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Record W4403214050 · doi:10.1021/acsagscitech.4c00341

Synergistic and Broad-Spectrum Efficacy of Phenylacetate and Acetophenone Combination Against Mycotoxin-Producing Fungi

2024· article· en· W4403214050 on OpenAlex

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

VenueACS Agricultural Science & Technology · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycotoxins in Agriculture and Food
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersAgricultural Research Service
KeywordsAcetophenoneMycotoxinPhenylacetateBroad spectrumChemistryFood scienceOrganic chemistryCombinatorial chemistryBiochemistry

Abstract

fetched live from OpenAlex

Mycotoxin contamination of food may lead to cancer and is caused by fungal pathogens. In this study, we discovered that two natural products, phenylacetate and acetophenone, inhibit the growth of mycotoxin-producing fungi of agricultural importance. Using disc diffusion assays, we observed that both chemicals demonstrated antifungal activity against mycotoxin-producing Aspergillus flavus . The efficacies of acetophenone and phenylacetate synergized against A. flavus and four additional mycotoxin-producing fungi such as A. parasiticus, Penicillium expansum, Fusarium oxysporum, and F. verticillioides . Using growth kinetic assay, we observed that phenylacetate and acetophenone inhibited growth rates of human fungal pathogens, Candida albicans and C. auris . High-performance liquid chromatography analysis of aflatoxins extracted from A. flavus demonstrated that acetophenone treatment inhibited the production of aflatoxins, while phenylacetate did not have such an effect. This study identifies the phenylacetate–acetophenone combination as a potential antifungal for the mycotoxin-producing fungal treatment of food.

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 score0.451
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.216
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