Evidence map›Paper›PMID 41976544›Full record

ReviewFoods (Basel, Switzerland)2026

Advances of Digital Detection for Foodborne Pathogens.

Ruonan He, Diming Hua, Wenwen Wu, Mojun Shi, Xuejiao Huang, Xuhan Xia, Ruijie Deng

Abstract readReview
In one paragraph

Review in Foods (Basel, Switzerland), 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

7 authors.

Ruonan HeCollege of Ecology and Environment, Chengdu University of Technology, Chengdu 610059, China.
Diming HuaCollege of Biomass Science and Engineering, Sichuan University, Chengdu 610065, China.
Wenwen WuKey Laboratory of Baijiu Supervising Technology, State Administration for Market Regulation, Chengdu 610000, China.
Mojun ShiKey Laboratory of Baijiu Supervising Technology, State Administration for Market Regulation, Chengdu 610000, China.
Xuejiao HuangKey Laboratory of Baijiu Supervising Technology, State Administration for Market Regulation, Chengdu 610000, China.
Xuhan XiaCollege of Biomass Science and Engineering, Sichuan University, Chengdu 610065, China.
Ruijie DengCollege of Biomass Science and Engineering, Sichuan University, Chengdu 610065, China.ORCID 0000-0001-9094-124X

Funding

National Natural Science Foundation of China 32502323
6 · The paper itself

Abstract

The implementation of stringent regulatory policies for foodborne pathogens necessitates ultra-sensitive analytical methods. Digital detection, characterized by absolute quantification and tolerance to complex matrices, serves as a robust approach for food safety monitoring. This review summarizes recent advances in digital detection for foodborne pathogens, including nucleic acid amplification-based platforms such as droplet digital PCR and digital isothermal amplification, as well as emerging preamplification-free approaches based on enzyme-mediated signal conversion, functional nanomaterials, and microfluidic devices. We also profile the applications of digital detection technologies for achieving highly specific and accurate detection of foodborne pathogens and discuss their capabilities in viable bacteria quantification, antimicrobial resistance analysis, and multiplex detection. We finally discuss emerging trends, including partition-free digital detection and artificial intelligence-assisted analysis. These advances are expected to promote the development of intelligent and data-driven food safety surveillance strategies.

Indexed as

biosensingdigital detectionfoodborne pathogenfood safetynucleic acid

Identifiers

PMID41976544
PMCPMC13072714

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.