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Record W3163327533 · doi:10.3390/microorganisms9051082

Detection of Quebec Polyomavirus DNA in Samples from Different Patient Groups

2021· article· en· W3163327533 on OpenAlexaboutno aff
Carla Prezioso, Marijke Van Ghelue, Ugo Moens

Bibliographic record

VenueMicroorganisms · 2021
Typearticle
Languageen
FieldMedicine
TopicPolyomavirus and related diseases
Canadian institutionsnot available
FundersMinistero della SaluteErna and Olav Aakre Foundation for Cancer Research
KeywordsGenBankJC virusCerebrospinal fluidUrinePolyomavirus InfectionsMedicineVirologyCapsidGastroenterologyBiologyInternal medicineImmunologyVirusGeneProgressive multifocal leukoencephalopathyBK virusGenetics

Abstract

fetched live from OpenAlex

Polyomaviruses infect many species, including humans. So far, 15 polyomaviruses have been described in humans, but it remains to be established whether all of these are genuine human polyomaviruses. The most recent polyomavirus to be detected in a person is Quebec polyomavirus (QPyV), which was identified in a metagenomic analysis of a stool sample from an 85-year-old hospitalized man. We used PCR to investigate the presence of QPyV DNA in urine samples from systemic lupus erythematosus (SLE) patients (67 patients; 135 samples), multiple sclerosis patients (n = 35), HIV-positive patients (n = 66) and pregnant women (n = 65). Moreover, cerebrospinal fluid from patients with suspected neurological diseases (n = 63), nasopharyngeal aspirates from patients (n = 80) with respiratory symptoms and plasma samples from HIV-positive patients (n = 65) were examined. QPyV DNA was found in urine from 11 (16.4%), 10 (15.4%) and 5 (14.3%) SLE patients, pregnant women, and multiple sclerosis patients, respectively. No QPyV DNA could be detected in the other samples. Alignment with the only available QPyV sequence in the GenBank revealed amino acid substitutions in the HI-loop of capsid protein VP1 in 6/28 of the isolates. Our results show that QPyV viruria can occur, but whether it may cause clinical symptoms in the patients remains to be determined.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.253
Threshold uncertainty score0.997

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 head0.009
GPT teacher head0.215
Teacher spread0.206 · 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 designBench or experimental
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

Citations11
Published2021
Admission routes1
Has abstractyes

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