Using movies to analyse gene circuit dynamics in single cells

Many bacterial systems rely on dynamic genetic circuits to control crucial biological processes. A major goal of systems biology is to understand these behaviours in terms of individual genes and their interactions. However, traditional techniques based on population averages 'wash out' crucial dynamics that are either unsynchronized between cells or are driven by fluctuations, or 'noise', in cellular components. Recently, the combination of time-lapse microscopy, quantitative image analysis and fluorescent protein reporters has enabled direct observation of multiple cellular components over time in individual cells. In conjunction with mathematical modelling, these techniques are now providing powerful insights into genetic circuit behaviour in diverse microbial systems

Understanding the Dynamics of Embryonic Stem Cell Differentiation

The two defining features of mouse embryonic stem (ES) cells are self-renewal and naive pluripotency, the ability to give rise to all cell lineages in the adult body. In addition to being a unique and interesting cell type, pluripotent ES cells have demonstrated their potential for continued advancements in biomedical science. Currently, there is an improved understanding in the chemical signals and the gene regulatory network responsible for the maintenance of ES cells in the naive pluripotent state. However, less is understood about how ES cells exit pluripotency. My main aim is to study the dynamics and the factors affecting the irreversible exit from pluripotency. Expression of the reporter Rex1-GFPd2, which is inactivated upon exit from naive pluripotency, was analyzed by quantitative long-term single-cell imaging over many generations. This technique allowed chemical, physical, and genealogical information to be recorded during the transition to exit. Culture conditions that provided homogeneous populations were used in all assays and these data were validated against bulk-culture data where appropriate. Changes in real-time cell behavior were seen in cell-cell contact, motility, and cell-cycle duration. Undifferentiated ES cells form tightly joined colonies, with cells that exhibit low motility and a constant cell-cycle duration. Exit is associated with increasing cell motility, decreased cell-cell contact, and an acceleration in cell proliferation. The onset of exit is associated with a sudden and irreversible inactivation of the Rex1-GFPd2 reporter. This inactivation is asynchronous, as it occurs at different times and in different generations during ES cell differentiation. However, examination of daughter cells generated from the same mother revealed a high level of synchronicity. Further investigation revealed that high levels of correlation in cell-cycle duration and Rex1-GFPd2 expression exist between differentiating sister and cousin cells, providing strong evidence that cell potency is inherited symmetrically in cell divisions during exit $\textit{in vitro}$. How cells change fate is a fundamental question in developmental biology. Knowing the cellular dynamics during the transition out of naive pluripotency is important for harnessing the potential of ES cells and understanding how cell fate decisions are made during embryonic development. The quantification of the timing of exit from naive pluripotency coupled with identifiable changes in cellular behaviors, such as motility, cell size, and cell-cycle duration, enhances the understanding of how cell fate changes are regulated during directed differentiation.Microsoft Research PhD Scholarship Programm

A Promethean Philosophy of External Technologies, Empiricism, & the Concept: Second-Order Cybernetics, Deep Learning, and Predictive Processing

Beginning with a survey of the shortcoming of theories of organology/media-as-externalization of mind/body—a philosophical-anthropological tradition that stretches from Plato through Ernst Kapp and finds its contemporary proponent in Bernard Stiegler—I propose that the phenomenological treatment of media as an outpouching and extension of mind qua intentionality is not sufficient to counter the ̳black-box‘ mystification of today‘s deep learning‘s algorithms. Focusing on a close study of Simondon‘s On the Existence of Technical Objectsand Individuation, I argue that the process-philosophical work of Gilbert Simondon, with its critique of Norbert Wiener‘s first-order cybernetics, offers a precursor to the conception of second-order cybernetics (as endorsed byFrancisco Varela, Humberto Maturana, and Ricardo B. Uribe) and, specifically, its autopoietic treatment of information. It has been argued by those such as Frank Pasquale that neuro-inferential deep learning systems premised on predictive patterning, suchas AlphaGo Zero, have a veiled logic and, thus, are ̳black boxes‘. In detailing a philosophical-historical approach to demystify predictive patterning/processing and the logic of such deep learning algorithms, this paper attempts to shine a light on such systems and their inner workingsàla Simondon

