Evidence map›Paper›PMID 41719764›Full record

ArticleUltrasonics sonochemistry2026

Ultrasound-assisted quercetin treatment for mono- and dual-species biofilm eradication in milk: Modeling and optimization using GA-ANN approach.

Abhishek Kaushik, Ansh Singh, Neetu Kumra Taneja, Pankaj Taneja

Abstract read
In one paragraph

Article in Ultrasonics sonochemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Abhishek KaushikDepartment of Interdisciplinary Sciences, National Institute of Food Technology Entrepreneurship and Management (NIFTEM), Sonipat, Haryana 131028, India.
Ansh SinghDepartment of Interdisciplinary Sciences, National Institute of Food Technology Entrepreneurship and Management (NIFTEM), Sonipat, Haryana 131028, India.
Neetu Kumra TanejaDepartment of Interdisciplinary Sciences, National Institute of Food Technology Entrepreneurship and Management (NIFTEM), Sonipat, Haryana 131028, India. Electronic address: neetu.taneja@niftem.ac.in.
Pankaj TanejaDepartment of Biotechnology, Sharda School of Bioscience and Technology, Sharda University, Greater Noida, Uttar Pradesh 201306, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The presence of mono- and dual-species biofilms in food industry poses a critical threat with respect to food security and safety at a global scale. This study explored a novel synergistic eradication strategy using ultrasonication and quercetin, for the eradication of mono and dual-species biofilms of Escherichia coli and Salmonella Typhimurium in milk. The eradication of biofilms was simulated via Response Surface Methodology (RSM) and a Genetic Algorithm-Artificial Neural Network (GA-ANN), taking treatment parameters like ultrasonic amplitude, time and bioactive concentration as inputs variable. Quercetin alone exhibited a significant dose- and time-dependent biofilm inactivation, with the maximum reduction of 2.49 ± 0.08 log for S. Typhimurium and 2.14 ± 0.14 log for E. coli mono-species biofilms, at 4 mg/mL after 4 h of exposure. However, this efficacy decreased in dual-species biofilms, confirming their enhanced structural integrity and resilience. The GA-ANN models showed a better predictive accuracy (R

Indexed as

BiofilmsMilkNeural Networks, ComputerQuercetinUltrasonic WavesAnimalsEscherichia coliGenetic AlgorithmsSalmonella typhimuriumQuercetinBioactiveOptimization dual-species biofilmsPredictive modellingSynergistic eradicationUltrasonication

Identifiers

PMID41719764
PMCPMC12936950

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.