Epidemiological and Biological Evidence for a Compensatory Effect of Connection Domain Mutation N348I on M184V in HIV‐1 Reverse Transcriptase
Bibliographic record
Abstract
BACKGROUND: The connection domain mutation N348I confers resistance to zidovudine (AZT) and is associated with the lamivudine (3TC) mutation M184V. We explored the biochemical and virological influence of N348I in the context of M184V. METHODS: Genotypic resistance data for patients receiving monotherapy or dual therapy with AZT, lamivudine (3TC), or AZT/3TC were analyzed. Rates of N348I emergence were compared between treatment groups. Mutant reverse transcriptases (RTs) containing M184V and/or N348I were generated to study enzymatic and virological properties. RESULTS: We included 50 AZT-treated, 11 3TC-treated, and 10 AZT/3TC-treated patients. N348I was observed in 3 (6%), 0, and 4 (40%) of these patients, respectively. The rate of N348I emergence was increased by 5-fold in the AZT/3TC group (11.7 instances [95% confidence interval {CI}, 3.2-30.1 instances] per 100 person-years of receipt of AZT), compared with the rate noted for the AZT group (2.3 instances [95% CI, 0.4-6.8 instances] per 100 person-years of receipt of AZT; P = .04). Biochemical data show that N348I can partially compensate for the diminution in processive DNA synthesis and the reduction in AZT excision associated with M184V. Furthermore, virological analyses demonstrate that N348I confers low-level resistance to AZT and partly restores the reduced RT activity of the M184V variant. CONCLUSION: In vivo selection of N348I is driven by AZT and is further facilitated when 3TC is coadministered. Compensatory interactions between N348I and M184V help to explain these findings.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".