HIV Diversity Considerations in the Application of the Intact Proviral DNA Assay (IPDA)
Bibliographic record
Abstract
Opening Paragraph (serves as abstract for submission) and Body The Intact Proviral DNA Assay (IPDA) was developed to address the critical need for a precise and scalable method for intact HIV reservoir quantification 1 . This duplexed droplet digital PCR (ddPCR) assay simultaneously targets the HIV Packaging Signal (Ψ) and the Rev Responsive Element (RRE) within Envelope ( env ) to distinguish genomically intact proviruses against a large background of defective ones 2 . The IPDA requires less time, resources, and biological material than the gold standard for replication-competent HIV reservoir measurement, the Quantitative Viral Outgrowth Assay (QVOA) 3 , and is being adopted in research and clinical studies 4–7 . In our cohort of HIV-1 subtype B-infected individuals from North America however, the IPDA yielded a 28% failure rate due to HIV polymorphism. We further demonstrate that within-host HIV diversity can lead the IPDA to underestimate intact HIV reservoir size, which could negatively impact clinical trial results interpretation. While the IPDA represents an important methodological advance, HIV diversity should be addressed before its widespread adoption.
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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 | 0.036 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".