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Growth Inhibition of Foodborne Pathogens by  <i>Oenococcus oeni</i>

2011· article· en· W2044035628 on OpenAlexfundno aff
I‐Yuan Chiang, Randy W. Worobo, John J. Churey, Thomas Henick‐Kling

Bibliographic record

VenueJournal of Food Science · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsnot available
FundersLallemand
KeywordsOenococcus oeniListeria monocytogenesAntimicrobialEscherichia coliMicrobiologyProteasesSalmonellaBiologyPathogenSalmonella entericaFood scienceBacteriaMalolactic fermentationEnzymeBiochemistryLactic acid

Abstract

fetched live from OpenAlex

UNLABELLED: To explore the possibility of using Oenococcus oeni to inhibit foodborne pathogens, and to characterize antimicrobial compounds produced by O. oeni, 24 strains of O. oeni were tested for their ability to inhibit growth of foodborne pathogens, Escherichia coli O157:H7, Salmonella enteritidis, and Listeria monocytogenes by using the spot-on-lawn method. Of the 24 strains, 17 strains were able to inhibit all 3 pathogens in this study. Proteases, catalase, and buffer solutions were used for determining the type of inhibitory compounds produced from 4 selected strains with stronger inhibitory activity. Antimicrobial activity of 2 strains against the pathogens was completely inactivated by buffer solution, and other 2 strains against E. coli O157:H7 were partially removed. The antimicrobial compound was not sensitive to selected proteases and catalase. PRACTICAL APPLICATION: There is little information available about using O. oeni for human pathogens control. The results of this study revealed such discovery and potential applications for pathogen control.

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)0.001
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 score0.030
Threshold uncertainty score0.127

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.025
GPT teacher head0.198
Teacher spread0.173 · 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 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

Citations1
Published2011
Admission routes1
Has abstractyes

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