The arrow of time and the nature of spacetime

This paper extends the work of a previous paper [arXiv:1208.2611] on the flow of time, to consider the origin of the arrow of time. It proposes that a `past condition' cascades down from cosmological to micro scales, being realized in many microstructures and setting the arrow of time at the quantum level by top-down causation. This physics arrow of time then propagates up, through underlying emergence of higher level structures, to geology, astronomy, engineering, and biology. The appropriate space-time picture to view all this is an emergent block universe (`EBU'), that recognizes the way the present is different from both the past and the future. This essential difference is the ultimate reason the arrow of time has to be the way it is.Comment: 56 pages, 7 figure

Studies of Single-Molecule Dynamics in Microorganisms

Fluorescence microscopy is one of the most extensively used techniques in the life sciences. Considering the non-invasive sample preparation, enabling live-cell compliant imaging, and the specific fluorescence labeling, allowing for a specific visualization of virtually any cellular compound, it is possible to localize even a single molecule in living cells. This makes modern fluorescence microscopy a powerful toolbox. In the recent decades, the development of new, "super-resolution" fluorescence microscopy techniques, which surpass the diffraction limit, revolutionized the field. Single-Molecule Localization Microscopy (SMLM) is a class of super-resolution microscopy methods and it enables resolution of down to tens of nanometers. SMLM methods like Photoactivated Localization Microscopy (PALM), (direct) Stochastic Optical Reconstruction Microscopy ((d)STORM), Ground-State Depletion followed by Individual Molecule Return (GSDIM) and Point Accumulation for Imaging in Nanoscale Topography (PAINT) have allowed to investigate both, the intracellular spatial organization of proteins and to observe their real-time dynamics at the single-molecule level in live cells. The focus of this thesis was the development of novel tools and strategies for live-cell SingleParticle Tracking PALM (sptPALM) imaging and implementing them for biological research. In the first part of this thesis, I describe the development of new Photoconvertible Fluorescent Proteins (pcFPs) which are optimized for sptPALM lowering the phototoxic damage caused by the imaging procedure. Furthermore, we show that we can utilize them together with Photoactivatable Fluorescent Proteins (paFPs) to enable multi-target labeling and read-out in a single color channel, which significantly simplifies the sample preparation and imaging routines as well as data analysis of multi-color PALM imaging of live cells. In parallel to developing new fluorescent proteins, I developed a high throughput data analysis pipeline. I have implemented this pipeline in my second project, described in the second part of this thesis, where I have investigated the protein organization and dynamics of the CRISPR-Cas antiviral defense mechanism of bacteria in vivo at a high spatiotemporal level with the sptPALM approach. I was successful to show the differences in the target search dynamics of the CRISPR effector complexes as well as of single Cas proteins for different target complementarities. I have also first data describing longer-lasting bound-times between effector complex and their potential targets in vivo, for which only in vitro data has been available till today. In summary, this thesis is a significant contribution for both, the advances of current sptPALM imaging methods, as well as for the understanding of the native behavior of CRISPR-Cas systems in vivo

A dynamical model of the distributed interaction of intracellular signals

A major goal of modern cell biology is to understand the regulation of cell behavior in the reductive terms of all the molecular interactions. This aim is made explicit by the assertion that understanding a cell\u27s response to stimuli requires a full inventory of details. Currently, no satisfactory explanation exists to explain why cells exhibit only a relatively small number of different behavioral modes. In this thesis, a discrete dynamical model is developed to study interactions between certain types of signaling proteins. The model is generic and connectionist in nature and incorporates important concepts from the biology. The emphasis is on examining dynamic properties that occur on short-term time scales and are independent of gene expression. A number of modeling assumptions are made. However, the framework is flexible enough to be extended in future studies. The dynamical states of the system are explored both computationally and analytically. Monte Carlo methods are used to study the state space of simulated networks over selected parameter regimes. Networks show a tendency to settle into fixed points or oscillations over a wide range of initial conditions. A genetic algorithm (GA) is also designed to explore properties of networks. It evolves a population of modeled cells, selecting and ranking them according to a fitness function, which is designed to mimic features of real biological evolution. An analogue of protein domain shuffling is used as the crossover operator and cells are reproduced asexually. The effects of changing the parameters of the GA are explored. A clustering algorithm is developed to test the effectiveness of the GA search at generating cells, which display a limited number of different behavioral modes. Stability properties of equilibrium states in small networks are analyzed. The ability to generalize these techniques to larger networks is discussed. Topological properties of networks generated by the GA are examined. Structural properties of networks are used to provide insight into their dynamic properties. The dynamic attractors exhibited by such signaling networks may provide a framework for understanding why cells persist in only a small number of stable behavioral modes

