Synergy against drug-resistant HIV-1 with the microbicide antiretrovirals, dapivirine and tenofovir, in combination
Bibliographic record
Abstract
OBJECTIVE: To evaluate the candidate antiretroviral microbicide compounds, dapivirine (DAP) and tenofovir (TFV), alone and in combination against the transmission of wild-type and nonnucleoside reverse transcriptase inhibitor (NNRTI)-resistant HIV-1 from different subtypes. DESIGN AND METHODS: We determined single-drug efficacy of the RTIs, DAP and TFV, against subtype B and non-B wild-type and NNRTI-resistant HIV-1 in vitro. To assess breadth of activity, compounds were tested alone and in combination against wild-type and NNRTI-resistant subtype C primary HIV-1 isolates and complimentary clonal HIV-1 from subtypes B, C and CRF02_AG to control for viral variation. Early infection was quantified by counting light units emitted from TZM-bl cells less than 48-h postinfection. Combination ratios were based on drug inhibitory concentrations (IC(50)s) and combined effects were determined by calculating combination indices. RESULTS: Both candidate microbicide antiretrovirals demonstrated potent anti-NNRTI-resistant HIV-1 activity in vitro, albeit the combination protected better than the single-drug treatments. Of particular interest, the DAP with TFV combination exhibited synergy (50% combination index, CI(50) = 0.567) against subtype C NNRTI-resistant HIV-1, whereas additivity (CI(50) = 0.987) was observed against the wild-type counterpart from the same patient. The effect was not compounded by the presence of subdominant viral fractions, as experiments using complimentary clonal subtype C wild-type (CI(50) = 0.968) and NNRTI-resistant (CI(50) = 0.672) HIV-1, in lieu of the patient quasispecies, gave similar results. CONCLUSION: This study supports the notion that antiretroviral drug combinations may retain antiviral activity against some drug-resistant HIV-1 despite subtype classification and quasispecies diversity.
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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) | 0.001 | 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) | 0.002 | 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".