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Discordant phenotypes and genotypes of Cytomegalovirus (CMV) in patients with AIDS and relapsing CMV retinitis

2003· article· en· W2334288161 on OpenAlexaff
Christian Gilbert, Guy Boivin

Bibliographic record

VenueAIDS · 2003
Typearticle
Languageen
FieldMedicine
TopicCytomegalovirus and herpesvirus research
Canadian institutionsUniversité LavalCentre hospitalier de l'Université LavalCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsGenotypeGanciclovirRetinitisVirologyCytomegalovirusHuman cytomegalovirusBetaherpesvirinaeBiologyImmunologyViral diseaseHerpesviridaeCytomegalovirus retinitisVirusViral loadGeneGenetics

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the correlation between genotypic studies performed on blood leukocytes and phenotypic results obtained from the corresponding blood viral isolates in AIDS patients with relapsing cytomegalovirus (CMV) retinitis. METHODS: Sequential blood samples were collected from patients failing intravenous or oral ganciclovir therapy. The CMV UL97 gene was amplified directly from leukocyte DNA extracts for assessing the presence of viral mutations using restriction fragment length polymorphism analysis and direct sequencing. Positive viral cultures from the same blood samples were also analyzed for their susceptibility to ganciclovir and their UL97 genotype was determined. RESULTS: Discordant CMV genotypes between the clinical specimen and the viral culture were found in at least one blood sample from three of the four patients with relapsing CMV retinitis. Furthermore, some UL97 mutations at known resistance codons (592, 594) were associated with a drug-susceptible phenotype. In all four cases, genotypic analyses of blood samples better correlated with clinical progression than phenotypic analyses of viral cultures. CONCLUSIONS: The presence of mixed viral populations in blood samples of AIDS patients and the potential selection bias introduced by susceptibility testing may underestimate the real impact of CMV resistance in patients failing antiviral therapy.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

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

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 head0.012
GPT teacher head0.256
Teacher spread0.244 · 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

Citations18
Published2003
Admission routes1
Has abstractyes

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