Development of a Novel Codon-Specific Polymerase Chain Reaction for the Detection of CXCR4-Utilizing HIV Type 1 Subtype B
Bibliographic record
Abstract
Insight concerning the switch in HIV-1 coreceptor use will lead to a better understanding of HIV-1 pathogenesis and host-virus dynamics. Predicting CXCR4 utilization by analyzing HIV-1 envelope consensus sequences is highly specific, but minority variants in the viral population are often missed resulting in low sensitivity. Commercial phenotypic assays are costly, and the development of sensitive in-house phenotypic assays to detect CXCR4-using HIV may not be feasible for some laboratories. A sensitive, inexpensive genotyping assay was developed to detect viral sequences associated with CXCR4-utilizing virus (X4). Codon-specific primer pairs were used to detect X4-associated codons at five positions in the HIV-1 envelope V3 loop (11, 13, 24, 25, and 32). Sixty plasma samples from HIV-1-infected individuals were analyzed by consensus sequencing and codon-specific PCR (CS-PCR). Forty-six of these were also phenotyped by Trofile or Enhanced Sensitivity Trofile (ESTA). CS-PCR detected X4 variants 17% more often than 11/24/25 consensus sequencing alone (n=60), 30% more often than Trofile (n=27), and in a limited data set, 16% more often than ESTA (n=19). CS-PCR combined with consensus sequencing had approximately 80% concordance with ESTA.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".