Splitting of target fibers: Myopathic signs in denervation phenomena

1977 ◽  
Vol 214 (2) ◽  
pp. 159-162 ◽  
Author(s):  
H. P. Schmitt
Keyword(s):  
Target Fibers

The Significance of Target Fibers: A Clinicopathologic Review of 100 Patients with Neurogenic Atrophy

1973 ◽  
Vol 59 (6) ◽  
pp. 790-797 ◽  
Author(s):  
Joel Kovarsky ◽  
Sydney S. Schochet ◽  
William F. McCormick
Keyword(s):  
Neurogenic Atrophy ◽  
Target Fibers

Autophagic degradation in human skeletal muscle target fibers

1982 ◽  
Vol 5 (9) ◽  
pp. 745-753 ◽  
Author(s):  
Robert E. Mrak ◽  
Akitsugu Saito ◽  
Owen B. Evans ◽  
Sidney Fleischer
Keyword(s):  
Skeletal Muscle ◽  
Human Skeletal Muscle ◽  
Autophagic Degradation ◽  
Target Fibers

scholarly journals Expression of a cell death marker (clusterin) in muscle target fibers

1993 ◽  
Vol 51 (3) ◽  
pp. 371-376 ◽  
Author(s):  
Acary Souza Bulle Oliveira ◽  
Massimo Corbo ◽  
Greg Duigou ◽  
Alberto Alain Gabbai ◽  
Arthur P. Hays
Keyword(s):  
Skeletal Muscle ◽  
Cell Death ◽  
Programmed Cell Death ◽  
Muscle Biopsy ◽  
Neuromuscular Disorders ◽  
High Concentration ◽  
A Cell ◽  
Target Fibers ◽  
First Time

We report, for the first time, the expression of immunoractivity to clusterin in skeletal muscle. Clusterin, a protein probably related to the process of programmed cell death (apoptosis), was specifically very highly expressed in target fibers. All target fibers found in 50 muscle biopsy samples from a variety of neuromuscular disorders expressed a high concentration of clusterin in the middle of the targets. Clusterin was not expressed in any targetoid fibers or cores. Acute denervation, where targets are mostly seen, may be the beginning of apoptosis. Hence our findings support the concept that targets are harbingers of acute denervation.

Target fibers in multiple sclerosis: Implications for pathogenesis

Neurology ◽  
1986 ◽  
Vol 36 (2) ◽  
pp. 297-297 ◽  
Author(s):  
J. E. Riggs ◽  
S. S. Schochet ◽  
T. A. Kopitnik ◽  
L. Gutmann
Keyword(s):  
Multiple Sclerosis ◽  
Target Fibers

scholarly journals Textile Fiber Identification Using Near-Infrared Spectroscopy and Pattern Recognition

2019 ◽  
Vol 19 (2) ◽  
pp. 201-209 ◽  
Author(s):  
Jinfeng Zhou ◽  
Lingjie Yu ◽  
Qian Ding ◽  
Rongwu Wang
Keyword(s):  
Pattern Recognition ◽  
Near Infrared ◽  
Raw Materials ◽  
Recognition Rate ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Rejection Rate ◽  
Chemical Compositions ◽  
Target Fibers ◽  
Materials Used

Abstract Fibers are raw materials used for manufacturing yarns and fabrics, and their properties are closely related to the performances of their derivatives. It is indispensable to implement fiber identification in analyzing textile raw materials. In this paper, seven common fibers, including cotton, tencel, wool, cashmere, polyethylene terephthalate (PET), polylactic acid (PLA), and polypropylene (PP), were prepared. After analyzing the merits and demerits of the current methods used to identify fibers, near-infrared (NIR) spectroscopy was used owing to its significant superiorities, the foremost of which is it can capture the tiny information differences in chemical compositions and morphological features to display the characteristic spectral curve of each fiber. First, the fibers’ spectra were collected, and then, the relationships between the vibrations of characteristic chemical groups and the corresponding wavelengths were researched to organize a spectral information library that would be beneficial to achieve quick identification and classification. Finally, to achieve intelligent detection, pattern recognition approaches, including principal component analysis (PCA) (used to extract information of interest), soft independent modeling of class analogy (SIMCA), and linear discrimination analysis (LDA) (defined using two classifiers), assisted in accomplishing fiber identification. The experimental results – obtained by combining PCA and SIMCA – displayed that five of seven target fibers, namely, cotton, tencel, PP, PLA, and PET, were distributed with 100% recognition rate and 100% rejection rate, but wool and cashmere fibers yielded confusing results and led to relatively low recognition rate because of the high proportion of similarities between these two fibers. Therefore, the six spectral bands of interest unique to wool and cashmere fibers were selected, and the absorbance intensities were imported into the classifier LDA, where wool and cashmere were group-distributed in two different regions with 100% recognition rate. Consequently, the seven target fibers were accurately and quickly distinguished by the NIR method to guide the fiber identification of textile materials.

Drawing of Spatially Oriented Electrospun Fibers

2009 ◽  
Author(s):  
Z. Sun ◽  
J. Knopf ◽  
J. M. Deitzel ◽  
J. W. Gillespie
Keyword(s):  
Dielectric Constant ◽  
Electrospinning Process ◽  
Critical Threshold ◽  
Electrospun Fibers ◽  
Low Dielectric ◽  
Theoretical Predictions ◽  
Target Fibers ◽  
High Degree ◽  
Spatially Oriented ◽  
Multiphase Composite

A simple approach to electrospinning has been developed that enables the collection of polymer, ceramic, and multiphase composite fibers, in quantity, with a high degree of spatial orientation. It has been demonstrated that a careful choice of solvent effectively eliminates the onset of the characteristic “bending” instability that is commonly associated with the electrospinning process. This allows collection of spatially oriented submicron electrospun fibers on a rotating drum without the need for elaborate mechanical or electrostatic manipulation of the electrospinning jet and/or collection target. Fibers have been electrospun from a series of model polyethylene oxide/CHCL3 solutions with a range of conductivities. The experimental data confirms theoretical predictions that the onset of the bending instability is a function of the available “free” charge in the solution, which in turn is strongly influenced by the dielectric constant of the solvent. The results show that fiber orientation becomes random as the conductivity increases, indicating the need for the surface charge density to exceed a critical threshold in order for the bending instability to initiate. Furthermore, it has been demonstrated that fiber diameter can be effectively controlled by controlling drum take-up speed. This method has been experimentally demonstrated with other low dielectric constant solvents and other common polymer, ceramic, composite materials.

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