14,635 research outputs found

    Improving technology transfer through national systems of innovation: climate relevant innovation-system builders (CRIBs)

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    The Technology Executive Committee (TEC) of the United Nations Framework Convention on Climate Change (UNFCCC) recently convened a workshop seeking to understand how strengthening national systems of innovation (NSIs) might help to foster the transfer of climate technologies to developing countries. This article reviews insights from the literatures on Innovation Studies and Socio-Technical Transitions to demonstrate why this focus on fostering innovation systems has potential to be more transformative as an international policy mechanism for climate technology transfer than anything the UNFCCC has considered to date. Based on insights from empirical research, the article also articulates how the existing architecture of the UNFCCC Technology Mechanism could be usefully extended by supporting the establishment of CRIBs (climate relevant innovation-system builders) in developing countries – key institutions focused on nurturing the climate-relevant innovation systems and building technological capabilities that form the bedrock of transformative, climate-compatible technological change and development

    Mathematical modelling plant signalling networks

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    During the last two decades, molecular genetic studies and the completion of the sequencing of the Arabidopsis thaliana genome have increased knowledge of hormonal regulation in plants. These signal transduction pathways act in concert through gene regulatory and signalling networks whose main components have begun to be elucidated. Our understanding of the resulting cellular processes is hindered by the complex, and sometimes counter-intuitive, dynamics of the networks, which may be interconnected through feedback controls and cross-regulation. Mathematical modelling provides a valuable tool to investigate such dynamics and to perform in silico experiments that may not be easily carried out in a laboratory. In this article, we firstly review general methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This sub-cellular analysis paves the way for more comprehensive mathematical studies of hormonal transport and signalling in a multi-scale setting

    Oscillatory dynamics in a model of vascular tumour growth -- implications for chemotherapy

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    Background\ud \ud Investigations of solid tumours suggest that vessel occlusion may occur when increased pressure from the tumour mass is exerted on the vessel walls. Since immature vessels are frequently found in tumours and may be particularly sensitive, such occlusion may impair tumour blood flow and have a negative impact on therapeutic outcome. In order to study the effects that occlusion may have on tumour growth patterns and therapeutic response, in this paper we develop and investigate a continuum model of vascular tumour growth.\ud Results\ud \ud By analysing a spatially uniform submodel, we identify regions of parameter space in which the combination of tumour cell proliferation and vessel occlusion give rise to sustained temporal oscillations in the tumour cell population and in the vessel density. Alternatively, if the vessels are assumed to be less prone to collapse, stable steady state solutions are observed. When spatial effects are considered, the pattern of tumour invasion depends on the dynamics of the spatially uniform submodel. If the submodel predicts a stable steady state, then steady travelling waves are observed in the full model, and the system evolves to the same stable steady state behind the invading front. When the submodel yields oscillatory behaviour, the full model produces periodic travelling waves. The stability of the waves (which can be predicted by approximating the system as one of λ-ω type) dictates whether the waves develop into regular or irregular spatio-temporal oscillations. Simulations of chemotherapy reveal that treatment outcome depends crucially on the underlying tumour growth dynamics. In particular, if the dynamics are oscillatory, then therapeutic efficacy is difficult to assess since the fluctuations in the size of the tumour cell population are enhanced, compared to untreated controls.\ud Conclusions\ud \ud We have developed a mathematical model of vascular tumour growth formulated as a system of partial differential equations (PDEs). Employing a combination of numerical and analytical techniques, we demonstrate how the spatio-temporal dynamics of the untreated tumour may influence its response to chemotherapy.\ud Reviewers\ud \ud This manuscript was reviewed by Professor Zvia Agur and Professor Marek Kimmel

    Modelling the response of vascular tumours to chemotherapy: A multiscale approach

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    An existing multiscale model is extended to study the response of a vascularised tumour to treatment with chemotherapeutic drugs which target proliferating cells. The underlying hybrid cellular automaton model couples tissue-level processes (e.g. blood flow, vascular adaptation, oxygen and drug transport) with cellular and subcellular phenomena (e.g. competition for space, progress through the cell cycle, natural cell death and drug-induced cell kill and the expression of angiogenic factors). New simulations suggest that, in the absence of therapy, vascular adaptation induced by angiogenic factors can stimulate spatio-temporal oscillations in the tumour's composition.\ud \ud Numerical simulations are presented and show that, depending on the choice of model parameters, when a drug which kills proliferating cells is continuously infused through the vasculature, three cases may arise: the tumour is eliminated by the drug; the tumour continues to expand into the normal tissue; or, the tumour undergoes spatio-temporal oscillations, with regions of high vascular and tumour cell density alternating with regions of low vascular and tumour cell density. The implications of these results and possible directions for future research are also discussed

    The interplay between tissue growth and scaffold degradation in engineered tissue constructs

