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

G-protein Coupled Receptors01:21

G-protein Coupled Receptors

G-protein coupled receptors are ligand binding receptors that indirectly affect changes in the cell. The actual receptor is a single polypeptide that transverses the cell membrane seven times creating intracellular and extracellular loops. The extracellular loops create a ligand specific pocket which binds to neurotransmitters or hormones. The intracellular loops holds onto the G-protein.
Activation and Inactivation of G Proteins01:22

Activation and Inactivation of G Proteins

Heterotrimeric G proteins are guanine nucleotide-binding proteins. As the name suggests, heterotrimeric G proteins are composed of three subunits: alpha, beta, and gamma. They remain GDP-bound or GTP-bound inside the cells and switch between inactive/active states. The Gα subunit possesses the nucleotide-binding pocket that binds guanine nucleotides and switches between GDP or GTP-bound states. In contrast, the Gꞵ and Gγ subunits are always bound together with high affinity and are together...
GPCRs Regulate Adenylyl Cylase Activity01:09

GPCRs Regulate Adenylyl Cylase Activity

Some GPCRs transmit signals through adenylyl cyclase (AC), a transmembrane enzyme. AC helps synthesize second messenger cyclic adenosine monophosphate (cAMP). AC catalyzes cyclization reaction and converts ATP to cAMP by releasing a pyrophosphate. The pyrophosphate is further hydrolyzed to phosphate by the enzyme pyrophosphatase, which drives cAMP synthesis to completion. However, cAMP is rapidly degraded to 5′ AMP by the enzymes phosphodiesterase (PDE), preventing overstimulation of cells.
Two...
IP3/DAG Signaling Pathway01:11

IP3/DAG Signaling Pathway

Membrane lipids such as phosphatidylinositol (PI) are precursors for several membrane-bound and soluble second messengers. Specific kinases phosphorylate PI and produce phosphorylated inositol phospholipids. One such inositol phospholipids are the  phosphatidylinositol-4,5 bisphosphate [PI(4,5)P2], present in the inner half of the lipid bilayer. Upon ligand binding, GPCR stimulates Gq proteins to turn on phospholipase Cꞵ. Activated phospholipase Cꞵ cleaves PI(4,5)P2 and produces two-second...
Network Function of a Circuit01:25

Network Function of a Circuit

Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.
Global Regulatory Systems01:28

Global Regulatory Systems

Global regulatory systems in bacteria enable rapid and coordinated responses to environmental changes by integrating sensory inputs with gene expression, ensuring efficient adaptation to fluctuating conditions. Key global regulatory mechanisms include regulons, two-component systems, sigma factors, and secondary messengers.Regulons and Global RegulatorsA regulon is a collection of genes and operons controlled by a common global regulator. These regulators enable bacteria to prioritize resource...

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

Respiratory microbiota transplantation: optimized framework and its impact on metabolic and immune characteristics.

Chinese medical journal pulmonary and critical care medicine·2026
Same author

AGCECDA: attention-guided heterogeneous graph collaborative embedding for circRNA-drug sensitivity association prediction.

BMC biology·2026
Same author

Community-level modeling of gyral folding patterns for robust and anatomically informed individualized brain mapping.

NeuroImage·2026
Same author

Evidence summary for optimal glycemic variability management during enteral nutrition in adult ICU patients with cerebral infarction.

Frontiers in nutrition·2026
Same author

Plain language summary: comparing ivonescimab plus chemotherapy with tislelizumab plus chemotherapy in people with advanced squamous non-small cell lung cancer in the HARMONi-6 study.

Future oncology (London, England)·2026
Same author

AD-GPT: large language models in Alzheimer's disease.

BMC medical informatics and decision making·2026
Same journal

LEARNABLE HIERARCHICAL VISUAL CONTEXTS FOR TUMOR SEGMENTATION IN COMPUTED TOMOGRAPHY IMAGES.

