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Record W2212339353 · doi:10.3920/bm2015.0047

In vitro evaluation of nutrients that selectively confer a competitive advantage to lactobacilli

2015· article· en· W2212339353 on OpenAlex
Rebecca Vongsa, R.A. Minerath, Madison Busch, Joo Shun Tan, David W. Koenig

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBeneficial Microbes · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsKimberly-Clark (Canada)
Fundersnot available
KeywordsIn vitroBiologyNutrientBiotechnologyFood scienceChemistryMicrobiologyBiochemistryEcology

Abstract

fetched live from OpenAlex

An assay was developed that tested the ability of Lactobacillus acidophilus to outcompete a challenge of Escherichia coli in a mixed culture containing different test nutrients. Using this assay, addition of fructo-oligosaccharide to the media allowed L. acidophilus to outcompete a challenge of E. coli, whereas in a mixed culture without the prebiotic the trend was reversed. Growth curves generated for E. coli in a single culture showed that fructo-oligosaccharide did not affect growth, indicating that the carbohydrate was not toxic to E. coli. This indicates that fructo-oligosaccharides may increase the ability of beneficial microbes to outcompete a pathogenic challenge. These results were confirmed using a skin simulant model that incorporates growth of the organisms at an air-surface interface to mimic the vulvar environment. It is possible to use a co-culture assay as an in vitro screening tool to define nutrients that confer a competitive advantage to beneficial flora specific to the female urogenital tract.

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.

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 score0.090
Threshold uncertainty score0.183

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 head0.060
GPT teacher head0.281
Teacher spread0.221 · 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