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Record W2753961871 · doi:10.1038/s41598-017-11814-9

Population genomics of virulence genes of Plasmodium falciparum in clinical isolates from Uganda

2017· article· en· W2753961871 on OpenAlexfundno aff
Shazia Ruybal‐Pesántez, Kathryn E. Tiedje, Gerry Tonkin‐Hill, Thomas S. Rask, Moses R. Kamya, Bryan Greenhouse, Grant Dorsey, Michael F. Duffy, Karen P. Day

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesFogarty International CenterNational Institutes of HealthYork University
KeywordsBiologyPlasmodium falciparumMalariaGeneVirulenceGenomePopulation genomicsPopulationGeneticsAntigenic variationGenomicsParasite hostingImmunologyMedicine

Abstract

fetched live from OpenAlex

Plasmodium falciparum causes a spectrum of malarial disease from asymptomatic to uncomplicated through to severe. Investigations of parasite virulence have associated the expression of distinct variants of the major surface antigen of the blood stages known as Pf EMP1 encoded by up to 60 var genes per genome. Looking at the population genomics of var genes in cases of uncomplicated malaria, we set out to determine if there was any evidence of a selective sweep of specific var genes or clonal epidemic structure related to the incidence of uncomplicated disease in children. By sequencing the conserved DBLα domain of var genes from six sentinel sites in Uganda we found that the parasites causing uncomplicated P. falciparum disease in children were highly diverse and that every child had a unique var DBLα repertoire. Despite extensive var DBLα diversity and minimal overlap between repertoires, specific DBLα types and groups were conserved at the population level across Uganda. This pattern was the same regardless of the geographic distance or malaria transmission intensity. These data lead us to propose that any parasite can cause uncomplicated malarial disease and that these diverse parasite repertoires are composed of both upsA and non-upsA var gene groups.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.249

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 studies0.0000.000
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 head0.045
GPT teacher head0.354
Teacher spread0.309 · 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

Citations50
Published2017
Admission routes1
Has abstractyes

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