From single-cell migration to the emergence of collective motion using microstructured surfaces

Cell migration is a fundamental process that is essential for the development, maintenance, and functionality of multicellular organisms. A detailed understanding of the underlying mechanisms and phenomenological characteristics of cell migration is hence of central interest in life sciences. However, the bio-mechanical machinery propelling the cell is highly complex and its emergent migration patterns are difficult to grasp, even in the case of individually migrating cells. Additionally, at the scale of multi-cellular assemblies, interaction mechanisms that are not entirely understood result in long-ranged correlations and a rich set of collective phenomena in cell motion. A possible approach to break down this complexity is to restrict cell adhesion and migration to predefined areas by using micropatterning techniques. By choosing suitable pattern geometries, the degrees of freedom of the confined cells can be diminished so that specific features of cell migration can be addressed and studied selectively. Furthermore, micropatterning techniques allow to create large arrays of standardized microenvironments, thereby enabling the automated analysis of multiple experimental systems in parallel. In the course of this work, micropatterning techniques were developed and employed to systematically study single-cell migration and the emergence of collective motion in small cell assemblies. The developed micropatterning technique termed “microscale plasma-induced protein patterning” (µPIPP) is easy to implement and produces homogeneous protein patterns on various biocompatible substrates such as glass, tissue culture polystyrene, cyclic olefin copolymers, and parylene C. Moreover, the _PIPP protocol was extended to enable the formation of surface-bound protein gradients as well as of pattern designs featuring multiple proteins. Utilizing the controlled environment provided by micropatterning, we studied single-cell migration within arrays of ring-shaped microlanes. In contrast to conventional descriptions of cell migration, the resulting quasi-one-dimensional motion showed pronounced bimodality, exhibiting states of directionally persistent migration (“run states”) as well as states of localized erratic motion (“rest states”). Applying a change-point analysis based on cumulative sum statistics, the lifetimes of both states were identified to be exponentially distributed. The corresponding characteristic persistence times together with the cell velocity in the run state provided a set of parameters characterizing cell motion. By introducing cell-repellent barriers of different width into the setup, this parameter set was extended by quantifying the turning probability both in the presence and in the absence of chemical barriers. Similar to a migrational “fingerprint”, these five phenomenological measures were used to thoroughly quantify and compare the migration behavior of different cell types as well as the effect of different pharmaceutics. The corresponding results illustrate that micropattern-based assays in combination with detailed, multi-parameter assessment of cell motion have potential applications in cell biology as well as in sophisticated drug screening. In a second assay, the emergence of collective behavior in the motion of small cell assemblies was studied. As pattern geometry, we chose circles of different diameters, in which collective migration manifests in form of a coherent angular motion (CAMo) of the confined cells. Analyzing the dynamics in dependence on the number of cells, N, within a system, periods of CAMo as well as periods of disordered motion (DisMo) were identified. Both states showed exponential lifetime distributions. The persistence of CAMo was found to increase with N but exhibited a pronounced discontinuity between systems containing four and systems containing five cells. An assessment of the cell conformations within the patterns revealed that this discontinuity was accompanied by a geometric rearrangement of cells towards a configuration containing a central cell. Numerical simulations, which are based on the cellular Potts model and account for intracellular polarization as well as intercellular coupling via mechanotransduction, reproduced these features and hence confirmed our finding that the persistence of rotational states depends on the interplay of spatial arrangement and internal polarization of neighboring cells. The distinct migration states within confined environments hence provides significant insights into the local interaction rules guiding collective migration. Taken together, the results of this thesis shed new light on the process of cell migration and illustrate how the controlled and standardized microenvironments provided by micropatterning techniques can be used to systematically assess and examine cell migration on a quantitative basis. Furthermore, the introduced techniques and assays are a step towards establishing micropatterning as a standard tool for cell science.Zellmigration