Video-tracking of zebrafish (Danio rerio) as a biological early warning system using two distinct artificial neural networks: Probabilistic neural network (PNN) and self-organizing map (SOM)

Reducing the Number of Individuals to Monitor Shoaling Fish Systems – Application of the Shannon Entropy to Construct a Biological Warning System Model

“…The aim of the present work was to obtain an essential piece of information for BWS design purposes and for physiological research: to elucidate whether the number of fish affected the SE of the system in a known shoaling fish species (European seabass) and, if so, what type of relationship these two variables kept. As we have already mentioned, it must be noted that we did not aim at mapping behavioral characteristics such as time swimming or resting, aggressive behavior, the kind of shoaling and schooling itself or inter-individual interactions which would require a different methodological approach and algorithms more sophisticated than the SE to analyze the data (see for example the works by Tunstrøm et al, 2013 ; Teles et al, 2015 ; Gauvrit et al, 2017 ; Crosato et al, 2018 ).…”

“…Fish cognition and behavior is a well-established research field ( Vila Pouca and Brown, 2017 and references therein), and the characterisation of fish model systems’ behavior, using behavioral measurable changes, has found several practical applications, such as the detection of leaders in a group ( Mwaffo et al, 2017 ), the identification of information flows within a school of fish ( Crosato et al, 2018 ), the presence in the aquatic environment of contaminants including caffeine ( Ladu et al, 2015 ), drugs ( Liu et al, 2011 ), hypochlorite ( Magalhães et al, 2007 ; Nimkerdphol and Nakagawa, 2008 ; Teles et al, 2015 ), methyl-mercury ( Eguiraun et al, 2014 , 2016 ), the Se:Hg molar ratio in their feeds ( Eguiraun et al, 2018 ) and alterations in environmental parameters such as hypoxia, feeding regime ( Polonschii et al, 2013 ), and high fish density ( Papoutsoglou et al, 1998 ; Di Marco et al, 2008 ).…”

“…To identify this lowest possible number is in itself a challenge, since there is usually no explanation regarding the criteria used to select the number of fish in physiological and toxicological experiments. The studies published on the effect of perturbations on fish systems, as well as behavioral studies, use different numbers of fish: some use only one fish ( Magalhães et al, 2007 ; Brodin et al, 2013 ), while others use three fish ( Teles et al, 2015 ), five fish ( Crosato et al, 2018 ), fewer than 15 fish ( Krause, 1993 ; Huth and Wissel, 1994 ; Krause and Tegeder, 1994 ; Ladu et al, 2015 ), 18–40 fish ( Sadoul et al, 2014 ), 19–26 fish ( Eguiraun et al, 2016 ), 30–300 fish ( Tunstrøm et al, 2013 ), and 81 fish ( Eguiraun et al, 2014 ). However, we have not been able to find any publication providing any scientific explanation about the reasons that led the authors to use those particular numbers of individuals.…”

Enantio-alteration of gene transcription associated with bioconcentration in adult zebrafish (Danio rerio) exposed to chiral PCB149

“…Zebrafish, an informative model for studies of human biology 19 20 , is a standard species in aquatic toxicology studies 21 ; however, owing to the rapid life cycle of this species, the applications of zebrafish extend far beyond the fields of toxicology, cell biology, and developmental genetics 22 . Compared to mammals, fish exhibit far lower abundances and activities of CYPs, lower rates of electron transportation, and less active mono-oxygenates, resulting in far lower capacities for the detoxification and biotransformation of xenobiotic chemicals such as PCBs 23 .…”

Indication of Electromagnetic Field Exposure via RBF-SVM Using Time-Series Features of Zebrafish Locomotion

“…They detect the presence of toxic substances by continuously tracking the physiological performance of organisms [6] and could provide more reliable predictions of substance toxicity than the chemical concentration alone, especially in case of mixtures of substances [7]. The fast development of a fish tracking system supports enhancing the ability of biological monitors-or more specifically, a biological early warning system (BEWS)-to observe and sense the behavioral response of bio-organisms [8][9][10][11][12][13]. The tracking systems of BEWS could provide abundant and explicit information for the behavior and movement analysis, contributing to the satisfying result of water quality assessment when the concentration of pollutants in the water is relatively low.…”