Related Experiment Video

Updated: Jan 30, 2026

Generation of Lymph Node-fat Pad Chimeras for the Study of Lymph Node Stromal Cell Origin
09:10

Generation of Lymph Node-fat Pad Chimeras for the Study of Lymph Node Stromal Cell Origin

Published on: December 16, 2013

6.4K

Positive nonsentinel lymph nodes are associated with poor survival in breast cancer: results from a retrospective

P Si1, P Zhang2, T Chen3

  • 1Department of Breast Surgery, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, School of Clinical Medicine, Henan University, Zhengzhou, 450003, Henan, China.

Clinical & Translational Oncology : Official Publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
|January 12, 2019
PubMed
Abstract

Keywords:
Axillary lymph-node dissectionBreast cancerNonsentinel lymph nodeSentinel lymph-node biopsySurvival

More Related Videos

Collection and Processing of Lymph Nodes from Large Animals for RNA Analysis: Preparing for Lymph Node Transcriptomic Studies of Large Animal Species12:53

Collection and Processing of Lymph Nodes from Large Animals for RNA Analysis: Preparing for Lymph Node Transcriptomic Studies of Large Animal Species

Published on: May 19, 2018

28.7K
Sentinel Lymph Node Mapping and Biopsy for Endometrial Cancer at Early Stage with Laparoscopy05:52

Sentinel Lymph Node Mapping and Biopsy for Endometrial Cancer at Early Stage with Laparoscopy

Published on: August 19, 2021

13.2K

Related Concept Videos

Detailed Structure and Function of Lymph Nodes01:23

Detailed Structure and Function of Lymph Nodes

Lymph nodes are bean-shaped structures that cluster along the lymphatic vessels in the inguinal, axillary, and cervical regions. Each node is divided into compartments by a capsule that extends trabeculae inward.
From a histological perspective, lymph nodes can be split into two main areas: the superficial cortex and the deep medulla. The outer cortex is populated by dendritic cells, macrophages, and B lymphocytes, which are densely packed into follicles. When these B-lymphocytes are presented...
4.7K
Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
759
Position-effect Variegation02:32

Position-effect Variegation

In 1928, a German botanist Emil Heitz observed the moss nuclei with a DNA binding dye. He observed that while some chromatin regions decondense and spread out in the interphase nucleus, others do not. He termed them euchromatin and heterochromatin, respectively. He proposed that the heterochromatin regions reflect a functionally inactive state of the genome. It was later confirmed that heterochromatin is transcriptionally repressed, and euchromatin is transcriptionally active chromatin.
7.1K
Survival Curves01:18

Survival Curves

Survival curves are graphical representations that depict the survival experience of a population over time, offering an intuitive way to track the proportion of individuals who remain event-free at each time point. These curves are widely used in fields such as medicine, public health, and reliability engineering to visualize and compare survival probabilities across different groups or conditions.
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
710
Survival Tree01:19

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
423
Introduction To Survival Analysis01:18

Introduction To Survival Analysis

Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
783