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Record W2110189040 · doi:10.5539/jfr.v2n1p1

Inhibitory Effects of Commercial and Enriched Green Tea Extracts on the Growth of Brochothrix thermosphacta, Pseudomonas putida and Escherichia coli

2012· article· en· W2110189040 on OpenAlexafffundvenue
Élodie Rozoy, Laurent Bazinet, Monica Araya-Farias, Anthony Guernec, Linda Saucier

Bibliographic record

VenueJournal of Food Research · 2012
Typearticle
Languageen
FieldMedicine
TopicTea Polyphenols and Effects
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaAdvanced Foods and Materials Network
KeywordsEscherichia coliPseudomonas putidaCatechinAntimicrobialMinimum inhibitory concentrationEpigallocatechin gallateMicrobiologyChemistryFood scienceGreen tea extractBiologyGreen teaBiochemistryPolyphenolAntioxidant

Abstract

fetched live from OpenAlex

The major catechin found in green tea, called epigallocatechin gallate (EGCG), have been reported to have antimicrobial properties. In this study, we examined in vitro the antimicrobial effects of a commercial green tea extract sold in a capsule form, and two prepared green tea extracts enriched in catechins against Brochothrix thermosphacta, Pseudomonsas putida and Escherichia coli which have been associated with meat spoilage. The antimicrobial activity of the different tea extracts was evaluated by Spot-On-Lawn and Well Diffusion assays and the Minimum Inhibitory Concentration (MIC) was also determined in Brain Heart Infusion broth. The three methods used showed an inhibition of Brochothrix thermosphacta, whereas the inhibition of Pseudomonas putida and Escherichia coli was only detected with the MIC assay. The determination of the MIC in broth culture appeared to be the most reliable method to determine the inhibitory activity of catechin compounds.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0010.000

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 head0.044
GPT teacher head0.326
Teacher spread0.282 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2012
Admission routes3
Has abstractyes

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