Mathematical modeling of plaque progression and associated microenvironment: How far from predicting the fate of atherosclerosis?

计算模型 计算机科学 补语(音乐) 疾病 脆弱性(计算) 平滑肌 炎症 神经科学 医学 人工智能 病理 生物 免疫学 基因 内科学 表型 互补 生物化学 计算机安全
作者
Yan Cai,Zhiyong Li
出处
期刊:Computer Methods and Programs in Biomedicine [Elsevier BV]
卷期号:211: 106435-106435 被引量:10
标识
DOI:10.1016/j.cmpb.2021.106435
摘要

• We summarize the current ‘state of the art’ on the mathematical modeling of the effects of biomechanical factors and microenvironmental factors on the plaque progression, and its potential help in prediction of plaque development. • We present an outlook on open problems and multiple challenges that require novel modelling techniques and more integrations with experimental and clinical investigations. Mathematical modeling contributes to pathophysiological research of atherosclerosis by helping to elucidate mechanisms and by providing quantitative predictions that can be validated. In turn, the complexity of atherosclerosis is well suited to quantitative approaches as it provides challenges and opportunities for new developments of modeling. In this review, we summarize the current ‘state of the art’ on the mathematical modeling of the effects of biomechanical factors and microenvironmental factors on the plaque progression, and its potential help in prediction of plaque development. We begin with models that describe the biomechanical environment inside and outside the plaque and its influence on its growth and rupture. We then discuss mathematical models that describe the dynamic evolution of plaque microenvironmental factors, such as lipid deposition, inflammation, smooth muscle cells migration and intraplaque hemorrhage, followed by studies on plaque growth and progression using these modelling approaches. Moreover, we present several key questions for future research. Mathematical models can complement experimental and clinical studies, but also challenge current paradigms, redefine our understanding of mechanisms driving plaque vulnerability and propose future potential direction in therapy for cardiovascular disease.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
dunk芒果完成签到 ,获得积分10
刚刚
研友_VZG7GZ应助少年去游荡采纳,获得10
刚刚
科研通AI2S应助taosha998采纳,获得10
刚刚
zezeze11111111完成签到,获得积分20
2秒前
Hypnos发布了新的文献求助10
2秒前
一只鲨呱完成签到,获得积分10
3秒前
3秒前
4秒前
圆圆完成签到,获得积分10
5秒前
大桶茄子完成签到,获得积分10
6秒前
6秒前
我是老大应助DAVID采纳,获得10
8秒前
逆光飞翔发布了新的文献求助10
8秒前
清脆大树发布了新的文献求助10
9秒前
9秒前
NexusExplorer应助123采纳,获得10
13秒前
14秒前
14秒前
卡冈图雅完成签到,获得积分10
14秒前
危机的芝麻完成签到,获得积分10
14秒前
15秒前
15秒前
15秒前
Genius发布了新的文献求助10
15秒前
15秒前
俞佳美完成签到,获得积分20
17秒前
田様应助AY采纳,获得10
17秒前
迷路太清完成签到,获得积分10
18秒前
18秒前
小迪发布了新的文献求助10
18秒前
18秒前
18秒前
19秒前
hrr发布了新的文献求助10
20秒前
曾经尔云发布了新的文献求助10
20秒前
HotWire99完成签到,获得积分10
21秒前
21秒前
22秒前
23秒前
23秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Applied Min-Max Approach to Missile Guidance and Control 3000
Metallurgy at high pressures and high temperatures 2000
Inorganic Chemistry Eighth Edition 1200
High Pressures-Temperatures Apparatus 1000
Free parameter models in liquid scintillation counting 1000
Standards for Molecular Testing for Red Cell, Platelet, and Neutrophil Antigens, 7th edition 1000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6318359
求助须知:如何正确求助?哪些是违规求助? 8134625
关于积分的说明 17052670
捐赠科研通 5373307
什么是DOI,文献DOI怎么找? 2852250
邀请新用户注册赠送积分活动 1830165
关于科研通互助平台的介绍 1681813