Explanation in Biology

This book examines philosophical accounts of scientific explanation, particularly those that apply to biology and the life sciences. Two main categories of scientific explanation are examined in detail—causal explanations and non-causal explanations. The first section of this book provides a brief history and some basics on philosophical accounts of scientific explanation. Section two covers causal explanation, first by discussing foundational topics in the area, such as defining causation, causal selection, and reductive explanation. This is followed by an examination of distinct types of causal explanation, including those that appeal to mechanisms, pathways, and cascades. The third section of this book covers non-causal, mathematical explanations, which have received significant attention in recent philosophy of biology and the life sciences. Three main types of non-causal, mathematical explanation are discussed: topological and constraint-based explanation, optimality and efficiency explanations, and minimal model explanations. This work examines similarities and differences across accounts of scientific explanation, while situating them in the context of common goals, methods, and reasoning present in biology and the life sciences

Basic Cell and Molecular Biology 5e: What We Know and How We Find Out

https://dc.uwm.edu/biosci_facbooks_bergtrom/1014/thumbnail.jp

Annotated Cell and Molecular Biology 5e: What We Know and How We Found Out

https://dc.uwm.edu/biosci_facbooks_bergtrom/1013/thumbnail.jp

Active Materials

What is an active material? This book aims to redefine perceptions of the materials that respond to their environment. Through the theory of the structure and functionality of materials found in nature a scientific approach to active materials is first identified. Further interviews with experts from the natural sciences and humanities then seeks to question and redefine this view of materials to create a new definition of active materials

Organická paměť v embryonálním vývoji

Předložená disertační práce se zabývá tématem organické paměti, její definicí a funkcí, a stejně tak i jejími pojetími z různých historických hledisek. Užívám pojem "organické paměti" ve vztahu k autorům, kteří se tímto tématem již dříve zabývali (Elsasser 1987, Otis 1994, Barbieri 2003) a dále i jako pojem, který představuje paměť jinou než neuronovou/mozkovou. Obecné metafory paměti (v tomto případě paměti neuronové) jsou zásadně spojeny s pojmy jako úložiště, matice či místo. Pro spíše materialisticky založená pojetí paměti je navíc příznačné, že různé stavy jako emoce či vlastnosti mysli mohou být konkrétně lokalizovány v mozku. Na druhou stranu někteří filosofové popisovali paměť jako primárně časovou entitu bez konkrétní závislosti na hmotě či místě. Otázka organické paměti byla živá již v biologii 19. století, spojena především s filosofií lamarkismu (Hering 1870, Haeckel 1876, Butler 1910). Představy o organické paměti se v té době pohybovaly mezi vitalistickými a spíše materialistickými koncepcemi: v těch prvních byly buňkám či částečkám paměti přisuzovány psychologické atributy; ty druhé byly založeny na fyzikální či karteziánské doktríně a popisovaly paměť jako lokalizovatelné úložiště stop či fyzikálních vln. Nejdeterminističtější koncepce paměti jsou zakořeněny v metafoře počítače, i...The submitted thesis deals with the topic of organic memory, its definition and function, as well as its conceptions from various historical points of view. I use the term "organic memory" in respect to some authors who have previously dealt with this subject (Elsasser 1987, Otis 1994, Barbieri 2003) and also as a term by which to represent a kind of memory distinct from neuronal/cerebral memory. The general memory metaphors (in the case of neuronal memory) are essentially connected with terms such as storage, matrix, or place. For rather materialistic conception of memory, it is also symptomatic that different states such as emotions or mental faculties can be concretely localized in the brain tissue. On the contrary, some philosophers described memory as a primarily temporal entity without connection to place or matter. The question of organic memory was already vivid in 19th century biology, linked to Lamarckian philosophy (Hering 1870, Haeckel 1876, Butler 1910). The organic memory ideas floundered between vitalistic and rather materialistic conceptions: the first attributed some psychological features to cells or memory particles; the second was based on physics or in Cartesian doctrine, and described memory as essentially localized as a kind of storage of traces or patterns of physical waves....Katedra filosofie a dějin přírodních vědDepartment of Philosophy and History of SciencePřírodovědecká fakultaFaculty of Scienc