Scalable and flexible inference framework for stochastic dynamic single-cell models

Understanding the inherited nature of how biological processes dynamically change over time and exhibit intra- and inter-individual variability, due to the different responses to environmental stimuli and when interacting with other processes, has been a major focus of systems biology. The rise of single-cell fluorescent microscopy has enabled the study of those phenomena. The analysis of single-cell data with mechanistic models offers an invaluable tool to describe dynamic cellular processes and to rationalise cell-to-cell variability within the population. However, extracting mechanistic information from single-cell data has proven difficult. This requires statistical methods to infer unknown model parameters from dynamic, multi-individual data accounting for heterogeneity caused by both intrinsic (e.g. variations in chemical reactions) and extrinsic (e.g. variability in protein concentrations) noise. Although several inference methods exist, the availability of efficient, general and accessible methods that facilitate modelling of single-cell data, remains lacking. Here we present a scalable and flexible framework for Bayesian inference in state-space mixed-effects single-cell models with stochastic dynamic. Our approach infers model parameters when intrinsic noise is modelled by either exact or approximate stochastic simulators, and when extrinsic noise is modelled by either time-varying, or time-constant parameters that vary between cells. We demonstrate the relevance of our approach by studying how cell-to-cell variation in carbon source utilisation affects heterogeneity in the budding yeast Saccharomyces cerevisiae SNF1 nutrient sensing pathway. We identify hexokinase activity as a source of extrinsic noise and deduce that sugar availability dictates cell-to-cell variability

Contributions to autonomous robust navigation of mobile robots in industrial applications

151 p.Un aspecto en el que las plataformas móviles actuales se quedan atrás en comparación con el punto que se ha alcanzado ya en la industria es la precisión. La cuarta revolución industrial trajo consigo la implantación de maquinaria en la mayor parte de procesos industriales, y una fortaleza de estos es su repetitividad. Los robots móviles autónomos, que son los que ofrecen una mayor flexibilidad, carecen de esta capacidad, principalmente debido al ruido inherente a las lecturas ofrecidas por los sensores y al dinamismo existente en la mayoría de entornos. Por este motivo, gran parte de este trabajo se centra en cuantificar el error cometido por los principales métodos de mapeado y localización de robots móviles,ofreciendo distintas alternativas para la mejora del posicionamiento.Asimismo, las principales fuentes de información con las que los robots móviles son capaces de realizarlas funciones descritas son los sensores exteroceptivos, los cuales miden el entorno y no tanto el estado del propio robot. Por esta misma razón, algunos métodos son muy dependientes del escenario en el que se han desarrollado, y no obtienen los mismos resultados cuando este varía. La mayoría de plataformas móviles generan un mapa que representa el entorno que les rodea, y fundamentan en este muchos de sus cálculos para realizar acciones como navegar. Dicha generación es un proceso que requiere de intervención humana en la mayoría de casos y que tiene una gran repercusión en el posterior funcionamiento del robot. En la última parte del presente trabajo, se propone un método que pretende optimizar este paso para así generar un modelo más rico del entorno sin requerir de tiempo adicional para ello

The discipline and disciplining of Margaret Sanger: US birth control rhetoric in the early twentieth century

