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

Flow Cytometry01:23

Flow Cytometry

15.6K
The development of flow cytometry techniques began in 1934 with initial attempts by Andrew Moldavan, a bacteriologist who counted the cells in a flowing capillary system. Moldavan pumped cells through a capillary tube focused under a microscope for visualization. The invention of photometry allowed the measurement of differentially-stained cells, and Louis Kamentsky developed the first multiparameter flow cytometer in 1965 to identify and count the cancer cells in cervical tissue specimens.
In...
15.6K

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

Aqueous MXene-Assisted Charge Transport for Sliding Cu/n-Si DC Triboelectric Nanogenerators.

Nanomaterials (Basel, Switzerland)·2026
Same author

Concurrently Achieving 4.6 W/M<sup>2</sup> and 120,000 Cyclability Enabled by Extendable Swing Arms in Rotational Triboelectric Nanogenerator.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Mental health emergencies and mortality following public fine particulate matter alerts: A Nationwide case-crossover study in South Korea.

Preventive medicine·2025
Same author

Are long-term care systems aligned with person-centered integrated care? Evidence from the Western Pacific.

Health policy (Amsterdam, Netherlands)·2025
Same author

Fabrication of Highly Uniform, Well-Aligned ZnO Nanorod Arrays via Hydrothermal Synthesis for RGB Micro- and Submicron-Scale LEDs.

Small methods·2025
Same author

Extreme ambient temperature and emergency healthcare service utilization due to substance use disorders: a systematic review and meta-analysis.

Scientific reports·2025
Same journal

A Coumarin-Based Probe for Sequential ON-OFF-ON Detection of Cu<sup>2+</sup> and Biothiols: Naked-Eye Detection, Smartphone RGB Readout and In Vivo Imaging.

Biosensors·2026
Same journal

Electropolymerized Molecularly Imprinted Polymers Supported on Carbon-Based Materials for (Bio)sensing: Direct and Indirect Detection Strategies.

Biosensors·2026
Same journal

Progress in (Photo)electrochemical Biosensors for the Detection of Amyloid-Beta Oligomer.

Biosensors·2026
Same journal

Design and Simulation of Lamotrigine Intermittent Release from a Subcutaneous Implant with an Enzymatic Biosensor Based on Clinical Data.

Biosensors·2026
Same journal

Prediction of Chronic Kidney Disease Based on Simulated Serum Analysis by Vibrational Spectroscopy.

Biosensors·2026
Same journal

AI/ML-Assisted SERS Biosensing for Biomolecular Detection: From Direct Spectral Response to Integrated Diagnostic Systems.

Biosensors·2026
查看所有相关文章

相关实验视频

Updated: Jan 10, 2026

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps
08:59

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Published on: October 28, 2018

7.5K

基于深度学习的预测个体细胞的散容量从形态特征.

Tae Young Kang1, Soojung Kim2, Yoon-Hwae Hwang3

  • 1Institute for Future Earth, Pusan National University (PNU), Busan 46241, Republic of Korea.

Biosensors
|November 26, 2025
PubMed
概括
此摘要是机器生成的。

这项研究开发了一种深度学习方法,以纠正影响电气测量的细胞形状变化. 这提高了癌症诊断的准确性,因为它可以从测量器件中分离出真正的生物信号.

关键词:
细胞形态细胞形态学深度学习是一种深度学习.非侵入性的细胞表征.一个单细胞的单细胞.α-分散电容度的扩散能力.

更多相关视频

Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging
11:38

Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging

Published on: October 4, 2024

1.0K
Analysis of Multidimensional Microscopy Data Using Cell-ACDC
06:17

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

434

相关实验视频

Last Updated: Jan 10, 2026

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps
08:59

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Published on: October 28, 2018

7.5K
Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging
11:38

Author Spotlight: Enhancing PSC-to-Functional Cell Differentiation Using ML Models Based on Live-Cell Bright-Field Imaging

Published on: October 4, 2024

1.0K
Analysis of Multidimensional Microscopy Data Using Cell-ACDC
06:17

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

434

科学领域:

  • 生物物理学的生物物理.
  • 细胞生物学 细胞生物学
  • 计算生物学 计算生物学

背景情况:

  • 细胞膜的电特性通过表皮生长因子受体 (EGFR) 表达提供了对细胞状态和癌症诊断的洞察.
  • 观察期间的形态变化混了电气测量,掩盖了对表皮生长因子 (EGF) 的真实生物反应.

研究的目的:

  • 开发一种深度学习方法,以计算方式将细胞形态和电气特性联系起来.
  • 在细胞的电学分析中纠正形态学诱导的测量错误.

主要方法:

  • 在DPBS和EGF刺激下对HeLa细胞进行了光学捕捉和电容测量.
  • 开发了一个卷积神经网络 (CNN) 来从形态图像中预测电容谱.

主要成果:

  • 根据形态图像,CNN准确地预测了电容谱 (0.1-2 kHz) (在0.1-0.8 kHz时<10%的误差).
  • 方法有效地通过减去形态依赖的电容成分来隔离真正的生物反应.
  • 在多样化的细胞形态和实验条件下表现出强大的预测.

结论:

  • 开发的深度学习方法提供了一个计算框架,用于纠正电气测量的形态诱导错误.
  • 这大大提高了基于EGFR的癌症诊断的精度和可靠性.