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Record W1986075569 · doi:10.1371/journal.pntd.0002582

Geographic Distribution and Genetic Characterization of Lassa Virus in Sub-Saharan Mali

2013· article· en· W1986075569 on OpenAlexaff
David Safronetz, Nafomon Sogoba, Job E. López, Ousmane Maïga, Eric Dahlstrom, Marko Zivcec, Friederike Feldmann, Elaine Haddock, Robert J. Fischer, Jennifer M. Anderson, Vincent J. Munster, Luis M. Branco, Robert F. Garry, Stephen F. Porcella, Tom G. Schwan, Heinz Feldmann

Bibliographic record

VenuePLoS neglected tropical diseases · 2013
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Outbreaks Research
Canadian institutionsUniversity of Manitoba
FundersNational Institute of Allergy and Infectious DiseasesNHLBI Division of Intramural ResearchNational Institutes of HealthDivision of Intramural Research, National Institute of Allergy and Infectious Diseases
KeywordsLassa feverLassa virusSierra leoneArenavirusMastomysVirologyBiologyVirusImmunologyImmune systemSocioeconomics

Abstract

fetched live from OpenAlex

BACKGROUND: Lassa fever is an acute viral illness characterized by multi-organ failure and hemorrhagic manifestations. Lassa fever is most frequently diagnosed in Nigeria, Sierra Leone, Liberia, and Guinea, although sporadic cases have been recorded in other West African countries, including Mali. The etiological agent of Lassa fever is Lassa virus (LASV), an Arenavirus which is maintained in nature and frequently transmitted to humans by Mastomys natalensis. The purpose of this study was to better define the geographic distribution of LASV-infected rodents in sub-Saharan Mali. METHODOLOGIES/PRINCIPAL FINDINGS: Small mammals were live-trapped at various locations across Mali for the purpose of identifying potential zoonotic pathogens. Serological and molecular assays were employed and determined LASV infected rodents were exclusively found in the southern Mali near the border of Côte d'Ivoire. Overall, 19.4% of Mastomys natalensis sampled in this region had evidence of LASV infection, with prevalence rates for individual villages ranging from 0 to 52%. Full-length genomic sequences were determined using high throughput sequencing methodologies for LASV isolates generated from tissue samples of rodents collected in four villages and confirmed the phylogenetic clustering of Malian LASV with strain AV. CONCLUSIONS/SIGNIFICANCE: The risk of human infections with LASV is greatest in villages in southern Mali. Lassa fever should be considered in the differential diagnosis for febrile individuals and appropriate diagnostic techniques need to be established to determine the incidence of infection and disease in these regions.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.350

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 head0.011
GPT teacher head0.244
Teacher spread0.232 · 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

Citations64
Published2013
Admission routes1
Has abstractyes

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