Lactoflora Species Diversity in the Vaginal Microbiome of Russian Women
Bibliographic record
Abstract
Abstract The purpose of this study was to investigate the distribution and assess the quantitative prevalence of various species of lactobacilli in the vaginal biocenosis of women in the Russian Federation with various physiological and dysbiotic conditions of the pelvic organs. During the research, 840 vaginal smears obtained from four 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 checkups. Determination of the total content of bacteria and lactobacilli was carried out using quantitative polymerase chain reaction (PCR) with SYBR Green. Multiplex quantitative PCR using species-specific probes was used to detect and differentiate a total of 12 species of lactobacilli, potentially capable of colonizing the vaginal biocenosis. The most common species were L. iners (51.2%) and L. crispatus (43%), while L. jensenii (18.3%) and L. gasseri (7.9%) were seen less commonly. Other types of lactobacilli were sporadic. In 75% of cases, only one species of lactobacilli was predominant, whereas in 25% two to four species were co-dominating. Given a high proportion of lactobacilli in the total bacterial mass (>70%), L. crispatus was more common, while L. iners predominated if this proportion was low (<30%). However, no relationship was found between the age or region of residence of patients and the prevalence of Lactobacillus species. Only four species of lactobacilli, namely, L. crispatus, L. iners, L. jensenii, and L. gasseri, prevailed in the vaginal biocenosis of 97% of study participants, including both healthy women and women with various disorders of genital tract.
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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".