Margaret Sanger\u27s rhetoric in the US birth control movement demonstrates the social forces that act upon rhetors and women\u27s bodies, conforming both to established gender norms even as they attempt to violate those standards. This project studies Sanger\u27s birth control rhetoric to understand how her arguments for women\u27s right to contraception conformed women\u27s bodies to traditional feminine notions despite her early efforts to contradict such dictates of domesticity. Research on nineteenth-century feminist rhetors demonstrates a pattern of women challenging feminine ideals by speaking publicly but replicating the familiar themes that women must care for others. To explain such a pattern, this study combines the theories of interpretation and genealogy to analyze texts\u27 meanings with a respect for the ways that social forces conform speakers to already established norms and themes. This project follows genealogical demands for a complex history by discussing the discourses that challenge and support early twentieth century birth control rhetoric . Early themes in Sanger\u27s rhetoric focus on issues of class and women\u27s personal liberation. Analysis shows that Sanger begins by addressing the class oppression working class experience before engaging in class maternalism in which she condescends to lower class women setting upper class women as examples of bodily discipline. Sanger\u27s early themes of birth control as women\u27s liberation give way to an emphasis upon women using birth control to better serve their families, thereby fulfilling their maternal duties. Later themes in Sanger\u27s rhetoric emphasize birth control\u27s utility to the state for managing the rate and quality of women\u27s reproduction. The movement from earlier to later themes in Sanger\u27s rhetoric shifts from speaking about women as subject with control of their bodies to objects whose bodies must be controlled. Employing capitalistic themes, Sanger argues that women\u27s rate of reproduction must be controlled to safeguard national security. Using notions of social evolution, Sanger engages in eugenic discourse to demand the control of women\u27s bodies who produce unfit offspring. The sweep of Sanger\u27s rhetoric proves the utility of genealogical interpretation to understand the dynamics of power and discourse that conform feminist speakers to accepted gender definitions

Particle-kernel estimation of the filter density in state-space models

Sequential Monte Carlo (SMC) methods, also known as particle filters, are simulation-based recursive algorithms for the approximation of the a posteriori probability measures generated by state-space dynamical models. At any given time $t$, a SMC method produces a set of samples over the state space of the system of interest (often termed "particles") that is used to build a discrete and random approximation of the posterior probability distribution of the state variables, conditional on a sequence of available observations. One potential application of the methodology is the estimation of the densities associated to the sequence of a posteriori distributions. While practitioners have rather freely applied such density approximations in the past, the issue has received less attention from a theoretical perspective. In this paper, we address the problem of constructing kernel-based estimates of the posterior probability density function and its derivatives, and obtain asymptotic convergence results for the estimation errors. In particular, we find convergence rates for the approximation errors that hold uniformly on the state space and guarantee that the error vanishes almost surely as the number of particles in the filter grows. Based on this uniform convergence result, we first show how to build continuous measures that converge almost surely (with known rate) toward the posterior measure and then address a few applications. The latter include maximum a posteriori estimation of the system state using the approximate derivatives of the posterior density and the approximation of functionals of it, for example, Shannon's entropy. This manuscript is identical to the published paper, including a gap in the proof of Theorem 4.2. The Theorem itself is correct. We provide an {\em erratum} at the end of this document with a complete proof and a brief discussion.Comment: IMPORTANT: This manuscript is identical to the published paper, including a gap in the proof of Theorem 4.2. The Theorem itself is correct. We provide an erratum at the end of this document. Published at http://dx.doi.org/10.3150/13-BEJ545 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

Biocultural Restoration in Hawaiʻi

Biocultural restoration is a process by which the various connections between humanity and nature, as well as between People and Place are revived to restore the health and function of social-ecological systems. This collection explores the subject of biocultural restoration and does so within the context of Hawaiʻi, the most remote archipelago on the planet. The Hawaiian Renaissance, which started in the 1970s, has led to a revival of Hawaiian language, practices, philosophy, spirituality, knowledge systems, and systems of resource management. Many of the leading Indigenous and local scholars of Hawaiʻi who were born into the time of the Hawaiian Renaissance contributed to this collection. More than a third of the authors are of Indigenous Hawaiian ancestry; each paper had at least one Indigenous Hawaiian author, and several papers had a Hawaiian lead author, making this the largest collection to date of scientific publications authored by Indigenous Hawaiians (Kānaka ʻŌiwi). In addition, the majority of authors are women, and two of the papers had 100 percent authorship by women. This collection represents a new emphasis in applied participatory research that involves academics, government agencies, communities and both private and non-profit sectors