Impact of Insertions in the HIV-1 P6 Ptapp Region on the Virological Response to Amprenavir
Bibliographic record
Abstract
We evaluated the impact of genetic changes within p6Gag gene on the virological response (VR, mean decrease in plasma viral load at week 12) to unboosted amprenavir (APV). Gag-protease fragments, including gag p2, p7, p1, p6 regions and whole protease (PR) were sequenced from baseline plasma specimens of 84 highly pre-treated but APV-naive patients included in the NARVAL (ANRS 088) trial. The correlation between baseline p6Gag polymorphism, PR mutations, baseline characteristics and VR to APV was analysed in univariate analysis. Insertions (P459Ins) within p6 protein, leading to partial or complete duplication of the PTAPP motif, were significantly associated with a decreased VR (P459Ins versus wild-type; -0.3 +/- 0.8 vs -1.1 +/- 1.2 log copies/ml, P=0.007) and were more frequent when the V82A/F/T/S PR mutation was present (P=0.020). In multivariate analysis, after adjustment on the predictive factors of the VR in the NARVAL trial and on the PR mutations linked with response, there was a strong trend to an association (P=0.058) between the presence of P459Ins and an altered VR. In conclusion, these results suggest that insertions in the p6 region of HIV-1 gag gene may affect the VR, in highly pre-treated patients receiving an unboosted APV-containing regimen.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".