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Record W2151544312 · doi:10.4269/ajtmh.12-0739

Selection of Antimalarial Drug Resistance after Intermittent Preventive Treatment of Infants and Children (IPTi/c) in Senegal

2013· article· en· W2151544312 on OpenAlexfundno aff
Magatte Ndiaye, Roger Tine, Babacar Faye, Jean Louis Ndiaye, Ami Colle Lo, Khadime Sylla, Annie Abiola, Yémou Dieng, Daouda Ndiaye, Rachel Hallett, Oumar Gaye, Michael Alifrangis

Bibliographic record

VenueAmerican Journal of Tropical Medicine and Hygiene · 2013
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsnot available
FundersCenters for Disease Control and PreventionCanadian Immunization Research NetworkWellcome Trust
KeywordsDrug resistanceMedicineDrugSelection (genetic algorithm)MalariaPharmacologyIntensive care medicineEnvironmental healthBiologyImmunology

Abstract

fetched live from OpenAlex

Our study investigated the possible impact of SP-IPT given to infants and children on the prevalence of SP-resistant haplotypes in the Plasmodium falciparum genes Pfdhfr and Pfdhps, comparing sites with and without IPTi/c. P. falciparum positive samples (N = 352) collected from children < 5 years were analyzed to determine the prevalence of SP resistance-related haplotypes by nested PCR followed by sequence-specific oligonucleotide probe-enzyme-linked immunosorbent assay. The prevalence of the Pfdhfr triple mutant haplotype (CIRN) increased in both groups, but only significantly in the IPTi/c group from 41% to 65% in 2011 (P = 0.005). Conversely, the Pfdhps 437G mutation decreased in both groups from 44.6% to 28.6% (P = 0.07) and from 66.7% to 47.5% (P = 0.02) between 2010 and 2011 in the control and the IPTi/c groups, respectively. A weak trend for decreasing prevalence of quadruple mutants (triple Pfdhfr + Pfdhps 437G) was noted in both groups (P = 0.15 and P = 0.34). During the two cross-sectional surveys some significant changes were observed in the SP resistance-related genes.

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 score0.122
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.006
GPT teacher head0.262
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 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

Citations10
Published2013
Admission routes1
Has abstractyes

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