152 research outputs found

    A systematic review of strategies to recruit and retain primary care doctors

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    Background There is a workforce crisis in primary care. Previous research has looked at the reasons underlying recruitment and retention problems, but little research has looked at what works to improve recruitment and retention. The aim of this systematic review is to evaluate interventions and strategies used to recruit and retain primary care doctors internationally. Methods A systematic review was undertaken. MEDLINE, EMBASE, CENTRAL and grey literature were searched from inception to January 2015.Articles assessing interventions aimed at recruiting or retaining doctors in high income countries, applicable to primary care doctors were included. No restrictions on language or year of publication. The first author screened all titles and abstracts and a second author screened 20%. Data extraction was carried out by one author and checked by a second. Meta-analysis was not possible due to heterogeneity. Results 51 studies assessing 42 interventions were retrieved. Interventions were categorised into thirteen groups: financial incentives (n=11), recruiting rural students (n=6), international recruitment (n=4), rural or primary care focused undergraduate placements (n=3), rural or underserved postgraduate training (n=3), well-being or peer support initiatives (n=3), marketing (n=2), mixed interventions (n=5), support for professional development or research (n=5), retainer schemes (n=4), re-entry schemes (n=1), specialised recruiters or case managers (n=2) and delayed partnerships (n=2). Studies were of low methodological quality with no RCTs and only 15 studies with a comparison group. Weak evidence supported the use of postgraduate placements in underserved areas, undergraduate rural placements and recruiting students to medical school from rural areas. There was mixed evidence about financial incentives. A marketing campaign was associated with lower recruitment. Conclusions This is the first systematic review of interventions to improve recruitment and retention of primary care doctors. Although the evidence base for recruiting and care doctors is weak and more high quality research is needed, this review found evidence to support undergraduate and postgraduate placements in underserved areas, and selective recruitment of medical students. Other initiatives covered may have potential to improve recruitment and retention of primary care practitioners, but their effectiveness has not been established

    Automated Three-Dimensional Detection and Shape Classification of Dendritic Spines from Fluorescence Microscopy Images

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    A fundamental challenge in understanding how dendritic spine morphology controls learning and memory has been quantifying three-dimensional (3D) spine shapes with sufficient precision to distinguish morphologic types, and sufficient throughput for robust statistical analysis. The necessity to analyze large volumetric data sets accurately, efficiently, and in true 3D has been a major bottleneck in deriving reliable relationships between altered neuronal function and changes in spine morphology. We introduce a novel system for automated detection, shape analysis and classification of dendritic spines from laser scanning microscopy (LSM) images that directly addresses these limitations. The system is more accurate, and at least an order of magnitude faster, than existing technologies. By operating fully in 3D the algorithm resolves spines that are undetectable with standard two-dimensional (2D) tools. Adaptive local thresholding, voxel clustering and Rayburst Sampling generate a profile of diameter estimates used to classify spines into morphologic types, while minimizing optical smear and quantization artifacts. The technique opens new horizons on the objective evaluation of spine changes with synaptic plasticity, normal development and aging, and with neurodegenerative disorders that impair cognitive function

    Image informatics strategies for deciphering neuronal network connectivity

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    Brain function relies on an intricate network of highly dynamic neuronal connections that rewires dramatically under the impulse of various external cues and pathological conditions. Among the neuronal structures that show morphologi- cal plasticity are neurites, synapses, dendritic spines and even nuclei. This structural remodelling is directly connected with functional changes such as intercellular com- munication and the associated calcium-bursting behaviour. In vitro cultured neu- ronal networks are valuable models for studying these morpho-functional changes. Owing to the automation and standardisation of both image acquisition and image analysis, it has become possible to extract statistically relevant readout from such networks. Here, we focus on the current state-of-the-art in image informatics that enables quantitative microscopic interrogation of neuronal networks. We describe the major correlates of neuronal connectivity and present workflows for analysing them. Finally, we provide an outlook on the challenges that remain to be addressed, and discuss how imaging algorithms can be extended beyond in vitro imaging studies

    Automated Reconstruction of Neuronal Morphology Based on Local Geometrical and Global Structural Models

