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

Proteomics01:33

Proteomics

9.3K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
9.3K

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

Genomic Analysis of Puerto Rican Hispanic/Latino Men with Prostate Cancer.

Cancers·2026
Same author

Glucagon-Like Peptide-1 Receptor Agonists in Chronic Kidney Disease: Mechanisms and Clinical Perspectives.

Kidney medicine·2026
Same author

Biomarkers for Prostate Cancer Aggressiveness in Puerto Rican Men: Analysis of Phospho-Rb S249, N-cadherin, β-catenin, and E-cadherin Expression in Prostate Biopsies.

Ponce Health Sciences University scientific journal·2025
Same author

Calcium Sulfide Nanoclusters Trigger DNA Damage and Induce Cell Cycle Arrest in Non-Small-Cell Lung Adenocarcinoma Cells.

International journal of molecular sciences·2025
Same author

Hyper-phosphorylation of Rb S249 together with CDK5R2/p39 overexpression are associated with impaired cell adhesion and epithelial-to-mesenchymal transition: Implications as a potential lung cancer grading and staging biomarker.

PloS one·2018
Same journal

A Practical Framework for Incorporating Complex Survey Design in Bayesian Kernel Machine Regression.

Stats·2026
Same journal

Doubly Robust Estimation and Semiparametric Efficiency in Generalized Partially Linear Models with Missing Outcomes.

Stats·2025
Same journal

Exact Inference for Random Effects Meta-Analyses for Small, Sparse Data.

Stats·2025
Same journal

Assessing Spillover Effects of Medications for Opioid Use Disorder on HIV Risk Behaviors among a Network of People Who Inject Drugs.

Stats·2025
Same journal

Bidirectional f-Divergence-Based Deep Generative Method for Imputing Missing Values in Time-Series Data.

Stats·2025
Same journal

Bayesian Mediation Analysis with an Application to Explore Racial Disparities in the Diagnostic Age of Breast Cancer.

Stats·2025
查看所有相关文章

相关实验视频

Updated: Jan 15, 2026

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence
08:05

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Published on: June 10, 2025

1.1K

整合蛋白质组分析和机器学习来预测前列腺癌的攻击性.

Sheila M Valle Cortés1, Jaileene Pérez Morales2, Mariely Nieves Plaza3

  • 1Ponce Research Institute, Ponce Health Sciences University, Biochemistry and Cancer Biology Divisions, Ponce, PR 00716, USA.

Stats
|October 6, 2025
PubMed
概括
此摘要是机器生成的。

识别侵袭性前列腺癌 (PCa) 是关键. 像E-cadherin和Phospho-Rb S249这样的生物标志物,通过分类树进行分析,有助于预测瘤的攻击性,以便更好地监测患者.

关键词:
汽车车上的车辆.电子阴素的使用.这是一种N-cadherin.积极的 积极的 侵略性的从上皮细胞转变为介质细胞转变 (EMT).酸化的方法是:光化.前列腺癌是前列腺癌.视网母细胞瘤 视网母细胞瘤这是一种β-catenin.

更多相关视频

Phosphopeptide Enrichment Coupled with Label-free Quantitative Mass Spectrometry to Investigate the Phosphoproteome in Prostate Cancer
12:23

Phosphopeptide Enrichment Coupled with Label-free Quantitative Mass Spectrometry to Investigate the Phosphoproteome in Prostate Cancer

Published on: August 2, 2018

12.7K
Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

800

相关实验视频

Last Updated: Jan 15, 2026

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence
08:05

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Published on: June 10, 2025

1.1K
Phosphopeptide Enrichment Coupled with Label-free Quantitative Mass Spectrometry to Investigate the Phosphoproteome in Prostate Cancer
12:23

Phosphopeptide Enrichment Coupled with Label-free Quantitative Mass Spectrometry to Investigate the Phosphoproteome in Prostate Cancer

Published on: August 2, 2018

12.7K
Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

800

科学领域:

  • 在瘤学瘤学.
  • 分子病理学分子病理学
  • 生物标志物发现发现

背景情况:

  • 前列腺癌 (PCa) 诊断受到攻击性瘤识别困难的挑战,导致过度治疗.
  • 准确预测PCa的攻击性对于个性化治疗和避免不必要的干预至关重要.

研究的目的:

  • 调查素249 (Phospho-Rb S249),N-cadherin,β-catenin和E-cadherin作为侵略性PCa.生物标志物的视网膜母细胞瘤酸化的实用性.
  • 将生物标志物表达与临床病理学数据相关联,以提高诊断准确度.

主要方法:

  • 免疫组织化学 (IHC) 用于评估PCa组织中的生物标志物表达.
  • 使用后勤回归和分类和回归树 (CART) 模型,分析生物标志物与瘤攻击性和临床病理学数据的相关性.

主要成果:

  • 乙素和β-catenin与瘤的攻击性行为呈现负相关性.
  • -Rb S249和N-cadherin与增加的PCa攻击性正相关.
  • 卡特分析发现β-catenin,瘤等级和格里森等级是识别格里森分数≥4+3的患者的关键决定因素.

结论:

  • 包括E-cadherin,β-catenin,Phospho-Rb S249和N-cadherin在内的生物标志物显示出识别侵袭性前列腺癌的潜力.
  • 分类和回归树 (CART) 模型提供了一种有效的方法来评估这些生物标志物的临床实用性.
  • 通过这些生物标志物的早期检测,可以指导患者监测和治疗策略.