Exploring the therapeutic potential of layered double hydroxides and transition metal dichalcogenides through the convergence of rheumatology and nanotechnology using generative adversarial network

趋同(经济学) 生成语法 过渡金属 对抗制 纳米技术 材料科学 计算机科学 化学 人工智能 催化作用 生物化学 经济 经济增长
作者
Suxian Lin,Weiwei Chen,Mohammed S. Alqahtani,Dalia H. Elkamchouchi,Yisu Ge,Yanjie Lu,Guodao Zhang,Mudan Wang
出处
期刊:Environmental Research [Elsevier]
卷期号:241: 117262-117262 被引量:6
标识
DOI:10.1016/j.envres.2023.117262
摘要

Two-dimensional Layered double hydroxides (LDHs) are highly used in the biomedical domain due to their biocompatibility, biodegradability, controlled drug loading and release capabilities, and improved cellular permeability. The interaction of LDHs with biological systems could facilitate targeted drug delivery and make them an attractive option for various biomedical applications. Rheumatoid Arthritis (RA) requires targeted drug delivery for optimum therapeutic outcomes. In this study, stacked double hydroxide nanocomposites with dextran sulphate modification (LDH-DS) were developed while exhibiting both targeting and pH-sensitivity for rheumatological conditions. This research examines the loading, release kinetics, and efficiency of the therapeutics of interest in the LDH-based drug delivery system. The mean size of LDH-DS particles (300.1 ± 8.12 nm) is -12.11 ± 0.4 mV. The encapsulation efficiency was 48.52%, and the loading efficacy was 16.81%. In vitro release tests indicate that the drug's discharge is modified more rapidly in PBS at pH 5.4 compared to pH 5.6, which later reached 7.3, showing the case sensitivity to pH. A generative adversarial network (GAN) is used to analyze the drug delivery system in rheumatology. The GAN model achieved high accuracy and classification rates of 99.3% and 99.0%, respectively, and a validity of 99.5%. The second and third administrations resulted in a significant change with p-values of 0.001 and 0.05, respectively. This investigation unequivocally demonstrated that LDH functions as a biocompatible drug delivery matrix, significantly improving delivery effectiveness.
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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
1秒前
谢皮皮发布了新的文献求助10
1秒前
无花果应助Lee采纳,获得10
2秒前
nan发布了新的文献求助10
2秒前
2秒前
2秒前
尔尔发布了新的文献求助10
3秒前
3秒前
3秒前
淑文完成签到 ,获得积分10
4秒前
无极微光应助汉堡包采纳,获得20
4秒前
深情安青应助bakbak采纳,获得10
5秒前
YYH发布了新的文献求助10
5秒前
xiexie发布了新的文献求助10
5秒前
6秒前
6秒前
哎一古完成签到,获得积分10
8秒前
obsession发布了新的文献求助10
9秒前
深情安青应助yaoxueli采纳,获得30
9秒前
归海连碧完成签到,获得积分10
11秒前
11秒前
长白雪茫茫完成签到,获得积分20
13秒前
14秒前
ss发布了新的文献求助10
15秒前
量子星尘发布了新的文献求助10
15秒前
zmj应助你好采纳,获得10
15秒前
October完成签到,获得积分10
15秒前
15秒前
17秒前
科研通AI2S应助科研通管家采纳,获得10
17秒前
Frank应助科研通管家采纳,获得10
17秒前
浮游应助科研通管家采纳,获得10
17秒前
Hello应助科研通管家采纳,获得10
17秒前
华仔应助科研通管家采纳,获得10
17秒前
研友_VZG7GZ应助科研通管家采纳,获得10
17秒前
小猴子应助科研通管家采纳,获得10
18秒前
Lucas应助科研通管家采纳,获得30
18秒前
JamesPei应助科研通管家采纳,获得10
18秒前
浮游应助科研通管家采纳,获得10
18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
List of 1,091 Public Pension Profiles by Region 1581
Encyclopedia of Agriculture and Food Systems Third Edition 1500
Specialist Periodical Reports - Organometallic Chemistry Organometallic Chemistry: Volume 46 1000
Current Trends in Drug Discovery, Development and Delivery (CTD4-2022) 800
The Scope of Slavic Aspect 600
Foregrounding Marking Shift in Sundanese Written Narrative Segments 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5532279
求助须知:如何正确求助?哪些是违规求助? 4621012
关于积分的说明 14576204
捐赠科研通 4560859
什么是DOI,文献DOI怎么找? 2498989
邀请新用户注册赠送积分活动 1478948
关于科研通互助平台的介绍 1450218