Next-generation sequencing to assess HIV tropism
Bibliographic record
Abstract
PURPOSE OF REVIEW: Deep sequencing of the V3 region of the HIV envelope gene can detect minority non-R5 variants in patients with high sensitivity and specificity. As next-generation sequencing approaches have matured, the clinical utility of deep sequencing for HIV tropism has entered the clinic. Accurate and sensitive tropism testing is essential for successful treatment with the CCR5 antagonist class of antiretrovirals. RECENT FINDINGS: This review will focus on five aspects of next-generation sequencing for assessing HIV tropism: some background on the necessity of deep sequencing versus other tropism methods; the methodological process of 454 sequencing and analysis; other next-generation sequencing technologies; the diagnostic performance of deep sequencing relative to other tropism assays; and the use of deep sequencing in clinical practice. SUMMARY: This method has emerged quickly as both a research and clinical tool because of its high concordance with commonly used phenotypic tropism assays and its ability to predict virological response to CCR5 antagonist-containing regimens.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 teacher head, 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".