Targeting host nucleotide biosynthesis with resveratrol inhibits emtricitabine-resistant HIV-1
Bibliographic record
Abstract
OBJECTIVE: The M184V mutation in the HIV-1 reverse transcriptase gene is frequent (>50%) in patients, both in resource-rich and resource-limited countries, conferring high-level resistance (>100-fold) to the cytosine analog reverse transcriptase inhibitors lamivudine and emtricitabine. The reverse transcriptase enzyme of M184V HIV-1 mutants has reduced processivity, resulting in reduced viral replication, particularly at low deoxynucleotide (dNTP) levels. We hypothesized that lowering intracellular dNTPs with resveratrol, a dietary supplement, could interfere with replication of M184V HIV-1 mutants. DESIGN AND METHODS: Evaluation of the activity of resveratrol on infection of primary peripheral blood lymphocytes by wild-type and M184V mutant HIV-1. We assayed both molecular clones and primary isolates of HIV-1, containing M184V alone and in combination with other reverse transcriptase mutations. Viral infection was quantified by p24 ELISA and by quantitative real-time PCR analysis. Cell viability was measured by colorimetric 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide (MTT) assays. RESULTS: In virus-infectivity assays, resveratrol did not inhibit replication of wild-type NL4-3 (resveratrol EC50 > 10 μmol/l), but it inhibited NL4-3 184V mutant (resveratrol EC50 = 5.8 μmol/l). These results were confirmed by real-time PCR analysis of early and late products of reverse transcription. Resveratrol inhibited molecular clones and primary isolates carrying M184V, alone or in combination with other reverse transcriptase mutations (resveratrol EC50 values ranging from 2.5 to 7.7 μmol/l). CONCLUSIONS: Resveratrol inhibits HIV-1 strains carrying the M184V mutation in reverse transcriptase. We propose resveratrol as a potential adjuvant in HIV-1 therapy, particularly in resource-limited settings, to help control emtricitabine-resistant M184V HIV-1 mutants.
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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 | 0.000 |
| 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".