Investigating Signs of Recent Evolution in the Pool of Proviral HIV Type 1 DNA during Years of Successful HAART
Bibliographic record
Abstract
In order to shed light on the nature of the persistent reservoir of human immunodeficiency virus type 1 (HIV-1), we investigated signs of recent evolution in the pool of proviral DNA in patients on successful HAART. Pro-viral DNA, corresponding to the C2-V3-C3 region of the HIV-1 env gene, was collected from PBMCs isolated from 57 patients. Both "consensus" (57 patients) and clonal (7 patients) sequences were obtained from five time points spanning a 24-month period. The main computational strategy was to use maximum likelihood to fit a set of alternative phylogenetic models to the clonal data, and then determine the support for models that imply evolution between time points. Model fit and model-selection uncertainty was assessed using the Akaike information criterion (AIC) and Akaike weights. The consensus sequence data was also analyzed using a range of phylogenetic techniques to determine whether there were temporal trends indicating ongoing replication and evolution. In summary, it was not possible to detect definitive signs of ongoing evolution in either the bulk-sequenced or the clonal data with the methods employed here, but our results could be consistent with localized expression of archival HIV genomes in some patients. Interestingly, stop-codons were present at the same two positions in several independent clones and across patients. Simulation studies indicated that this phenomenon could be explained as the result of parallel evolution and that some sites were inherently more likely to evolve into stop codons.
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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 | 0.001 | 0.003 |
| 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 | 0.000 |
| 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".