Evidence map›Paper›PMID 40243318›Full record

ArticleApplied and environmental microbiology2025

A simulation model to quantify the efficacy of dry cleaning interventions on a contaminated milk powder line.

Devin Daeschel, Long Chen, Claire Zoellner, Abigail B Snyder

Abstract read
In one paragraph

Article in Applied and environmental microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Devin Daeschel *Department of Food Science, Cornell University Department of Food Science, Ithaca, New York, USA.ORCID 0000-0001-9113-2129
Long Chen *College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, Shaanxi, China.
Claire ZoellneriFood Decision Sciences, Inc., Seattle, Washington, USA.
Abigail B SnyderDepartment of Food Science, Cornell University Department of Food Science, Ithaca, New York, USA.ORCID 0000-0003-1141-4746

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Outbreaks of IMPORTANCE: This work demonstrates the utility of modeling as a decision support tool to (i) estimate Salmonella cross-contamination into product under different scenarios, (ii) compare different cleaning interventions, and (iii) help inform the selection of a Salmonella surrogate for cleaning validation studies. Risk models can describe the tradeoffs associated with different dry cleaning strategies in low moisture food environments. For example, the model presented in this study can estimate the differences in product contamination as a consequence of flushing a processing line with increasing quantities of material. Additionally, outputs from this model can be used to evaluate the risk of cross-contamination from a contaminated dry cleaning tool. Finally, comparing outputs from a simulation model is an alternative method for comparing Salmonella surrogates used in dry cleaning validation. Simulation model outputs (i.e., prevalence and concentration of contaminated units) may be more broadly interpretable than comparing transfer coefficients alone, enhancing decision support.

Indexed as

DisinfectionFood ContaminationFood MicrobiologyMilkSalmonellaAnimalsComputer SimulationEquipment ContaminationMonte Carlo MethodPowdersPowderscomputer modelingdry cleaningdry sanitationflushingfood-borne pathogenslow moisture foodmilk powderMonte Carlo simulation

Identifiers

PMID40243318
PMCPMC12093965

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.