Mentalizing in mothers and children with type 1 diabetes

Studies suggest that the relationship between psychosocial well-being and type 1 diabetes (T1D) is bidirectional, with T1D typically having a negative influence on psychological functioning, which in turn negatively affects the course of T1D. Here, we investigate the potential role of the capacity for mentalizing, or reflective functioning, in children and their mothers in diabetes control. We tested differences in mentalizing as assessed by the Reflective Functioning Scale in two groups of mother–son dyads with good (GDC) versus poor (PDC) diabetes control. Fifty-five boys (8–12 years old) and their mothers were recruited from the Juvenile Diabetes Foundation in Santiago, Chile. The mothers were interviewed with the Parental Development Interview and the children with the Child Attachment Interview, and both were scored for reflective functioning by using the Reflective Functioning Scale. Self-report measures of stress and diabetes outcomes were completed by the mothers and children, and levels of glycated hemoglobin (HbA1c) were assessed as an index of diabetes control. The results showed that both maternal and child reflective functioning were higher in the GDC than the PDC group and were negatively correlated with HbA1c in the total sample. Our findings suggest an important role for mentalizing in diabetes outcomes, but further prospective research is needed

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

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

Near infrared light emission quenching in organolanthanide complexes

We investigate the quenching of the near infrared light emission in Er3+ complexes induced by the resonant dipolar interaction between the rare-earth ion and high frequency vibrations of the organic ligand. The nonradiative decay rate of the lanthanide ion is discussed in terms of a continuous medium approximation, which depends only on a few, easily accessible spectroscopic and structural data. The model accounts well for the available experimental results in Er3+ complexes, and predicts an similar to 100% light emission quantum yield in fully halogenated systems

Covid-19 vaccine hesitancy in systemic sclerosis

Non

Thermal neutron detection by means of Timepix3

Thermal neutron detection plays a crucial role in numerous scientific and technical applications such as nuclear reactor physics, particle accelerators, radiotherapy,materials analysis and space exploration. There are several challenges associated with the accurate identification and quantification of thermal neutrons. The present work proposes a detailed characterization of a Timepix3 (TPX3) detector equipped with a Lithium Fluoride (6LiF) converter in order to study its response to thermal neutrons that are identified through the 6Li(n,α)3H reaction. The TPX3-based test system has been installed at the HOTNES facility in ENEA and the analysis highlighted its excellent performance showing high effectiveness in the identification of neutrons through morphological analysis of tracks produced by alpha and triton particles, after accurate discrimination from the gamma background. With the use of Monte Carlo simulations, it has been demonstrated that the main contribution is due to tritons and its signal can be used effectively in the identification of thermal neutrons obtaining an efficiency of 0.9 % for 25 meV neutrons. This allows the TPX3 to have important applications as an environmental monitor for thermal neutrons. This monitoring system can be simply realized and is easy to manage because of its compact size and its digital acquisition that allows a real-time analysis

Unsupervised Polygonal Reconstruction of Noisy Contours by a Discrete Irregular Approach

International audienceIn this paper, we present an original algorithm to build a polygonal reconstruction of noisy digital contours. For this purpose, we first improve an algorithm devoted to the vectorization of discrete irregular isothetic objects. Afterwards we propose to use it to define a reconstruction process of noisy digital contours. More precisely, we use a local noise detector, introduced by Kerautret and Lachaud in IWCIA 2009, that builds a multi-scale representation of the digital contour, which is composed of pixels of various size depending of the local amount of noise. Finally, we compare our approach with previous works, by con- sidering the Hausdorff distance and the error on tangent orientations of the computed line segments to the original perfect contour. Thanks to both synthetic and real noisy objects, we show that our approach has interesting performance, and could be applied in document analysis systems

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

Vocational knowledge in motion: rethinking vocational knowledge through vocational teachers' professional development

The paper presents empirical data to consider some of the current debates concerning the nature of vocational knowledge taught in Further Education colleges to students following craft, vocational and occupational courses. The concept of ‘knowledge in motion’ and workplace learning theories are employed as a conceptual framework to examine the continuing professional development (CPD) activities of vocational teachers. This is used to shed light on the ways in which teachers use CPD as a means of accessing and transporting vocational knowledge from occupations to classrooms. Empirical data were gathered through questionnaire, in-depth interviews and participant observation. The findings are presented around five themes: (1) the range of CPD engaged with by vocational teachers; (2) the limitations of propositional, explicit knowledge; (3) engaging with and capturing tacit knowledge; (4) managing the temporality of vocational knowledge; and (5) networking within and to the occupation. Findings suggests that vocational knowledge is distributed and networked and this conceptualisation makes visible some of the ways teachers are able, through CPD activity, to transport vocational knowledge from occupations to classrooms