An experiential approach to developing teachers’ understanding of service-learning

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Architecture, constraints, and behavior

This paper aims to bridge progress in neuroscience involving sophisticated quantitative analysis of behavior, including the use of robust control, with other relevant conceptual and theoretical frameworks from systems engineering, systems biology, and mathematics. Familiar and accessible case studies are used to illustrate concepts of robustness, organization, and architecture (modularity and protocols) that are central to understanding complex networks. These essential organizational features are hidden during normal function of a system but are fundamental for understanding the nature, design, and function of complex biologic and technologic systems

e3Learning Tools: Showcasing and Test Driving

Using examples from a variety of disciplines - nursing, business, design, engineering, languages, and science - this seminar will demonstrate how the Web can foster interactions with content, instructors, and peers. The Web materials are drawn from more than 100 purpose-built learning objects, utilizing many different web tools and methods like animations, simulations, quizzes, games, and peer critiques. Please refer to http://e3learning.edc.polyu.edu.hk/examples.htm for examples.Josephine Csete has a PhD. In Educational Systems Development and more than 15 years experience in designing, developing and implementing educational innovations as well as teaching others to do so. She has been working at Hong Kong Polytechnic University since 1995 - in a department charged with "improving the quality of teaching and learning" on a campus of over 1,000 full time teaching staff and over 15,000 undergraduate and graduate students. She was the Principal Project Supervisor of the "e3Learning Project" and is now the Section Leader of the newly created "e-Learning Development and Support Section" at the Hong Kong Polytechnic University. She believes the web has the potential to redefine what and how we learn, as well as broaden the definition of "learner".published_or_final_versionCentre for Information Technology in Educaiton, University of Hong Kon

Culture in Reduced Levels of Oxygen Promotes Clonogenic Sympathoadrenal Differentiation by Isolated Neural Crest Stem Cells

Isolated neural crest stem cells (NCSCs) differentiate to autonomic neurons in response to bone morphogenetic protein 2 (BMP2) in clonal cultures, but these neurons do not express sympathoadrenal (SA) lineage markers. Whether this reflects a developmental restriction in NCSCs or simply inappropriate culture conditions was not clear. We tested the growth and differentiation potential of NCSCs at ∼5% O_2, which more closely approximates physiological oxygen levels. Eighty-three percent of p75^+P_0 ^− cells isolated from embryonic day 14.5 sciatic nerve behaved as stem cells under these conditions, suggesting that this is a nearly pure population. Furthermore, addition of BMP2 plus forskolin in decreased oxygen cultures elicited differentiation of thousands of cells expressing tyrosine hydroxylase, dopamine-β-hydroxylase, and the SA lineage marker SA-1 in nearly all colonies. Such cells also synthesized and released dopamine and norepinephrine. These data demonstrate that isolated mammalian NCSCs uniformly possess SA lineage capacity and further suggest that oxygen levels can influence cell fate. Parallel results indicating that reduced oxygen levels can also promote the survival, proliferation, and catecholaminergic differentiation of CNS stem cells (Studer et al., 2000) suggests that neural stem cells may exhibit a conserved response to reduced oxygen levels

Visualizing electromagnetic fields at the nanoscale by single molecule localization.

Coupling of light to the free electrons at metallic surfaces allows the confinement of electric fields to subwavelength dimensions, far below the optical diffraction limit. While this is routinely used to manipulate light at the nanoscale, in electro-optic devices and enhanced spectroscopic techniques, no characterization technique for imaging the underlying nanoscopic electromagnetic fields exists, which does not perturb the field or employ complex electron beam imaging. Here, we demonstrate the direct visualization of electromagnetic fields on patterned metallic substrates at nanometer resolution, exploiting a strong "autonomous" fluorescence-blinking behavior of single molecules within the confined fields allowing their localization. Use of DNA-constructs for precise positioning of fluorescence dyes on the surface induces this distance-dependent autonomous blinking thus completely obviating the need for exogenous agents or switching methods. Mapping such electromagnetic field distributions at nanometer resolution aids the rational design of nanometals for diverse photonic applications.We acknowledge financial support from EPSRC grant EP/G060649/1, EP/H028757/1-2, EP/I012060/1, EP/L015889/1, MRC grant MR/K015850/1 and ERC grant LINASS 320503.This is the author accepted manuscript. The final version is available from ACS at http://pubs.acs.org/doi/abs/10.1021/acs.nanolett.5b00405

Highly optimised global organisation of metabolic networks

Abstract: High-level, mathematically precise descriptions of the global organisation of complex metabolic networks are necessary for understanding the global structure of metabolic networks, the interpretation and integration of large amounts of biologic data (sequences, various -omics) and ultimately for rational design of therapies for disease processes. Metabolic networks are highly organised to execute their function efficiently while tolerating wide variation in their environment. These networks are constrained by physical requirements (e.g. conservation of energy, redox and small moieties) but are also remarkably robust and evolvable. The authors use well-known features of the stoichiometry of bacterial metabolic networks to demonstrate how network architecture facilitates such capabilities, and to develop a minimal abstract metabolism which incorporates the known features of the stoichiometry and respects the constraints on enzymes and reactions. This model shows that the essential functionality and constraints drive the tradeoffs between robustness and fragility, as well as the large-scale structure and organisation of the whole network, particularly high variability. The authors emphasise how domainspecific constraints and tradeoffs imposed by the environment are important factors in shaping stoichiometry. Importantly, the consequence of these highly organised tradeoffs and tolerances is an architecture that has a highly structured modularity that is self-dissimilar and scale-rich. Introduction Metabolic networks, which have been extensively studied for decades, are emblematic of how evolution has sculpted biologic systems for optimal function. In addition to unambiguous functional descriptions of core metabolism, this conserved network has been recently described in detail in terms of its stoichiometry (mass and energy balance). A higher level, mathematically defined description of the global organisation of complex metabolic networks is critical for a deep understanding of metabolism, from the interpretation of huge amounts of biologic data (sequences, various -omics) to design of therapies for disease processes. The stakes are high for obtaining the big picture right: biologic data plugged into a distorted model or interpreted in the context of a flawed universal law propagates misinterpretations. In flux analyses [1], stoichiometry is considered as a constraint, and fluxes are optimised to satisfy a global objective, typically growth. Previous studies, however, have not directly addressed whether the stoichiometry itself is highly optimal or organised in any sense and contributes to the origins and purpose of complexity in biological networks. Yet biochemistry textbooks describe metabolism as having evolved to be 'highly integrated' with the appearance of a 'coherent design' [2]. Here we explore both important 'design' (with no implication of a 'designer') features of metabolism and the sense in which stoichiometry itself has highly organised and optimised tolerances and tradeoffs (HOT) Basic features of metabolic networks Metabolism is essentially a linked series of chemical reactions, which function to synthesise building blocks for usable cellular components and to extract energy and reducing power from the cellular environment, in the context of total organism homeostasis. Constraints on the network are imposed by highly unpredictable intracellular and extracellular environments as well as the details of enzyme molecular structure, the cost of making enzymes and the conservation of atoms, energy and small moieties. The simplest model of metabolic networks is a stoichiometry matrix (s-matrix for short) of chemical reactions with the metabolites in rows and reactions in columns and is defined unambiguously except for permutations of rows # IEE, 200