ist ein essenzieller Prozess in der Entwicklung und Erhaltung vielzelliger Organismen. Ein tiefgreifendes Verständnis der involvierten Mechanismen und phänomenologischen Charakteristika ist folglich von zentralem Interesse für die Zellforschung. Allerdings ist die involvierte Maschinerie komplex, was sich in Bewegungsmustern wiederspiegelt, die schon für vereinzelte Zellen schwer zu fassen sind. Zusätzlich führen auf der Skala größerer Zellansammlungen Interaktionsmechanismen, deren genaue Funktionsweise noch nicht geklärt ist, zu langreichweitigen Korrelationen und vielfältigen kollektiven Phänomenen in den Bewegungsmustern. Eine Möglichkeit diese Komplexität im Experiment herunterzubrechen bietet die räumliche Begrenzung der Migration durch Mikrostrukturierung. Durch die Wahl geeigneter Strukturgeometrien können auf diese Weise die Freiheitsgrade der Zellen so eingeschränkt werden, dass spezifische Merkmale der Zellmigration gezielt adressiert und untersucht werden können. Zusätzlich können mit geeigneten Techniken weite Oberflächenbereiche strukturiert werden, was die automatisierte und parallelisierte Auswertung großer Anzahlen standardisierter Einzelexperimente ermöglicht. Im Zuge dieser Arbeit wurden daher neue Verfahren zur Mikrostrukturierung entwickelt und verwendet, um Einzelzellmigration wie auch die Interaktion kleiner Zellgruppen systematisch zu untersuchen. Die hier entwickelte Mikrostrukturierungsmethode, genannt “microscale plasma-induced protein patterning” (µPIPP), ist einfach in der Anwendung und produziert homogene Proteinstrukturen auf verschiedenen biokompatiblen Oberflächen wie Glas, Zellkultur Polystyrol, Cyclo-Olefin-Copolymeren, und Parylen C. Darüber hinaus wurde das µPIPP-Protokoll erweitert, um die Generierung von oberflächengebundenen Proteingradienten sowie Strukturen bestehend aus mehreren Proteinkomponenten zu ermöglichen. Um das Migrationsverhalten von Einzelzellen zu untersuchen, wurden ringförmige Mikrostrukturen verwendet. Im Kontrast zu klassischen Beschreibungen der Zellmigration zeigte die quasi-eindimensionale Bewegung der Zellen in diesen Systemen ausgeprägte Bimodalität, alternierend zwischen Phasen persistenter Migration und Phasen der Zufallsbewegung. Durch Einführung eines Algorithmus’ zum Erfassen charakteristischer Änderungen im Migrationsverhalten wurden die typischen Lebensdauern beider Zustände bestimmt. Zusammen mit der Zellgeschwindigkeit im persistenten Zustand ergaben diese einen charakteristischen Parametersatz um das Bewegungsverhalten einer Zelle zu beschreiben. Durch das Einbinden einer zellabweisenden Barriere in das System wurde dieser noch um die Umkehrwahrscheinlichkeiten in Abwesenheit und Anwesenheit chemischer Grenzflächen erweitert. Zusammengenommen wurden diese fünf Parametern gleich einem Fingerabdruck des Migrationsverhaltens einer Zelle verwendet, um die Bewegungsmuster von Zelltypen verschiedener Invasivität und den Effekt verschiedener Pharmazeutika auf diese detailliert zu charakterisieren und zu quantifizieren. Die verwendete Untersuchungsmethode gibt somit ein umfassendes Bild des Migrationsverhaltens von Einzelzellen und hat zudem Potential im Hinblick auf die Entwicklung eines Standardverfahrens zur vergleichenden Analyse von Zellmotilität in Zellbiologie und Pharmakologie. In einer zweiten Versuchsanordnung wurde das Auftreten kollektiven Verhaltens in der Migration kleiner Zellgruppen untersucht. Hierfür wurden kreisförmige Mikrostrukturen von verschiedenem Durchmesser eingesetzt, in welchen kollektive Bewegung in der Form kohärenter Rotation aller Zellen innerhalb einer Kreisstruktur auftritt. Die Zellbewegung innerhalb der Systeme wurden in Abhängigkeit der enthaltenen Zellenanzahl untersucht, wobei immer sowohl Phasen kohärenter Rotation als auch Phasen ungeordneter Bewegung zu beobachten waren. Die Persistenz der Rotationszustände stieg dabei zwar generell mit steigender Zellenzahl an, dieser Trend wurde jedoch durch einen starken Abfall der Persistenz zwischen Systemen mit vier und Systemen mit fünf Zellen unterbrochen. Das Auslesen der relativen Zellpositionen innerhalb der Einzelsysteme zeigte, dass dieser Abfall mit einer Veränderung der Zellkonformation einherging. Numerische Simulationen basierend auf dem zellulären Potts- Modell, welche sowohl intrazelluläre Polarisation als auch interzelluläre Koppelung durch Mechanotransduktion berücksichtigen, reproduzierten diese Ergebnisse und lassen somit den Schluss zu, dass das Wechselspiel von relativer räumlicher Anordnung und der Ausrichtung der internen Polarisationsachsen benachbarter Zellen die Lebensdauer kollektiver Rotationszustande in der Zellmigration bestimmt. Die Untersuchung der verschiedenen Bewegungszustände innerhalb derMikrostrukturen gibt somit Einblick in die, der kollektiven Zellbewegung zugrundeliegenden, Interaktionsmuster. Zusammengefasst liefern die Ergebnisse dieser Arbeit somit tiefere Erkenntnis über den Prozess der Zellmigration und stellen einen weiteren Schritt dar, Mikrostrukturierung als Standardverfahren zur Analyse und Quantifizierung von Zellbewegung zu etablieren

