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

Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

6.8K
Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...
6.8K

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

Label-free detection of microRNA by polymerization and isomerization cyclic amplification coupled with G/Hemin DNAzyme.

Journal of pharmaceutical analysis·2026
Same author

A Novel Technology Platform for Extracellular Vesicle-Targeted Expression of Drug-Metabolizing Enzymes: Driving CYP3A4 Expression and Secretion via the EABR Motif.

Biomedicines·2026
Same author

A Single Probe for Two Separate Imaging Applications: Turn-On Labeling of the Cell-Surface Proteome and Wash-Free Detection of Membrane Damage.

Analytical chemistry·2026
Same author

An active marker-based strategy for Anti-inflammatory Enhancement of Qiangli Pipa Syrup.

Journal of ethnopharmacology·2026
Same author

Cost-effectiveness of hetrombopag, eltrombopag, and avatrombopag for chronic immune thrombocytopenia in China: a cost-utility analysis.

Frontiers in public health·2026
Same author

Accumulated dose on daily iCBCT for rectal cancer: Effects of inter-fraction bowel cavity motion volume.

Journal of applied clinical medical physics·2026

相关实验视频

Updated: May 13, 2025

Substructure Analyzer: A User-Friendly Workflow for Rapid Exploration and Accurate Analysis of Cellular Bodies in Fluorescence Microscopy Images
14:28

Substructure Analyzer: A User-Friendly Workflow for Rapid Exploration and Accurate Analysis of Cellular Bodies in Fluorescence Microscopy Images

Published on: July 15, 2020

7.8K

一个模块化的人工智能框架,以促进光体设计.

Yuchen Zhu1, Jiebin Fang2,3, Shadi Ali Hassen Ahmed1

  • 1Institute of Drug Metabolism and Pharmaceutical Analysis, Research Center for Clinical Pharmacy, College of Pharmaceutical Sciences, State Key Laboratory of Advanced Drug Delivery and Release Systems, Zhejiang University, Hangzhou, 310058, China.

Nature communications
|April 15, 2025
PubMed
概括

研究人员开发了FLAME,这是一个AI框架,用于加速光成像的光体设计. 该工具集成了数据库和预测模型,使得高性能光材料的更快发现成为可能.

更多相关视频

An Analytical Tool that Quantifies Cellular Morphology Changes from Three-dimensional Fluorescence Images
10:00

An Analytical Tool that Quantifies Cellular Morphology Changes from Three-dimensional Fluorescence Images

Published on: August 31, 2012

14.5K
Conducting Multiple Imaging Modes with One Fluorescence Microscope
08:32

Conducting Multiple Imaging Modes with One Fluorescence Microscope

Published on: October 28, 2018

9.8K

相关实验视频

Last Updated: May 13, 2025

Substructure Analyzer: A User-Friendly Workflow for Rapid Exploration and Accurate Analysis of Cellular Bodies in Fluorescence Microscopy Images
14:28

Substructure Analyzer: A User-Friendly Workflow for Rapid Exploration and Accurate Analysis of Cellular Bodies in Fluorescence Microscopy Images

Published on: July 15, 2020

7.8K
An Analytical Tool that Quantifies Cellular Morphology Changes from Three-dimensional Fluorescence Images
10:00

An Analytical Tool that Quantifies Cellular Morphology Changes from Three-dimensional Fluorescence Images

Published on: August 31, 2012

14.5K
Conducting Multiple Imaging Modes with One Fluorescence Microscope
08:32

Conducting Multiple Imaging Modes with One Fluorescence Microscope

Published on: October 28, 2018

9.8K

科学领域:

  • 化学 化学 化学
  • 材料科学 材料科学 材料科学
  • 计算化学的计算化学

背景情况:

  • 光成像在研究和医学中至关重要.
  • 目前的光体开发主要依赖于低效的试错方法.
  • 现有的光体通常由于复杂的结构性质和溶剂效应而具有低于最佳的性能.

研究的目的:

  • 开发一个人工智能驱动的框架,FLAME,以加速新型光体的设计.
  • 创建一个全面的开源数据库的光溶剂对.
  • 为了提高光体光学性质的预测准确性和效率.

主要方法:

  • 构建FluoDB,这是最大的开源光剂数据库 (55,169对).
  • 使用域知识指纹开发FLSF (使用fluoroScaFfold驱动模型进行光预测).
  • 整合一个分子发生器用于新型化合物合成.

主要成果:

  • FLAME框架成功地加速了光体设计.
  • FLSF模型准确地预测了可解释的光学特性.
  • 合成新型3,4-oxazole-fused coumarins,其中包括一种高度光的化合物.

结论:

  • FLAME提供了一个强大的AI解决方案,用于合理的光体设计.
  • 开发的数据库和预测模型显著推进了光体的发现.
  • 这项工作为下一代光成像剂铺平了道路.