Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Precipitate Formation and Particle Size Control01:16

Precipitate Formation and Particle Size Control

In precipitation gravimetry, the precipitating agent should react specifically or selectively with the analyte. While a specific reagent reacts with the analyte alone, a selective reagent can react with a limited number of chemical species.
The obtained precipitate should be either a pure substance of known composition or easily converted to one by a simple process, such as ignition or drying. In addition, the precipitate should be insoluble and easily filterable. In general, filterability...

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Real-Time Observation of Thermal Reshaping Mechanisms in Gold Nanostars.

Nano letters·2026
Same author

Clinical diagnosis of diabetes using machine learning and surface-enhanced Raman spectroscopy liquid biopsy: an exploratory study.

Nanoscale advances·2025
Same author

Unraveling the role of MAG, PTEN, and NOTCH1 in axonal regeneration: a network analysis and molecular dynamics study of siRNA/drugs/nanocarriers interactions.

Journal of translational medicine·2025
Same author

The binding mechanism of Covalent Organic Frameworks (COFs) to Calcitonin Gene-Related Peptide Receptors (CGRPRs).

International journal of biological macromolecules·2025
Same author

Sequential EXtreme Gradient Boosting-Based Descriptor Reduction for Size Prediction of Zwitterionic Polymer-Based Nanoparticles.

ACS omega·2025
Same author

Corrigendum to "3D printing of complicated GelMA-coated alginate/tri‑calcium silicate scaffold for accelerated bone regeneration" [Int. J. Biol. Macromol. 229 (2023) 636-653].

International journal of biological macromolecules·2025

相关实验视频

Updated: Jul 16, 2026

Hydrogel Nanoparticle Harvesting of Plasma or Urine for Detecting Low Abundance Proteins
10:05

Hydrogel Nanoparticle Harvesting of Plasma or Urine for Detecting Low Abundance Proteins

Published on: August 7, 2014

14.3K

微流体制备的纳米粒子的智能预测.

Nima Hanari1, Sara Mihandoost2, Sima Rezvantalab3

  • 1Electrical Engineering Department, Urmia University of Technology, Urmia, 57166‑419, Iran.

Scientific reports
|October 28, 2025
PubMed
概括

机器学习模型可以预测药物加载和封装效率对多样乳糖合甘油酸 (PLGA) 纳米粒子. 这加速了具有所需性质的先进药物输送系统的设计.

关键词:
数据挖掘是一种数据挖掘.毒品装载 毒品装载封装效率 封装效率是指封装效率是指封装效率.机器学习 机器学习

更多相关视频

Flash NanoPrecipitation for the Encapsulation of Hydrophobic and Hydrophilic Compounds in Polymeric Nanoparticles
10:12

Flash NanoPrecipitation for the Encapsulation of Hydrophobic and Hydrophilic Compounds in Polymeric Nanoparticles

Published on: January 7, 2019

23.4K
Computer Numerical Control Micromilling of a Microfluidic Acrylic Device with a Staggered Restriction for Magnetic Nanoparticle-Based Immunoassays
09:58

Computer Numerical Control Micromilling of a Microfluidic Acrylic Device with a Staggered Restriction for Magnetic Nanoparticle-Based Immunoassays

Published on: June 23, 2022

2.6K

相关实验视频

Last Updated: Jul 16, 2026

Hydrogel Nanoparticle Harvesting of Plasma or Urine for Detecting Low Abundance Proteins
10:05

Hydrogel Nanoparticle Harvesting of Plasma or Urine for Detecting Low Abundance Proteins

Published on: August 7, 2014

14.3K
Flash NanoPrecipitation for the Encapsulation of Hydrophobic and Hydrophilic Compounds in Polymeric Nanoparticles
10:12

Flash NanoPrecipitation for the Encapsulation of Hydrophobic and Hydrophilic Compounds in Polymeric Nanoparticles

Published on: January 7, 2019

23.4K
Computer Numerical Control Micromilling of a Microfluidic Acrylic Device with a Staggered Restriction for Magnetic Nanoparticle-Based Immunoassays
09:58

Computer Numerical Control Micromilling of a Microfluidic Acrylic Device with a Staggered Restriction for Magnetic Nanoparticle-Based Immunoassays

Published on: June 23, 2022

2.6K

科学领域:

  • 生物材料科学 生物材料科学
  • 纳米技术 纳米技术
  • 制药科学 制药科学

背景情况:

  • 在药物输送过程中,开发聚乳糖糖酸 (PLGA) 纳米粒子至关重要.
  • 控制纳米粒子物理化学特性,以实现最佳的药物封装和加载仍然是一个重大挑战.

研究的目的:

  • 编制PLGA纳米粒子配方的综合数据集.
  • 应用机器学习算法来预测药物负载 (DL) 和封装效率 (EE).

主要方法:

  • 从文献中编制了一个超过300个PLGA纳米粒子配方的数据集.
  • 包括与微流体制备相关的25个关键功能.
  • 利用各种机器学习算法,包括随机森林,来预测DL和EE.

主要成果:

  • 随机森林模型展示了高预测性能.
  • 实现了DL的0.93和EE预测的0.96的R2值.
  • 发现EE和DL预测之间的影响最小,表明不同的配方见解.

结论:

  • 机器学习有效地预测PLGA纳米粒子的关键性质.
  • 这种方法可以指导药物输送系统的合理设计.
  • 加快纳米颗粒的开发,以量身定制的药物加载和封装效率.