Real-Time PCR Quantification of Genital Shedding of Herpes Simplex Virus (HSV) and Human Immunodeficiency Virus (HIV) in Women Coinfected with HSV and HIV
Bibliographic record
Abstract
The accuracy and usefulness of laboratory-developed real-time PCR procedures using a Light Cycler instrument (Roche Diagnostics) for detecting and quantifying human immunodeficiency virus type 1 (HIV-1) RNA and DNA as well as herpes simplex virus type 1 (HSV-1)/HSV-2 DNA in cervicovaginal secretions from women coinfected with HIV and HSV were evaluated. For HIV-1, the use of the NEC152 and NEC131 primer set and the NEC-LTR probe in the long terminal repeat gene allowed us to detect accurately the majority of HIV-1 subtypes of group M circulating in sub-Saharan Africa, including subtypes A, B, C, D, and G as well as circulating recombinant forms 02 and 11. The detection threshold of real-time PCR for HIV in cervicovaginal lavage samples was 5 copies per assay for both RNA and DNA; the intra- and interassay coefficients of variation of C(T) values were 1.30% and 0.69% (HIV-1 RNA) and 1.84% and 0.67% (HIV-1 DNA), respectively. Real-time PCR for HSV using primers and probe targeting the HSV DNA polymerase gene allowed both detection and quantification of HSV DNA and also differentiation between HSV-1 and HSV-2 genotypes. The detection threshold of real-time PCR for HSV was 5 copies per assay; the intra- and interassay coefficients of variation of C(T) values were 0.96% and 1.49%, respectively. Both manual and automated silica-based procedures were appropriate for combined extraction of HIV and HSV genomes from female genital secretions. Taken together, these findings indicate that real-time PCR may be used as a unique nucleic acid amplification procedure to detect and quantify HIV and HSV genomes in cervicovaginal secretions and thus to assess at reduced costs the genital shedding of both viruses in women included in intervention studies.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".