Evidence map›Paper›PMID 36772386›Full record

ArticleSensors (Basel, Switzerland)2023

Novel Dual-Signal SiO

Lingjun Geng, Mengyue Liu, Jingcheng Huang, Falan Li, Yanyan Zhang, Yemin Guo, Xia Sun

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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.

Lingjun GengSchool of Agricultural Engineering and Food Science, Shandong University of Technology, No. 266 Xincun Xilu, Zibo 255049, China.
Mengyue LiuSchool of Agricultural Engineering and Food Science, Shandong University of Technology, No. 266 Xincun Xilu, Zibo 255049, China.
Jingcheng HuangSchool of Agricultural Engineering and Food Science, Shandong University of Technology, No. 266 Xincun Xilu, Zibo 255049, China.
Falan LiSchool of Agricultural Engineering and Food Science, Shandong University of Technology, No. 266 Xincun Xilu, Zibo 255049, China.
Yanyan ZhangSchool of Agricultural Engineering and Food Science, Shandong University of Technology, No. 266 Xincun Xilu, Zibo 255049, China.ORCID 0000-0002-1059-643X
Yemin GuoSchool of Agricultural Engineering and Food Science, Shandong University of Technology, No. 266 Xincun Xilu, Zibo 255049, China.
Xia SunSchool of Agricultural Engineering and Food Science, Shandong University of Technology, No. 266 Xincun Xilu, Zibo 255049, China.

Funding

National Natural Science Foundation of China 31872909National Natural Science Foundation of China 32001781
6 · The paper itself

Abstract

In view of the great threat of chloramphenicol (CAP) to human health and the fact that a few producers have illegally used CAP in the food production process to seek economic benefits in disregard of laws and regulations and consumer health, we urgently need a detection method with convenient operation, rapid response, and high sensitivity capabilities to detect CAP in food to ensure people's health. Herein, a molecularly imprinted polymer (MIP) electrochemical sensor based on a dual-signal strategy was designed for the highly sensitive analysis of CAP in milk. The NiFe Prussian blue analog (NiFe-PBA) and SnS

Indexed as

Molecular ImprintingSilicon DioxideAnimalsChloramphenicolElectrochemical TechniquesElectrodesHumansLimit of DetectionMilkPolymersReproducibility of ResultsChloramphenicolPolymersSilicon Dioxidechloramphenicoldual-signal electrochemical sensorNiFe Prussian blue analogueSnS2 nanoflowerssurface molecularly imprinted polymers

Identifiers

PMID36772386
PMCPMC9920509

What OpenQuestion holds

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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.