ArticleBMC veterinary research2015
Analysis of zebrafish (Danio rerio) behavior in response to bacterial infection using a self-organizing map.
Article in BMC veterinary research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 20 citations in OpenAlex.
- Diving into drug-screening: zebrafish embryos as an in vivo platform for antimicrobial drug discovery and assessment.FEMS microbiology reviews · 2024Review
- Furan-based Chalcone Annihilates the Multi-Drug-Resistant Pseudomonas aeruginosa and Protects Zebra Fish Against its Infection.Journal of microbiology (Seoul, Korea) · 2024Article
- Trans- and Multigenerational Effects of Isothiazolinone Biocide CMIT/MIT on Genotoxicity and Epigenotoxicity inToxics · 2023Article
- Animal Inflammation-Based Models of Neuropsychiatric Disorders.Advances in experimental medicine and biology · 2023Article
- Article
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- Aquatic Toxic Analysis by Monitoring Fish Behavior Using Computer Vision: A Recent Progress.Journal of toxicology · 2018Review
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAnimal behavioral responses have been recently established as a suitable tool for detecting contaminants in the environment for risk assessment in situ. In this study, we observed movement behavior of zebrafish (Danio rerio) before and after infection with Edwardsiella tarda CK41 for 3 days until death.
methodsInfection status of zebrafish was confirmed through PCR and colonization assay as time progressed and lesion development in the tails of zebrafish was also examined. Movement behaviors in response to bacterial infection were patterned by self-organizing map (SOM) based on movement parameters, including speed (mm/s), acceleration (mm/s (2) ), stop duration (t), stop number (n), locomotory rate (mm/s), turning rate (rad/s), and meander (rad/mm).
resultsAccording to SOM result, clusters were identified firstly according to time and secondly according to infection. Two movement patterns were observed in the early period of infection: one group with minimum turning rate and meander (i.e., stiff movement) and the other group with maximum strop number. Late infection was characterized by long stop duration.
conclusionSOM was suitable for extracting complex behavioral data and thus can serve as a referencing system for diagnosing disease development in order to reveal the mechanism of the infection process.
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