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基于神经网络的大鼠肾小球滤过率计算器

Neural Network-Based Calculator for Rat Glomerular Filtration Rate.

作者信息

Pellicer-Valero Óscar J, Massaro Giampiero A, Casanova Alfredo G, Paniagua-Sancho María, Fuentes-Calvo Isabel, Harvat Mykola, Martín-Guerrero José D, Martínez-Salgado Carlos, López-Hernández Francisco J

机构信息

Intelligent Data Analysis Laboratory (IDAL), Department Electronic Engineering, School of Engineering (ETSE-UV), Universitat de València, 46100 Valencia, Spain.

Institute of Biomedical Research of Salamanca, 37007 Salamanca, Spain.

出版信息

Biomedicines. 2022 Mar 5;10(3):610. doi: 10.3390/biomedicines10030610.

Abstract

Glomerular filtration is a pivotal process of renal physiology, and its alterations are a central pathological event in acute kidney injury and chronic kidney disease. Creatinine clearance (ClCr), a standard method for glomerular filtration rate (GFR) measurement, requires a long and tedious procedure of timed (usually 24 h) urine collection. We have developed a neural network (NN)-based calculator of rat ClCr from plasma creatinine (pCr) and body weight. For this purpose, matched pCr, weight, and ClCr trios from our historical records on male Wistar rats were used. When evaluated on the training (1165 trios), validation (389), and test sets (660), the model committed an average prediction error of 0.196, 0.178, and 0.203 mL/min and had a correlation coefficient of 0.863, 0.902, and 0.856, respectively. More importantly, for all datasets, the NN seemed especially effective at comparing ClCr among groups within individual experiments, providing results that were often more congruent than those measured experimentally. ACLARA, a friendly interface for this calculator, has been made publicly available to ease and expedite experimental procedures and to enhance animal welfare in alignment with the 3Rs principles by avoiding unnecessary stressing metabolic caging for individual urine collection.

摘要

肾小球滤过是肾脏生理学的一个关键过程,其改变是急性肾损伤和慢性肾病的核心病理事件。肌酐清除率(ClCr)是测量肾小球滤过率(GFR)的标准方法,需要进行长时间且繁琐的定时(通常为24小时)尿液收集程序。我们开发了一种基于神经网络(NN)的计算器,可根据血浆肌酐(pCr)和体重计算大鼠的ClCr。为此,我们使用了来自雄性Wistar大鼠历史记录中的匹配pCr、体重和ClCr三联数据。在训练集(1165个三联数据)、验证集(389个)和测试集(660个)上进行评估时,该模型的平均预测误差分别为0.196、0.178和0.203 mL/min,相关系数分别为0.863、0.902和0.856。更重要的是,对于所有数据集,NN在比较单个实验中不同组的ClCr时似乎特别有效,提供的结果通常比实验测量结果更一致。ACLARA是该计算器的友好界面,已公开提供,以简化和加快实验程序,并通过避免为个体尿液收集进行不必要的应激代谢笼养,按照3R原则提高动物福利。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f32b/8945373/0498d1cb21ef/biomedicines-10-00610-g001.jpg

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