Multiscale Metabolic Modeling Approach for Predicting Blood Alcohol Concentration

M. K. Toroghi, W. R. Cluett, R. Mahadevan
{"title":"Multiscale Metabolic Modeling Approach for Predicting Blood Alcohol Concentration","authors":"M. K. Toroghi, W. R. Cluett, R. Mahadevan","doi":"10.1109/LLS.2016.2644647","DOIUrl":null,"url":null,"abstract":"Alcohol is one of the most widely consumed and abused substances, and is a major factor in many alcohol-related diseases, incidents of impaired driving, and crimes. In this letter, we develop a mechanistic model for alcohol metabolism in the human body based on the dynamic parsimonious flux balance analysis technique. The developed whole body alcohol metabolic model contains two main mechanisms for ethanol metabolism in the body, namely, oxidative and non-oxidative mechanisms. The model is able to demonstrate the effect of variations in biochemical kinetics associated with the alcohol dehydrogenase enzyme, gender differences, physiological properties of the human body such as age, weight, and height, and the meal effect on the alcohol clearance from the body. Simulation results show that the model predictions are consistent with in vivo studies. The results from this letter indicate that the proposed metabolic modeling approach may open the door to new opportunities in the area of metabolic nutrition research and personalized medicine since it accounts for physiological properties and biochemical information related to the human body.","PeriodicalId":87271,"journal":{"name":"IEEE life sciences letters","volume":"2 1","pages":"59-62"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/LLS.2016.2644647","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE life sciences letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LLS.2016.2644647","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

Alcohol is one of the most widely consumed and abused substances, and is a major factor in many alcohol-related diseases, incidents of impaired driving, and crimes. In this letter, we develop a mechanistic model for alcohol metabolism in the human body based on the dynamic parsimonious flux balance analysis technique. The developed whole body alcohol metabolic model contains two main mechanisms for ethanol metabolism in the body, namely, oxidative and non-oxidative mechanisms. The model is able to demonstrate the effect of variations in biochemical kinetics associated with the alcohol dehydrogenase enzyme, gender differences, physiological properties of the human body such as age, weight, and height, and the meal effect on the alcohol clearance from the body. Simulation results show that the model predictions are consistent with in vivo studies. The results from this letter indicate that the proposed metabolic modeling approach may open the door to new opportunities in the area of metabolic nutrition research and personalized medicine since it accounts for physiological properties and biochemical information related to the human body.
预测血液酒精浓度的多尺度代谢建模方法
酒精是最广泛消费和滥用的物质之一,是许多与酒精有关的疾病、驾驶障碍事件和犯罪的主要因素。在这封信中,我们建立了一个基于动态简约通量平衡分析技术的人体酒精代谢机制模型。已建立的全身酒精代谢模型包含体内乙醇代谢的两种主要机制,即氧化机制和非氧化机制。该模型能够证明与酒精脱氢酶、性别差异、人体生理特性(如年龄、体重和身高)相关的生化动力学变化的影响,以及膳食对体内酒精清除的影响。模拟结果表明,模型预测与体内研究结果一致。这封信的结果表明,所提出的代谢建模方法可能为代谢营养研究和个性化医疗领域打开新的机遇之门,因为它考虑了与人体相关的生理特性和生化信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信