Substitutions in the Reverse Transcriptase and Protease Genes of HIV‐1 Subtype B in Untreated Individuals and Patients Treated With Antiretroviral Drugs
Bibliographic record
Abstract
The nucleotide transition G-->A is known as a hypermutation due to its high prevalence in HIV-1 and other pathogens. However, the contribution of the G-->A transition in the generation of drug resistance mutations is unknown. Our objective was to ascertain the rate of nucleotide substitutions in protease (PR) and reverse transcriptase (RT) in both untreated and treated HIV-1 patients. Genotypic analysis was performed on viruses from both treated and untreated patients with subtype B infections. Nucleotide genomic diversity was compared with a consensus subtype B reference virus. Then, the prevalence of resistance-associated mutations in different subgroups of treated patients was evaluated in relation to the patterns of nucleotide transitions. In untreated patients (n = 50) G-->A was most prevalent, followed by A-->G, C-->T, and T-->C transitions. In treated patients (n = 51), the prevalence of A-->G was similar to that of G-->A. Among mutations that confer resistance to antiretroviral drugs, M184V was present in 76% of treated patients and K70R in 31% (A-->G transitions). Other frequent mutations in RT included T215Y (C-->A and A-->T substitutions), which was prevalent in 31% of treated patients. In PR, a L90M (T-->A substitution) was prevalent in 47% of protease inhibitor (PI)-treated patients. In conclusion, the G-->A transition was most prevalent in RT and PR among untreated patients. In contrast, A-->G was the most prevalent transition in patients treated with antiretroviral drugs.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".