Evidence map›Paper›PMID 36995409›Full record

ArticleAnalytical and bioanalytical chemistry2023

Nanozyme-based dual-signal sensing system for colorimetric and photothermal detection of AChE activity in the blood of liver-injured mice.

Chang He, Zhenyi Ke, Kai Liu, Jiasheng Peng, Qinghui Yang, Lixiang Wang, Guangfu Feng, Jun Fang

Abstract read
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In one paragraph

Article in Analytical and bioanalytical chemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 30% 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

5 citing papers in PubMed, 10 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

8 authors at 1 institution in 1 country.

Chang He *School of Bioscience and Biotechnology, Hunan Agricultural University, Changsha, 410128, China.
Zhenyi Ke *School of Bioscience and Biotechnology, Hunan Agricultural University, Changsha, 410128, China.
Kai LiuSchool of Bioscience and Biotechnology, Hunan Agricultural University, Changsha, 410128, China.
Jiasheng PengSchool of Bioscience and Biotechnology, Hunan Agricultural University, Changsha, 410128, China.
Qinghui YangSchool of Bioscience and Biotechnology, Hunan Agricultural University, Changsha, 410128, China.
Lixiang WangSchool of Bioscience and Biotechnology, Hunan Agricultural University, Changsha, 410128, China.
Guangfu FengSchool of Bioscience and Biotechnology, Hunan Agricultural University, Changsha, 410128, China. GuangfuFeng@hunau.edu.cn.ORCID http://orcid.org/0000-0001-7335-166X
Jun FangSchool of Bioscience and Biotechnology, Hunan Agricultural University, Changsha, 410128, China. fangjun1973@hunau.edu.cn.
Hunan Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acetylcholinesterase (AChE), a crucial enzyme related to liver function, is involved in numerous physiological processes such as neurotransmission and muscular contraction. The currently reported techniques for detecting AChE mainly rely on a single signal output, limiting their high-accuracy quantification. The few reported dual-signal assays are challenging to implement in dual-signal point-of-care testing (POCT) because of the need for large instruments, costly modifications, and trained operators. Herein, we report a colorimetric and photothermal dual-signal POCT sensing platform based on CeO

Indexed as

AcetylcholinesteraseBiosensing TechniquesAnimalsBenzidinesColorimetryLiverMiceAcetylcholinesteraseBenzidinesAChECeO2 nanoparticlesLiver injuryOrganophosphorusPhotothermal effectPOCT

Identifiers

PMID36995409
OpenAlexW4361268338

What OpenQuestion holds

Textmetadata
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.