Proceedings. IEEE International Symposium on Biomedical Imaging·2026
Same journal

DUAL CROSS-ATTENTION SIAMESE TRANSFORMER FOR RECTAL TUMOR REGROWTH ASSESSMENT IN WATCH-AND-WAIT ENDOSCOPY.

Proceedings. IEEE International Symposium on Biomedical Imaging·2026
Same journal

LUMEN: LONGITUDINAL MULTI-MODAL RADIOLOGY MODEL FOR PROGNOSIS AND DIAGNOSIS.

Proceedings. IEEE International Symposium on Biomedical Imaging·2026
Same journal

OVERVIEW OF THE CXR-LT 2026 CHALLENGE: MULTI-CENTER LONG-TAILED AND ZERO SHOT CHEST X-RAY CLASSIFICATION.

Proceedings. IEEE International Symposium on Biomedical Imaging·2026
Same journal

CROSS-MODAL FINE-TUNING OF 3D CONVOLUTIONAL FOUNDATION MODELS FOR ADHD CLASSIFICATION WITH LOW-RANK ADAPTATION.

Proceedings. IEEE International Symposium on Biomedical Imaging·2026
Same journal

AN IN SILICO STUDY OF LOW-INTENSITY FOCUSED ULTRASOUND DISPLACEMENT MAPPING WITH A 220 KHZ CLINICAL PHASED-ARRAY TRANSDUCER.

Proceedings. IEEE International Symposium on Biomedical Imaging·2026
查看所有相关文章

相关实验视频

Updated: Jun 21, 2026

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index
09:57

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index

Published on: January 2, 2012

28.1K

没有监督的皮质室表面注册网络调整GYRALNET网络.

Jiale Cheng1,2, Fenqiang Zhao1, Dan Hu1

  • 1Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, NC, USA.

Proceedings. IEEE International Symposium on Biomedical Imaging
|June 20, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一个无监督学习框架,用于为3环 (3HG) 和其网络 (GyralNet) 创建大脑图谱. 这提高了对各个个体大脑结构对齐的准确性.

关键词:
3个脚的状环.皮层表面注册的记录.在GyralNet上,我们可以看到GyralNet.球形U-net是一种球形U-net.

更多相关视频

Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings
08:20

Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings

Published on: June 6, 2015

15.5K
Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
11:28

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Published on: June 30, 2018

11.8K

相关实验视频

Last Updated: Jun 21, 2026

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index
09:57

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index

Published on: January 2, 2012

28.1K
Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings
08:20

Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings

Published on: June 6, 2015

15.5K
Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
11:28

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Published on: June 30, 2018

11.8K

科学领域:

  • 神经成像是一种神经成像.
  • 计算神经科学是一种神经科学.
  • 医学图像分析 医学图像分析

背景情况:

  • 三环 (3HG) 和它的网络 (GyralNet) 对于理解大脑结构和功能至关重要.
  • 目前的皮质表面记录方法不充分考虑3HG和GyralNet,导致次优对齐.
  • 现有的3HG和GyralNet地图库无法使用,传统地图库生成需要大量的时间.

研究的目的:

  • 开发一个无监督学习框架,共同创建3HG和GyralNet地图.
  • 为了在生成的地图上准确地记录单个皮质特征.
  • 通过结合3HG和GyralNet信息来改善大脑结构的对齐.

主要方法:

  • 开发了一个无监督学习框架,共同生成3HG和GyralNet地图.
  • 3HG和GyralNet的图形结构被转换为表面距离地图,以便集成到注册网络中.
  • 基于球体U-Net的多层球体注册网络用于粗细的注册,以处理大变形.

主要成果:

  • 拟议的框架成功生成了详细的3HG和GyralNet地图.
  • 与现有方法相比,该方法证明了更好的注册准确性.
  • 表面距离地图的集成有效地纳入了3HG和Gyral.Net的图形结构.

结论:

  • 无监督学习框架为生成3HG和GyralNet地图提供了一种高效有效的方法.
  • 这种方法通过考虑关键的旋转特征,显著提高皮质表面注册的准确性.
  • 开发的框架为神经成像研究提供了有价值的工具,需要精确的脑结构对齐.