Cao Bokai, Kong Xiangnan, Kettering Casey, Yu Philip, Ragin Ann
Department of Computer Science, University of Illinois at Chicago, 851 S. Morgan, Chicago, IL 60607, USA.
Department of Computer Science, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609, USA.
Neuroimage Clin. 2015 Aug 1;9:75-82. doi: 10.1016/j.nicl.2015.07.012. eCollection 2015.
To inform an understanding of brain status in HIV infection, quantitative imaging measurements were derived at structural, microstructural and macromolecular levels in three different periods of early infection and then analyzed simultaneously at each stage using data mining. Support vector machine recursive feature elimination was then used for simultaneous analysis of subject characteristics, clinical and behavioral variables, and immunologic measures in plasma and CSF to rank features associated with the most discriminating brain alterations in each period. The results indicate alterations beginning in initial infection and in all periods studied. The severity of immunosuppression in the initial virus host interaction was the most highly ranked determinant of earliest brain alterations. These results shed light on the initial brain changes induced by a neurotropic virus and their subsequent evolution. The pattern of ongoing alterations occurring during and beyond the period in which virus is suppressed in the systemic circulation supports the brain as a viral reservoir that may preclude eradication in the host. Data mining capabilities that can address high dimensionality and simultaneous analysis of disparate information sources have considerable utility for identifying mechanisms underlying onset of neurological injury and for informing new therapeutic targets.
为了深入了解HIV感染中的脑状态，在早期感染的三个不同阶段，从结构、微观结构和大分子水平进行了定量成像测量，然后在每个阶段使用数据挖掘进行同步分析。然后，支持向量机递归特征消除法被用于同时分析受试者特征、临床和行为变量以及血浆和脑脊液中的免疫指标，以对与每个时期最具鉴别性的脑改变相关的特征进行排名。结果表明，在初始感染及所有研究阶段均出现了改变。初始病毒宿主相互作用中免疫抑制的严重程度是最早脑改变的最高排名决定因素。这些结果揭示了嗜神经病毒引起的初始脑变化及其后续演变。在全身循环中病毒被抑制期间及之后持续发生的改变模式支持脑作为一个病毒库，这可能会妨碍在宿主中根除病毒。能够处理高维度并同时分析不同信息源的数据挖掘能力，对于识别神经损伤发病机制和为新的治疗靶点提供信息具有相当大的实用价值。
