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

Circadian Rhythms and Gene Regulation02:19

Circadian Rhythms and Gene Regulation

4.0K
The biological clock is involved in many aspects of regulating complex physiology in all animals. It was in 1935 when German zoologists, Hans Kalmus and Erwin Bünning, discovered the existence of circadian rhythm in Drosophila melanogaster. However, the internal molecular mechanisms behind the circadian clock remained a mystery until 1984, when Jeffrey C. Hall, Michael Rosbash, and Michael W. Young discovered the expression of the Per gene oscillating over a 24-hour cycle. In subsequent...
4.0K

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

Artificial Intelligence-Enabled Cardiac Function Estimation from Phone Videos of Echocardiograms.

medRxiv : the preprint server for health sciences·2026
Same author

Targeting immune cells in the aged brain reveals that engineered cytokine IL-10 enhances neurogenesis and improves cognition.

Immunity·2026
Same author

Type I interferon primes the alveolar epithelium to receive reparative signals from tissue-resident macrophages.

bioRxiv : the preprint server for biology·2026
Same author

Engulfment by brain macrophages in a short-lived vertebrate.

bioRxiv : the preprint server for biology·2026
Same author

SyntheMol-RL: a flexible reinforcement learning framework for designing easily synthesizable antibiotics.

Molecular systems biology·2026
Same author

Reimagining human-centric drug development with new approach methodologies.

Science (New York, N.Y.)·2026

相关实验视频

Updated: Jun 4, 2025

Monitoring Cell-autonomous Circadian Clock Rhythms of Gene Expression Using Luciferase Bioluminescence Reporters
10:38

Monitoring Cell-autonomous Circadian Clock Rhythms of Gene Expression Using Luciferase Bioluminescence Reporters

Published on: September 27, 2012

22.3K

空间转录原子钟揭示了大脑衰老中的细胞近距离影响

Eric D Sun1,2,3, Olivia Y Zhou3,4,5, Max Hauptschein3

  • 1Biomedical Data Science Graduate Program, Stanford University, Stanford, CA, USA.

Nature
|December 18, 2024
PubMed
概括

大脑衰老涉及到细胞变化和未知的细胞相互作用. 新的空间转录学揭示T细胞促进衰老, 而神经干细胞再生, 提供干预的目标.

更多相关视频

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
09:19

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

4.8K
Fluorescence-Activated Nuclei Negative Sorting of Neurons Combined with Single Nuclei RNA Sequencing to Study the Hippocampal Neurogenic Niche
08:16

Fluorescence-Activated Nuclei Negative Sorting of Neurons Combined with Single Nuclei RNA Sequencing to Study the Hippocampal Neurogenic Niche

Published on: October 20, 2022

2.8K

相关实验视频

Last Updated: Jun 4, 2025

Monitoring Cell-autonomous Circadian Clock Rhythms of Gene Expression Using Luciferase Bioluminescence Reporters
10:38

Monitoring Cell-autonomous Circadian Clock Rhythms of Gene Expression Using Luciferase Bioluminescence Reporters

Published on: September 27, 2012

22.3K
Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
09:19

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

4.8K
Fluorescence-Activated Nuclei Negative Sorting of Neurons Combined with Single Nuclei RNA Sequencing to Study the Hippocampal Neurogenic Niche
08:16

Fluorescence-Activated Nuclei Negative Sorting of Neurons Combined with Single Nuclei RNA Sequencing to Study the Hippocampal Neurogenic Niche

Published on: October 20, 2022

2.8K

科学领域:

  • 神经科学
  • 基因组学
  • 计算生物学

背景情况:

  • 认知能力下降和神经退行性疾病的风险随着年龄的增长而增加.
  • 大脑老化涉及复杂的细胞变化,老细胞对邻居的影响尚不清楚.
  • 需要研究衰老组织中的细胞相互作用的工具.

研究的目的:

  • 在成年人一生中创建一个空间解析的单细胞转录学大脑图谱.
  • 开发空间衰老时钟以识别与年龄相关的转录组变化和细胞间相互作用.
  • 研究衰老和复苏干预措施 (运动,部分重编程) 对大脑细胞的影响.

主要方法:

  • 从20个年龄段的420万个脑细胞生成了一个大规模的空间转录图集.
  • 开发基于机器学习的空间衰老时钟来分析转录指纹.
  • 利用深度学习来评估细胞对细胞的近距离效应.

主要成果:

  • 识别了衰老,再生和疾病的空间和细胞类型特征,包括罕见的细胞类型.
  • 发现透的T细胞有助于衰老,而神经干细胞则有助于衰老.
  • 确定了这些近距离效应的潜在媒介.

结论:

  • 罕见的细胞类型,如T细胞和神经干细胞,
  • 针对这些细胞类型可以提供抵消组织衰老的策略.
  • 空间衰老时钟为研究细胞相互作用和评估干预提供了可扩展的工具.