A method of determining the cross sectional area of muscle fibres

IF 3.6 3区 医学 Q1 CLINICAL NEUROLOGY Journal of the Neurological Sciences Pub Date : 1968-11-01 DOI:10.1016/0022-510X(68)90057-9
W. Aherne
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引用次数: 25

Abstract

A simple and convenient method is presented of measuring the size, and the variation in size, of muscle fibres cut in cross section. The method is based upon two theorems in geometrical probability. The computing formula is A = Ll where A is the mean cross sectional area of the fibres in the particular muscle, L is the mean value of measurements made across the fibres from the most lateral point on one side to the most lateral point on the other, and l is the mean value of measurements made at random across the fibre (i.e. the mean chord). Both measurements are easily made concurrently, by direct microscopy, using a screw micrometer eyepiece having crossed hair lines.

The standard error is calculated from the various values of L. From a provisional estimate of the standard deviation the optimum number of fibres to measure can be estimated. In normal muscle the mean fibre cross sectional area A can be determined with a relative standard error (RSE) of approximately 2.0% by measuring approximately 250 fibres. Greater accuracy is obtainable by measuring more fibres: the error is halved when the number of measurements is quadrupled.

The variability in size from fibre to fibre is conveniently expressed as the coefficient of variation of A.

Two subsidiary techniques are briefly described. One is an abridged version of the principal method, for use where the standard deviation is not required and precision is not essential. It estimates: mean fibre diameter D = 1.3 l, and mean fibre cross sectional area A = 1.3 l2 where l has the same meaning as in the principal method. The other technique, based on point-counting, is suggested for cases where, once again, the standard deviation is irrelevant but an accurate measure of fibre cross sectional area is demanded.

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测定肌肉纤维横截面积的方法
提出了一种测量横切肌纤维尺寸及尺寸变化的简便方法。该方法基于几何概率中的两个定理。计算公式为A = Ll,其中A为特定肌肉中纤维的平均横截面积,L为从一侧最外侧点到另一侧最外侧点的纤维测量的平均值,L为纤维随机测量的平均值(即平均弦)。这两种测量都很容易同时进行,通过直接显微镜,使用螺旋千分尺目镜有交叉的头发线。标准误差是根据l的各种值计算出来的。根据标准偏差的临时估计,可以估计出要测量的纤维的最佳数量。在正常肌肉中,通过测量大约250根纤维,平均纤维横截面积A可以以大约2.0%的相对标准误差(RSE)确定。通过测量更多的纤维,可以获得更高的精度:当测量次数增加四倍时,误差减半。纤维间尺寸的变化可以方便地表示为a的变化系数。本文简要介绍了两种辅助技术。一种是主要方法的简化版本,用于不需要标准偏差和不需要精度的地方。它估计:平均纤维直径D = 1.3 l,平均纤维横截面积A = 1.3 l2,其中l的含义与主方法相同。另一种基于点计数的技术,同样适用于标准偏差无关但需要精确测量纤维横截面积的情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of the Neurological Sciences
Journal of the Neurological Sciences 医学-临床神经学
CiteScore
7.60
自引率
2.30%
发文量
313
审稿时长
22 days
期刊介绍: The Journal of the Neurological Sciences provides a medium for the prompt publication of original articles in neurology and neuroscience from around the world. JNS places special emphasis on articles that: 1) provide guidance to clinicians around the world (Best Practices, Global Neurology); 2) report cutting-edge science related to neurology (Basic and Translational Sciences); 3) educate readers about relevant and practical clinical outcomes in neurology (Outcomes Research); and 4) summarize or editorialize the current state of the literature (Reviews, Commentaries, and Editorials). JNS accepts most types of manuscripts for consideration including original research papers, short communications, reviews, book reviews, letters to the Editor, opinions and editorials. Topics considered will be from neurology-related fields that are of interest to practicing physicians around the world. Examples include neuromuscular diseases, demyelination, atrophies, dementia, neoplasms, infections, epilepsies, disturbances of consciousness, stroke and cerebral circulation, growth and development, plasticity and intermediary metabolism.
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