Human Umbilical Vein Endothelial Cells (HUVECs) in Pharmacology and Toxicology: A Review

脐静脉 药理学 医学 静脉 毒理 化学 生物 外科 体外 生物化学
作者
Yi Cao
出处
期刊:Journal of Applied Toxicology [Wiley]
卷期号:45 (12): 2512-2545 被引量:17
标识
DOI:10.1002/jat.4885
摘要

Endothelial cells (ECs) are interior surface cells covering blood vessels, which play a crucial role in maintaining vascular homeostasis. In vascular pharmacology and toxicology, ECs directly contact drugs or toxicants entering circulation. Therefore, the bio-effects of pharmacological/toxicological substances on ECs have gained extensive research interest, which needs to be evaluated by reliable models. Human umbilical vein endothelial cells (HUVECs) have been served as versatile platforms to mimic diverse pathophysiological processes in vitro, stemming from their unique fetal arterial-like exposure microenvironment, expression of key EC markers, and comparable EC responses to various pathophysiological stimuli. This review provides an overview of the application of HUVECs in pharmacology and toxicology, with a focus on their utility and limitations. HUVECs have been widely used to model the effects of pharmacological or toxicological substances on material exchange, barrier functions, cell death, endothelial nitric oxide synthase (eNOS) uncoupling, and EC dysfunction, angiogenesis, and thrombosis. However, their applicability is constrained primarily due to vascular-type and organ-specific heterogeneity. The review highlights key mechanisms investigated using HUVECs, including oxidative stress, inflammation, organelle damage, and autophagy, metabolic reprogramming (endometabolism), and epigenetic regulation. Strategies to overcome HUVECs' limitations, such as microfluidic techniques, co-culture, and organoid models, are discussed. Finally, future directions are outlined, emphasizing the integration of HUVECs into multi-scale models, dynamic microenvironment simulations, artificial intelligence (AI)-assisted big data analysis, and patient-derived ECs for precision toxicology and personalized medicine. This review aims to guide researchers in optimizing the use of HUVECs in pharmacological and toxicological studies.
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
刚刚
爱吃泡芙完成签到,获得积分10
刚刚
bkagyin应助Zjy采纳,获得10
1秒前
yslyslysl发布了新的文献求助10
1秒前
1秒前
1秒前
勤劳的以冬完成签到,获得积分10
2秒前
科研通AI6.4应助麋鹿采纳,获得10
3秒前
zx完成签到,获得积分10
4秒前
Hh完成签到,获得积分10
4秒前
活力断天完成签到,获得积分10
4秒前
啦啦啦啦啦完成签到,获得积分10
7秒前
lbwnb2112发布了新的文献求助10
7秒前
安静一曲完成签到 ,获得积分10
7秒前
明月清风完成签到,获得积分10
8秒前
陶醉如松完成签到,获得积分10
8秒前
fsf完成签到,获得积分10
8秒前
9秒前
bluebell完成签到,获得积分10
10秒前
NexusExplorer应助yslyslysl采纳,获得10
12秒前
JamesPei应助江宜采纳,获得10
13秒前
13秒前
英吉利25发布了新的文献求助10
13秒前
14秒前
崔雨禾完成签到 ,获得积分10
15秒前
Chunyan_Yu完成签到,获得积分10
17秒前
micomico发布了新的文献求助10
17秒前
oi完成签到,获得积分10
18秒前
emberlynn发布了新的文献求助20
18秒前
云间倚山水应助失雪采纳,获得40
19秒前
20秒前
酷波er应助lbwnb2112采纳,获得10
21秒前
YSL完成签到,获得积分10
21秒前
22秒前
22秒前
深情安青应助星掠采纳,获得10
23秒前
25秒前
粗犷的蛟凤完成签到,获得积分20
26秒前
烟花应助FeiL采纳,获得10
27秒前
lmmcss发布了新的文献求助10
29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
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
What is the Future of Psychotherapy in Digital Age? Technology, AI Bots, and Psychotherapy after Covid 444
Management and the Arts 310
Teaching Social and Emotional Learning in Physical Education 300
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 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7635929
求助须知:如何正确求助?哪些是违规求助? 9209864
关于积分的说明 19753841
捐赠科研通 7203694
什么是DOI,文献DOI怎么找? 3275325
关于科研通互助平台的介绍 2437151
邀请新用户注册赠送积分活动 2272434