کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4329133 1614206 2008 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Automated characterization of nerve fibers labeled fluorescently: Determination of size, class and spatial distribution
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب (عمومی)
پیش نمایش صفحه اول مقاله
Automated characterization of nerve fibers labeled fluorescently: Determination of size, class and spatial distribution
چکیده انگلیسی

Morphological classification of nerve fibers could help interpret the assessment of neural regeneration and the understanding of selectivity of nerve stimulation. Specific populations of myelinated nerve fibers can be investigated by retrograde tracing from a muscle followed by microscopic measurements of the labeled fibers at different anatomical levels. Gastrocnemius muscles of adult rats were injected with the retrograde tracer Fluoro-Gold. After a survival period of 3 days, cross-sections of spinal cords, ventral roots, sciatic, and tibial nerves were collected and imaged on a fluorescence microscope. Nerve fibers were classified using a variation-based criterion acting on the distribution of their equivalent diameters. The same criterion was used to classify the labeled axons using the size of the fluorescent marker. Measurements of the axons were paired to those of the entire fibers (axons + myelin sheaths) in order to establish the correspondence between so-established axonal and fiber classifications. It was found that nerve fibers in L6 ventral roots could be classified into four populations comprising two classes of Aα (denoted Aα1 and Aα2), Aγ, and an additional class of Aγα fibers. Cut-off borders between Aγ and Aγα fiber classes were estimated to be 5.00 ± 0.09 μm (SEM); between Aγα and Aα1 fiber classes to be 6.86 ± 0.11 μm (SEM); and between Aα1 and Aα2 fiber classes to be 8.66 ± 0.16 μm (SEM). Topographical maps of the nerve fibers that innervate the gastrocnemius muscles were constructed per fiber class for the spinal root L6. The major advantage of the presented approach consists of the combined indirect classification of nerve fiber types and the construction of topographical maps of so-identified fiber classes.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Brain Research - Volume 1233, 3 October 2008, Pages 35–50
نویسندگان
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