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Record W4282963959 · doi:10.1111/nyas.14807

<i>Staphylococcus aureus</i> adhesion to the host

2022· review· en· W4282963959 on OpenAlexafffund
Kirsten A. Berry, Mackenzie T. A. Verhoef, Allison C. Leonard, Georgina Cox

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2022
Typereview
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsUniversity of Guelph
FundersInstitute of Infection and ImmunityCanadian Institutes of Health Research
KeywordsBacterial adhesinStaphylococcus aureusMicrobiologyPathogenVirulenceBiologyHost (biology)Human pathogenBiofilmColonizationAntimicrobialPathogenicityOpportunistic pathogenAdhesionBacteriaChemistryGeneticsGene

Abstract

fetched live from OpenAlex

Staphylococcus aureus is a pathobiont capable of colonizing and infecting most tissues within the human body, resulting in a multitude of different clinical outcomes. Adhesion of S. aureus to the host is crucial for both host colonization and the establishment of infections. Underlying the pathogen's success is a complex and diverse arsenal of adhesins. In this review, we discuss the different classes of adhesins, including a consideration of the various adhesion sites throughout the body and the clinical outcomes of each infection type. The development of therapeutics targeting the S. aureus host-pathogen interaction is a relatively understudied area. Due to the increasing global threat of antimicrobial resistance, it is crucial that innovative and alternative approaches are considered. Neutralizing virulence factors, through the development of antivirulence agents, could reduce bacterial pathogenicity and the ever-increasing burden of S. aureus infections. This review provides insight into potentially efficacious adhesion-associated targets for the development of novel decolonizing and antivirulence strategies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.161
GPT teacher head0.397
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations40
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueAnnals of the New York Academy of SciencesSame topicAntimicrobial Resistance in StaphylococcusFrench-language works237,207