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Record W2002809090 · doi:10.1021/ac4034938

Impedimetric Detection of Pathogenic Gram-Positive Bacteria Using an Antimicrobial Peptide from Class IIa Bacteriocins

2014· article· en· W2002809090 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnalytical Chemistry · 2014
Typearticle
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPeptideChemistryBacteriaListeria monocytogenesAntimicrobialBacteriocinAntimicrobial peptidesPathogenic bacteriaGram-negative bacteriaGram-positive bacteriaLinkerBiochemistryCombinatorial chemistryBiosensorMicrobiologyEscherichia coliOrganic chemistryBiology

Abstract

fetched live from OpenAlex

Real-time, label-free detection of Gram-positive bacteria with high selectivity and sensitivity is demonstrated using an interdigitated impedimetric array functionalized with naturally produced antimicrobial peptide from class IIa bacteriocins. The antimicrobial peptide, leucocin A, was chemically synthesized and covalently immobilized on interdigitated gold microelectrodes via the interaction between the C-terminal carboxylic acid of the peptide and free amines of a preattached thiolated linker. Exposing the peptide sensor to various concentrations of Gram-positive bacteria generated reproducible impedance spectra that detected peptide-bacteria interactions at a concentration of 1 cell/μL. The peptide sensor also selectively detected Listeria monocytogenes from other Gram-positive strains at a concentration of 10(3) cfu mL(-1). The study highlights that short peptide ligands from bacteriocin class offer high selectivity in bacterial detection and can be used in developing a robust, portable biosensor device to efficiently detect pathogenic Gram-positive bacteria in food samples.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.341
Threshold uncertainty score0.945

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 head0.008
GPT teacher head0.206
Teacher spread0.198 · 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