Contact area, pressure distribution and mechanical stability in external arthrodesis of the ankle joint

The ankle joint is often affected by arthritis, giving a joint that is painful, stiff, and restricts movement. This can result in a huge loss of mobility for the sufferer. Unlike replacement of the hip, the replacement of a diseased ankle joint is not as straightforward and the outcomes do not reach the same success levels. The preferred surgical choice is arthrodesis, a procedure whereby the two bones forming the joint are fused together to eliminate the joint and hence pain. The success of the procedure is dependent upon several factors, two of the most significant being the levels of contact area and pressure achieved during the compression period, during which bone growth occurs across the two bones being compressed together. These factors influence joint stability and micromotion at the bone to bone interface during this growth phase. This study investigates the levels of contact areas and pressures that can be achieved for different arthodesis variables. These variables include the joint shape, which can be curved or flat, and the position of the compression pin within the talus, namely anteriorly or centrally positioned with reference to the talar dome. Influence of the Achilles tendon in joint stability is also investigated. A test rig was developed allowing load/deflection curves to be determined for various configurations of these variables. Models representing the bones under consideration, together with pressure sensitive film, allowed measurement of contact areas and pressures within the joint under compression, achieved using pins and instrumented compression rods. Results indicate there is little significant variation in contact area and pressure for the different shaped joint cuts, however, if the talar pin is placed in a more anterior position then the contact area can be improved over a centrally positioned pin. Anterior pin placement also gives increased resistance to motion and mechanical stability. It has been established that the athrodesis construct is especially weak in terms of rotation about the tibial axis, and the results from this study indicate that through the use of a curved joint shape the resistance to this motion can be improved greatly

Projector - a partially typed language for querying XML

We describe Projector, a language that can be used to perform a mixture of typed and untyped computation against data represented in XML. For some problems, notably when the data is unstructured or semistructured, the most desirable programming model is against the tree structure underlying the document. When this tree structure has been used to model regular data structures, then these regular structures themselves are a more desirable programming model. The language Projector, described here in outline, gives both models within a single partially typed algebra and is well suited for hybrid applications, for example when fragments of a known structure are embedded in a document whose overall structure is unknown. Projector is an extension of ECMA-262 (aka JavaScript), and therefore inherits an untyped DOM interface. To this has been added some static typing and a dynamic projection primitive, which can be used to assert the presence of a regular structure modelled within the XML. If this structure does exist, the data is extracted and presented as a typed value within the programming language

A Clinical Guideline Driven Automated Linear Feature Extraction for Vestibular Schwannoma

Vestibular Schwannoma is a benign brain tumour that grows from one of the balance nerves. Patients may be treated by surgery, radiosurgery or with a conservative "wait-and-scan" strategy. Clinicians typically use manually extracted linear measurements to aid clinical decision making. This work aims to automate and improve this process by using deep learning based segmentation to extract relevant clinical features through computational algorithms. To the best of our knowledge, our study is the first to propose an automated approach to replicate local clinical guidelines. Our deep learning based segmentation provided Dice-scores of 0.8124 +- 0.2343 and 0.8969 +- 0.0521 for extrameatal and whole tumour regions respectively for T2 weighted MRI, whereas 0.8222 +- 0.2108 and 0.9049 +- 0.0646 were obtained for T1 weighted MRI. We propose a novel algorithm to choose and extract the most appropriate maximum linear measurement from the segmented regions based on the size of the extrameatal portion of the tumour. Using this tool, clinicians will be provided with a visual guide and related metrics relating to tumour progression that will function as a clinical decision aid. In this study, we utilize 187 scans obtained from 50 patients referred to a tertiary specialist neurosurgical service in the United Kingdom. The measurements extracted manually by an expert neuroradiologist indicated a significant correlation with the automated measurements (p < 0.0001).Comment: SPIE Medical Imagin

Semantically Linking In Silico Cancer Models

Multiscale models are commonplace in cancer modeling, where individual models acting on different biological scales are combined within a single, cohesive modeling framework. However, model composition gives rise to challenges in understanding interfaces and interactions between them. Based on specific domain expertise, typically these computational models are developed by separate research groups using different methodologies, programming languages, and parameters. This paper introduces a graph-based model for semantically linking computational cancer models via domain graphs that can help us better understand and explore combinations of models spanning multiple biological scales. We take the data model encoded by TumorML, an XML-based markup language for storing cancer models in online repositories, and transpose its model description elements into a graph-based representation. By taking such an approach, we can link domain models, such as controlled vocabularies, taxonomic schemes, and ontologies, with cancer model descriptions to better understand and explore relationships between models. The union of these graphs creates a connected property graph that links cancer models by categorizations, by computational compatibility, and by semantic interoperability, yielding a framework in which opportunities for exploration and discovery of combinations of models become possible

Extraction of Protein from Four Different Seaweeds Using Three Different Physical Pre-Treatment Strategies

peer-reviewedSeaweeds are a rich source of protein and can contain up to 47% on the dry weight basis. It is challenging to extract proteins from the raw biomass of seaweed due to resilient cell-wall complexes. Four species of macroalgae were used in this study-two brown, Fucus vesiculosus and Alaria esculenta, and two red, Palmaria palmata and Chondrus crispus. Three treatments were applied individually to the macroalgal species: (I) high-pressure processing (HPP); (II) laboratory autoclave processing and (III) a classical sonication and salting out method. The protein, ash and lipid contents of the resulting extracts were estimated. Yields of protein recovered ranged from 3.2% for Fucus vesiculosus pre-treated with high pressure processing to 28.9% protein recovered for Chondrus crispus treated with the classical method. The yields of protein recovered using the classical, HPP and autoclave pre-treatments applied to Fucus vesiculosus were 35.1, 23.7% and 24.3%, respectively; yields from Alaria esculenta were 18.2%, 15.0% and 17.1% respectively; yields from Palmaria palmata were 12.5%, 14.9% and 21.5% respectively, and finally, yields from Chondrus crispus were 35.2%, 16.1% and 21.9%, respectively. These results demonstrate that while macroalgal proteins may be extracted using either physical or enzymatic methods, the specific extraction procedure should be tailored to individual species

From Anopheles to Spatial Surveillance: A Roadmap Through a Multidisciplinary Challenge

When working on vector borne diseases, decision makers and researchers often face a lack of specific high quality data. However the results/decisions can be critical as they can impact on the lives of many people. This chapter reviews the challenges posed by spatial surveillance of anopheles-borne diseases with particular attention for malaria surveillance. These challenges will mainly reside in the difficulty of getting the appropriate raw data and the large spectrum of multidisciplinary expertise. Raw data include anopheles attributes. Design of sampling strategies is a compromise between the best sampling size for analysis, optimal sampling in space or time and cost-related factors. On the other hand, raw environmental factors from remote sensing products are increasingly available and used but ready to use information on temperature mainly available in Africa and resolution too coarse for detection of water bodies. Moreover the quality and interpretation of final product is dependent of image pre-processing which should be understood by the final user. Those include production of the pixels which do not totally represent environmental value at location, compositing which summarize several images into one to eliminate clouds contamination and production of land cover which represent environmental value at the time of original images capture, develop mosaic classes to gather pixel difficult to discriminate and propose land cover classes not always adapted to the anopheles species habitat. Remote sensing however provides a unique source of information which would not be available otherwise. Modelling techniques are then discussed as well as initiatives to help transfer results and expertise to health professionals in countries.JRC.H.4-Monitoring Agricultural Resource