Abstract

Stereological analysis is the optimal tool for quantitative assessment of brain morphological and cellular changes induced by neurotoxic lesions or treatment interventions. Stereological methods based on random sampling techniques yield unbiased estimates of particle counts within a defined volume, thereby providing a true quantitative estimate of the target cell population. Neurodegenerative diseases involve loss of specific neuron types, such as the midbrain tyrosine hydroxylase-positive dopamine neurons in Parkinson's disease and in animal models of nigrostriatal degeneration. Therefore, we applied an established automated physical disector principle in a fractionator design for efficient stereological quantitative analysis of tyrosine hydroxylase (TH)-positive dopamine neurons in the substantia nigra pars compacta of hemiparkinsonian rats with unilateral 6-hydroxydopamine (6-OHDA) lesions. We obtained reliable estimates of dopamine neuron numbers, and established the relationship between behavioral asymmetry and dopamine neuron loss on the lesioned side. In conclusion, the automated physical disector principle provided a useful and efficient tool for unbiased estimation of TH-positive neurons in rat midbrain, and should prove valuable for investigating neuroprotective strategies in 6-OHDA model of parkinsonism, while generalizing to other immunohistochemically-defined cell populations.

Highlights

  • Application of basic principles of stereology can be applied to the task of estimating the total number of particles in a three-dimensional object; these particles can be neurons, glial cells, or organelles

  • The stereological technique known as the physical disector was first described in 1984 (Sterio, 1984), and has since become an established tool in quantitative neurobiology (e.g., Kristiansen and Nyengaard, 2012).We emphasize that stereological techniques are based on unbiased principles, which means that estimations, when obtained according to geometrically-defined rules, are “without systematic deviation from the true value.”

  • The optical disector is often used for neuron counts, but the physical disector method is more suited for the Abbreviations: 6-OHDA, 6-hydroxydopamine; asf, area sampling fraction; DA, dopaminergic; hsf, height sampling fraction; i.p., intraperitoneal; MFB, medial forebrain bundle; PD, Parkinson’s disease; ROI, region of interest; s.c., subcutaneous; SEM, standard error of the mean; SNc, substantia nigra pars compacta; SPD, Sprague-Dawley; ssf, section sampling fraction; Systematic uniform random sampling (SURS), systematic uniform random sampling; TBS, Tris-buffered saline; TH, tyrosine hydroxylase

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Summary

INTRODUCTION

Application of basic principles of stereology can be applied to the task of estimating the total number of particles in a three-dimensional object; these particles can be neurons, glial cells, or organelles. Use of the physical disector can be rather time-consuming compared to the optical disector, due to the requirement that the experimenter must align the sections manually on a computer screen This obstacle is circumvented by automated systems, which obtain an operator-independent alignment of microscopic images from the reference and lookup sections e.g., the Visiopharm newCast Autodisector system (Visiopharm, Denmark). The optical disector is often used for neuron counts, but the physical disector method is more suited for the Abbreviations: 6-OHDA, 6-hydroxydopamine; asf, area sampling fraction; DA, dopaminergic; hsf, height sampling fraction; i.p., intraperitoneal; MFB, medial forebrain bundle; PD, Parkinson’s disease; ROI, region of interest; s.c., subcutaneous; SEM, standard error of the mean; SNc, substantia nigra pars compacta; SPD, Sprague-Dawley; ssf, section sampling fraction; SURS, systematic uniform random sampling; TBS, Tris-buffered saline; TH, tyrosine hydroxylase. The present 6-OHDA study is the first stereological study in a neurodegeneration model that combines the use of digital images of immunohistologicallystained brain sections using the automated aligning of images for the physical disector set-up

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