Type 1 diabetes

Type 1 diabetes is a chronic autoimmune disease characterised by insulin deficiency and resultant hyperglycaemia. Knowledge of type 1 diabetes has rapidly increased over the past 25 years, resulting in a broad understanding about many aspects of the disease, including its genetics, epidemiology, immune and β-cell phenotypes, and disease burden. Interventions to preserve β cells have been tested, and several methods to improve clinical disease management have been assessed. However, wide gaps still exist in our understanding of type 1 diabetes and our ability to standardise clinical care and decrease disease-associated complications and burden. This Seminar gives an overview of the current understanding of the disease and potential future directions for research and care

Lordship and Environmental Change in Central Highland Scotland c.1300–c.1400

Whilst there has been an increasing recognition of the infl uence of natural agency on human society in Scotland in the medieval period, conventional historiography has generally presented the wholesale reconfi guration of structures of secular lordship in the Scottish central Highlands in the 14th century as an essentially political consequence of the sociopolitical dislocation associated with the Anglo-Scottish wars that occurred after 1296. The establishment within the region of militarised Gaelic kindreds from the West Highlands and Hebrides of Scotland has come to be regarded as either a symptom of efforts by externally based regional lords to bolster their authority, or an opportunistic territorial aggrandisement by newly dominant neighbouring lords. Feuding and predatory raiding associated with these kindreds is recognised as competition for resources but generally in a context of projection of superior lordship over weaker neighbours. Evidence for long-term changes in climate extrapolated from North Atlantic proxy data, however, suggests that the cattle-based economy of Atlantic Scotland was experiencing protracted environmentally induced stress in the period c.1300–c.1350. Using this evidence, we discuss whether exchange systems operating within traditional lordship structures could offset localised and short-term pressures on the livestock-based regime, but could not be sustained long-term on the reduced fodder and contracting herd sizes caused by climatic deterioration. Territorial expansion and development of a predatory culture, it is argued, were responses to an environment-triggered economic crisis

Operational semantics for signal handling

Signals are a lightweight form of interprocess communication in Unix. When a process receives a signal, the control flow is interrupted and a previously installed signal handler is run. Signal handling is reminiscent both of exception handling and concurrent interleaving of processes. In this paper, we investigate different approaches to formalizing signal handling in operational semantics, and compare them in a series of examples. We find the big-step style of operational semantics to be well suited to modelling signal handling. We integrate exception handling with our big-step semantics of signal handling, by adopting the exception convention as defined in the Definition of Standard ML. The semantics needs to capture the complex interactions between signal handling and exception handling.Comment: In Proceedings EXPRESS/SOS 2012, arXiv:1208.244

Applying a genetic risk score for prostate cancer to men with lower urinary tract symptoms in primary care to predict prostate cancer diagnosis : a cohort study in the UK Biobank

Background Prostate cancer is highly heritable, with >250 common variants associated in genome-wide association studies. It commonly presents with non-specific lower urinary tract symptoms that are frequently associated with benign conditions. Methods Cohort study using UK Biobank data linked to primary care records. Participants were men with a record showing a general practice consultation for a lower urinary tract symptom. The outcome measure was prostate cancer diagnosis within 2 years of consultation. The predictor was a genetic risk score of 269 genetic variants for prostate cancer. Results A genetic risk score (GRS) is associated with prostate cancer in symptomatic men (OR per SD increase = 2.12 [1.86-2.41] P = 3.5e-30). An integrated risk model including age and GRS applied to symptomatic men predicted prostate cancer (AUC 0.768 [0.739-0.796]). Prostate cancer incidence was 8.1% (6.7-9.7) in the highest risk quintile. In the lowest quintile, prostate cancer incidence was Conclusions This study is the first to apply GRS in primary care to improve the triage of symptomatic patients. Men with the lowest genetic risk of developing prostate cancer could safely avoid invasive investigation, whilst those identified with the greatest risk could be fast-tracked for further investigation. These results show that a GRS has potential application to improve the diagnostic pathway of symptomatic patients in primary care.Peer reviewe

Remote Infrared Imaging of the Space Shuttle During Hypersonic Flight: HYTHIRM Mission Operations and Coordination

The Hypersonic Thermodynamic Infrared Measurements (HYTHIRM) project has been responsible for obtaining spatially resolved, scientifically calibrated in-flight thermal imagery of the Space Shuttle Orbiter during reentry. Starting with STS-119 in March of 2009 and continuing through to the majority of final flights of the Space Shuttle, the HYTHIRM team has to date deployed during seven Shuttle missions with a mix of airborne and ground based imaging platforms. Each deployment of the HYTHIRM team has resulted in obtaining imagery suitable for processing and comparison with computational models and wind tunnel data at Mach numbers ranging from over 18 to under Mach 5. This paper will discuss the detailed mission planning and coordination with the NASA Johnson Space Center Mission Control Center that the HYTHIRM team undergoes to prepare for and execute each mission

Histological validation of a type 1 diabetes clinical diagnostic model for classification of diabetes