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    Digital reconstruction of neurons from microscope images is an important and challenging problem in neuroscience. In this paper, we propose a model-based method to tackle this problem. We first formulate a model structure, then develop an algorithm for computing it by carefully taking into account morphological characteristics of neurons, as well as the image properties under typical imaging protocols. The method has been tested on the data sets used in the DIADEM competition and produced promising results for four out of the five data sets

    The N-glycome of human embryonic stem cells

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    <p>Abstract</p> <p>Background</p> <p>Complex carbohydrate structures, glycans, are essential components of glycoproteins, glycolipids, and proteoglycans. While individual glycan structures including the SSEA and Tra antigens are already used to define undifferentiated human embryonic stem cells (hESC), the whole spectrum of stem cell glycans has remained unknown. We undertook a global study of the asparagine-linked glycoprotein glycans (N-glycans) of hESC and their differentiated progeny using MALDI-TOF mass spectrometric and NMR spectroscopic profiling. Structural analyses were performed by specific glycosidase enzymes and mass spectrometric fragmentation analyses.</p> <p>Results</p> <p>The data demonstrated that hESC have a characteristic N-glycome which consists of both a constant part and a variable part that changes during hESC differentiation. hESC-associated N-glycans were downregulated and new structures emerged in the differentiated cells. Previously mouse embryonic stem cells have been associated with complex fucosylation by use of SSEA-1 antibody. In the present study we found that complex fucosylation was the most characteristic glycosylation feature also in undifferentiated hESC. The most abundant complex fucosylated structures were Le<sup>x </sup>and H type 2 antennae in sialylated complex-type N-glycans.</p> <p>Conclusion</p> <p>The N-glycan phenotype of hESC was shown to reflect their differentiation stage. During differentiation, hESC-associated N-glycan features were replaced by differentiated cell-associated structures. The results indicated that hESC differentiation stage can be determined by direct analysis of the N-glycan profile. These results provide the first overview of the N-glycan profile of hESC and form the basis for future strategies to target stem cell glycans.</p

    Self-organization of developing embryo using scale-invariant approach

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    <p>Abstract</p> <p>Background</p> <p>Self-organization is a fundamental feature of living organisms at all hierarchical levels from molecule to organ. It has also been documented in developing embryos.</p> <p>Methods</p> <p>In this study, a scale-invariant power law (SIPL) method has been used to study self-organization in developing embryos. The SIPL coefficient was calculated using a centro-axial skew symmetrical matrix (CSSM) generated by entering the components of the Cartesian coordinates; for each component, one CSSM was generated. A basic square matrix (BSM) was constructed and the determinant was calculated in order to estimate the SIPL coefficient. This was applied to developing <it>C. elegans </it>during early stages of embryogenesis. The power law property of the method was evaluated using the straight line and Koch curve and the results were consistent with fractal dimensions (fd). Diffusion-limited aggregation (DLA) was used to validate the SIPL method.</p> <p>Results and conclusion</p> <p>The fractal dimensions of both the straight line and Koch curve showed consistency with the SIPL coefficients, which indicated the power law behavior of the SIPL method. The results showed that the ABp sublineage had a higher SIPL coefficient than EMS, indicating that ABp is more organized than EMS. The fd determined using DLA was higher in ABp than in EMS and its value was consistent with type 1 cluster formation, while that in EMS was consistent with type 2.</p

    Plant lectins: the ties that bind in root symbiosis and plant defense

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    Lectins are a diverse group of carbohydrate-binding proteins that are found within and associated with organisms from all kingdoms of life. Several different classes of plant lectins serve a diverse array of functions. The most prominent of these include participation in plant defense against predators and pathogens and involvement in symbiotic interactions between host plants and symbiotic microbes, including mycorrhizal fungi and nitrogen-fixing rhizobia. Extensive biological, biochemical, and molecular studies have shed light on the functions of plant lectins, and a plethora of uncharacterized lectin genes are being revealed at the genomic scale, suggesting unexplored and novel diversity in plant lectin structure and function. Integration of the results from these different types of research is beginning to yield a more detailed understanding of the function of lectins in symbiosis, defense, and plant biology in general
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