FEB 03, 2016 7:30 AM PST

Keynote: Vibration, Noise & Ultrasonic Noise From Vivarium and Lab Equipment as Rapidly Growing Confounds in Animal Research

Speaker
  • CEO, OtoScience Labs, Professor of Psychology, Illinois College
    Biography
      Jeremy Turner, PhD, is co-founder and CEO of OtoScience Labs, a company that conducts noise and vibration measurement, 24-hour monitoring services, and consulting for animal facilities. His research focuses on rat and mouse models of hearing, the impacts of noise on the ear and brain, and the neuroscience of hearing loss and tinnitus. His research has been supported by the United States National Institutes of Health, the Tinnitus Research Consortium, and most recently a grant from the US Department of Defense Psychological Health and Traumatic Brain Injury Program to OtoScience Labs.

    Abstract

    Noise and vibration are very effective activators of stress pathways in rodent models that can increase variability in animal models, thereby confounding virtually every area of biomedical and behavioral research. Noise and vibration in animal facilities is generally not well controlled, managed, or even monitored. With the introduction of more mechanical and technological sources of such noise and vibration in the vivarium space (e.g., IVC caging cage changing stations, computers) the potential impacts of these confounds are greater today than ever. In addition, much of the noise produced by such modern technology is in the ultrasonic range, which we human observers cannot hear, and the noise meters we typically use cannot measure. This talk will focus on the sources of such noise and vibration (IVC caging, animal transport, fluorescent lighting, computers, cage changing stations, lab equipment), why and how they should be measured and monitored, and what strategies administrators and staff can use to minimize or control them as confounds in biomedical research. This talk will also discuss practical steps for minimizing these confounds. Special emphasis will be placed on how these confounds introduce variability in our animal models, serving to hamper our goals of animal model reduction and refinement.


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