2026-04-14T07:58:29Zhttps://recercat.cat/oai/request

oai:recercat.cat:10230/351952025-12-12T04:10:05Zcom_2072_6col_2072_452952

00925njm 22002777a 4500 dc Mayer, Jürgen, 1977- author Swoger, Jim author Ozga, Aleksandra J. author Stein, Jens V. author Sharpe, James author 2018-07-19T07:33:20Z 2018-07-19T07:33:20Z 2012 Deep tissue imaging has become state of the art in biology, but now the problem is to quantify spatial information in a global, organ-wide context. Although access to the raw data is no longer a limitation, the computational tools to extract biologically useful information out of these large data sets is still catching up. In many cases, to understand the mechanism behind a biological process, where molecules or cells interact with each other, it is mandatory to know their mutual positions. We illustrate this principle here with the immune system. Although the general functions of lymph nodes as immune sentinels are well described, many cellular and molecular details governing the interactions of lymphocytes and dendritic cells remain unclear to date and prevent an in-depth mechanistic understanding of the immune system. We imaged ex vivo lymph nodes isolated from both wild-type and transgenic mice lacking key factors for dendritic cell positioning and used software written in MATLAB to determine the spatial distances between the dendritic cells and the internal high endothelial vascular network. This allowed us to quantify the spatial localization of the dendritic cells in the lymph node, which is a critical parameter determining the effectiveness of an adaptive immune response. The authors are grateful for funding from VIBRANT Grant CP-IP 228933-2 from the FP7-NMP and Sinergia Grant CRSII3 125447 from the Swiss National Science Foundation (SNSF) Nodes limfàtics Quantitative measurements in 3-dimensional datasets of mouse lymph nodes resolve organ-wide functional dependencies