Biomaterial Database

Neurofilament distribution and organization in the myelinated axons of the peripheral nervous system. 1994

S T Hsieh, and T O Crawford, and J W Griffin

Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21287.

The nature of neurofilament organization within the axonal cytoskeleton has been the subject of controversy for many years. Previous reports have suggested that neurofilaments are randomly distributed in the radial dimension of the myelinated axon. Randomness of distribution implies that there is no interaction between neurofilaments, while order in distribution suggest the presence of forces between neurofilaments. To address the issue of randomness vs. order, we evaluated neurofilament distribution by two different statistical approaches--nearest-neighbor distance and the Poisson tile-counting method. Neurofilament nearest-neighbor distances in a myelinated axon differ from nearest-neighbor distances of a set of random points with similar density (40.6 +/- 7.0 nm vs. 30.7 +/- 12.9 nm, P < 0.0001). The Poisson tile-counting method also indicated that neurofilament distribution is different from a random distribution, under conditions of appropriate tile size and masking of other organelles. To further characterize the distribution of neurofilaments, we compared the relationship between nearest-neighbor distance and density for three sets of data: evenly spaced points, randomly distributed points and measured neurofilament coordinates. Neurofilaments do not conform to either evenly spaced or random distribution models. Instead, neurofilament distribution falls into an intermediate position between evenly spaced and random distributions. This study also demonstrates that the nearest-neighbor distance method of assessing neurofilament distribution offers several technical and theoretical advantages to the Poisson tile-counting method.

UI	MeSH Term	Description	Entries
D009186	Myelin Sheath	The lipid-rich sheath surrounding AXONS in both the CENTRAL NERVOUS SYSTEMS and PERIPHERAL NERVOUS SYSTEM. The myelin sheath is an electrical insulator and allows faster and more energetically efficient conduction of impulses. The sheath is formed by the cell membranes of glial cells (SCHWANN CELLS in the peripheral and OLIGODENDROGLIA in the central nervous system). Deterioration of the sheath in DEMYELINATING DISEASES is a serious clinical problem.	Myelin,Myelin Sheaths,Sheath, Myelin,Sheaths, Myelin
D009454	Neurofibrils	The delicate interlacing threads, formed by aggregations of neurofilaments and neurotubules, coursing through the CYTOPLASM of the body of a NEURON and extending from one DENDRITE into another or into the AXON.	Neurofibril
D003198	Computer Simulation	Computer-based representation of physical systems and phenomena such as chemical processes.	Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D000818	Animals	Unicellular or multicellular, heterotrophic organisms, that have sensation and the power of voluntary movement. Under the older five kingdom paradigm, Animalia was one of the kingdoms. Under the modern three domain model, Animalia represents one of the many groups in the domain EUKARYOTA.	Animal,Metazoa,Animalia
D001369	Axons	Nerve fibers that are capable of rapidly conducting impulses away from the neuron cell body.	Axon
D015233	Models, Statistical	Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.	Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D016012	Poisson Distribution	A distribution function used to describe the occurrence of rare events or to describe the sampling distribution of isolated counts in a continuum of time or space.	Distribution, Poisson
D017207	Rats, Sprague-Dawley	A strain of albino rat used widely for experimental purposes because of its calmness and ease of handling. It was developed by the Sprague-Dawley Animal Company.	Holtzman Rat,Rats, Holtzman,Sprague-Dawley Rat,Rats, Sprague Dawley,Holtzman Rats,Rat, Holtzman,Rat, Sprague-Dawley,Sprague Dawley Rat,Sprague Dawley Rats,Sprague-Dawley Rats
D051381	Rats	The common name for the genus Rattus.	Rattus,Rats, Laboratory,Rats, Norway,Rattus norvegicus,Laboratory Rat,Laboratory Rats,Norway Rat,Norway Rats,Rat,Rat, Laboratory,Rat, Norway,norvegicus, Rattus
D017933	Peripheral Nervous System	The nervous system outside of the brain and spinal cord. The peripheral nervous system has autonomic and somatic divisions. The autonomic nervous system includes the enteric, parasympathetic, and sympathetic subdivisions. The somatic nervous system includes the cranial and spinal nerves and their ganglia and the peripheral sensory receptors.	Nervous System, Peripheral,Nervous Systems, Peripheral,Peripheral Nervous Systems,System, Peripheral Nervous,Systems, Peripheral Nervous