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Record W2075924254 · doi:10.5539/jfr.v1n4p35

Increase of Glutathione by Listeria monocytogenesscott A Cmremr When It Is Challenged by Gallic Acid and Nisin

2012· article· en· W2075924254 on OpenAlexvenueno aff
Caroline Galina Dal Moro, Camila Shultz, Jane Mary Lafayette Neves Gelinski, Claudriana Locatelli

Bibliographic record

VenueJournal of Food Research · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsnot available
Fundersnot available
KeywordsGallic acidNisinChemistryListeria monocytogenesLipid peroxidationGlutathioneTBARSThiobarbituric acidFood scienceBiochemistryMicrobiologyAntimicrobialAntioxidantBacteriaBiologyEnzymeOrganic chemistry

Abstract

fetched live from OpenAlex

<p class="Contedodetabela">This work investigates the activities of nisin and gallic acid, used either alone or in combination, against <em>Listeria monocytogenes</em><em> </em>Scott A Cm<sup>r</sup>Em<sup>r</sup>. The antimicrobial activity was determined using agar diffusion tests. The growth profile was evaluated by measurements of optical density and the numbers of viable cells. Lipid peroxidation was measured by the thiobarbituric acid-reactive substances (TBARS) technique, and the levels of reduced glutathione (GSH) were determined by the 5,5-dithio-bis-2-nitrobenzoic acid (DTNB) method. Growth of the pathogen was inhibited by the combined use of nisin and gallic acid, with an inhibition zone of approximately 11 mm at concentrations of 8 mg/ml and 100 IU/ml, respectively. No significant reduction in the number of viable pathogen cells was observed after 18 hours of exposure to nisin and gallic acid. There was a significant increase in the GSH concentration, and a decrease in lipid peroxidation, when the pathogen was exposed to increasing concentrations of nisin and gallic acid, used either alone or in combination, for a period of 18 hours. It was concluded that the <em>Listeria monocytogenes</em> cell line studied was able to resist the action of oxidizing agents by increasing the synthesis of GSH.</p>

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 score0.012
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.103
GPT teacher head0.325
Teacher spread0.222 · 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

Citations4
Published2012
Admission routes1
Has abstractyes

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