Networks and navigation in the knowledge economy: Studies on the structural conditions and consequences of path-dependent and relational action

In the wake of a relational turn, economic geographers have begun to scrutinize the relationships and interactions between people and organizations as a driving force behind economic processes at both global and local scales. Through a focus on contingent contextuality and path dependence, relational economic geography and network thinking have provided the necessary conceptual toolbox for untangling the structural effects and drivers of these relationships and their spatial embeddedness. However, despite the conceptual richness of the relational approach, empirical studies have often fallen short of capturing its core tenets: First, there is a prevalence to focus on places, infrastructures, and similarities as aggregate proxies for actors and their socio-economic relationships as the unit of geographical network analysis; While often convenient, this approach misses out on the capacity of networks to represent spatially embedded social contexts as enablers or constraints of economic action. Second, while path dependence is at the heart of evolutionary approaches towards economic geography, few studies actually trace how path-dependent and interrelated innovation shapes the long-term emergence of fields. Relational processes are especially salient when outcomes are opaque, decisions are interdependent, and when formal rules and roles are weak or absent. In this thesis, I ask how actors navigate such contexts and investigate the structural conditions and consequences of their navigation efforts. In my pursuit of this question, I draw on literatures from sociology, economics, and organization studies and build on novel methods of network analysis capable of empirically capturing contextuality and path dependence to investigate relational processes at three levels of economic activity: The thesis first looks towards a localized and informal trade platform to demonstrate how consumers rely on their former transactions to navigate exchange uncertainty and how such an exchange system can become liable to personal lock-in. It then moves on to show how the geographically and organizationally diversified search for innovation opportunities structures the transfer of knowledge across a globalized and partially informal corporate scouting community. Finally, the thesis shows how the linkage of distinct knowledge domains drives the long-term emergence of heterogeneous technological fields. In its endeavor to trace these processes, the thesis contributes a set of distinct relational research designs that demonstrate how advances in methods and data can be employed to empirically exploit the conceptual richness of relational economic geography

Strong atom-field coupling for Bose-Einstein condensates in an optical cavity on a chip

An optical cavity enhances the interaction between atoms and light, and the rate of coherent atom-photon coupling can be made larger than all decoherence rates of the system. For single atoms, this strong coupling regime of cavity quantum electrodynamics (cQED) has been the subject of spectacular experimental advances, and great efforts have been made to control the coupling rate by trapping and cooling the atom towards the motional ground state, which has been achieved in one dimension so far. For N atoms, the three-dimensional ground state of motion is routinely achieved in atomic Bose-Einstein condensates (BECs), but although first experiments combining BECs and optical cavities have been reported recently, coupling BECs to strong-coupling cavities has remained an elusive goal. Here we report such an experiment, which is made possible by combining a new type of fibre-based cavity with atom chip technology. This allows single-atom cQED experiments with a simplified setup and realizes the new situation of N atoms in a cavity each of which is identically and strongly coupled to the cavity mode. Moreover, the BEC can be positioned deterministically anywhere within the cavity and localized entirely within a single antinode of the standing-wave cavity field. This gives rise to a controlled, tunable coupling rate, as we confirm experimentally. We study the heating rate caused by a cavity transmission measurement as a function of the coupling rate and find no measurable heating for strongly coupled BECs. The spectrum of the coupled atoms-cavity system, which we map out over a wide range of atom numbers and cavity-atom detunings, shows vacuum Rabi splittings exceeding 20 gigahertz, as well as an unpredicted additional splitting which we attribute to the atomic hyperfine structure.Comment: 20 pages. Revised version following referees' comments. Detailed notes adde

Human-Robot Gym: Benchmarking Reinforcement Learning in Human-Robot Collaboration

