Understanding the Myelin g Ratio from First Principles, Its Derivation, Uses and Artifacts.

IF 3.9 4区 医学 Q2 NEUROSCIENCES
ASN NEURO Pub Date : 2025-01-01 Epub Date: 2025-01-24 DOI:10.1080/17590914.2024.2445624
Alexander Gow
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引用次数: 0

Abstract

In light of the increasing importance for measuring myelin g ratios - the ratio of axon-to-fiber (axon + myelin) diameters in myelin internodes - to understand normal physiology, disease states, repair mechanisms and myelin plasticity, there is urgent need to minimize processing and statistical artifacts in current methodologies. Many contemporary studies fall prey to a variety of artifacts, reducing study outcome robustness and slowing development of novel therapeutics. Underlying causes stem from a lack of understanding of the myelin g ratio, which has persisted more than a century. An extended exploratory data analysis from first principles (the axon-fiber diameter relation) is presented herein and has major consequences for interpreting published g ratio studies. Indeed, a model of the myelin internode naturally emerges because of (1) the strong positive correlation between axon and fiber diameters and (2) the demonstration that the relation between these variables is one of direct proportionality. From this model, a robust framework for data analysis, interpretation and understanding allows specific predictions about myelin internode structure under normal physiological conditions. Further, the model establishes that a regression fit to g ratio plots has zero slope, and it identifies the underlying causes of several data processing artifacts that can be mitigated by plotting g ratios against fiber diameter (not axon diameter). Hypothesis testing can then be used for extending the model and evaluating myelin internodal properties under pathophysiological conditions (forthcoming). For without a statistical model as anchor, hypothesis testing is aimless like a rudderless ship on the ocean.

从基本原理、推导、用途和人工制品理解髓磷脂比率。
鉴于测量髓磷脂比值(髓鞘节间轴突与纤维(轴突+髓鞘)直径的比值)对了解正常生理、疾病状态、修复机制和髓鞘可塑性的重要性日益增加,迫切需要在当前的方法中尽量减少处理和统计误差。许多当代研究受到各种人为因素的影响,降低了研究结果的稳健性,减缓了新疗法的发展。潜在的原因是缺乏对髓磷脂比率的了解,这种情况已经持续了一个多世纪。本文提出了从第一性原理(轴-纤维直径关系)扩展的探索性数据分析,并对解释已发表的g比研究具有重要影响。事实上,髓鞘节间的模型自然出现,因为(1)轴突和纤维直径之间存在很强的正相关关系,(2)这些变量之间的关系是成正比的。从这个模型中,一个强大的数据分析、解释和理解框架允许在正常生理条件下对髓鞘节间结构进行具体预测。此外,该模型确定回归拟合到g比率图的斜率为零,并且它确定了几个数据处理伪影的潜在原因,这些伪影可以通过绘制g比率与纤维直径(而不是轴索直径)的关系来减轻。假设检验可用于扩展模型和评估病理生理条件下髓鞘节间特性(即将出版)。因为没有统计模型作为锚,假设检验就像大海上没有舵的船一样漫无目的。
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
ASN NEURO
ASN NEURO NEUROSCIENCES-
CiteScore
7.70
自引率
4.30%
发文量
35
审稿时长
>12 weeks
期刊介绍: ASN NEURO is an open access, peer-reviewed journal uniquely positioned to provide investigators with the most recent advances across the breadth of the cellular and molecular neurosciences. The official journal of the American Society for Neurochemistry, ASN NEURO is dedicated to the promotion, support, and facilitation of communication among cellular and molecular neuroscientists of all specializations.
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