Department of Biomedical Engineering and Computational Science, Aalto University, Espoo, Finland.
J Microsc. 2012 Sep;247(3):228-39. doi: 10.1111/j.1365-2818.2012.03636.x.
Epidermal nerve fiber (ENF) density and morphology are used to diagnose small fiber involvement in diabetic, HIV, chemotherapy induced, and other neuropathies. ENF density and summed length of ENFs per epidermal surface area are reduced, and ENFs may appear clustered within the epidermis in subjects with small fiber neuropathy compared to healthy subjects. Therefore, it is important to understand the spatial behaviour of ENFs in healthy and diseased subjects. This work investigates the spatial structure of ENF entry points, which are locations where the nerves enter the epidermis (the outmost living layer of the skin). The study is based on suction skin blister specimens from two body locations of 25 healthy subjects. The ENF entry points are regarded as a realization of a spatial point process and a second-order characteristic, namely Ripley's K function, is used to investigate the effect of covariates (e.g. gender) on the degree of clustering of ENF entry points. First, the effects of covariates are evaluated by means of pooled K functions for groups and, secondly, the statistical significance of the effects and individual variation are characterized by a mixed model approach. Based on our results the spatial pattern of ENFs in samples taken from calf is affected by the covariates but not in samples taken from foot.
表皮神经纤维（ENF）密度和形态结构可用于诊断糖尿病、HIV、化疗诱导以及其他神经病变中的小纤维受累情况。与健康受试者相比，患有小纤维神经病变的受试者的表皮神经纤维密度和每单位表皮面积的表皮神经纤维总长度降低，并且表皮神经纤维可能在表皮内聚集。因此，了解健康和患病受试者中表皮神经纤维的空间行为非常重要。本工作研究了表皮神经纤维进入点（神经进入表皮（皮肤的最外层）的位置）的空间结构。该研究基于从 25 名健康受试者的两个身体部位采集的抽吸性皮肤水疱标本。表皮神经纤维进入点被视为空间点过程的实现，并且使用 Ripley 的 K 函数（second-order characteristic）来研究协变量（例如性别）对表皮神经纤维进入点聚类程度的影响。首先，通过组的混合 K 函数评估协变量的影响，其次，通过混合模型方法来描述效应和个体变异的统计显著性。基于我们的结果，取自小腿的样本中的表皮神经纤维的空间模式受协变量的影响，但取自足部的样本不受影响。
