\documentclass[a4paper]{article}

\usepackage{csquotes}
\usepackage[acronym]{glossaries}
\usepackage[utf8x]{inputenc}
\usepackage{siunitx}

\makeglossaries{}
\newacronym{cis}{CiS}{Cells in Silico}
\newacronym{cpm}{CPM}{Cellular Potts Model}
\newacronym{ecm}{ECM}{Extracellular Matrix}
\newacronym{mcs}{MCS}{Monte-Carlo Step}
\newacronym{nastja}{NAStJA}{Neoteric Autonomous Stencil code for Jolly Algorithms}

\begin{document}

\title{Research Summary}
\author{Paul Brinkmeier}
\date{June 2023}
\maketitle

\section{\acrfull{ecm}}

For an extensive overview, see \cite{frantz2010}.

\begin{itemize}
	\item The \acrshort{ecm} constitutes the non-cellular parts of all tissues.
	\item It consists of:
	\begin{itemize}
		\item Fibrous proteins, most importantly collagen, elastin and fibronectin.
		\item Up to 30\% collagen.
                      Forms fibrils and fibers of different sizes which can \enquote{stick together} to make up networks.
		      There are a bunch of different collagen types.
		\item Proteoglycans, which fill the interstitial space in the form of a hydrated gel.
	\end{itemize}
	\item Cells move through and remodel their \acrshort{ecm}, which in turn changes their behavior. \\
	      $\implies$ \emph{in silico} models need to take this into account.
	\item Different tissues have different \acrshortpl{ecm}.
\end{itemize}

\subsection{Properties of the Extracellular Matrix}

Our approach takes a macroscopic view of the \acrshort{ecm}.
Individual fibrils/fibers should not be modeled.
Nevertheless we include some microscopic properties.

\begin{itemize}
	\item \textbf{Density}
	\item \textbf{Stiffness}: Matrix stiffness has an effect on tumor gowth, e.g. \cite{levental2009}.
	Measured using Young's modulus/elastic modulus which is given in \si{\Pa}.
	\item \textbf{Viscoelasticity}
	\item \textbf{Pore size}
\end{itemize}

\cite{frantz2010} mentions Matrigel™ and collagen type I gels, so we will focus on these.

\section{\acrfull{cpm}}

\begin{itemize}
	\item The \acrshort{cpm} is a grid-based Monte-Carlo simulation for cells.
	\item Each cell consists of many voxels.
              These voxels contain its cell ID.
	\item In each \acrfull{mcs}, a random voxel copies the cell ID of its neighbor.
	\item The hamiltonian $H$ gives the energy of a generation. It depends on the volume and surface of cells and their reciprocal adhesion.
	\item A \acrshort{mcs} is always accepted if it reduces $H$.
              If it does not reduce $H$, it is accepted probabilistically.
\end{itemize}

\section{\acrshort{nastja} \& \acrshort{cis}}

\begin{itemize}
	\item \acrfull{nastja} is a massively parallel stencil code solver based on OpenMPI.
	\item \acrfull{cis} is an implementation of the \acrshort{cpm} in \acrshort{nastja}.
\end{itemize}

\section{The \acrshort{ecm} in the \acrshort{cpm}}

\clearpage

\section{Glossary}

\printglossary[type=\acronymtype]

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\bibliography{references}

\end{document}