Expressing Privacy Preferences in terms of Invasiveness

Dynamic context aware systems need highly flexible privacy protection mechanisms. We describe an extension to an existing RBAC-based mechanism that utilises a dynamic measure of invasiveness to determine whether contextual information should be released

Alternative Archaeological Representations within Virtual Worlds

Traditional VR methods allow the user to tour and view the virtual world from different perspectives. Increasingly, more interactive and adaptive worlds are being generated, potentially allowing the user to interact with and affect objects in the virtual world. We describe and compare four models of operation that allow the publisher to generate views, with the client manipulating and affecting specific objects in the world. We demonstrate these approaches through a problem in archaeological visualization

Capturing Regular Human Activity through a Learning Context Memory

A learning context memory consisting of two main parts is presented. The first part performs lossy data compression, keeping the amount of stored data at a minimum by combining similar context attributes — the compression rate for the presented GPS data is 150:1 on average. The resulting data is stored in an appropriate data structure highlighting the level of compression. Elements with a high level of compression are used in the second part to form the start and end points of episodes capturing common activity consisting of consecutive events. The context memory is used to investigate how little context data can be stored containing still enough information to capture regular human activity

Clinical considerations in early-onset cerebral amyloid angiopathy

Cerebral amyloid angiopathy (CAA) is an important cerebral small vessel disease associated with brain haemorrhage and cognitive change. The commonest form, sporadic amyloid-beta CAA, usually affects people in mid- to later life. However, early-onset forms, though uncommon, are increasingly recognised and may result from genetic or iatrogenic causes that warrant specific and focussed investigation and management. In this review, we firstly describe the causes of early-onset CAA, including monogenic causes of amyloid-beta CAA (APP missense mutations and copy number variants; mutations of PSEN1 and PSEN2) and non-amyloid-beta CAA (associated with ITM2B, CST3, GSN, PRNP and TTR mutations), and other unusual sporadic and acquired causes including the newly-recognised iatrogenic subtype. We then provide a structured approach for investigating early-onset CAA, and highlight important management considerations. Improving awareness of these unusual forms of CAA amongst healthcare professionals is essential for facilitating their prompt diagnosis, and an understanding of their underlying pathophysiology may have implications for more common, late-onset, forms of the disease

Presymptomatic cortical thinning in familial Alzheimer disease: A longitudinal MRI study.

OBJECTIVE: To identify a cortical signature pattern of cortical thinning in familial Alzheimer disease (FAD) and assess its utility in detecting and tracking presymptomatic neurodegeneration. METHODS: We recruited 43 FAD mutation carriers-36 PSEN1, 7 APP (20 symptomatic, 23 presymptomatic)-and 42 healthy controls to a longitudinal clinical and MRI study. T1-weighted MRI scans were acquired at baseline in all participants; 55 individuals (33 mutation carriers; 22 controls) had multiple (mean 2.9) follow-up scans approximately annually. Cortical thickness was measured using FreeSurfer. A cortical thinning signature was identified from symptomatic FAD participants. We then examined cortical thickness changes in this signature region in presymptomatic carriers and assessed associations with cognitive performance. RESULTS: The cortical signature included 6 regions: entorhinal cortex, inferior parietal cortex, precuneus, superior parietal cortex, superior frontal cortex, and supramarginal gyrus. There were significant differences in mean cortical signature thickness between mutation carriers and controls 3 years before predicted symptom onset. The earliest significant difference in a single region, detectable 4 years preonset, was in the precuneus. Rate of change in cortical thickness became significantly different in the cortical signature at 5 years before predicted onset, and in the precuneus at 8 years preonset. Baseline mean signature thickness predicted rate of subsequent thinning and correlated with presymptomatic cognitive change. CONCLUSIONS: The FAD cortical signature appears to be similar to that described for sporadic AD. All component regions showed significant presymptomatic thinning. A composite signature may provide more robust results than a single region and have utility as an outcome measure in presymptomatic trials

Aβ profiles generated by Alzheimer's disease causing PSEN1 variants determine the pathogenicity of the mutation and predict age at disease onset.

