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相关概念视频

The Nucleus01:32

The Nucleus

90.4K
The nucleus is a membrane-bound organelle that acts as a control center in a eukaryotic cell. It contains chromosomal DNA, which controls gene expression and precisely regulates the production of proteins within the cell. In contrast, the DNA inside the mitochondria and chloroplast only carries out functions that are specific to those organelles.
Arrangement of DNA within Nucleus
The regulation of gene expression inside the nucleus is dependent on many factors, including the DNA structure. The...
90.4K
Additional Subnuclear Structures02:10

Additional Subnuclear Structures

4.6K
The eukaryotic nucleus is a double membrane-bound organelle that contains nearly all of the cell’s genetic material in the form of chromosomes. It is rightly called the “brain” of the cell as it shoulders the responsibility of responding to various physiological processes, stress, altered metabolic conditions, and other cellular signals. 
The nucleus contains many membrane-less subnuclear organelles or nuclear bodies, such as nucleoli, Cajal bodies, speckles,...
4.6K
Classification of Leukocytes01:30

Classification of Leukocytes

1.9K
Leukocytes are classified into two groups based on the presence or absence of cytoplasmic granules. Granular leukocytes, which contain granules, belong to the myeloid lineage and are divided into three subtypes: neutrophils, eosinophils, and basophils. These cells are roughly spherical and characterized by the granules in their cytoplasm.
Neutrophils are the most abundant type of granular leukocytes, comprising 50-70% of all leukocytes. They feature small, evenly distributed granules and a...
1.9K
The Nucleolus02:55

The Nucleolus

8.8K
The nucleolus is the most prominent substructure of the nucleus. When it was first discovered, it was considered to be an isolated organelle that forms fibrils and granules. In 1931, the relationship between the nucleolus and chromosomes was first described by Heitz. He observed that the appearance and size of nucleolus varies depending on the stage of the cell cycle. He also noticed constricted regions on different chromosomes clustered together at definite cell cycle stages. These regions,...
8.8K
Classification of Epithelial Tissues: Overview01:22

Classification of Epithelial Tissues: Overview

13.3K
Epithelial tissues are classified according to the shape of the cells and the number of cell layers formed. Cell shapes can be squamous (flattened and thin), cuboidal (square-like, as wide as it is tall), or columnar (rectangular, taller than it is wide). Additionally, the nucleus shape helps identify the type of epithelial cells. Squamous cells have flattened disc-shaped nuclei, cuboidal cells have spherical nuclei, and columnar cells have elongated nuclei.
Based on the number of cell layers,...
13.3K
Immunogold Electron Microscopy01:20

Immunogold Electron Microscopy

4.0K
Immunoelectron microscopy utilizes immunogold labeling of endogenous proteins with specific antibodies to detect and localize these proteins in cells and tissues. The procedure provides insights into the distribution and quantification of protein under different stimulation conditions offering clues about their functions. Conjugating highly electron-dense gold particles with primary or secondary antibodies allow antigen detection on and within cells, with high resolution and specificity.
4.0K

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相关实验视频

Updated: Jun 28, 2025

Exploiting Live Imaging to Track Nuclei During Myoblast Differentiation and Fusion
09:03

Exploiting Live Imaging to Track Nuclei During Myoblast Differentiation and Fusion

Published on: April 13, 2019

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结构嵌入式核对组织病理学的分类图像

Wei Lou, Xiang Wan, Guanbin Li

    IEEE transactions on medical imaging
    |April 12, 2024
    PubMed
    概括

    这项研究引入了一个新的框架,用于核的分类在他的病理学图像,通过分析核形状和空间分布来提高准确性. 该方法显著改进了用于识别不同类型细胞核的现有技术.

    科学领域:

    • 数字病理学数字病理学
    • 计算生物学 计算生物学
    • 医学图像分析 医学图像分析

    背景情况:

    • 准确的细胞核分类对于组织病理学图像分析至关重要.
    • 卷积神经网络 (CNN) 中的核外观变化和有限的受体场对精确的核识别构成挑战.
    • 现有的方法往往忽略了原子核的空间分布和复杂的形状.

    研究的目的:

    • 开发一个先进的框架,用于核的分类在他的病理学图像.
    • 解决目前捕捉核形状和空间背景的方法的局限性.
    • 为了提高识别不同类型核的准确性.

    主要方法:

    • 一个多边形结构的特征学习机制,使用循环神经网络 (RNN) 来从核轮中提取形状特征.
    • 一个图形神经网络 (GNN) 来建模原子核的空间分布,将原子核表示为节点,并结合周围组织模式的边缘特征.
    • 将多边形和图形结构学习集成到一个统一的框架中,用于全面的特征提取.

    主要成果:

    • 拟议的框架有效地提取了内核 (形状) 和内核 (空间分布) 结构特征.
    • 实验结果表明,与以前的方法相比,核的分类准确性有了显著的改善.
    • 该方法成功地捕捉了核类别与它们周围组织微环境之间的相关性.

    更多相关视频

    Nuclei Isolation from Whole Tissue using a Detergent and Enzyme-Free Method
    07:00

    Nuclei Isolation from Whole Tissue using a Detergent and Enzyme-Free Method

    Published on: June 24, 2020

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    Using Computer Vision Libraries to Streamline Nuclei Quantification
    06:25

    Using Computer Vision Libraries to Streamline Nuclei Quantification

    Published on: June 6, 2025

    136

    相关实验视频

    Last Updated: Jun 28, 2025

    Exploiting Live Imaging to Track Nuclei During Myoblast Differentiation and Fusion
    09:03

    Exploiting Live Imaging to Track Nuclei During Myoblast Differentiation and Fusion

    Published on: April 13, 2019

    8.2K
    Nuclei Isolation from Whole Tissue using a Detergent and Enzyme-Free Method
    07:00

    Nuclei Isolation from Whole Tissue using a Detergent and Enzyme-Free Method

    Published on: June 24, 2020

    24.7K
    Using Computer Vision Libraries to Streamline Nuclei Quantification
    06:25

    Using Computer Vision Libraries to Streamline Nuclei Quantification

    Published on: June 6, 2025

    136

    结论:

    • 集成的多边形和图形结构学习框架提供了一个强大的解决方案,用于核的分类在他的病理学.
    • 这种方法增强了对细胞结构及其在组织图像中的空间关系的理解.
    • 开发的技术为推进数字病理学和癌症诊断提供了宝贵的工具.