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相关概念视频

Functional Classification of Joints01:09

Functional Classification of Joints

6.5K
Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...
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Knee Joint01:23

Knee Joint

3.1K
The knee joint is the most complicated joint in the body. It consists of three articulations– two tibiofemoral and one patellofemoral. As is characteristic of synovial joints, the knee joint has a thin articular capsule that partially surrounds this joint cavity. Additionally, several ligaments, muscles, and cartilaginous structures support the movement of the knee.
A total of seven ligaments support the knee joint. The patellar ligament, which is also attached to the quadriceps femoris...
3.1K
Classification of Bones01:18

Classification of Bones

9.5K
The bones of the human skeletal system are of varied shapes, sizes, and functions. They can be classified based on their shape and function into four major classes: long bones, short bones, flat bones, and irregular bones. Some classifications include a fifth type, the sesamoid bones, as a separate class, whereas others categorize them under short bones.
Long and Short Bones
The appendicular skeleton, particularly the upper and lower limbs, is primarily made of long and short bones. The...
9.5K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

15.3K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
15.3K
Structural Classification of Joints01:20

Structural Classification of Joints

6.9K
Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
6.9K
Ankle Joint01:10

Ankle Joint

2.8K
The ankle is formed by the talocrural joint (crural = leg). It consists of the articulations between the talus bone of the foot and the distal ends of the tibia and fibula of the leg. The superior aspect of the talus bone is square-shaped and has three areas of articulation. The top of the talus articulates with the inferior tibia. This is the portion of the ankle joint that carries the body weight between the leg and foot. The sides of the talus are firmly held in position by the articulations...
2.8K

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相关实验视频

Updated: Jan 13, 2026

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

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对骨关节炎候选人预测的知识图嵌入.

Zhenggang Wang1, Zhengyu Lu2,3, Meng Li4

  • 1Department of Orthopedics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.

NPJ digital medicine
|January 10, 2026
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的知识图方法,CausalPathKG,通过整合遗传数据来发现新的骨关节炎治疗方法. 该方法通过分析因果基因关联成功确定了有前途的候选药物,为这种致残关节疾病推进了治疗发现.

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科学领域:

  • 生物医学信息学 生物医学信息学
  • 计算生物学 计算生物学
  • 遗传学 是一个遗传学.

背景情况:

  • 骨关节炎 (OA) 是一种广泛且使人虚弱的关节疾病,缺乏疾病修饰性治疗.
  • 目前的治疗策略主要是管理OA症状,而不是解决潜在的疾病机制.
  • 整合大规模的生物医学数据为发现新型OA治疗提供了有希望的途径.

研究的目的:

  • 开发和验证基于知识图的计算方法,用于识别候选OA治疗方法.
  • 从全基因组关联研究 (GWAS) 中利用因果遗传关联,以加强对OA的药物重新定位.
  • 创建一个专门的骨关节炎知识图 (OKG),整合各种生物医学信息.

主要方法:

  • 构建骨关节炎知识图 (OKG) 通过将药物重定位知识图 (DRKG) 与来自大规模OA GWAS的因果遗传关联相结合.
  • 开发了CausalPathKG,这是一个基于RotatE的新型知识图嵌入模型,包含加权边缘,基于路径的规范化,多跳图注意力和对抗性负样本.
  • 培训和评估CausalPathKG用于链接预测,特别是预测缺失的OA治疗,使用已知OA相关边缘进行测试.

主要成果:

  • 与基线模型 (TransE,RotatE) 相比,CausalPathKG在预测持久性OA治疗方面表现优异,实现了更高的链接预测准确度.
  • 该模型在识别潜在的OA疗法方面表现出强大的分类性能.
  • 案例研究证实,由CausalPathKG识别的排名第一的重用药物准了关键的OA相关基因和人类遗传学涉及的途径.

结论:

  • 将人类遗传证据集成到知识图模型中,显著提高了对OA等复杂疾病的治疗方法的发现.
  • CausalPathKG通过有效地将基因组数据与现有药物知识相结合,为药物重定向提供了强大的计算策略.
  • 这种方法提供了一个有前途的途径,以加快疾病修饰性关节炎治疗方法的开发.