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Record W2029213791 · doi:10.1128/jcm.00637-11

Extensive Horizontal Gene Transfer in Ureaplasmas from Humans Questions the Utility of Serotyping for Diagnostic Purposes

2011· article· en· W2029213791 on OpenAlexaff
Li Xiao, Vanya Paralanov, John I. Glass, Lynn B. Duffy, Janet A. Robertson, Gail H. Cassell, Yuying Chen, Ken B. Waites

Bibliographic record

VenueJournal of Clinical Microbiology · 2011
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsUniversity of Alberta
FundersNational Institute of Child Health and Human DevelopmentNational Institute of Allergy and Infectious Diseases
KeywordsSerotypeUreaplasma urealyticumBiologyUreaplasmaVirulenceVirologyMycoplasmataceaeMicrobiologyGeneticsGeneMycoplasmaMollicutes

Abstract

fetched live from OpenAlex

Ureaplasma parvum and Ureaplasma urealyticum are sexually transmitted, opportunistic pathogens of the human urogenital tract. There are 14 known serovars distributed between the two species. For decades, it has been postulated based upon limited data that virulence is related to serotype specificity. The results were often inconclusive due to the small sample size and extensive cross-reactivity between certain serovars. We developed real-time quantitative PCRs that allow reliable differentiation of the two species and type strains of each of the 14 serovars. To investigate species and serovar distributions, we typed 1,061 clinical isolates of human ureaplasmas from diverse patient populations. There was only a tenuous association between individual Ureaplasma serovars and certain patient populations. This may in part be explained by the fact that almost 40% of the isolates were genetic mosaics, apparently arising from the recombination of multiple serovars. This explains the extensive cross-reactivity based upon serotyping and the lack of consistent association of given serotypes with disease.

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)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.604
Threshold uncertainty score0.861

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.129
GPT teacher head0.385
Teacher spread0.256 · 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

Citations77
Published2011
Admission routes1
Has abstractyes

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