Familial Alzheimer’s disease (FAD), caused by mutations in Presenilin (PSEN1/2) and Amyloid Precursor Protein (APP) genes, is associated with an early age at onset (AAO) of symptoms. AAO is relatively consistent within families and between carriers of the same mutations, but differs markedly between individuals carrying different mutations. Gaining a mechanistic understanding of why certain mutations manifest several decades earlier than others is extremely important in elucidating the foundations of pathogenesis and AAO. Pathogenic mutations affect the protease (PSEN/γ-secretase) and the substrate (APP) that generate amyloid β (Aβ) peptides. Altered Aβ metabolism has long been associated with AD pathogenesis, with absolute or relative increases in Aβ42 levels most commonly implicated in the disease development. However, analyses addressing the relationships between these Aβ42 increments and AAO are inconsistent. Here, we investigated this central aspect of AD pathophysiology via comprehensive analysis of 25 FAD-linked Aβ profiles. Hypothesis- and data-driven approaches demonstrate linear correlations between mutation-driven alterations in Aβ profiles and AAO. In addition, our studies show that the Aβ (37 + 38 + 40) / (42 + 43) ratio offers predictive value in the assessment of ‘unclear’ PSEN1 variants. Of note, the analysis of PSEN1 variants presenting additionally with spastic paraparesis, indicates that a different mechanism underlies the aetiology of this distinct clinical phenotype. This study thus delivers valuable assays for fundamental, clinical and genetic research as well as supports therapeutic interventions aimed at shifting Aβ profiles towards shorter Aβ peptides

Variability in the type and layer distribution of cortical Aβ pathology in familial Alzheimer's disease.

Familial Alzheimer's disease (FAD) is caused by autosomal dominant mutations in the PSEN1, PSEN2 or APP genes, giving rise to considerable clinical and pathological heterogeneity in FAD. Here we investigate variability in clinical data and the type and distribution of Aβ pathologies throughout the cortical layers of different FAD mutation cases. Brain tissue from 20 FAD cases [PSEN1 pre-codon 200 (n = 10), PSEN1 post-codon 200 (n = 6), APP (n = 4)] were investigated. Frontal cortex sections were stained immunohistochemically for Aβ, and Nissl to define the cortical layers. The frequency of different amyloid-beta plaque types was graded for each cortical layer and the severity of cerebral amyloid angiopathy (CAA) was determined in cortical and leptomeningeal blood vessels. Comparisons were made between FAD mutations and APOE4 status, with associations between pathology, clinical and genetic data investigated. In this cohort, possession of an APOE4 allele was associated with increased disease duration but not with age at onset, after adjusting for mutation sub-group and sex. We found Aβ pathology to be heterogeneous between cases although Aβ load was highest in cortical layer 3 for all mutation groups and a higher Aβ load was associated with APOE4. The PSEN1 post-codon 200 group had a higher Aβ load in lower cortical layers, with a small number of this group having increased cotton wool plaque pathology in lower layers. Cotton wool plaque frequency was positively associated with the severity of CAA in the whole cohort and in the PSEN1 post-codon 200 group. Carriers of the same PSEN1 mutation can have differing patterns of Aβ deposition, potentially because of differences in risk factors. Our results highlight possible influences of APOE4 genotype, and PSEN1 mutation type on Aβ deposition, which may have effects on the clinical heterogeneity of FAD

The PSEN1 E280G mutation leads to increased amyloid-β43 production in induced pluripotent stem cell neurons and deposition in brain tissue

Mutations in the presenilin 1 gene, PSEN1, which cause familial Alzheimer’s disease alter processing of amyloid precursor protein, leading to the generation of various amyloid-β peptide species. These species differ in their potential for aggregation. Mutation-specific amyloid-β peptide profiles may thereby influence pathogenicity and clinical heterogeneity. There is particular interest in comparing mutations with typical and atypical clinical presentations, such as E280G. We generated PSEN1 E280G mutation induced pluripotent stem cells from two patients and differentiated them into cortical neurons, along with previously reported PSEN1 M146I, PSEN1 R278I and two control lines. We assessed both the amyloid-β peptide profiles and presenilin 1 protein maturity. We also compared amyloid-β peptide profiles in human post-mortem brain tissue from cases with matched mutations. Amyloid-β ratios significantly differed compared with controls and between different patients, implicating mutation-specific alterations in amyloid-β ratios. Amyloid-β42:40 was increased in the M146I and both E280G lines compared with controls. Amyloid-β42:40 was not increased in the R278I line compared with controls. The amyloid-β43:40 ratio was increased in R278I and both E280G lines compared with controls, but not in M146I cells. Distinct amyloid-β peptide patterns were also observed in human brain tissue from individuals with these mutations, showing some similar patterns to cell line observations. Reduced presenilin 1 maturation was observed in neurons with the PSEN1 R278I and E280G mutations, but not the M146I mutation. These results suggest that mutation location can differentially alter the presenilin 1 protein and affect its autoendoproteolysis and processivity, contributing to the pathological phenotype. Investigating differences in underlying molecular mechanisms of familial Alzheimer’s disease may inform our understanding of clinical heterogeneity