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Record W2152930926 · doi:10.1093/infdis/jiv095

Immune Response to Marburg Virus Angola Infection in Nonhuman Primates

2015· article· en· W2152930926 on OpenAlexafffund
Lisa Fernando, Xiangguo Qiu, Pasquale L. Melito, Kinola J.N. Williams, Friederike Feldmann, Heinz Feldmann, Judie B. Alimonti

Bibliographic record

VenueThe Journal of Infectious Diseases · 2015
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Outbreaks Research
Canadian institutionsPublic Health Agency of Canada
FundersHealth CanadaPublic Health AgencyPublic Health Agency of CanadaCanadian Food Inspection Agency
KeywordsMarburg virusVirologyOutbreakEbolavirusImmune systemBiologyEbola virusVirusCase fatality rateImmunologyMedicineEpidemiologyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: The 2005 outbreak of Marburg virus (MARV) infection in Angola was the most lethal MARV infection outbreak in history, with a case-fatality rate (90%) similar to that for Zaire ebolavirus (EBOV) infection. However, very little is known about the pathogenicity of MARV Angola, as few studies have been conducted to date. Therefore, the immune response was examined in MARV Angola-infected nonhuman primates. METHODS: Cynomolgus macaques were infected with MARV Angola and monitored for survival. The effect of MARV Angola on the immune system was examined by immunophenotyping whole-blood and by analyzing cytokine and chemokine levels in plasma and spleen specimens, using flow cytometry. RESULTS: The prominent clinical findings were rapid onset of disease and death (mean time after infection, 6.7 days), fever, depression, anorexia, petechial rash, and lymphopenia. Specifically, T, B, and natural killer cells were severely depleted in the blood by day 6. The typical cytokine storm was present, with levels of interferon γ, tumor necrosis factor, interleukin 6, and CCL2 rising in the blood early during infection. CONCLUSIONS: MARV Angola displayed the same virulence and disease pathology as EBOV. MARV Angola appears to cause a more rapid onset and severe outcome of infection than other MARV strains.

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 score0.136
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.025
GPT teacher head0.338
Teacher spread0.313 · 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

Citations43
Published2015
Admission routes2
Has abstractyes

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