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Gliadin Degradation Ability of Artisanal Lactic Acid Bacteria, The Potential Probiotics from Dairy Products

2013· article· en· W2096011362 on OpenAlexvenueno aff
Gökçen Kömen, Ayşe Handan Baysal, Hayriye Şebnem Harsa

Bibliographic record

VenueJournal of Nutritional Therapeutics · 2013
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsnot available
Fundersİzmir Yüksek Teknoloji Enstitüsü
KeywordsFood scienceChemistryGliadinLactic acidFermentationTitratable acidHigh-performance liquid chromatographyBioconversionChromatographyBacteriaLactobacillus plantarumGel electrophoresisPopulationGlutenBiochemistryBiology

Abstract

fetched live from OpenAlex

Selected Lactobacillus spp. with high protease and acid producing capacity was explored for effective gliadin degradation in wheat sourdough environment. The total titratable acidity (TTA), pH and lactic acid bacteria (LAB) counts were evaluated. At the end of fermentation, the acidity and pH of the sourdough samples reached to 13.49-17.34 and 3.84-3.52 range, respectively. LAB population was enumerated as 107-109 colony forming unit (CFU)/g dough. Gliadin profiles were examined qualitatively using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), two-dimensional electrophoresis (2-DE) and reverse phase-high performance liquid chromatography (RP-HPLC) techniques. Especially RP-HPLC could be considered as a sensitive technique and is useful to determine the biochemical changes in gliadin fragmentation throughout sourdough fermentation process. LAB inoculated sourdoughs and chemically acidified sourdoughs generally represent similar gliadin degradation patterns. Although the total removal of gliadin toxicity could not be achieved in all dough formulations, it may be beneficial to use LAB to improve the dough and bread quality through the exploration of its bioconversion by-products.

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 score0.145
Threshold uncertainty score0.353

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 head0.034
GPT teacher head0.256
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

Citations0
Published2013
Admission routes1
Has abstractyes

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