Bibliographic record
Abstract
Darunavir is a second-generation protease inhibitor designed to have antiviral efficacy against HIV-1 isolates harboring multiple resistance mutations to protease inhibitors. Pivotal trials conducted in treatment-experienced HIV-infected individuals have demonstrated significantly greater virological suppression when darunavir was added to an optimized background treatment compared with a control protease inhibitor. This virological suppression was associated with an increase in CD4 counts and was sustained over time. Darunavir resistance-associated mutations have been defined as V11I, V32I, L33F, I47V, I50V, I54L/M, G73S, L76V, I84V, and L89V. In clinical trials, baseline darunavir susceptibility was a strong predictor of virological response. Prior use of fosamprenavir was associated with darunavir resistance mutations. Darunavir has a high genetic barrier and has a distinct resistance profile. Although some cross-resistance exists with other second-generation protease inhibitors such as tipranavir, different resistance mutation patterns have been observed upon failure to these regimens. It was found that mutations at 47V, 54M, 85V, and 73T were most prevalent in isolates resistant to both PIs. Mutations 48V, 50V, and 54L were associated with resistance to darunavir but not to tipranavir. 82S and 82T were associated with resistance to tipranavir but not to darunavir. Therefore, darunavir provides potent virological efficacy as well as high genetic barrier that can be useful to preserve treatment options in HIV-infected, treatment-experienced individuals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".