Effect of soiling agents on disinfection efficacy of a pulsed‐xenon <scp>UV</scp> lamp towards <scp> <i>Listeria monocytogenes</i> </scp> on stainless steel surfaces
Bibliographic record
Abstract
Abstract Listeria monocytogenes is a foodborne illness that poses a significant threat to human health in young, old, and immunocompromised persons and accordingly, prevention of Listeria contamination is of the utmost importance. Pulsed xenon ultraviolet radiation (PX‐UV) is a fast method with broad effectiveness against a spectrum of pathogens including Listeria spp. However, the effect of soiling agent present in food preparation environments on the efficacy of PX‐UV inactivation of L. monocytogenes is not well understood. In this work, the effect on PX‐UV treatment for protein‐based (BSA, peptone, and amino acids), carbohydrate (starch, glycogen, D‐lactose, trehalose), and lipid soiling agents (triolein and fish oil) were each evaluated. BSA, D‐lactose, trehalose, glycogen, and triolein were found to increase the amount of colonies recovered on the positive control plates (no treatment) while only trehalose (60% w/v) and fish oil (0.5% w/v) were found to significantly ( p < 0.05) decrease the log‐reduction, while casamino acids (1% w/v) actually increased the efficacy of the PX‐UV treatment. All other compounds had no effect at the concentrations tested. As similar types of compounds had similar UV absorption profiles, it is unlikely that UV absorption plays a significant role in the mechanism of protection exhibited by fish oil and trehalose.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".