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Record W3087683692 · doi:10.3390/pathogens9090764

Uropathogens Preferrentially Interact with Conditioning Film Components on the Surface of Indwelling Ureteral Stents Rather than Stent Material

2020· article· en· W3087683692 on OpenAlexaff
Kymora B. Scotland, Sonia H.Y. Kung, Ben H. Chew, Dirk Lange

Bibliographic record

VenuePathogens · 2020
Typearticle
Languageen
FieldMedicine
TopicKidney Stones and Urolithiasis Treatments
Canadian institutionsVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsStentTamm–Horsfall proteinBiofilmAdhesionLumen (anatomy)FibrinogenMicrobiologyMedicineBacteriaChemistryBiologySurgeryUrinary systemAnatomyInternal medicine

Abstract

fetched live from OpenAlex

Despite routine implementation in urology, indwelling ureteral stents pose as a nidus for infection. Conditioning film accumulates on stents, which prime pathogen adhesion, promoting infectious biofilm formation. However, the extent to which conditioning film components play a role in facilitating bacterial adhesion and biofilm formation remains largely unknown. Here, we examined the interaction of previously identified stent-bound conditioning film components (fibrinogen, uromodulin, and albumin) with bacterial uropathogens. Cytoscopically removed stents were incubated with common uropathogens (Escherichia coli, Enterococcus faecalis, and Staphylococcus aureus). Immunofluorescent double staining was performed to study the localization of uropathogens relative to stent-bound conditioning film proteins. Conditioning film components were identified on the external stent surface with some deposition in the inner lumen. Bacteria co-localized with fibrinogen, uromodulin, and albumin, suggesting a potential mechanism for stent-associated infections. Here, we determine strong co-localization between common uropathogenic bacterial species with prominent conditioning film components on ureteral stents. Further functional validation of interactions amongst these uropathogens and conditioning film proteins may enhance clinical management for stent-associated infections and development of improved stent technologies.

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 score0.399
Threshold uncertainty score0.661

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 head0.043
GPT teacher head0.250
Teacher spread0.207 · 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

Citations9
Published2020
Admission routes1
Has abstractyes

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