Quercetin inhibits neutrophil extracellular traps release and their cytotoxic effects on A549 cells, as well the release and enzymatic activity of elastase and myeloperoxidase

髓过氧化物酶 中性粒细胞胞外陷阱 槲皮素 弹性蛋白酶 中性粒细胞弹性蛋白酶 生物 细胞外 细胞毒性T细胞 生物化学 胰弹性蛋白酶 体外 炎症 分子生物学 抗氧化剂 免疫学
作者
Gabriela Sterle Pereira,I. Percebom,Samuel Gabriel Mendes,Priscila Silva Sampaio de Souza,Larissa Figueiredo Alves Diniz,M. F. Costa,Bruno Rafael Pereira Lopes,Karina Alves Toledo
出处
期刊:Brazilian Journal of Biology [Instituto Internacional de Ecologia (Brazil)]
卷期号:84 被引量:9
标识
DOI:10.1590/1519-6984.252936
摘要

Neutrophil extracellular traps (NETs) were first reported as a microbicidal strategy for activated neutrophils. Through an immunologic response against several stimuli, neutrophils release their DNA together with proteins from granules, nucleus, and cytoplasm (e.g., elastase and myeloperoxidase). To date, NETs have been implicated in tissue damage during intense inflammatory processes, mainly when their release is dependent on oxygen radical generation. Flavonoids are antioxidant and anti-inflammatory agents; of these, quercetin is commonly found in our daily diet. Therefore, quercetin could exert some protective activity against tissue damage induced by NETs. In our in vitro assays, quercetin reduced NETs, myeloperoxidase (MPO), and elastase release from neutrophils stimulated with phorbol 12-myristate 13-acetate (PMA). The activity of these enzymes also decreased in the presence of quercetin. Quercetin also reduced the cytotoxic effect of NETs on alveolar cells (A549 cell line). Further, in silico assays indicated favorable interactions between quercetin and NET proteins (MPO and elastase). Overall, our results demonstrate that quercetin decreases deleterious cellular effects of NETs by reducing their release from activated neutrophils, and diminishing the enzymatic activity of MPO and elastase, possibly through direct interaction.

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
Balala发布了新的文献求助10
刚刚
zhengzhao完成签到,获得积分10
1秒前
今日晴朗铺完成签到 ,获得积分10
1秒前
寻梦完成签到,获得积分10
1秒前
馫X发布了新的文献求助10
2秒前
阿啵呲嘚完成签到,获得积分10
2秒前
Owen应助含糖量超标采纳,获得10
2秒前
2秒前
Nokia发布了新的文献求助10
3秒前
王鸿博完成签到,获得积分10
3秒前
思源应助明月采纳,获得10
4秒前
4秒前
大个应助Liang采纳,获得10
4秒前
闫永娟发布了新的文献求助10
5秒前
行行行完成签到,获得积分10
5秒前
开心叫兽完成签到,获得积分10
5秒前
5秒前
6秒前
春困秋乏完成签到,获得积分10
6秒前
7秒前
温柔语梦应助小熊还给我8采纳,获得10
8秒前
8秒前
yyllyy完成签到,获得积分10
8秒前
柚子茶发布了新的文献求助10
9秒前
ning发布了新的文献求助20
9秒前
mashumin发布了新的文献求助10
10秒前
脑洞疼应助藏匿采纳,获得10
10秒前
winter发布了新的文献求助10
10秒前
11秒前
冷傲夏波发布了新的文献求助10
11秒前
11秒前
无辜从阳完成签到,获得积分10
11秒前
12秒前
cdercder应助GTR的我采纳,获得10
12秒前
小巧的箴发布了新的文献求助10
12秒前
Orange应助zhizhi采纳,获得10
13秒前
14秒前
情怀应助123采纳,获得10
14秒前
上官若男应助冷傲夏波采纳,获得10
15秒前
洁净的幼珊完成签到,获得积分10
15秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(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
Matrix Methods in Data Mining and Pattern Recognition 510
Social Skills Improvement System-Rating Scales--Chinese Version 500
Dynamische Polarisation von H-1 und B-11 in (CH-3)-3NBH-3 500
CLSI M07 2024 500
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 7249571
求助须知:如何正确求助?哪些是违规求助? 8872206
关于积分的说明 18722027
捐赠科研通 6928823
什么是DOI,文献DOI怎么找? 3198793
关于科研通互助平台的介绍 2374019
邀请新用户注册赠送积分活动 2173341