MétaCan
Menu
Back to cohort
Record W6939211615 · doi:10.60692/apray-qzw32

Synergistic photoinactivation of Escherichia coli and Listeria innocua by curcumin and lauric arginate ethyl ester micelles

2023· article· en· W6939211615 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCurcumin's Biomedical Applications
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCurcuminListeriaLauric acidAntimicrobialEscherichia coliMembrane permeabilityAqueous solution

Abstract

fetched live from OpenAlex

This study evaluated the changes in dispersibility in the aqueous phase, chemical stability, and antimicrobial activity of curcumin after being encapsulated in a lauric arginate ethyl ester (LAE) micelle. Stock curcumin-LAE solutions were prepared by titrating curcumin dissolved in ethanol into LAE aqueous solutions (pH 3.5). The LAE in the stock solutions inhibited the crystallization and prevented the chemical degradation of curcumin during storage at 20 °C. The antimicrobial activity of the curcumin-LAE solutions against Escherichia coli (E. coli) and Listeria innocua (L. innocua) cocktails was assessed by exposing the sample to UV-A light (λ = 365 nm) for 5 min. For samples with both LAE and curcumin at pH 3.5 during irradiation, synergistic antimicrobial activity was observed. The release of protein or nucleic acid from the cells indicated an increase in its membrane permeability after treatments which was due to LAE-facilitated interaction between the photosensitizer and the membrane. LAE could inactivate both bacteria within 10 min without UV-A light irradiation, only at pH 7, which shows that LAE's antimicrobial efficacy depends on the pH. Therefore, microbial inactivation by two mechanisms, photosensitization and permeability operating simultaneously, produced a curcumin-LAE solution that could inactivate bacteria at a broad pH range.

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 score0.127
Threshold uncertainty score0.482

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 head0.014
GPT teacher head0.216
Teacher spread0.202 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueGreater South Information SystemSame topicCurcumin's Biomedical ApplicationsFrench-language works237,207