Lactobacillus Vaginal Microbiota of Women Attending a Reproductive Health Care Service in Benin City, Nigeria
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to determine whether Lactobacillus species found in African women differ substantially to those of white decent, described in previous studies. The vaginal microbiota play an important role in female health, and when the naturally dominant lactobacilli are displaced resulting in bacterial vaginosis (BV), the host is more at risk of acquiring sexually transmitted diseases, including HIV. METHODS: Vaginal samples were collected from 241 healthy, premenopausal Nigerian women, which were then Gram-stained for Nugent scoring. Microbial DNA was extracted, amplified using polymerase chain reaction (PCR) and Lactobacillus primers, and processed by denaturing gradient gel electrophoresis (DGGE). Lactobacillus species were identified by DNA sequencing and BLAST algorithm. RESULTS: Of the samples, 207 (85.8%) had PCR products for lactobacilli, whereas 34 (14.2%) showed absence of lactobacilli, which correlated to the BV Nugent scores. On sequencing of amplicons, 149 subjects (72%) had sequence homologies to lactobacilli. Most women (64%) were colonized by L. iners as the predominant strain, similar to previous findings in Canadian and Swedish women. L. gasseri was found in 7.3% samples, followed by L. plantarum, L. suntoryeus, L. crispatus, L. rhamnosus, and other species. CONCLUSION: The findings indicate that even with geographic, racial, and other differences, the predominant vaginal Lactobacillus species is similar to species in women from Northern countries.
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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 | 0.001 | 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) | 0.002 | 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".