Machine learning classifies predictive kinematic features in a mouse model of neurodegeneration.
Machine learning classifies predictive kinematic features in a mouse model of neurodegeneration.
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DOI：
10.1038/s41598-021-82694-3
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发表时间：
2021-02-17
影响因子：
4.6
通讯作者：
Lu DC
中科院分区：
文献类型：
--
作者：
Huang R;Nikooyan AA;Xu B;Joseph MS;Damavandi HG;von Trotha N;Li L;Bhattarai A;Zadeh D;Seo Y;Liu X;Truong PA;Koo EH;Leiter JC;Lu DC
阿尔茨海默氏病 (AD) 在出现认知症状之前就会出现运动缺陷。为了研究淀粉样蛋白在步态障碍中的作用，我们对 APP 过表达的转基因 J20 小鼠的运动进行了表征。我们使用三维运动捕捉来表征 J20 和野生型小鼠在跑步机上的四足运动。对两个年龄（4 个月和 13 个月）的 16 只 J20 小鼠和 15 只野生型小鼠进行了研究。随机森林 (RF) 分类算法使用留一法交叉验证来区分每个年龄组内的基因型。 4个月组和13个月组的RF分类的平衡准确度分别为92.3±5.2%和93.3±4.5%，假阴性率(FNR)分别为0.0±0.0%和0.0±0.0%。特征排名算法识别出运动学特征，同时考虑这些特征时，可以实现较高的基因型分类准确性。所识别的特征证明了 APP 过度表达影响的年龄特异性运动学特征。躯干倾斜和不稳定的髋部运动模式对于 4 个月大的 J20 小鼠的分类很重要，而肩部和髂嵴运动模式对于 13 个月大的 J20 小鼠的分类至关重要。同时检查步态的多个运动学特征也可以用于对人类运动障碍进行分类。
Motor deficits are observed in Alzheimer’s disease (AD) prior to the appearance of cognitive symptoms. To investigate the role of amyloid proteins in gait disturbances, we characterized locomotion in APP-overexpressing transgenic J20 mice. We used three-dimensional motion capture to characterize quadrupedal locomotion on a treadmill in J20 and wild-type mice. Sixteen J20 mice and fifteen wild-type mice were studied at two ages (4- and 13-month). A random forest (RF) classification algorithm discriminated between the genotypes within each age group using a leave-one-out cross-validation. The balanced accuracy of the RF classification was 92.3 ± 5.2% and 93.3 ± 4.5% as well as False Negative Rate (FNR) of 0.0 ± 0.0% and 0.0 ± 0.0% for the 4-month and 13-month groups, respectively. Feature ranking algorithms identified kinematic features that when considered simultaneously, achieved high genotype classification accuracy. The identified features demonstrated an age-specific kinematic profile of the impact of APP-overexpression. Trunk tilt and unstable hip movement patterns were important in classifying the 4-month J20 mice, whereas patterns of shoulder and iliac crest movement were critical for classifying 13-month J20 mice. Examining multiple kinematic features of gait simultaneously could also be developed to classify motor disorders in humans.
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影响因子：
14.5
作者：
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