MétaCan
Menu
Back to cohort
Record W7133071440

Development of antimicrobial polypeptide bioactive fluorinated surface modifiers for biofilm reduction

2008· dissertation· W7133071440 on OpenAlexfundno aff
Jatinderpreet Singh

Bibliographic record

VenueTSpace · 2008
Typedissertation
Language
FieldChemistry
TopicAntimicrobial agents and applications
Canadian institutionsnot available
FundersFaculty of Dentistry, University of TorontoNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsBiofilmStreptococcus mutansAntimicrobialCationic polymerizationPeptideIn vitroCoatingBacteria
DOInot available

Abstract

fetched live from OpenAlex

Previous studies have demonstrated the ability of bioactive fluorinated surface modifiers (BFSMs) to co-deliver bioactive groups to the surface of a polycarbonate polyurethane (PCNU). In order to address the problem of medical device infections, it was the objective of this study to design cationic antimicrobial peptide (CAP) BFSMs, and test their biofilm-reducing abilities against Streptococcus mutans and Staphylococcus epidermidis, due in part to the latter peptides ability to kill a broad range of microorganisms at low concentrations and in a rapid manner. Dansyl labelled (*) CAPs, Bac8c (NH2-GGGK*GRIWVIWRR-CONH2) and Bac020 (NH2-GGGK*GRRAAVVLIVIRR-CONH 2), were attached to BFSM precursor molecules, and were shown to enrich the surfaces of PCNU films using 2-photon confocal microscopy. A 96-well plate safranin-staining assay was preformed, and demonstrated that both CAP-BFSMs were able to significantly reduce biofilm formation in a medium-dependent manner. This work demonstrates the potential of this approach as a coating strategy for reducing biomaterial-related infections.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.032
GPT teacher head0.319
Teacher spread0.287 · 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 designBench or experimental
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
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueTSpaceSame topicAntimicrobial agents and applicationsFrench-language works237,207