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Probiotic Characteristics of Streptococcus thermophilus and Lactobacillus bulgaricus as Influenced by New Food Sources

2023· article· en· W4386690235 on OpenAlexfundno aff
Ashley Castro, Ricardo S. Alemán, Miguel Tabora, Shirin Kazemzadeh Pournaki, Leyla K. Pournaki, Roberto Cedillos, Jhunior Marcía, Kayanush J. Aryana

Bibliographic record

VenueMicroorganisms · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsnot available
FundersHatchConsejo Superior Universitario CentroamericanoInternational Development Research CentreU.S. Department of Agriculture
KeywordsProbioticLactobacillusStreptococcus thermophilusBiologyFood scienceProteaseMicrobiologyBacteriaBiochemistryEnzyme

Abstract

fetched live from OpenAlex

The current research aimed to evaluate the potential effects of Solanum mammosum, Dioon mejiae, and Amanita caesarea on Streptococcus thermophilus and Lactobacillus delbrueckii subsp. bulgaricus survival and performance after exposure to different harsh conditions such as bile, acid, gastric juice, and lysozyme to mimic the digestive system from mouth to the intestine. Probiotic protease activity was observed to evaluate the proteolytic system. Probiotics were cultured in a broth mixed with plant material, and after incubation, the results were compared to the control sample. Therefore, plant material’s total phenolic compound, total carotenoid compound, antioxidant activity, sugar profile, and acid profile were obtained to discuss their impact on the survival of probiotics. The results indicate that Amanita caesarea negatively affected probiotic survival in the bile tolerance test and positively affected Lactobacillus bulgaricus in the protease activity test. Otherwise, the other plant material did not change the results significantly (p > 0.05) compared to the control in different tests. Consequently, Solanum mammosum and Dioon mejiae had no significant effects (p > 0.05) in increasing probiotic survival.

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 score0.319
Threshold uncertainty score0.311

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 head0.008
GPT teacher head0.188
Teacher spread0.180 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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