| Cell-cell-neighborhood relations in tissue sections--a quantitative model for tissue cytometry. | |
| | |
MedLine Citation:
|
PMID: 19184996 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
|
Physical interactions between different cell types are a requirement for the initiation and maintenance of immune responses. The distribution pattern of cells within a tissue may result from specific cell-cell-interactions or random distribution. Tissue architecture, degree of inflammation, frequencies of cells, number of contact partners, cell type, and size as well as cell movement and contact time determine the distribution of cells within tissues. We developed a matrix model to determine the degree of expected random distribution of two cell types (A and B) and cell-cell-contacts within tissue sections. The model predictions were compared with experimental data derived from immunofluorescence microscopy. We implemented a computer algorithm for automatic image analysis to visualize and quantify cell-cell-neighborhood relations. Using the number of cells type A (a), the total cell number (t) and the mean number of cells that are in contact with cells type B (c(B)), the ratio of cells type B in contact with cells type A can be described by b(A)/b = 1- (1- (a/t))[symbol: see text]c(B). We applied the model system to investigate the distribution of Foxp3(+) regulatory T cells with Ki-67(+) proliferating cells within mouse tissue sections. The matrix model provides a tool to describe the expected distribution of two different cell types and their cell-cell-contacts within tissues. Comparing the degree of expected random distribution with experimental data might help to propose functional cell-cell-interactions in tissue sections. |
| | |
Authors:
|
N Händel; A Brockel; M Heindl; E Klein; H H Uhlig |
Related Documents
:
|
18662776 - The stochastic nature of biochemical networks. 9610106 - A model for hepatocarcinogenesis treating phenotypical changes in focal hepatocellular ... 19619456 - Computational analysis of dynamical responses to the intrinsic pathway of programmed ce... 16297376 - Phase response characteristics of sinoatrial node cells. 1907476 - Magnesium in normal and neoplastic cell proliferation: state of the art on in vitro data. 8879306 - Giant cell fibroblastoma. new histological observations. |
Publication Detail:
|
Type: Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
|
Title: Cytometry. Part A : the journal of the International Society for Analytical Cytology Volume: 75 ISSN: 1552-4930 ISO Abbreviation: Cytometry A Publication Date: 2009 Apr |
Date Detail:
|
Created Date: 2009-03-25 Completed Date: 2009-06-26 Revised Date: - |
Medline Journal Info:
|
Nlm Unique ID: 101235694 Medline TA: Cytometry A Country: United States |
Other Details:
|
Languages: eng Pagination: 356-61 Citation Subset: IM |
Copyright Information:
|
(c) 2009 International Society for Advancement of Cytometry. |
Affiliation:
|
University Hospital for Children and Adolescents, Section of Pediatric Gastroenterology and Hepatology, University of Leipzig, Leipzig, Germany. |
Export Citation:
|
APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
|
Algorithms* Animals Cell Communication / physiology* Cell Proliferation Colon / cytology, immunology, metabolism Computer Simulation* Fluorescent Antibody Technique / methods Forkhead Transcription Factors / analysis, metabolism Image Cytometry / methods* Immunophenotyping / methods Ki-67 Antigen / analysis, metabolism Mice Mice, Inbred C57BL Software* T-Lymphocytes, Regulatory / cytology*, immunology, metabolism |
| Chemical | |
Reg. No./Substance:
|
0/Forkhead Transcription Factors; 0/Foxp3 protein, mouse; 0/Ki-67 Antigen |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
Previous Document: Strength of prefrontal activation predicts intensity of suggestion-induced pain.
Next Document: Dopaminergic modulation of brain systems subserving decision making under uncertainty: a study with ...