The Two-Way Interaction between the Molecules That Cause Vaginal Malodour and Lactobacilli: An Opportunity for Probiotics
Bibliographic record
Abstract
Vaginal malodour is a sign of dysbiosis. The biogenic amines (BAs) cadaverine, putrescine and tyramine are known to be causative compounds. Recent reports suggest these compounds produced by pathogens might have a role beyond causing malodour; namely inhibiting the growth of lactobacilli bacteria that are crucial in the maintenance of vaginal homeostasis. The aim of this study was to identify whether certain lactobacilli strains could reduce BAs and to evaluate how Lactobacillus species were affected by these compounds. Using LC–MS and HPLC-UV, five Lactobacillus crispatus strains were identified as being capable of significantly reducing BAs from the media under in vitro conditions. Through 16S rRNA gene sequencing of vaginal swabs exposed to Bas, cadaverine was found to reduce the relative abundance of lactobacilli. When L. crispatus was exposed to media supplemented with BAs with an HCl adjusted lower pH, its growth was enhanced, demonstrating the relevance of the maintenance of an acidic vaginal environment. If strains are to be developed for probiotic application to alleviate bacterial vaginosis and other conditions affecting large numbers of women worldwide, their ability to adapt to Bas and regulate pH should be part of the experimentation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".