal inflammation; however, 3 months after product cessation, CTV-05 colonization was only sustained in 48% of participants. Results This nested sub-study in 32 participants receiving LACTIN-V finds that 72% (23/32) demonstrate clinically relevant colonization (CTV-05 absolute abundance > 106 CFU/mL) during at least one visit while 28% (9/32) of women demonstrate colonization resistance, even during product administration. Immediately prior to LACTIN-V administration, the colonization-resistant group exhibited elevated vaginal microbiota diversity. During LACTIN-V administration, colonization resistance was associated with elevated vaginal markers of epithelial disruption and reduced chemokines, possibly due to elevated absolute abundance of BV-associated species and reduced L. crispatus. Colonization permissive women were stratified into sustained and transient colonization groups (31% and 41% of participants, respectively) based on CTV-05 colonization after cessation of product administration. These groups also exhibited distinct genital immune profiles during LACTIN-V administration. Conclusions The genital immune impact of LACTIN-V may be contingent on the CTV-05 colonization phenotype, which is in turn partially dependent on the success of BV clearance prior to LACTIN-V administration.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".