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Record W1875439130 · doi:10.1139/cjm-2014-0667

Effect of tea tree (<i>Melaleuca alternifolia</i>) oil as a natural antimicrobial agent in lipophilic formulations

2014· article· en· W1875439130 on OpenAlexaffvenue
Elisabeth Mantil, Grace Daly, Tyler J. Avis

Bibliographic record

VenueCanadian Journal of Microbiology · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsCarleton University
FundersEuropean Commission
KeywordsTea tree oilMelaleuca alternifoliaAntimicrobialPreservativeBacillus subtilisBiologyFood scienceMicrobiologyChemistryEssential oilBacteria

Abstract

fetched live from OpenAlex

There has been increased interest surrounding the use of tea tree oil (TTO) as a natural antimicrobial. In this study, the antimicrobial activity of TTO and its components were investigated in vitro and in a predominantly lipid-based personal care formulation. In vitro, TTO showed minimal inhibitory concentrations of 0.2% (for Saccharomyces cerevisiae and Pythium sulcatum), 0.4% (for Escherichia coli, Bacillus subtilis, and Rhizopus stolonifer), and 0.8% (for Botrytis cinerea). TTO at 0.08%-0.8% was often as efficient as parabens. Comparison of the antimicrobial activities of TTO components showed that terpinen-4-ol and γ-terpinene were generally most effective in inhibiting microbial growth. TTO activity in a personal care product was evaluated through air and water exposure, artificial inoculation, and shelf life studies. While TTO did not increase shelf life of unopened products, it decreased microbial load in products exposed to water and air. Results from this study support that antimicrobial activity of TTO can be attributed to varying levels of its components and that low levels of TTO were effective in reducing microbial growth during the use of the product. This study showed that TTO can act as a suitable preservative system within an oil-based formulation.

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 score0.121
Threshold uncertainty score0.998

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 head0.006
GPT teacher head0.203
Teacher spread0.197 · 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

Citations15
Published2014
Admission routes2
Has abstractyes

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