Screening recurrence and lymph node metastases in head and neck cancer: the role of computer tomography in follow-up

Introduction Follow-up of patients with oral cancer is being questioned with regard to financial costs and effectiveness. Therefore, the aim of the present study was to evaluate whether local recurrence and cervical lymph node metastases were first discovered clinically or by routine computer tomography. Materials and methods The records of all 317 patients that were treated for an oral cancer between 1998 and 2008 were systematically reviewed. Criteria for inclusion were tumor histology with a squamous cell carcinoma of the head and neck, and regular follow-up examinations with a minimum follow-up time of 12 months, including clinical and radiological (CT) controls. All patients had the first CT after 6 months, followed by yearly CT controls. Results Out of 315 patients with an oral squamous cell carcinoma, 294 were evaluated. Those experiencing neither recurrence of the tumor nor lymph node metastases constituted 62%. Local recurrence was seen in 36 (12%), lymph node metastases in 32 (11%), and both in 16 (6%). Of the 32 patients with lymph node metastases, 25 were recognized first clinically, and 7 were detected by routine CT scans; concerning local recurrence, 32 appeared clinically, and 4 were detected by routine CT scans. Conclusion Routine CT for follow-up is still indicated for detecting lymph node metastases as well as local recurrence

The Index-Based Subgraph Matching Algorithm (ISMA): Fast Subgraph Enumeration in Large Networks Using Optimized Search Trees

Subgraph matching algorithms are designed to find all instances of predefined subgraphs in a large graph or network and play an important role in the discovery and analysis of so-called network motifs, subgraph patterns which occur more often than expected by chance. We present the index-based subgraph matching algorithm (ISMA), a novel tree-based algorithm. ISMA realizes a speedup compared to existing algorithms by carefully selecting the order in which the nodes of a query subgraph are investigated. In order to achieve this, we developed a number of data structures and maximally exploited symmetry characteristics of the subgraph. We compared ISMA to a naive recursive tree-based algorithm and to a number of well-known subgraph matching algorithms. Our algorithm outperforms the other algorithms, especially on large networks and with large query subgraphs. An implementation of ISMA in Java is freely available at http://sourceforge.net/projects/isma

OrChem - An open source chemistry search engine for Oracle®

<p>Abstract</p> <p>Background</p> <p>Registration, indexing and searching of chemical structures in relational databases is one of the core areas of cheminformatics. However, little detail has been published on the inner workings of search engines and their development has been mostly closed-source. We decided to develop an open source chemistry extension for Oracle, the de facto database platform in the commercial world.</p> <p>Results</p> <p>Here we present OrChem, an extension for the Oracle 11G database that adds registration and indexing of chemical structures to support fast substructure and similarity searching. The cheminformatics functionality is provided by the Chemistry Development Kit. OrChem provides similarity searching with response times in the order of seconds for databases with millions of compounds, depending on a given similarity cut-off. For substructure searching, it can make use of multiple processor cores on today's powerful database servers to provide fast response times in equally large data sets.</p> <p>Availability</p> <p>OrChem is free software and can be redistributed and/or modified under the terms of the GNU Lesser General Public License as published by the Free Software Foundation. All software is available via <url>http://orchem.sourceforge.net</url>.</p

Roadmaps to Utopia: Tales of the Smart City

Notions of the Smart City are pervasive in urban development discourses. Various frameworks for the development of smart cities, often conceptualized as roadmaps, make a number of implicit claims about how smart city projects proceed but the legitimacy of those claims is unclear. This paper begins to address this gap in knowledge. We explore the development of a smart transport application, MotionMap, in the context of a £16M smart city programme taking place in Milton Keynes, UK. We examine how the idealized smart city narrative was locally inflected, and discuss the differences between the narrative and the processes and outcomes observed in Milton Keynes. The research shows that the vision of data-driven efficiency outlined in the roadmaps is not universally compelling, and that different approaches to the sensing and optimization of urban flows have potential for empowering or disempowering different actors. Roadmaps tend to emphasize the importance of delivering quick practical results. However, the benefits observed in Milton Keynes did not come from quick technical fixes but from a smart city narrative that reinforced existing city branding, mobilizing a growing network of actors towards the development of a smart region. Further research is needed to investigate this and other smart city developments, the significance of different smart city narratives, and how power relationships are reinforced and constructed through them

The Enactment of Professional Learning Policies: Performativity and Multiple Ontologies

While teacher learning has become a locus of school reform across many international settings, there is relatively little examination of the idiosyncratic ways in which policy discourses on teacher learning are enacted in schools. In this paper, we aim to investigate how these policy discourses are translated and configured into practices and thus, enacted into concrete realities. Using the conceptual notion of multiple ontologies proposed by Mol (1999; 2004), we argue that teacher learning is actualized in a multiplicity of socio-material entanglements, not as a single reality, but as a multiplicity of realities that coexist, simultaneously, in the mesh of assemblages that we call “school”. In this study, we describe and trace how particular socio-material configurations of teacher learning produce concrete realities of practice that mobilize and generate specific networked effects. We conclude that the postulation of multiple ontologies of teacher learning prompts a shift in how policy makers could conceive of and develop strategies aimed at transforming teaching practices

Dopamine neuronal loss contributes to memory and reward dysfunction in a model of Alzheimer's disease

Alterations of the dopaminergic (DAergic) system are frequently reported in Alzheimer's disease (AD) patients and are commonly linked to cognitive and non-cognitive symptoms. However, the cause of DAergic system dysfunction in AD remains to be elucidated. We investigated alterations of the midbrain DAergic system in the Tg2576 mouse model of AD, overexpressing a mutated human amyloid precursor protein (APPswe). Here, we found an age-dependent DAergic neuron loss in the ventral tegmental area (VTA) at pre-plaque stages, although substantia nigra pars compacta (SNpc) DAergic neurons were intact. The selective VTA DAergic neuron degeneration results in lower DA outflow in the hippocampus and nucleus accumbens (NAc) shell. The progression of DAergic cell death correlates with impairments in CA1 synaptic plasticity, memory performance and food reward processing. We conclude that in this mouse model of AD, degeneration of VTA DAergic neurons at pre-plaque stages contributes to memory deficits and dysfunction of reward processing

Automatic mapping of atoms across both simple and complex chemical reactions

Mapping atoms across chemical reactions is important for substructure searches, automatic extraction of reaction rules, identification of metabolic pathways, and more. Unfortunately, the existing mapping algorithms can deal adequately only with relatively simple reactions but not those in which expert chemists would benefit from computer&apos;s help. Here we report how a combination of algorithmics and expert chemical knowledge significantly improves the performance of atom mapping, allowing the machine to deal with even the most mechanistically complex chemical and biochemical transformations. The key feature of our approach is the use of few but judiciously chosen reaction templates that are used to generate plausible &quot;intermediate&quot; atom assignments which then guide a graph-theoretical algorithm towards the chemically correct isomorphic mappings. The algorithm performs significantly better than the available state-of-the-art reaction mappers, suggesting its uses in database curation, mechanism assignments, and - above all - machine extraction of reaction rules underlying modern synthesis-planning programs

Citokininek, a növényi in vitro fejlődés kulcsregulátorai

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