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Record W4409543916 · doi:10.62791/20209

Inhibition of Streptococcus and Enterococcus biofilms by cranberry bioactives

2022· dissertation· en· W4409543916 on OpenAlexaboutno aff
Ryan A. Magina

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicBee Products Chemical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMicrobiologyEnterococcusBiofilmStreptococcusBiologyChemistryBacteriaAntibiotics

Abstract

fetched live from OpenAlex

Cranberry (Vaccinium macrocarpon) is a low bush fruit cultivated throughout northern United States and Canada and is well-known for its ability to alleviate the symptoms and duration of urinary tract infections. Recent studies, however, have shown promising antimicrobial activity against several other organisms responsible for different infections. These studies have reported inhibition of bacterial adhesion, co-aggregation and biofilm formation, and have shown that several constituents including proanthocyanidins, flavonols and polysaccharides may work synergistically to reduce E. coli adhesion forces and co-aggregation of oral bacteria. The rise in antibiotic-resistance has driven investigations for alternative methods to treat infectious diseases. Inhibiting or disrupting the formation of biofilms is a potential method to prevent infectious disease without promoting the development of new antibiotic-resistant strains of bacteria. It is, therefore, important to explore the mechanisms by which cranberry phytochemicals prevent certain infectious processes by isolating, characterizing and assaying antimicrobial properties of phytochemicals found in cranberry fruit. The aims of this study were to first identify phytochemicals derived from cranberry fruit and then to compare their effects on the biofilm formation of different bacteria both alone or in combination. Whole cranberry fruit was extracted and then further separated into different fractions based on phytochemical types by open column chromatography. Composition of these extracts were determined by HPLC-PDA, UPLC-QTOF-MS, and MALDI-TOF-MS methods. These fractions were categorized as phenolic acid-containing, flavonol-containing, anthocyanin-containing, and proanthocyanidin-containing extracts. Phenolic acid-containing extracts were determined to contain organic acids such as chlorgenic acid. Flavonol-containing extracts were predominately composed of glycosylated myricetin, quercetin, and kaempeferol. Anthocyanin-containing extracts were mainly cyanidin and peonidin derivatives. Proanthocyanidin-containing extracts were composed of different proanthocyanindin oligomers ranging from monomer units to nine degrees of polymerization with varying numbers of A-type and B-type linkages. Several Enterococcus and Streptococcus strains were selected for further evaluation based on their clinical relevance in prostate infections, dental caries, and throat infections; information on cranberry’s efficacy against these organisms is lacking. Isolates from whole cranberry fruit were evaluated against five organisms for their biofilm inhibitory capability alone and in combination, using a crystal violet stain biofilm assay. The effects were varied based on phytochemical class and organism. Several fractions inhibited biofilm formation in a dose-dependent manner. A fraction containing primarily A-type proanthocyanidin oligomers ranging from 2 to 7 (epi)catechin units, was a potent biofilm inhibitor against all organisms tested. These fractions were able to prevent biofilm formation by all organisms tested at low concentrations. Other fractions were effective in reducing biofilm formation in specific cases. Anthocyanin-containing fractions showed greater selectivity for Enterococcus spp. while fractions containing primarily flavonols were more effective on Streptococcus spp. Phenolic acid-containing fractions showed no consistent effect against biofilm formation. The synergistic effect of fractions was also evaluated by combining flavonol-containing fractions and proanthocyanidin-containing fractions. In most cases, this combination was able to reduce biofilm formation better than the flavonol-containing and proanthocyanidin-containing fractions alone. These findings suggest there could be an ideal composition of cranberry phytochemicals that would be highly effective in reducing biofilm formation. Based on these results, cranberry may help reduce infection by these pathogens by interfering with the initial steps of adhesion and biofilm formation without promoting the development of antibiotic-resistant strains.

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 categoriesInsufficient payload (model declined to judge)
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 score0.030
Threshold uncertainty score0.996

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)0.0050.000

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 head0.007
GPT teacher head0.214
Teacher spread0.207 · 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.

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
Published2022
Admission routes1
Has abstractyes

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