Deep reinforcement learning (RL) has shown promising results in robot motion planning with first attempts in human-robot collaboration (HRC). However, a fair comparison of RL approaches in HRC under the constraint of guaranteed safety is yet to be made. We, therefore, present human-robot gym, a benchmark for safe RL in HRC. Our benchmark provides eight challenging, realistic HRC tasks in a modular simulation framework. Most importantly, human-robot gym includes a safety shield that provably guarantees human safety. We are, thereby, the first to provide a benchmark to train RL agents that adhere to the safety specifications of real-world HRC. This bridges a critical gap between theoretic RL research and its real-world deployment. Our evaluation of six environments led to three key results: (a) the diverse nature of the tasks offered by human-robot gym creates a challenging benchmark for state-of-the-art RL methods, (b) incorporating expert knowledge in the RL training in the form of an action-based reward can outperform the expert, and (c) our agents negligibly overfit to training data

Sparse Power Factorization: Balancing peakiness and sample complexity

In many applications, one is faced with an inverse problem, where the known signal depends in a bilinear way on two unknown input vectors. Often at least one of the input vectors is assumed to be sparse, i.e., to have only few non-zero entries. Sparse Power Factorization (SPF), proposed by Lee, Wu, and Bresler, aims to tackle this problem. They have established recovery guarantees for a somewhat restrictive class of signals under the assumption that the measurements are random. We generalize these recovery guarantees to a significantly enlarged and more realistic signal class at the expense of a moderately increased number of measurements.Comment: 18 page

Complex THz and DC inverse spin Hall effect in YIG/Cu1−x_{1-x}Irx_{x} bilayers across a wide concentration range

We measure the inverse spin Hall effect of Cu$_{1-x}$Ir$_{x}$ thin films on yttrium iron garnet over a wide range of Ir concentrations ($0.05 \leqslant x \leqslant 0.7$). Spin currents are triggered through the spin Seebeck effect, either by a DC temperature gradient or by ultrafast optical heating of the metal layer. The spin Hall current is detected by, respectively, electrical contacts or measurement of the emitted THz radiation. With both approaches, we reveal the same Ir concentration dependence that follows a novel complex, non-monotonous behavior as compared to previous studies. For small Ir concentrations a signal minimum is observed, while a pronounced maximum appears near the equiatomic composition. We identify this behavior as originating from the interplay of different spin Hall mechanisms as well as a concentration-dependent variation of the integrated spin current density in Cu$_{1-x}$Ir$_{x}$. The coinciding results obtained for DC and ultrafast stimuli show that the studied material allows for efficient spin-to-charge conversion even on ultrafast timescales, thus enabling a transfer of established spintronic measurement schemes into the terahertz regime.Comment: 12 pages, 4 figure

Cells in Silico – introducing a high-performance framework for large-scale tissue modeling

Background Discoveries in cellular dynamics and tissue development constantly reshape our understanding of fundamental biological processes such as embryogenesis, wound-healing, and tumorigenesis. High-quality microscopy data and ever-improving understanding of single-cell effects rapidly accelerate new discoveries. Still, many computational models either describe few cells highly detailed or larger cell ensembles and tissues more coarsely. Here, we connect these two scales in a joint theoretical model. Results We developed a highly parallel version of the cellular Potts model that can be flexibly applied and provides an agent-based model driving cellular events. The model can be modular extended to a multi-model simulation on both scales. Based on the NAStJA framework, a scaling implementation running efficiently on high-performance computing systems was realized. We demonstrate independence of bias in our approach as well as excellent scaling behavior. Conclusions Our model scales approximately linear beyond 10,000 cores and thus enables the simulation of large-scale three-dimensional tissues only confined by available computational resources. The strict modular design allows arbitrary models to be configured flexibly and enables applications in a wide range of research questions. Cells in Silico (CiS) can be easily molded to different model assumptions and help push computational scientists to expand their simulations to a new area in tissue simulations. As an example we highlight a 1000$^{3}$ voxel-sized cancerous tissue simulation at sub-cellular resolution

Datafication Markers: Curation and User Network Effects on Mobilization and Polarization During Elections

Social media platforms are crucial sources of political information during election campaigns, with datafication processes underlying the algorithmic curation of newsfeeds. Recognizing the role of individuals in shaping datafication processes and leveraging the metaphor of news attraction, we study the impact of user curation and networks on mobilization and polarization. In a two-wave online panel survey (n = 943) conducted during the 2021 German federal elections, we investigate the influence of self-reported user decisions, such as following politicians, curating their newsfeed, and being part of politically interested networks, on changes in five democratic key variables: vote choice certainty, campaign participation, turnout, issue reinforcement, and affective polarization. Our findings indicate a mobilizing rather than polarizing effect of algorithmic election news exposure and highlight the relevance of users’ political networks on algorithmic platforms