Multiplex Detection of Bacteria Associated with Normal Microbiota and with Bacterial Vaginosis in Vaginal Swabs by Use of Oligonucleotide-Coupled Fluorescent Microspheres
Bibliographic record
Abstract
Bacterial vaginosis (BV) is a recurrent condition that is associated with a range of negative outcomes, including the acquisition of human immunodeficiency virus and other sexually transmitted diseases, preterm births, and pelvic inflammatory disease. In contrast to the Lactobacillus-dominated normal vaginal microbiota, BV is characterized by a lack of lactobacilli and an abundance of anaerobic and gram-negative organisms, including Gardnerella vaginalis and Atopobium vaginae. To date, the laboratory diagnosis of BV has relied upon the fulfillment of criteria determined by microscopic observation of Gram-stained vaginal swabs. We describe a molecular-based method for the easy determination of the species profile within the vaginal microbiota based on the amplification of the chaperonin-60 genes of all bacteria present in the swab and hybridization of the amplicon to species-specific oligonucleotide-coupled fluorescent beads that are identified by flow cytometry with a Luminex instrument. We designed a nineplex Luminex array for characterization of the vaginal microbiota and applied it to the analysis of vaginal swabs from individuals from Africa and North America. Using the presence of A. vaginae or G. vaginalis, or both, as the defining criterion for BV, we found that the method was highly specific and sensitive for the diagnosis of BV using microscopy as a gold standard.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".