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In recent years there has been an increase in the generation of transgenic and knockout mouse lines as well as viral delivery of genes. These new genetic manipulations have revolutionized our understanding of the biological function of cellular and molecular processes in both normal and disease state of central nervous system ^^¿^^. The large numberof mouse models calls for rigorous, sensitive, and reproducible investigations of behavioral phenotypes of mutant mice lines ^^ ^¿, as well as pharmacological efficacy studies. Behavioral testing paradigms should be easily transferable and replicable between laboratories. Many of the standard behavioral tests used today are not easily reproduced between laboratories, due either to variation in the genetic background of mice ^^' ^¿, or to variations in environmental or experimental conditions ^^' ^^. Other confounding factors can include variations in animal handling, housing, transportation, and test conditions ^^¿^^¿ ^. Behavioral models used for phenotyping of mice are designed based on the models that have been designed for rats as the test subjects ^^. Often these classical tests do not satisfactorily transfer over to mice. Additionally, these standard tests introduce many outside variables such as the effects of environment and human handling ^\ forced isolation, interruption of sleep/wake cycle, and placement in unnatural, stressful environments. In order to minimize these experimental and environmental variables, we will establish an Automated Behavioral Core to monitor and record mouse behavior in the home cage environment. These novel tests have the benefit of decreasing variability and increasing reproducibility of behavioral outcome between experimental repeats ^^"^¿. By using these new technologies we are aiming to 1) reduce novelty factors inherent in many classical tests by performing the behavioral testing inside the home cage ^^; 2) test the Individual animals while they remain in social groups (Intellicage) or when they are individually housed (PhenoLab); 3) reduce the stress related to the handling and experimental condition; 4) perform the data acquisition using computer software in an independent and unbiased manner; and 5) conduct the experiments with higher throughput during the animals active cycle without human interruption.
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Development of selective cannabinoid receptor 2 agonists for treatment of addiction
  • 批准号:
    10467887
  • 项目类别:
  • 资助金额:
    $66.2万
  • 财政年份:
    2022
  • 负责人:
    Mehrdad Shamloo
  • 依托单位:
Development of selective cannabinoid receptor 2 agonists for treatment of addiction
  • 批准号:
    10732744
  • 项目类别:
  • 资助金额:
    $62.96万
  • 财政年份:
    2022
  • 负责人:
    Mehrdad Shamloo
  • 依托单位:
Role of beta-adrenergic receptors in modulation of cognition and central and peripheral immune systems in Alzheimer's disease
  • 批准号:
    9383638
  • 项目类别:
  • 资助金额:
    $51.1万
  • 财政年份:
    2017
  • 负责人:
    Mehrdad Shamloo
  • 依托单位:
海外基金