Real-time PCR assay design and validation for Prevotella bivia, Peptostreptococcus anaerobius, and Dialister micraerophilus, bacteria associated with increased HIV susceptibility
Bibliographic record
Abstract
Many genital anaerobes, including Prevotella bivia , Peptostreptococcus anaerobius , and Dialister micraerophilus , are underexplored despite being Bacteria Associated with HIV Seroconversion, Inflammation, and immune Cells (BASICs). This is partly due to the lack of molecular tools for their detection and quantification. To address this gap, we designed and validated three real-time qPCR assays for rapid and cost-effective analysis. qPCR assays were designed based on the species-specific core genomes of the three target genital anaerobic species. Assay sensitivity, specificity, and quantification characteristics were assessed using a synthetic oligonucleotide and DNA extracted from closely related species ( n = 27–42) and human urogenital swabs ( n = 111–114). The resultant assays demonstrated 100% sensitivity and specificity for bacterial isolates and high sensitivity (94.6%-97.7%) and specificity (92.8%-95.7%) for human urogenital swabs. The linear dynamic range was 5.0 × 10 1 to 1.0 × 10 7 copies/µL for P. bivia and D. micraerophilus assays, and 2.5 × 10 2 to 1.0 × 10 7 copies/µL for the P. anaerobius assay. Assay efficiency ranged from 99.0% to 112.0%. These assays provide a highly sensitive and specific method for the analysis of bacterial isolates, urogenital samples, and in vitro or ex vivo experiments, which can enhance our understanding of the epidemiology, clinical impact, and biology of key genital anaerobes associated with HIV risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".