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Ethical Considerations of Mitigating Data Loss: VLADISLAV, a Manifesto for Reliable Home Cage Systems
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Abstract
Home cage monitoring (HCM) captures longitudinal animal behavioural data without human intervention. However, the systems’ complexity is rarely addressed in their design, increasing the risk of data loss, which wastes workhours, resources, and animal lives.
To assess the feasibility of implementing modern, robust architectures in complex operant HCM paradigms, the
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utonomous
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ia Wi-Fi (VLADISLAV) was developed and employed to test cognitive deficits in the intracerebroventricular streptozotocin-induced rat model of sporadic Alzheimer’s disease (sAD). Reliability was modelled against a system architecture common in commercial HCM systems by modelling the failure rate of the devices’ critical components across typical durations of animal experiments.
VLADISLAV assessed multiple cognitive dimensions of a rat model of sAD with automated, scheduled testing. Its design enabled simultaneous, redundant recording to multiple devices in real time, as well as batch remote control and supervision of tens of VLADISLAVs. VLADISLAV is estimated to reduce component failure rate ∼200-fold at €40/device.
Data loss due to system failure shouldn’t be accepted as a normal occurrence and robust system design is an ethical imperative. VLADISLAV’s robustness and utility demonstrate the potential of embedded networked systems, used in other industries and consumer electronics for over a decade. Today, the open source ecosystem enables cost-effective implementation of such architectures in HCM by biomedical researchers with no electronic engineering education, preventing data loss and facilitating researchers’ and technicians’ day-to-day work. Considering these findings, it is apparent that the implementation of modern architectures in HCM is long overdue.
Title: Ethical Considerations of Mitigating Data Loss: VLADISLAV, a Manifesto for Reliable Home Cage Systems
Description:
Abstract
Home cage monitoring (HCM) captures longitudinal animal behavioural data without human intervention.
However, the systems’ complexity is rarely addressed in their design, increasing the risk of data loss, which wastes workhours, resources, and animal lives.
To assess the feasibility of implementing modern, robust architectures in complex operant HCM paradigms, the
V
ersati
L
e
A
utonomous
D
ev
I
ce for
S
cheduled
L
earning
A
ssessment
V
ia Wi-Fi (VLADISLAV) was developed and employed to test cognitive deficits in the intracerebroventricular streptozotocin-induced rat model of sporadic Alzheimer’s disease (sAD).
Reliability was modelled against a system architecture common in commercial HCM systems by modelling the failure rate of the devices’ critical components across typical durations of animal experiments.
VLADISLAV assessed multiple cognitive dimensions of a rat model of sAD with automated, scheduled testing.
Its design enabled simultaneous, redundant recording to multiple devices in real time, as well as batch remote control and supervision of tens of VLADISLAVs.
VLADISLAV is estimated to reduce component failure rate ∼200-fold at €40/device.
Data loss due to system failure shouldn’t be accepted as a normal occurrence and robust system design is an ethical imperative.
VLADISLAV’s robustness and utility demonstrate the potential of embedded networked systems, used in other industries and consumer electronics for over a decade.
Today, the open source ecosystem enables cost-effective implementation of such architectures in HCM by biomedical researchers with no electronic engineering education, preventing data loss and facilitating researchers’ and technicians’ day-to-day work.
Considering these findings, it is apparent that the implementation of modern architectures in HCM is long overdue.
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