相关实验视频

Updated: Sep 20, 2025

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
07:13

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

202

基于分子特征的分类 retroperitoneal 脂质肉瘤:一个前性队列研究

Mengmeng Xiao1,2, Xiangji Li2,3, Fanqin Bu3

  • 1Department of Retroperitoneal Tumor Surgery, Peking University People's Hospital, Beijing, China.

eLife
|May 23, 2025
PubMed
概括

这项研究基于分子特征确定了两种不同类型的逆皮质脂肉瘤 (RPLS),改善了患者分层. 一种新的生物标志物分类提供了一种具有成本效益的方法,用于指导RPLS中的治疗决策.

关键词:
对于LEP来说,这是一个很好的选择.在 PTTG1 的基础上.癌症生物学 癌症生物学人类 人类 人类 人类 人类 人类 人类医学 医学 医学 医学 医学分子分类的分子分类.后皮皮质脂肪肉瘤 (retroperitoneal liposarcoma) 是一种癌症.

更多相关视频

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

6.9K
On-Site Sampling and Extraction of Brain Tumors for Metabolomics and Lipidomics Analysis06:48

On-Site Sampling and Extraction of Brain Tumors for Metabolomics and Lipidomics Analysis

Published on: May 31, 2020

6.0K

相关概念视频

Non-LTR Retrotransposons03:18

Non-LTR Retrotransposons

As the name suggests, non-LTR retrotransposons lack the long terminal repeats characteristic of the LTR retrotransposons. Additionally, both LTR and non-LTR retrotransposons use distinct mechanisms of mobilization. Non-LTR retrotransposons are further divided into two classes - Long interspersed nuclear elements (LINEs) and short interspersed nuclear elements (SINEs), both of which occur abundantly in most mammals, including humans. Some of the active non-LTR retrotransposons in humans are L1...
11.9K