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Related Concept Videos

Structural Joints: Synovial Joints01:16

Structural Joints: Synovial Joints

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Synovial joints are the most common type of joint in the body. A key structural characteristic for a synovial joint is the presence of a joint cavity. This fluid-filled space is where the articulating surfaces of the bones contact each other. Also, unlike fibrous or cartilaginous joints, the articulating bone surfaces at a synovial joint are not directly connected to each other with fibrous connective tissue or cartilage. This gives the bones of a synovial joint the ability to move smoothly...
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Structural Joints: Fibrous Joints01:03

Structural Joints: Fibrous Joints

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Fibrous joints are a type of joint where the bones are connected by fibrous connective tissue. These joints provide stability and minimal to no movement between the articulating bones. There are three types of fibrous joints.
Suture
All the bones of the skull, except for the mandible, are joined to each other by a fibrous joint called a suture. The fibrous connective tissue found at a suture strongly unites the adjacent skull bones and thus helps to protect the brain and form the face. In...
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Structural Joints: Cartilaginous Joints01:17

Structural Joints: Cartilaginous Joints

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As the name indicates, at a cartilaginous joint, the adjacent bones are united by cartilage, a tough but flexible type of connective tissue. Unlike synovial joints, these types of joints lack a joint cavity and involve bones joined together by either hyaline cartilage or fibrocartilage.
There are two types of cartilaginous joints:
Synchondrosis
A synchondrosis ("joined by cartilage") is a cartilaginous joint where bones are connected by hyaline cartilage. Synchondrosis may be temporary...
4.0K
Joints01:26

Joints

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Joints, also called articulations or articular surfaces, are points at which ligaments or other tissues connect adjacent bones. Joints permit movement and stability, and can be classified based on their structure or function.
Structural joint classifications are based on the material that makes up the joint as well as whether or not the joint contains a space between the bones. Joints are structurally classified as fibrous, cartilaginous, or synovial.
Fibrous Joints Are Immovable
The bones of a...
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Trial and Error and Algorithm01:12

Trial and Error and Algorithm

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A problem-solving strategy is a plan of action used to find a solution. Different strategies have distinct action plans. Trial and error involves trying different solutions until one works. For instance, to fix a broken printer, you might check ink levels, ensure the paper tray isn't jammed, and verify the printer's connection to your laptop. This method can be time-consuming but is commonly used. Thomas Edison, for example, used trial and error to find a suitable filament for the light...
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Method of Joints01:30

Method of Joints

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The method of joints is a commonly used technique to analyze the forces in structural trusses. The method is based on the principle of equilibrium, which assumes that the truss members are connected by frictionless pins. The forces at each joint can be determined by considering the equilibrium of the forces acting on that joint.
Since plane truss members are in the same plane, each joint is subjected to a coplanar and concurrent force system. To apply the method of joints, the first step is to...
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Author Spotlight: Enhancing Rheumatoid Arthritis Research Through HR-pQCT Imaging Analysis
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Prior Knowledge Driven Joint NMF Algorithm for ceRNA Co-Module Identification.

Jin Deng1, Wei Kong1, Shuaiqun Wang1

  • 1College of Information Engineering, Shanghai Maritime University, 1550 Haigang Ave., Shanghai 201306, P. R. China.

International Journal of Biological Sciences
|November 17, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method for analyzing competing endogenous RNA (ceRNA) networks by integrating messenger RNA (mRNA), long non-coding RNA (lncRNA), and microRNA (miRNA) data. The approach effectively maps these interactions, revealing significant cancer-related modules and potential biological associations in tumor development.

Keywords:
ceRNAlncRNAmRNAmiRNAtumor

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Area of Science:

  • Bioinformatics
  • Molecular Biology
  • Cancer Research

Background:

  • Competing endogenous RNA (ceRNA) interactions, involving messenger RNA (mRNA), long non-coding RNA (lncRNA), and microRNA (miRNA), are crucial in post-transcriptional regulation and tumor progression.
  • Existing methods for constructing ceRNA networks are limited in their ability to integrate diverse RNA data and capture synchronized regulatory effects across multiple levels.

Purpose of the Study:

  • To develop an integrative analysis method for constructing ceRNA networks by considering the interplay of mRNA, lncRNA, and miRNA.
  • To identify cancer-related modules and potential biological associations within the ceRNA network.

Main Methods:

  • Developed a joint matrix factorization method that integrates prior knowledge to map diverse RNA data (mRNA, lncRNA, miRNA) into a common coordinate system.
  • Constructed a ceRNA network based on common modules derived from the integrated data.

Main Results:

  • The developed method successfully mapped three types of RNA data for lung cancer into a common coordinate system.
  • Over 90% of the identified modules showed a strong association with cancer, including lung cancer.
  • The constructed ceRNA network accurately identified known RNA correlations and uncovered novel potential biological associations.

Conclusions:

  • The joint matrix factorization method provides a robust framework for integrative analysis of multi-omics RNA data in cancer research.
  • The findings support the ceRNA hypothesis and offer a foundation for future validation of how competitive RNA interactions influence tumor development.