Literature DB >> 18703026

Automated characterization of nerve fibers labeled fluorescently: determination of size, class and spatial distribution.

Dimiter Prodanov1, Hans K P Feirabend.   

Abstract

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 Aalpha (denoted Aalpha1 and Aalpha2), Agamma, and an additional class of Agammaalpha fibers. Cut-off borders between Agamma and Agammaalpha fiber classes were estimated to be 5.00+/-0.09 microm (SEM); between Agammaalpha and Aalpha1 fiber classes to be 6.86+/-0.11 microm (SEM); and between Aalpha1 and Aalpha2 fiber classes to be 8.66+/-0.16 microm (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.

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Year:  2008        PMID: 18703026     DOI: 10.1016/j.brainres.2008.07.049

Source DB:  PubMed          Journal:  Brain Res        ISSN: 0006-8993            Impact factor:   3.252


  3 in total

1.  Data ontology and an information system realization for web-based management of image measurements.

Authors:  Dimiter Prodanov
Journal:  Front Neuroinform       Date:  2011-11-25       Impact factor: 4.081

2.  End-to-side neurorrhaphy repairs peripheral nerve injury: sensory nerve induces motor nerve regeneration.

Authors:  Qing Yu; She-Hong Zhang; Tao Wang; Feng Peng; Dong Han; Yu-Dong Gu
Journal:  Neural Regen Res       Date:  2017-10       Impact factor: 5.135

3.  Retrograde Axonal Transport of Liposomes from Peripheral Tissue to Spinal Cord and DRGs by Optimized Phospholipid and CTB Modification.

Authors:  Takafumi Fukui; Hironao Tateno; Takashi Nakamura; Yuma Yamada; Yusuke Sato; Norimasa Iwasaki; Hideyoshi Harashima; Ken Kadoya
Journal:  Int J Mol Sci       Date:  2022-06-15       Impact factor: 6.208

  3 in total

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