MétaCan
Menu
Back to cohort
Record W4410895596 · doi:10.1080/08927014.2025.2511002

Combined enzymes and Aleppo pine essential oil to control <i>Cronobacter sakazakii</i> biofilms on stainless steel and plastic surfaces

2025· article· en· W4410895596 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

VenueBiofouling · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnterobacteriaceae and Cronobacter Research
Canadian institutionsUniversity of Manitoba
FundersHashemite University
KeywordsBiofilmAleppo PineCronobacter sakazakiiEssential oilFood scienceChemistryMicrobiologyBiologyBotanyPulp and paper industryBacteriaEngineering

Abstract

fetched live from OpenAlex

This study aimed to investigate the antibiofilm activity of Aleppo pine essential oil (APEO); hydrolytic enzyme mixtures or their combination in two sequential washing steps against C. sakazakii on plastic and stainless steel surfaces. The minimum inhibitory (MIC) and minimum bactericidal concentrations (MBC) of APEO against C. sakazakii strains were 500–1,000 µg/ml, and 1,000–4,000 µg/ml, respectively. Further, APEO showed antibiofilm activity where 4 × MIC APEO at 25 °C for 30 min reduced C. sakazakii cells by 1.8 and 1.6 log CFU/coupon on plastic and stainless steel, respectively. Similarly, both enzyme mixtures reduced the C. sakazakii cells attached to both surfaces by 1.7–2.2 log CFU/coupon. However, the two-step sequential cleaning regime with enzyme mixture of 10% protease, 5% α-amylase, and 1% lipase at 50 °C for 30 min followed by 4 × MIC APEO for 30 min reduced C. sakazakii biofilm on both surfaces by 4.4–4.5 log CFU/coupon compared to the control.

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 score0.868

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 head0.005
GPT teacher head0.254
Teacher spread0.249 · 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