Aims: Misclassification of diabetes is common due to an overlap in the clinical features of type 1 and type 2 diabetes. Combined diagnostic models incorporating clinical and biomarker information have recently been developed that can aid classification, but they have not been validated using pancreatic pathology. We evaluated a clinical diagnostic model against histologically defined type 1 diabetes. Methods: We classified cases from the Network for Pancreatic Organ donors with Diabetes (nPOD) biobank as type 1 (n = 111) or non-type 1 (n = 42) diabetes using histopathology. Type 1 diabetes was defined by lobular loss of insulin-containing islets along with multiple insulin-deficient islets. We assessed the discriminative performance of previously described type 1 diabetes diagnostic models, based on clinical features (age at diagnosis, BMI) and biomarker data [autoantibodies, type 1 diabetes genetic risk score (T1D-GRS)], and singular features for identifying type 1 diabetes by the area under the curve of the receiver operator characteristic (AUC-ROC). Results: Diagnostic models validated well against histologically defined type 1 diabetes. The model combining clinical features, islet autoantibodies and T1D-GRS was strongly discriminative of type 1 diabetes, and performed better than clinical features alone (AUC-ROC 0.97 vs. 0.95; P = 0.03). Histological classification of type 1 diabetes was concordant with serum C-peptide [median < 17 pmol/l (limit of detection) vs. 1037 pmol/l in non-type 1 diabetes; P < 0.0001]. Conclusions: Our study provides robust histological evidence that a clinical diagnostic model, combining clinical features and biomarkers, could improve diabetes classification. Our study also provides reassurance that a C-peptide-based definition of type 1 diabetes is an appropriate surrogate outcome that can be used in large clinical studies where histological definition is impossible. Parts of this study were presented in abstract form at the Network for Pancreatic Organ Donors Conference, Florida, USA, 19-22 February 2019 and Diabetes UK Professional Conference, Liverpool, UK, 6-8 March 2019.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.Diabetes UK. Grant Number: 16/0005529 NIH. Grant Number: AI‐422388 NIHR. Grant Number: 17/0005624 Diabetes UK. Grant Number: 16/0005480 JDRF Career Development. Grant Number: 5‐CDA‐2014‐221‐A‐N Helmsley Charitable Trust. Grant Number: #2018PG‐T1D053published version, accepted version (12 month embargo), submitted versio

Can filesharers be triggered by economic incentives? Results of an experiment

Illegal filesharing on the internet leads to considerable financial losses for artists and copyright owners as well as producers and sellers of music. Thus far, measures to contain this phenomenon have been rather restrictive. However, there are still a considerable number of illegal systems, and users are able to decide quite freely between legal and illegal downloads because the latter are still difficult to sanction. Recent economic approaches account for the improved bargaining position of users. They are based on the idea of revenue-splitting between professional sellers and peers. In order to test such an innovative business model, the study reported in this article carried out an experiment with 100 undergraduate students, forming five small peer-to-peer networks.The networks were confronted with different economic conditions.The results indicate that even experienced filesharers hold favourable attitudes towards revenue-splitting.They seem to be willing to adjust their behaviour to different economic conditions

IgA Nephropathy Genetic Risk Score to Estimate the Prevalence of IgA Nephropathy in UK Biobank

Background: IgA nephropathy (IgAN) is the commonest glomerulonephritis worldwide. Its prevalence is difficult to estimate, as people with mild disease do not commonly receive a biopsy diagnosis. We aimed to generate an IgA nephropathy genetic risk score (IgAN-GRS) and estimate the proportion of people with hematuria who had IgAN in the UK Biobank (UKBB). Methods: We calculated an IgAN-GRS using 14 single-nucleotide polymorphisms (SNPs) drawn from the largest European Genome-Wide Association Study (GWAS) and validated the IgAN-GRS in 464 biopsy-proven IgAN European cases from the UK Glomerulonephritis DNA Bank (UKGDB) and in 379,767 Europeans in the UKBB. We used the mean of IgAN-GRS to calculate the proportion of potential IgAN in 14,181 with hematuria and other nonspecific renal phenotypes from 379,767 Europeans in the UKBB. Results: The IgAN-GRS was higher in the IgAN cohort (4.30; 95% confidence interval [95% CI: 4.23-4.38) than in controls (3.98; 3.97-3.98; P < 0.0001). The mean GRS in UKBB participants with hematuria (n = 12,858) was higher (4.04; 4.02-4.06) than UKBB controls (3.98; 3.97-3.98; P < 0.0001) and higher in those with hematuria, hypertension, and microalbuminuria (n = 1323) (4.07; 4.02-4.13) versus (3.98; 3.97-3.98; P = 0.0003). Using the difference in these means, we estimated that IgAN accounted for 19% of noncancer hematuria and 28% with hematuria, hypertension, and microalbuminuria in UKBB. Conclusions: We used an IgAN-GRS to estimate the prevalence of IgAN contributing to common phenotypes that are not always biopsied. The noninvasive use of polygenic risk in this setting may have further utility to identify likely etiology of nonspecific renal phenotypes in large population cohorts.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.This study was done with the UK Biobank resource (application 9072). UK Glomerulonephritis DNA Bank cohort. Piotr Słowinski, was consulted on the means method and helped with the simulation estimates and calculation. KS is funded by an Nation Institute for Health and Research (NIHR) Academic Clinical Fellowship. SAS is supported by a Diabetes UK PhD studentship (17/0005757). RAO is supported by a Diabetes UK Harry Keen Fellowship (16/0005529) MNW is supported by the Wellcome Trust Institutional Support Fund (WT097835MF). The views expressed are those of the authors and not necessarily those of the National Health Service (NHS), the NIHR, or the Department of Healthpublished version, accepted version, submitted versio

Preventing type 1 diabetes in childhood

Type 1 diabetes (T1D) is an autoimmune disease in which the insulin-producing β cells of the pancreas are destroyed by T lymphocytes. Recent studies have demonstrated that monitoring for pancreatic islet autoantibodies, combined with genetic risk assessment, can identify most children who will develop T1D when they still have sufficient β cell function to control glucose concentrations without the need for insulin. In addition, there has been recent success in secondary prevention using immunotherapy to delay the progression of preclinical disease, and primary prevention approaches to inhibiting the initiating autoimmune process have entered large-scale clinical trials. By changing the focus of T1D management from late diagnosis and insulin replacement to early diagnosis and β cell preservation, we can anticipate a future without the need for daily insulin injections for children with T1D