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    In vitro tissue engineering is emerging as a potential tool to meet the high demand for replacement tissue, caused by the increased incidence of tissue degeneration and damage. A key challenge in this field is ensuring that the mechanical properties of the engineered tissue are appropriate for the in vivo environment. Achieving this goal will require detailed understanding of the interplay between cell proliferation, extracellular matrix (ECM) deposition and scaffold degradation.\ud \ud In this paper, we use a mathematical model (based upon a multiphase continuum framework) to investigate the interplay between tissue growth and scaffold degradation during tissue construct evolution in vitro. Our model accommodates a cell population and culture medium, modelled as viscous fluids, together with a porous scaffold and ECM deposited by the cells, represented as rigid porous materials. We focus on tissue growth within a perfusion bioreactor system, and investigate how the predicted tissue composition is altered under the influence of (i) differential interactions between cells and the supporting scaffold and their associated ECM, (ii) scaffold degradation, and (iii) mechanotransduction-regulated cell proliferation and ECM deposition.\ud \ud Numerical simulation of the model equations reveals that scaffold heterogeneity typical of that obtained from ÎĽCT scans of tissue engineering scaffolds can lead to significant variation in the flow-induced mechanical stimuli experienced by cells seeded in the scaffold. This leads to strong heterogeneity in the deposition of ECM. Furthermore, preferential adherence of cells to the ECM in favour of the artificial scaffold appears to have no significant influence on the eventual construct composition; adherence of cells to these supporting structures does, however, lead to cell and ECM distributions which mimic and exaggerate the heterogeneity of the underlying scaffold. Such phenomena have important ramifications for the mechanical integrity of engineered tissue constructs and their suitability for implantation in vivo

    ASYMMETRIC LEAVES1 reveals knox gene redundancy in Arabidopsis

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    The shoot apical meristem comprises undifferentiated stem cells and their derivatives, which include founder cells for lateral organs such as leaves. Meristem maintenance and lateral organ specification are regulated in part by negative interactions between the myb domain transcription factor ASYMMETRIC LEAVES1, which is expressed in lateral organ primordia, and homeobox transcription factors which are expressed in the shoot apical meristem (knox genes). The knox gene SHOOT MERISTEMLESS (STAT) negatively regulates ASYMMETRIC LEAVES1 (AS1) which, in turn, negatively, regulates other knox genes including KNAT1 and KNAT2, and positively regulates the novel gene LATERAL ORGAN BOUNDARIES (LOB). Genetic interactions with a second gene, ASYMMETRIC LEAVES2 (AS2), indicate it acts at the same position in this hierarchy as AS1. We have used a second-site suppressor screen to isolate mutations in KNAT1 and we show that KNAT1 is partially redundant with STM in regulating stem cell function. Mutations in KNAT2 show no such interaction. We discuss the regulation and evolution of redundancy among knox genes

    Inference of the genetic network regulating lateral root initiation in Arabidopsis thaliana

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    Regulation of gene expression is crucial for organism growth, and it is one of the challenges in Systems Biology to reconstruct the underlying regulatory biological networks from transcriptomic data. The formation of lateral roots in Arabidopsis thaliana is stimulated by a cascade of regulators of which only the interactions of its initial elements have been identified. Using simulated gene expression data with known network topology, we compare the performance of inference algorithms, based on different approaches, for which ready-to-use software is available. We show that their performance improves with the network size and the inclusion of mutants. We then analyse two sets of genes, whose activity is likely to be relevant to lateral root initiation in Arabidopsis, by integrating sequence analysis with the intersection of the results of the best performing methods on time series and mutants to infer their regulatory network. The methods applied capture known interactions between genes that are candidate regulators at early stages of development. The network inferred from genes significantly expressed during lateral root formation exhibits distinct scale-free, small world and hierarchical properties and the nodes with a high out-degree may warrant further investigation

    The FHD/ε\boldsymbol{\varepsilon}ppsilon Epoch of Reionization Power Spectrum Pipeline

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    Epoch of Reionization data analysis requires unprecedented levels of accuracy in radio interferometer pipelines. We have developed an imaging power spectrum analysis to meet these requirements and generate robust 21 cm EoR measurements. In this work, we build a signal path framework to mathematically describe each step in the analysis, from data reduction in the FHD package to power spectrum generation in the ε\varepsilonppsilon package. In particular, we focus on the distinguishing characteristics of FHD/ε\varepsilonppsilon: highly accurate spectral calibration, extensive data verification products, and end-to-end error propagation. We present our key data analysis products in detail to facilitate understanding of the prominent systematics in image-based power spectrum analyses. As a verification to our analysis, we also highlight a full-pipeline analysis simulation to demonstrate signal preservation and lack of signal loss. This careful treatment ensures that the FHD/ε\varepsilonppsilon power spectrum pipeline can reduce radio interferometric data to produce credible 21 cm EoR measurements.Comment: 21 pages, 10 figures, accepted by PAS

    Comparison of two experiments on radiative neutron decay

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    Over 10 years ago we proposed an experiment on measuring the characteristics of radiative neutron decay in papers [1, 2]. At the same time we had published the theoretical spectrum of radiative gamma quanta, calculated within the framework of the electroweak interactions, on the basis of which we proposed the methodology for the future experiment [3,4]. However, because we were denied beam time on the intensive cold neutron beam at ILL (Grenoble, France) for a number of years, we could only conduct the experiment in 2005 on the newly opened FRMII reactor of Technical University of Muenchen. The main result of this experiment was the discovery of radiative neutron decay and the measurement of its relative intensity B.R.= (3.2+-1.6)10-3 with C.L.=99.7% for radiative gamma quanta with energy over 35 kev [5,6]. Over a year after our first announcement about the results of the conducted experiment, "Nature" [7] published a letter asserting that its authors have also measured the branching ratio of radiative neutron decay B.R.= (3.13+-0.34)10-3 with C.L.=68% and gamma quanta energy from 15 to 340 kev. This article aims to compare these two experiments. It is shown that the use of strong magnetic fields in the NIST (Washington, USA) experiment methodology not only prevents any exact measurement of the branching ratio and identification of radiative neutron decay events, but also makes registration of ordinary neutron decay events impossible.Comment: contribution on conference ISINN-1
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