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University of Edinburgh

Country: United Kingdom

University of Edinburgh

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6,938 Projects, page 1 of 1,388
  • Funder: WT Project Code: 093851
    Funder Contribution: 144,630 GBP
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  • Funder: UKRI Project Code: G1001971
    Funder Contribution: 234,401 GBP

    The human complement system provides defence against infections. It kills bacteria and viruses but in some circumstances can also cause injury to human tissue. Factor H (FH) is an important regulatory protein in the complement system which acts to prevent this injury. People who have certain mutations in their factor H gene may develop a serious kidney disease called atypical haemolytic uraemic syndrome. Other patients develop a rare kidney condition called dense deposit disease. Both sets of individuals have too little of the FH protein or it does not work properly. Many people (about a third of the UK population) have a common variant of the factor H gene that works well for most of their lives but malfunctions, in a poorly understood way, in later life predisposing them to blindness from age-related damage. It may be possible to treat some of these patients by providing more of a fully functional factor H protein. This is not currently possible. I am going to make large quantities of the pure protein using a unique protocol we have developed and will test if it can prevent or treat renal injury in animal models of disease prior to human trials.

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  • Funder: UKRI Project Code: G0802069
    Funder Contribution: 644,630 GBP

    When we breathe, we frequently inhale tiny particles that have potential to injure our lungs, especially bacteria or their components. Remarkably, however, our lungs usually resist this injury and do not develop inflammation, the influx into tissues of white blood cells that are ?licensed to kill? bacteria. This resistance to the induction of inflammation is usually a good thing as white blood cells can be indiscriminate killers, inducing undesirably persistent injury of the healthy lung in various inflammatory lung diseases such as bronchitis. Our work indicates that scavenger cells in the lung are triggered to generate anti-inflammatory, protective responses by a cell surface molecule called ?alpha-v integrin?. The trigger to protective responses is binding to scavenger cell alpha-v integrin of cells undergoing natural cell death or ?apoptosis?. These arise naturally in the lung, but their production is increased by lung injury, pointing to a negative feedback loop in healthy lungs ? inhaled bacteria trigger lung cell death, then binding of dying cells to scavenger cells via alpha-v integrin, and triggering of protective responses. We want to characterise the cellular and molecular mechanisms that constitute this protective system. We hope to uncover new insights into the mechanisms, prevention and treatment of chronic inflammatory lung diseases

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  • Funder: WT Project Code: 083928
    Funder Contribution: 348,877 GBP

    We want to allow non-experts to diagnose skin lesions by taking advantage of the ability of humans to make visual matches even when they are not able to describe the lesions (using words) in a consistent way. In order to attach semantics to images we have to discover the basis of similarity between different lesions such that we can construct a database in which those lesion images that are similar are tagged as similar. If the search space can be structured in this way then it becomes possible for non-experts to search it efficiently, and match an index case with a tagged-reference case. We will acquire images, construct a user interface, and use iterative testing and user interaction coupled with machine vision and machine learning techniques, to order the database. Just as the pattern of hypertext links reflects a webpage s importance, so does the pattern of clicks from one image to another reveal what users consider as similar. The approach is therefore that of computer based i mage retrieval. Our goal is a device that assists non-experts achieve the correct diagnosis suitable for use wherever PCs are available.

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  • Funder: NIH Project Code: 5F32EY013929-02
    Funder Contribution: 40,920 USD
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