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Record W2793549169 · doi:10.1111/1348-0421.12577

Pathogenic mechanisms of invasive group A <i>Streptococcus</i> infections by influenza virus–group A <i>Streptococcus</i> superinfection

2018· review· en· W2793549169 on OpenAlexaboutno aff
Shigefumi Okamoto, Satoshi Nagase

Bibliographic record

VenueMicrobiology and Immunology · 2018
Typereview
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsnot available
FundersOsaka UniversityJapan Agency for Medical Research and Development
KeywordsSuperinfectionBiologyStreptococcus pneumoniaeStreptococcusMicrobiologyInfluenza A virusToxic shock syndromeVirusVirologyCellulitisStreptococcus pyogenesFasciitisImmunologyStaphylococcus aureusMedicineBacteriaAntibiotics

Abstract

fetched live from OpenAlex

Group A Streptococcus (GAS) are pathogenic bacteria of the genus Streptococcus and cause severe invasive infections that comprise a wide range of diverse diseases, including acute respiratory distress syndrome, renal failure, toxic shock-like syndrome, sepsis, cellulitis and necrotizing fasciitis. The essential virulence, infected host and external environmental factors required for invasive GAS infections have not yet been determined. Superinfection with influenza virus and GAS induced invasive GAS infections was demonstrated by our team in a mouse model, after which clinical cases of invasive GAS infections secondary to influenza virus infection were reported by other investigators in Japan, USA, Canada, UK China, and other countries. However, the pathogenic mechanisms underlying influenza virus-GAS superinfection are not yet fully understood. The present review describes the current knowledge about invasive GAS infections by superinfection. Topics addressed include the bacteriological, virological and immunological mechanisms impacting invasion upon superinfection on top of underlying influenza virus infection by GAS and other bacteria (i.e., Streptococcus pneumoniae and Staphylococcus aureus). Future prospects are also discussed.

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 categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.968
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.290
Teacher spread0.269 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations37
Published2018
Admission routes1
Has abstractyes

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