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Record W1979531488 · doi:10.1089/aid.2006.0089

Investigating Signs of Recent Evolution in the Pool of Proviral HIV Type 1 DNA during Years of Successful HAART

2007· article· en· W1979531488 on OpenAlexaff
Helene Mens, Anders Gorm Pedersen, Louise B. Jørgensen, Stéphane Hué, Yizi Yang, Jan Gerstoft, Terese L. Katzenstein

Bibliographic record

VenueAIDS Research and Human Retroviruses · 2007
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsInstitute of Infection and Immunity
FundersAIDS Fondet
KeywordsAkaike information criterionPhylogenetic treeBiologyGenomeViral evolutionHuman immunodeficiency virus (HIV)PhylogeneticsGeneticsGeneComputational biologyVirologyEvolutionary biologyStatisticsMathematics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.066
GPT teacher head0.354
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2007
Admission routes1
Has abstractyes

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