Evidence mapPaperPMID 40807607Full record

ReviewFoods (Basel, Switzerland)2025

Electrochemical Biosensors Driving Model Transformation for Food Testing.

Xinxin Wu, Zhecong Yuan, Shujie Gao, Xinai Zhang, Hany S El-Mesery, Wenjie Lu, Xiaoli Dai, Rongjin Xu

Abstract readReview
In one paragraph

Review in Foods (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. 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

8 authors.

Xinxin WuSchool of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.
Zhecong YuanSchool of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.
Shujie GaoSchool of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.
Xinai ZhangSchool of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.
Hany S El-MeserySchool of Energy and Power Engineering, Jiangsu University, Zhenjiang 212013, China.
Wenjie LuSchool of Energy and Power Engineering, Jiangsu University, Zhenjiang 212013, China.
Xiaoli DaiSchool of Energy and Power Engineering, Jiangsu University, Zhenjiang 212013, China.
Rongjin XuSchool of Energy and Power Engineering, Jiangsu University, Zhenjiang 212013, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electrochemical biosensors are revolutionizing food testing by addressing critical limitations of conventional strategies that suffer from cost, complexity, and field-deployment challenges. Emerging fluorescence and Raman techniques, while promising, face intrinsic drawbacks like photobleaching and matrix interference in opaque or heterogeneous samples. In contrast, electrochemical biosensors leverage electrical signals to bypass optical constraints, enabling rapid, cost-effective, and pretreatment-free analysis of turbid food matrices. This review highlights their operational mechanisms, emphasizing nano-enhanced signal amplification (e.g., Au nanoparticles and graphene) and biorecognition elements (antibodies, aptamers, and molecularly imprinted polymers) for ultrasensitive assay of contaminants, additives, and adulterants. By integrating portability, scalability, and real-time capabilities, electrochemical biosensors align with global food safety regulations and sustainability goals. Challenges in standardization, multiplexed analysis, and long-term stability are discussed, alongside future directions toward AI-driven analytics, biodegradable sensors, and blockchain-enabled traceability, ultimately fostering precision-driven, next-generation food safety and quality testing.

Indexed as

electrochemical biosensorfood qualityfood safetynanostructuresspecific capture

Identifiers

PMID40807607
PMCPMC12346509

What Socratic 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 Socratic graph.