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利用网络理解医学数据:以 III 类错颌为例。

Using networks to understand medical data: the case of Class III malocclusions.

机构信息

Istituto dei Sistemi Complessi Udr La Sapienza, Roma, Italy.

出版信息

PLoS One. 2012;7(9):e44521. doi: 10.1371/journal.pone.0044521. Epub 2012 Sep 21.

Abstract

A system of elements that interact or regulate each other can be represented by a mathematical object called a network. While network analysis has been successfully applied to high-throughput biological systems, less has been done regarding their application in more applied fields of medicine; here we show an application based on standard medical diagnostic data. We apply network analysis to Class III malocclusion, one of the most difficult to understand and treat orofacial anomaly. We hypothesize that different interactions of the skeletal components can contribute to pathological disequilibrium; in order to test this hypothesis, we apply network analysis to 532 Class III young female patients. The topology of the Class III malocclusion obtained by network analysis shows a strong co-occurrence of abnormal skeletal features. The pattern of these occurrences influences the vertical and horizontal balance of disharmony in skeletal form and position. Patients with more unbalanced orthodontic phenotypes show preponderance of the pathological skeletal nodes and minor relevance of adaptive dentoalveolar equilibrating nodes. Furthermore, by applying Power Graphs analysis we identify some functional modules among orthodontic nodes. These modules correspond to groups of tightly inter-related features and presumably constitute the key regulators of plasticity and the sites of unbalance of the growing dentofacial Class III system. The data of the present study show that, in their most basic abstraction level, the orofacial characteristics can be represented as graphs using nodes to represent orthodontic characteristics, and edges to represent their various types of interactions. The applications of this mathematical model could improve the interpretation of the quantitative, patient-specific information, and help to better targeting therapy. Last but not least, the methodology we have applied in analyzing orthodontic features can be applied easily to other fields of the medical science.

摘要

一个相互作用或相互调节的元素系统可以用一个叫做网络的数学对象来表示。虽然网络分析已经成功地应用于高通量的生物系统,但在更应用的医学领域,应用相对较少;在这里,我们展示了一个基于标准医学诊断数据的应用。我们将网络分析应用于 III 类错颌,这是最难理解和治疗的颌面畸形之一。我们假设骨骼成分的不同相互作用可能导致病理性失衡;为了验证这一假设,我们对 532 名 III 类年轻女性患者进行了网络分析。网络分析得到的 III 类错颌的拓扑结构显示出骨骼特征异常的强烈共现。这些发生的模式影响骨骼形态和位置不和谐的垂直和水平平衡。具有更不平衡的正畸表型的患者表现出病理性骨骼节点的优势和适应性牙牙槽平衡节点的次要相关性。此外,通过应用幂图分析,我们在正畸节点之间识别出一些功能模块。这些模块对应于紧密相关特征的组,并且可能构成可塑性的关键调节剂和生长的牙颌面 III 类系统不平衡的部位。本研究的数据表明,在最基本的抽象水平上,口面特征可以用节点表示正畸特征,用边表示它们的各种相互作用,用图表示。该数学模型的应用可以改善对定量、患者特定信息的解释,并有助于更好地靶向治疗。最后但同样重要的是,我们应用于分析正畸特征的方法可以很容易地应用于医学科学的其他领域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ea6d/3448617/4a11bb6a0f2d/pone.0044521.g001.jpg

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