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Animal Models
Parkinson's Disease
Parkinson's disease is a progressive disorder of the central nervous system and caused by the degeneration of dopamine neurons in the substantia nigra of the brain, resulting in decreased dopamine availability, and sequentially the dopamine receptor changes. The major symptoms of the disease were originally described in 1817 by James Parkinson. Only in the 1960's, however, were pathological and biochemical changes in the brain of patients identified, opening the way to the animal models and effective medication for the disease. One of the most commonly employed rodent animal models for Parkinson’s disease involves unilateral injection of 6-hydroxydopamine (6-OHDA) into the substantia nigra or the medial forbrain bundle. This results in a massive, unilateral destruction of dopaminergic neurons. In response to dopaminergic agonists, lesioned rats exhibit rotational behavior, a marker for severe dopamine depletion and correction of the dopamine loss decrease rotation. This model offers the opportunity to study drugs before as well as after the 6-OHDA lesion of dopaminergic neurons in the substantia nigra.
 

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Stereology - Quantitation & Structural Analysis
“Stereology” is a body of mathematical methods relating three-dimensional parameters defining the structure (e.g. length, surface, and volume) to two-dimensional measurements obtainable on sections of the structure (Weibel, 1979). There are generally two categories of stereological methods: assumption-based and design-based methods.

Design based methods, an unbiased stereological technique, is the most commonly used method in recent years. Assumption based methods, such as the method of Abercrombie (1946), assuming that objects have particular size, shape, and orientation. In contrast, design based methods have been designed to eliminate the need for making assumptions about the size, shape, and orientation of objects. Therefore, one can count the objects directly in a defined volume of tissue based on sampling schemes, counting rules, and disectors, and thereby eliminate any potential systematic deviations from the true number that result from inappropriate assumptions about the objects.

Sampling, one of the estimation procedures, should be unbiased in the statistical sense. Estimates will not be unbiased if the sampling is biased. So it is critical to set-up counting rules that allow all sections of the region of interest have an equal probability of being sampled, and all objects in the section have equal probability of being counted (West 1999).

Disector, including optical and physical dissectors, is a 3D probe. An optical disector needs only one thick optical section. The object counting is accomplished by focusing a thin focal plane throughout the entire depth of the section to determine if the objects fall within the disector and then being counted. So it is an efficient application of the dissector principle for estimating total number of neurons in distinct regions of CNS at light microscopy level. A physical disector consists of two adjacent physical sections. The object counting is accomplished by comparing the two adjacent sections to determine if the objects fall within the disector and then being counted. So it is a valuable tool for estimating the total number of synapses, terminals and spines in various distinct regions of the CNS at the electron microscopy level (Geinisman et al., 1996).

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In general, Paragon Stereology Services using OPTICAL DISECTOR include: 

  • Experimental design
  • Tissue processing, sectioning and staining
  • Computer-assisted cell counting
  • Bar graphs and basic statistics (X ± SD) 
References:
1. Abercrombie, M. (1946) Estimation of nuclear population from microtome sections. Anat. Rec. 94: 239-247.
2. Geinisman, Y., H.J.G. et. al., (1996) Unbiased stereological estimation of the total number of synapses in brain region. J. Neurocytology 25: 805-819.
3. Weibel, E.R. (1979) Stereological Methods, Vol. 1: Practical Methods for Biological Morphometry, Academic Press, London.
4. West, M.J. (1999) Stereological Methods for Estimating the Total Number of Neurons and Synapses: Issues of Precision and Bias, Trends in Neuroscience, 22: 51-61.
 

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