Complexity of vaginal microflora as analyzed by PCR denaturing gradient gel electrophoresis in a patient with recurrent bacterial vaginosis.
Bibliographic record
Abstract
OBJECTIVE: Gardnerella vaginalis has long been the most common pathogen associated with bacterial vaginosis (BV). We aimed to test our hypothesis that symptoms and signs of BV do not necessarily indicate colonization by this organism, and often will not respond to standard metronidazole or clindamycin treatment. METHODS: Using a relatively new molecular tool, PCR denaturing gradient gel electrophoresis (DGGE), the vaginal microflora of a woman with recalcitrant signs and symptoms of BV was investigated over a 6-week timeframe. RESULTS: The vagina was colonized by pathogenic enterobacteriaceae, staphylococci and Candida albicans. The detection of the yeast by PCR-DGGE is particularly novel and enhances the ability of this tool to examine the true nature of the vaginal microflora. The patient had not responded to antifungal treatment, antibiotic therapy targeted at anaerobic Gram-negative pathogens such as Gardnerella, nor daily oral probiotic intake of Lactobacillus rhamnosus GG. The failure to find the GG strain in the vagina indicated it did not reach the site, and the low counts of lactobacilli demonstrated that therapy with this probiotic did not appear to influence the vaginal flora. CONCLUSIONS: BV is not well understood in terms of its causative organisms, and further studies appear warranted using non-culture, molecular methods. Only when the identities of infecting organisms are confirmed can effective therapy be devized. Such therapy may include the use of probiotic lactobacilli, but only using strains which confer a benefit on the vagina of pre- and postmenopausal women.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".