Evidence map›Paper›PMID 31323858›Full record

ReviewNanomaterials (Basel, Switzerland)2019

Recent Advances and Perspectives of Molecularly Imprinted Polymer-Based Fluorescent Sensors in Food and Environment Analysis.

Guangyang Liu, Xiaodong Huang, Lingyun Li, Xiaomin Xu, Yanguo Zhang, Jun Lv, Donghui Xu

Open access · goldAbstract readReview
In one paragraph

Review in Nanomaterials (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
6.3field-weighted citation impact, top 2% of its field
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

14 citing papers in PubMed, 89 citations in OpenAlex.

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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 at 3 institutions in 1 country.

Guangyang LiuInstitute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Vegetables Quality and Safety Control, Laboratory of Quality & Safety Risk Assessment for vegetable Products, Ministry of Agriculture and Rural Affairs of China, Beijing 100081, China.
Xiaodong HuangInstitute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Vegetables Quality and Safety Control, Laboratory of Quality & Safety Risk Assessment for vegetable Products, Ministry of Agriculture and Rural Affairs of China, Beijing 100081, China.
Lingyun LiInstitute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Vegetables Quality and Safety Control, Laboratory of Quality & Safety Risk Assessment for vegetable Products, Ministry of Agriculture and Rural Affairs of China, Beijing 100081, China.
Xiaomin XuInstitute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Vegetables Quality and Safety Control, Laboratory of Quality & Safety Risk Assessment for vegetable Products, Ministry of Agriculture and Rural Affairs of China, Beijing 100081, China.
Yanguo ZhangInstitute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Vegetables Quality and Safety Control, Laboratory of Quality & Safety Risk Assessment for vegetable Products, Ministry of Agriculture and Rural Affairs of China, Beijing 100081, China.
Jun LvInstitute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Vegetables Quality and Safety Control, Laboratory of Quality & Safety Risk Assessment for vegetable Products, Ministry of Agriculture and Rural Affairs of China, Beijing 100081, China.
Donghui XuInstitute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Key Laboratory of Vegetables Quality and Safety Control, Laboratory of Quality & Safety Risk Assessment for vegetable Products, Ministry of Agriculture and Rural Affairs of China, Beijing 100081, China. xudonghui@caas.cn.
Institute of Vegetables and Flowers · CNChinese Academy of Agricultural Sciences · CNMinistry of Agriculture and Rural Affairs · CN

Funding

National Natural Science Foundation of China 31701695
6 · The paper itself

Abstract

Molecular imprinting technology (MIT), also known as molecular template technology, is a new technology involving material chemistry, polymer chemistry, biochemistry, and other multi-disciplinary approaches. This technology is used to realize the unique recognition ability of three-dimensional crosslinked polymers, called the molecularly imprinted polymers (MIPs). MIPs demonstrate a wide range of applicability, good plasticity, stability, and high selectivity, and their internal recognition sites can be selectively combined with template molecules to achieve selective recognition. A molecularly imprinted fluorescence sensor (MIFs) incorporates fluorescent materials (fluorescein or fluorescent nanoparticles) into a molecularly imprinted polymer synthesis system and transforms the binding sites between target molecules and molecularly imprinted materials into readable fluorescence signals. This sensor demonstrates the advantages of high sensitivity and selectivity of fluorescence detection. Molecularly imprinted materials demonstrate considerable research significance and broad application prospects. They are a research hotspot in the field of food and environment safety sensing analysis. In this study, the progress in the construction and application of MIFs was reviewed with emphasis on the preparation principle, detection methods, and molecular recognition mechanism. The applications of MIFs in food and environment safety detection in recent years were summarized, and the research trends and development prospects of MIFs were discussed.

Indexed as

fluorescence sensorfood quality and safetymolecularly imprinted polymermolecular recognitionrapid detection

Identifiers

PMID31323858
PMCPMC6669699
OpenAlexW2957606267

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.