Evidence map›Paper›PMID 37038792›Full record

ArticleTechnology and health care : official journal of the European Society for Engineering and Medicine2023

An automatic recognition method of nematode survival rate based on bright field and dark field experimental images.

Nan Zhang, Wenjing Zhang, Maoli Wang, Guojun Li, Junyu Ning, Yanmin Nie, Bo Xian, Zhihang Huang, Weiyang Chen, Shan Gao

Abstract read
In one paragraph

Article in Technology and health care : official journal of the European Society for Engineering and Medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Article
  2. An automatic measurement method for the response of Caenorhabditis elegans to chemicals.Technology and health care : official journal of the European Society for Engineering and Medicine · 2024
    Article
4 · The record

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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

10 authors.

Nan ZhangBeijing Center for Disease Prevention and Control, Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing, China.
Wenjing ZhangBeijing Center for Disease Prevention and Control, Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing, China.
Maoli WangSchool of Cyber Science and Engineering, Qufu Normal University, Qufu, Shandong, China.
Guojun LiBeijing Center for Disease Prevention and Control, Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing, China.
Junyu NingBeijing Center for Disease Prevention and Control, Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing, China.
Yanmin NieBeijing Center for Disease Prevention and Control, Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing, China.
Bo XianSchool of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Zhihang HuangSchool of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Weiyang ChenSchool of Cyber Science and Engineering, Qufu Normal University, Qufu, Shandong, China.
Shan GaoBeijing Center for Disease Prevention and Control, Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe survival rate of experimental animals is a very important index in chemical toxicity evaluation experiments. The calculation of nematode survival rate is used in many experiments.

objectiveTraditional survival rate quantification methods require manual counting. This is a time-consuming and laborious work when using 384-well plate for high-throughput chemical toxicity assessment experiments. At present, there is a great need for an automatic method to identify the survival rate of nematodes in the experiment of chemical toxicity evaluation.

methodsWe designed an automatic nematode survival rate recognition method by combining the bright field experimental image of nematodes and the dark field image of nematodes which is captured after adding Propidium Iodide dye, and used it to calculate the nematode survival rate in different chemical environments. Experiment results show that the survival rate obtained by our automatic counting method is very similar to the survival rate obtained by manual counting.

resultsThrough several different chemical experiments, we can see that chemicals with different toxicity have different effects on the survival rate of nematodes. And the survival rate of nematodes under different chemical concentrations has an obvious gradient trend from high concentration to low concentration. In addition, our method can quantify the motility of nematodes. There are also significant differences in the motility of nematodes cultured in different chemical environments. Moreover, the nematode motility under different chemical concentrations showed an obvious gradient change trend from high concentration to low concentration.

conclusionOur study provides an accurate and efficient nematode survival rate recognition method for chemical toxicology research.

Indexed as

Bone PlatesNematodaAnimalsSurvival Ratebright field imagechemical toxicitydark field image

Identifiers

PMID37038792
PMCPMC10200152

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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.