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Record W2086096027 · doi:10.1111/jam.12391

<i>Pediococcus acidilactici</i>UL5 and<i>Lactococcus lactis</i>ATCC 11454 are able to survive and express their bacteriocin genes under simulated gastrointestinal conditions

2013· article· en· W2086096027 on OpenAlexaff
Benoît Fernandez, Riadh Hammami, Patricia Savard, Julie Jean, Ismaı̈l Fliss

Bibliographic record

VenueJournal of Applied Microbiology · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPediococcus acidilacticiLibrary scienceMedicineBiologyComputer science

Abstract

fetched live from OpenAlex

AIMS: The aim of this work is to study the expression of stress genes and those involved in pediocin and nisin production in Pediococcus acidilactici UL5 and Lactococcus lactis ATCC11454 under simulated gastrointestinal (GI) physiological conditions. METHODS AND RESULTS: The two strains were fed to a dynamic GI model (TIM-1). Samples were taken from different compartments and analysed for strain survival as well as for the expression of pediocin PA-1 operon, nisin A production gene and stress genes using RT-qPCR. Ileal-delivered efflux showed a survival rate of 17 and 0·0007% for Ped. acidilactici and La. lactis, respectively. Pediocin operon genes from stressed cells were generally expressed at least at the same level as for unstressed cells. However, pedA is up-regulated in the effluent at 120 and 180 min. Nisin A genes were always up-regulated with particularly in the stomach after 70 min compared with control. CONCLUSIONS: Bacteriocin production of Ped. acidilactici UL5 and Lc. lactis ATCC 11454 are not affected by upper GI simulated conditions and thus could be considered as relevant probiotic candidates. SIGNIFICANCE AND IMPACT OF THE STUDY: This study demonstrates the capacity of lactic acid bacteria to survive and express their bacteriocins genes under simulated GI conditions.

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 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 score0.451
Threshold uncertainty score0.420

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 head0.010
GPT teacher head0.198
Teacher spread0.188 · 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

Citations29
Published2013
Admission routes1
Has abstractyes

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