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Mednarodni projekti vir: SICRIS

Improving biomedical research by automated behaviour monitoring in the animal home-cage

Raziskovalci (1)
št. Evidenčna št. Ime in priimek Razisk. področje Vloga Obdobje Štev. publikacijŠtev. publikacij
1.  33148  dr. Maša Čater  Biotehnologija  Vodja  2021 - 2024  105 
Organizacije (1)
št. Evidenčna št. Razisk. organizacija Kraj Matična številka Štev. publikacijŠtev. publikacij
1.  0481  Univerza v Ljubljani, Biotehniška fakulteta  Ljubljana  1626914  66.599 
Povzetek
Animal use for scientific purposes is guided by the principles of 3Rs (Reduction, Refinement and Replacement). Developing refined experimental conditions can substantially improve animal welfare and importantly, enhance the translational value and data reproducibility. Novel and emerging technologies allow 24/7 collection of behavioural data in undisturbed mice, the most widely used species in biomedical research. These recently developed technologies minimize the impact of stressors, such as human interaction and testing in novel arenas, which are known to influence data collection and animal welfare. It is now possible to assess a more naturalistic behavioural profile in familiar environment, such as the animals’ home-cage. In addition to promoting welfare, it can improve research in a wide spectrum of research fields ranging from psychology and neuroscience to translational psychiatry and neurology, and may further provide valuable insights into other types of pathologies and genetic alterations. However, addressing the complex problem of monitoring the full 24-hour behavioural repertoire of a rodent still presents many challenges, with each technology having its strengths and limitations. The aim of this Action is to bring together European organizations developing and using automated home-cage monitoring technologies, combining experts in mouse behaviour, laboratory animal science and data science, to critically and transparently assess the potential of these technologies, to develop user guidelines and standard operating procedures and to identify needs for further technological development, including analysis of big data. The Action will also contribute to building capacities for adoption of these technologies by holding workshops, laboratory rotations and disseminating knowledge.
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