Evidence map›Paper›PMID 36900607›Full record

ArticleFoods (Basel, Switzerland)2023

Preparation, Identification and Preliminary Application of the Fenvalerate Monoclonal Antibody in Six Kinds of Dark Tea.

Kang Wei, Qihui Yang, Yang Wei, Yuanfeng Wang, Naifeng Xu, Xinlin Wei

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Article in Foods (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. Review
  2. Review
  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

6 authors.

Kang WeiDepartment of Food Science & Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China.
Qihui YangInstitute of Food Engineering, College of Life Science, Shanghai Normal University, 100 Guilin Road, Shanghai 200234, China.
Yang WeiDepartment of Food Science & Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID 0000-0001-8302-8903
Yuanfeng WangInstitute of Food Engineering, College of Life Science, Shanghai Normal University, 100 Guilin Road, Shanghai 200234, China.ORCID 0000-0003-3743-4008
Naifeng XuInstitute of Food Engineering, College of Life Science, Shanghai Normal University, 100 Guilin Road, Shanghai 200234, China.ORCID 0000-0001-6457-7659
Xinlin WeiDepartment of Food Science & Technology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China.

Funding

Key Project of Science and Technology Commission of Shanghai, China 20392002100National Key R & D Program of China 2018YFC1604401
6 · The paper itself

Abstract

Fenvalerate has the advantages of a broad insecticidal spectrum, high efficiency, low toxicity and low cost, and it is widely used in agriculture, especially in tea, resulting in the accumulation of fenvalerate residues in tea and the environment, posing a serious threat to human health. Therefore, the timely monitoring of fenvalerate residue dynamics is vital for ensuring the health of humans and the ecological environment, and it is necessary for establishing a fast, reliable, accurate and on-site method for detecting fenvalerate residues. Based on the methods of immunology, biochemistry and molecular biology, mammalian spleen cells, myeloma cells and mice were used as experimental materials to establish a rapid detection method of an enzyme-linked immunosorbent assay to detect the residues of fenvalerate in dark tea. Three cell lines-1B6, 2A11 and 5G2-that can stably secrete fenvalerate antibodies were obtained by McAb technology, and their sensitivities (IC

Indexed as

ELISAhaptenhybridoma techniquemonoclonal antibodytest strip

Identifiers

PMID36900607
PMCPMC10001202

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LicenceCC BY
reference markers read22
measurements read55
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.