Resolution and Characterization of Distinct cpn60-Based Subgroups of Gardnerella vaginalis in the Vaginal Microbiota
Bibliographic record
Abstract
Bacterial vaginosis (BV), characterized by a shift of the vaginal microbiota from a Lactobacillus-dominated community to a dense biofilm containing a complex mixture of organisms, is an important risk factor in poor reproductive health outcomes. The Nugent score, based on Gram stain, is used to diagnose BV and Gardnerella vaginalis abundance in the sample is one factor determining Nugent score. A high Nugent score is indicative of BV but does not always correspond to the presence of clinical symptoms. G. vaginalis is recognized as a heterogeneous group of organisms, which can also be part of the normal, healthy vaginal microbiome. In addition, asymptomatic BV and non-Gardnerella types of BV are being recognized. In an attempt to resolve the heterogeneous group of G. vaginalis, a phylogenetic tree of cpn60 universal target sequences from G. vaginalis isolates was constructed that indicates the existence of four subgroups of G. vaginalis. This subdivision, supported by whole genome similarity calculation of representative strains using JSpecies, demonstrates that these subgroups may represent different species. The cpn60 subgroupings did not correspond with the Piot biotyping scheme, but did show consistency with ARDRA genotyping and sialidase gene presence. Isolates from all four subgroups produced biofilm in vitro. We also investigated the distribution of G. vaginalis subgroups in vaginal samples from Kenyan women with Nugent scores consistent with BV, Intermediate and Normal microbiota (n = 44). All subgroups of G. vaginalis were detected in these women, with a significant difference (z = -3.372, n = 39, p = 0.001) in frequency of G. vaginalis subgroup B between BV and Normal groups. Establishment of a quantifiable relationship between G. vaginalis subgroup distribution and clinical status could have significant diagnostic implications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".