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Record W2073523050 · doi:10.1089/08892220050140964

Mutations in the HIV Type 1 Integrase of Patients Receiving Long-Term Dideoxynucleoside Therapy Do Not Confer Resistance to Zidovudine

2000· article· en· W2073523050 on OpenAlexaff
André A. Pilon, Chistophe Marchand, Mark F. Kavlick, Kamini Bajaj, Joshua M. Owen, Hiroaki Mitsuya, Yves Pommier

Bibliographic record

VenueAIDS Research and Human Retroviruses · 2000
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsOttawa Hospital
FundersNational Institutes of Health
KeywordsIntegraseZidovudineIntegrasesVirologyBiologyIntegrase inhibitorMutationGeneticsLentivirusMutantRecombinant DNAResistance mutationVirusReverse transcriptaseGeneHuman immunodeficiency virus (HIV)RNAAntiretroviral therapyViral diseaseViral load

Abstract

fetched live from OpenAlex

Metabolites of AZT can inhibit HIV-1 integrase in vitro (Mazumder A, et al., Proc Natl Acad Sci USA 1994;91:5771-5775). To determine if long-term dideoxynucleoside therapy can lead to the emergence of HIV-1 AZT-resistant variants containing mutations in the integrase, we have sequenced the proviral DNA encoding the HIV-1 integrase of nine HIV-1-infected patients at different time points during treatment. Four of the nine patients developed mutations during the course of treatment. Although most mutations occurred at nonconserved amino acids, one patient developed a mutation at codon (R166T), a residue that is conserved among all integrases from known HIV-1 isolates. This mutation was introduced in the recombinant HIV-1 integrase protein to determine if it could confer resistance to AZT in vitro. We show that the R166T integrase mutant is still proficient at carrying 3'-processing and 3' end-joining but that the enzyme is not resistant to AZT-TP. Our results suggest that it is unlikely that integrase inhibition contributes to the antiviral activity of AZT.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.073
GPT teacher head0.376
Teacher spread0.303 · 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.

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

Citations3
Published2000
Admission routes1
Has abstractyes

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