Concurrent Genotyping and Quantitation of Cytomegalovirus gB Genotypes in Solid-Organ-Transplant Recipients by Use of a Real-Time PCR Assay
Bibliographic record
Abstract
We have developed a real-time genotyping and quantitative PCR (RT-GQ-PCR) assay to genotype cytomegalovirus (CMV) and quantify viral loads simultaneously in solid organ transplant (SOT) recipients. Special minor-groove DNA-binding probes were designed based on sequence polymorphism in the gB gene to increase genotyping specificity for gB1 to gB4. For validation, 28 samples with known genotypes determined by restriction fragment analysis (RFA) and 121 with unknown genotypes were tested. All samples were from SOT patients with CMV viremia. A 100% concordance for genotyping was achieved by using the RT-GQ-PCR with known genotypes determined by RFA. The RT-GQ-PCR identified more cases of CMV infections with mixed genotypes than RFA did. No cross-reaction between genotypes was observed. All four gB genotypes were detected in the 121 samples of unknown genotype. gB1 was the predominant single genotype (n = 61, 50.4%), followed by gB2 (n = 26, 21.0%), gB3, (n = 11, 9.1%), and gB4 (n = 3, 2.5%). Mixed-genotype infections were detected in 17% (20/121) of the samples. Patients with mixed-genotype infections had significantly higher CMV viral loads than those with single-genotype infections (P = 0.019). The RT-GQ-PCR assay was found to be highly sensitive and specific, with a wide dynamic range (2.7 to 10.7 log(10) copies/ml) and very good precision (coefficient of variation, approximately 1.78%). With the prominent feature of concurrent CMV gB genotyping and quantitation in a single reaction, the new assay provides a rapid and cost-effective method for monitoring CMV infection in SOT recipients.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".