Lactobacilli and bacterial vaginosis. Species typing and analysis of content levels in the microbiome
Bibliographic record
Abstract
Objective. To examine changes in lactobacilli composition in the vaginal microbiocenosis associated with bacterial vaginosis (BV) and to assess the frequency of individual species. Material and methods. The study included 40 patients who presented with pathological discharge from the genital tract and had a confirmed diagnosis of BV based on the Amsel criteria. Quantitative assessment and typing of lactobacilli were performed using real-time PCR. Results. All women with BV were found to have lactobacilli present in quantities ranging from 0.01% to 100% of the total bacterial content. Analysis of the distribution of the lactobacilli index (LI), which indicates the proportion of lactobacilli in the total bacterial content, revealed three peaks corresponding to samples with low, intermediate, and high values. During the typing, all four species of lactobacilli characteristic of the vaginal microbiocenosis were identified: L. iners, L. crispatus, L. jensenii, and L. gasseri/L. johnsonii. No samples were found that lacked at least one of these species; L. crispatus and L. iners were the most frequently detected. Despite a general trend toward decreased LI levels in BV, patients were categorized into three subgroups based on their LI values: high, moderately reduced, and low. Conclusion. The positive correlation observed for L. iners and the negative correlation for L. crispatus with the degree of dysbiosis do not, in our opinion, reflect direct cause-and-effect relationships regarding BV, as these correlations are more closely associated with lactobacilli content than with clinical manifestations of the disease. A significant proportion of BV cases with the preservation of lactobacilli dominance suggests the existence of at least two forms of this syndrome. One of them, despite the presence of clinical symptoms, is not associated with a decrease in the number of lactobacilli in the vaginal microbiome.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".