An Acidity‐Unlocked Magnetic Nanoplatform Enables Self‐Boosting ROS Generation through Upregulation of Lactate for Imaging‐Guided Highly Specific Chemodynamic Therapy

Boosting(机器学习) 下调和上调 化学 生物化学 计算机科学 机器学习 基因
作者
Linan Shi,Youjuan Wang,Cheng Zhang,Yan Zhao,Chang Lu,Baoli Yin,Yue Yang,Xiangyang Gong,Lili Teng,Yanlan Liu,Xiaobing Zhang,Guosheng Song
出处
期刊:Angewandte Chemie [Wiley]
卷期号:60 (17): 9562-9572 被引量:169
标识
DOI:10.1002/anie.202014415
摘要

Chemodynamic therapy is an emerging tumor therapeutic strategy. However, the anticancer effects are greatly limited by the strong acidity requirements for effective Fenton-like reaction, and the inevitably "off-target" toxicity. Herein, we develop an acidity-unlocked nanoplatform (FePt@FeOx@TAM-PEG) that can accurately perform the high-efficient and tumor-specific catalysis for anticancer treatment, through dual pathway of cyclic amplification strategy. Notably, the pH-responsive peculiarity of tamoxifen (TAM) drug allows for the catalytic activity of FePt@FeOx to be "turn-on" in acidic tumor microenvironments, while keeping silence in neutral condition. Importantly, the released TAM within cancer cells is able to inhibit mitochondrial complex I, leading to the upregulated lactate content and thereby the accumulated intracellular H+, which can overcome the intrinsically insufficient acidity of tumor. Through the positive feedback loop, large amount of active FePt@FeOx nanocatalyzers are released and able to access to the endogenous H2O2, exerting the improved Fenton-like reaction within the more acidic condition. Finally, such smart nanoplatform enables self-boosting generation of reactive oxygen species (ROS) and induces strong intracellular oxidative stress, leading to the substantial anticancer outcomes in vivo, which may provide a new insight for tumor-specific cascade catalytic therapy and reducing the "off-target" toxicity to surrounding normal tissues.
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
好的好的完成签到 ,获得积分10
刚刚
wuming完成签到,获得积分10
刚刚
GGGirafe完成签到,获得积分10
1秒前
小二郎应助FY采纳,获得10
2秒前
浮浮世世发布了新的文献求助30
3秒前
北方知既白完成签到 ,获得积分10
4秒前
SciGPT应助爱听歌小蚂蚁采纳,获得10
4秒前
愛愛愛愛完成签到,获得积分10
7秒前
jnshen完成签到 ,获得积分10
7秒前
9秒前
10秒前
汉堡包应助pharmstudent采纳,获得10
11秒前
nieyicong应助务实寒天采纳,获得10
11秒前
111发布了新的文献求助10
11秒前
1104481279发布了新的文献求助10
11秒前
12秒前
科研通AI6.2应助认真幼萱采纳,获得10
12秒前
13秒前
牵墨完成签到,获得积分10
13秒前
小凯发布了新的文献求助20
13秒前
14秒前
15秒前
成就朋友发布了新的文献求助10
15秒前
15秒前
16秒前
愉快的梨愁完成签到,获得积分10
18秒前
英吉利25发布了新的文献求助10
18秒前
怕黑的白玉完成签到,获得积分10
19秒前
WK发布了新的文献求助10
19秒前
19秒前
19秒前
酷炫的初阳完成签到,获得积分10
19秒前
20秒前
张欢馨应助刘堂晖采纳,获得10
21秒前
FY发布了新的文献求助10
21秒前
22秒前
tamo完成签到,获得积分10
23秒前
项脊轩发布了新的文献求助30
23秒前
25秒前
赘婿应助想偶遇小H采纳,获得10
25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
Römisch-Germanische Forschungen 1000
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
Green Fire Retardants for Polymeric Materials 400
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 7614575
求助须知:如何正确求助?哪些是违规求助? 9189950
关于积分的说明 19690727
捐赠科研通 7187364
什么是DOI,文献DOI怎么找? 3271163
关于科研通互助平台的介绍 2434499
邀请新用户注册赠送积分活动 2266155