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Record W2964477617 · doi:10.1038/s41467-019-11249-y

Neutrophils-related host factors associated with severe disease and fatality in patients with influenza infection

2019· article· en· W2964477617 on OpenAlexafffund
Benjamin Tang, Maryam Shojaei, Sally Teoh, Adrienne F. A. Meyers, John Ho, T. Blake Ball, Yoav Keynan, Amarnath Pisipati, Aseem Kumar, Damon P. Eisen, Kevin Lai, Mark Gillett, Rahul Santram, Robert Geffers, Jens Schreiber, Khyobeni Mozhui, Stephen Huang, Grant P. Parnell, Marek Nalos, Monika Holubová, Tracy Chew, David R. Booth, Anand Kumar, Anthony S. McLean, Klaus Schughart

Bibliographic record

VenueNature Communications · 2019
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsLaurentian UniversityUniversity of ManitobaPublic Health Agency of CanadaInstitute of Infection and Immunity
FundersUniversity of TorontoDalhousie UniversityUniversity of AlbertaPublic Health Agency of CanadaMcMaster UniversityUniversitat Rovira i VirgiliMcGill UniversityPublic Health AgencyUniversity of Ottawa
KeywordsNeutrophil extracellular trapsImmunologyMedicineDiseaseImmune systemInflammationHost factorsHost responseHost (biology)BiologyVirusInternal medicine

Abstract

fetched live from OpenAlex

Severe influenza infection has no effective treatment available. One of the key barriers to developing host-directed therapy is a lack of reliable prognostic factors needed to guide such therapy. Here, we use a network analysis approach to identify host factors associated with severe influenza and fatal outcome. In influenza patients with moderate-to-severe diseases, we uncover a complex landscape of immunological pathways, with the main changes occurring in pathways related to circulating neutrophils. Patients with severe disease display excessive neutrophil extracellular traps formation, neutrophil-inflammation and delayed apoptosis, all of which have been associated with fatal outcome in animal models. Excessive neutrophil activation correlates with worsening oxygenation impairment and predicted fatal outcome (AUROC 0.817-0.898). These findings provide new evidence that neutrophil-dominated host response is associated with poor outcomes. Measuring neutrophil-related changes may improve risk stratification and patient selection, a critical first step in developing host-directed immune therapy.

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)0.001
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 score0.004
Threshold uncertainty score0.576

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.037
GPT teacher head0.337
Teacher spread0.300 · 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

Citations189
Published2019
Admission routes2
Has abstractyes

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