Lactoflora species diversity in the vaginal microbiome of russian women
Bibliographic record
Abstract
Objective. To study the distribution and assess the quantitative prevalence of various types of lactobacilli in the vaginal biocenosis of women in the Russian Federation with various physiological and dysbiotic conditions of the pelvic organs. Material and methods. 840 vaginal smears received from 4 cities of the Russian Federation were tested for the presence of lactobacilli and their species specificity. Smears were taken both for medical reasons and from apparently healthy women undergoing preventive examination. Determination of the total content of bacteria and lactobacilli was carried out using quantitative PCR with SYBR Green. Detection and differentiation of a total of 12 species of lactobacilli potentially capable of colonizing the vaginal biocenosis were carried out using multiplex quantitative PCR using species-specific probes. Results. The most common species were L. iners (51.2%) and L. crispatus (43%), less common were L. jensenii (18.3%) and L. gasseri (7.9%). Other types of lactobacilli were found extremely rarely. In 75% of cases, only one species of lactobacilli predominated; in 25%, co-dominance of 2 to 4 species was observed. With a high proportion of lactobacilli in the total bacterial mass (>70%), the species L. crispatus was more common, and with a low proportion (<30%) - L. iners. However, no relationship was found between the age and region of residence of patients with the prevalence of Lactobacillus species. Conclusion. Only 4 species of lactobacilli: L. crispatus, L. iners, L. jensenii, L. gasseri, predominated in the vaginal biocenosis of 97% of study participants, who included both healthy women and women with various genital disorders.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".