Modifying a Geodemographic Classification of the e-Society using public feedback

The e-Society geodemographic classification (Longley et al., 2008) categories neighbourhoods based on their engagement with new information communication technologies. This classification was launched online in 2006, and allowed users to both view and comment on the accuracy of their assigned neighbourhood Type. This paper utilises the user generated feedback on the accuracy of the e-Society classification and through external validation calculates their accuracy. The pilot methodology developed in this paper is scalable and could be repeated for any classification. We believe that this methodology gives the recipients of these classification procedures a voice that their concerns of classification accuracy can be heard

Creating Open Source Geodemographic Classifications for Higher Education Applications

This paper explores the use of geodemographic classifications to investigate the social, economic and spatial dimensions of participation in higher education. Education is a public service that confers very significant and tangible benefits upon receiving individuals: as such, we argue that understanding the geodemography of educational opportunity requires an application-specific classification, that exploits under-used educational data sources. We develop a classification for the UK higher education sector, and apply it to the Gospel Oak area of London. We discuss the wider merits of sector specific applications of geodemographics, with particular reference to issues of public service provision

Collaborative Mapping of London Using Google Maps: The LondonProfiler

This paper begins by reviewing the ways in which the innovation of Google Maps has transformed our ability to reference and view geographically referenced data. We describe the ways in which the GMap Creator tool developed under the ESRC National Centre for E Social Science programme enables users to ‘mashup’ thematic choropleth maps using the Google API. We illustrate the application of GMap Creator using the example of www.londonprofiler.org, which makes it possible to view a range of health, education and other socioeconomic datasets against a backcloth of Google Maps data. Our conclusions address the ways in which Google Map mashups developed using GMap Creator facilitate online exploratory cartographic visualisation in a range of areas of policy concern

Public Domain GIS, Mapping & Imaging Using Web-based Services

In this paper, we outline a series of related applications and a web service designed to enable non-expert users to develop online visualizations which are essentially map-based. In the last five years, public domain GIS (geographic information systems) software for map display and beyond has become available for non-expert users in the public domain, the best examples being the various products from Google such as Google Maps and Google Earth. We have devised various software to enable non-experts to take appropriate map data in standard formats and to transform them so that can be displayed by these software in a one stop action. The first system is called GMapCreator and we show how the software can be used to produce any number of map layers which can be overlaid on Google Maps, can be combined and toggled in combination, and whose transparency can be varied for a myriad of presentation purposes. We then evolve this into a form called ImageCutter which takes any large image and puts this into a Google Map so that the zoom and pan features of the software can be exploited. These software are now available through a site we call MapTube which is a server pointing to various maps created by GMapCreator which is a rudimentary archive of virtual map resources. Finally, we sketch how these software are being moved into 3D using the capabilities of Google Earth and Second Life to display geographic imagery

<i>C-elegans</i> model identifies genetic modifiers of alpha-synuclein inclusion formation during aging

Inclusions in the brain containing alpha-synuclein are the pathological hallmark of Parkinson's disease, but how these inclusions are formed and how this links to disease is poorly understood. We have developed a &lt;i&gt;C-elegans&lt;/i&gt; model that makes it possible to monitor, in living animals, the formation of alpha-synuclein inclusions. In worms of old age, inclusions contain aggregated alpha-synuclein, resembling a critical pathological feature. We used genome-wide RNA interference to identify processes involved in inclusion formation, and identified 80 genes that, when knocked down, resulted in a premature increase in the number of inclusions. Quality control and vesicle-trafficking genes expressed in the ER/Golgi complex and vesicular compartments were overrepresented, indicating a specific role for these processes in alpha-synuclein inclusion formation. Suppressors include aging-associated genes, such as sir-2.1/SIRT1 and lagr-1/LASS2. Altogether, our data suggest a link between alpha-synuclein inclusion formation and cellular aging, likely through an endomembrane-related mechanism. The processes and genes identified here present a framework for further study of the disease mechanism and provide candidate susceptibility genes and drug targets for Parkinson's disease and other alpha-synuclein related disorders

Developing an Individual-level Geodemographic Classification

Geodemographics is a spatially explicit classification of socio-economic data, which can be used to describe and analyse individuals by where they live. Geodemographic information is used by the public sector for planning and resource allocation but it also has considerable use within commercial sector applications. Early geodemographic systems, such as the UK’s ACORN (A Classification of Residential Neighbourhoods), used only area-based census data, but more recent systems have added supplementary layers of information, e.g. credit details and survey data, to provide better discrimination between classes. Although much more data has now become available, geodemographic systems are still fundamentally built from area-based census information. This is partly because privacy laws require release of census data at an aggregate level but mostly because much of the research remains proprietary. Household level classifications do exist but they are often based on regressions between area and household data sets. This paper presents a different approach for creating a geodemographic classification at the individual level using only census data. A generic framework is presented, which classifies data from the UK Census Small Area Microdata and then allocates the resulting clusters to a synthetic population created via microsimulation. The framework is then applied to the creation of an individual-based system for the city of Leeds, demonstrated using data from the 2001 census, and is further validated using individual and household survey data from the British Household Panel Survey

A neighbourhood Output Area Classification from the 2021 and 2022 UK censuses

UK-wide multivariate neighbourhood classifications have been built using small area population data following every census since 1971, and have been built using Output Area geographies since 2001. Policy makers in both the public and private sectors find such taxonomies, typically arranged into hierarchies of Supergroups, Groups and Subgroups, useful across a wide range of applications in business and service planning. Recent and forthcoming releases of small area census statistics pose new methodological challenges. For example, the 2022 Scottish Census was carried out a year after those in other UK nations, and some of the variables now collected across different jurisdictions do not bear direct comparison with one another. Here we develop a methodology to accommodate these issues alongside the more established procedures of variable selection, standardisation, transformation, class definition and labelling

TOM40 Mediates Mitochondrial Dysfunction Induced by α-Synuclein Accumulation in Parkinson's Disease.

Alpha-synuclein (α-Syn) accumulation/aggregation and mitochondrial dysfunction play prominent roles in the pathology of Parkinson's disease. We have previously shown that postmortem human dopaminergic neurons from PD brains accumulate high levels of mitochondrial DNA (mtDNA) deletions. We now addressed the question, whether alterations in a component of the mitochondrial import machinery -TOM40- might contribute to the mitochondrial dysfunction and damage in PD. For this purpose, we studied levels of TOM40, mtDNA deletions, oxidative damage, energy production, and complexes of the respiratory chain in brain homogenates as well as in single neurons, using laser-capture-microdissection in transgenic mice overexpressing human wildtype α-Syn. Additionally, we used lentivirus-mediated stereotactic delivery of a component of this import machinery into mouse brain as a novel therapeutic strategy. We report here that TOM40 is significantly reduced in the brain of PD patients and in α-Syn transgenic mice. TOM40 deficits were associated with increased mtDNA deletions and oxidative DNA damage, and with decreased energy production and altered levels of complex I proteins in α-Syn transgenic mice. Lentiviral-mediated overexpression of Tom40 in α-Syn-transgenic mice brains ameliorated energy deficits as well as oxidative burden. Our results suggest that alterations in the mitochondrial protein transport machinery might contribute to mitochondrial impairment in α-Synucleinopathies