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E. faecalis ADHESION ON MEDICAL GRADE POLYMERS

2003· article· en· W2091771483 on OpenAlexaff
Alain Sénéchal, Maryam Tabrizian

Bibliographic record

VenueASAIO Journal · 2003
Typearticle
Languageen
FieldMedicine
TopicSurgical Sutures and Adhesives
Canadian institutionsMcGill University
Fundersnot available
KeywordsAdhesionEnterococcus faecalisPolymerMaterials scienceSurface roughnessSurface energyPolyethyleneChemical engineeringSurface finishComposite materialHigh-density polyethyleneChemistryBiochemistry

Abstract

fetched live from OpenAlex

The aim of this study is to compare the initial interactions of Enterococcus faecalis, an uropathogen responsible for catheter-associated infections, with different polymers including polytetrafluoroethylene (PTFE), high-density polyethylene (HDPE), polyurethane (PU), and polymethylmethacrylate (PMMA), which are widely used for the fabrication of medical devices and artificial organs. To follow the kinetics E. faecalis adhesion, polymer samples were incubated at 37°C in bacterial solution, removed from this solution at pre-determined times, and then bacterial concentration on the surface was obtained. Moreover surface hydrophobicity, surface free energy, and surface roughness of the polymers were studied to investigate the parameters influencing bacterial adhesion. Preliminary results of the adhesion kinetics studies suggest that bacteria adhere quickly to the polymer surface independent of polymer composition; the adhesion occurs during the first 45 minutes. Although bacterial adhesion to PMMA occurred as quickly as to the other polymers, elapsed-time studies showed that PMMA seems to be more resistant to E. faecalis adhesion. Contact angle and surface free energy measurements showed that E. faecalis adhesion was lowest on the most hydrophilic and the most energetic surface. Further studies are required to determine if a correlation exists between surface characteristics and E. faecalis adhesion. AFM analyses indicated that all polymers possess a smooth surface with a mean roughness in the range of nanometres. This study suggests that the influence of the bulk properties of these materials is more significant than their surface roughness on bacterial adhesion.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.604
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.023
GPT teacher head0.298
Teacher spread0.274 · 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
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

Citations0
Published2003
Admission routes1
Has abstractyes

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