Use of proton pump inhibitors and histamine-2 receptor antagonists and risk of gastric cancer in two population-based studies

Acknowledgements Access to UK Biobank data was approved and facilitated by UK Biobank (application number: 34374). Access to Primary Care Clinical Informatics Unit (PCCIU) data was approved and facilitated by the PCCIU Research team, University of Aberdeen. Access to the UK Biobank was funded by a Cancer Research UK Population Research Postdoctoral Fellowship awarded to ÚCMcM. Funding: Access to the UK Biobank was funded by a Cancer Research UK Population Research Postdoctoral Fellowship awarded to ÚCMcM. Liu P was supported by a joint scholarship from Queen's University Belfast and the Chinese Scholarship Council (201708060458). Data availability: The UK Biobank data (https://www.ukbiobank.ac.uk/) and PCCIU data (https://www.abdn.ac.uk/iahs/research/primary-care/pcciur/) are available, following the access procedures, for researchers to access to conduct health related research in the public interest.Peer reviewedPostprin

Proton pump inhibitor and histamine-2 receptor antagonist use and risk of liver cancer in two population-based studies

The analysis of UK Biobank has been conducted using the UK Biobank Resource under Application Number 34374. We acknowledge collaboration with the Research Applications and Data Management Team lead by Ms Katie Wilde, University of Aberdeen in conducting this study. KTT is supported by the Vietnam International Education Cooperation Department. Access to PCCIU data was provided by Queen’s University Belfast and the Centre for Academic Primary Care, University of Aberdeen. Access to the UK Biobank was funded by a Cancer Research UK Population Research Postdoctoral Fellowship awarded to ÚCMcM. HGC is a co-investigator of the UKCRC Centre of Excellence for Public Health Northern Ireland.Peer reviewedPostprin

Quantifying signal changes in nano-wire based biosensors

In this work, we present a computational methodology for predicting the change in signal (conductance sensitivity) of a nano-BioFET sensor (a sensor based on a biomolecule binding another biomolecule attached to a nano-wire field effect transistor) upon binding its target molecule. The methodology is a combination of the screening model of surface charge sensors in liquids developed by Brandbyge and co-workers [Sørensen et al., Appl. Phys. Lett., 2007, 91, 102105], with the PROPKA method for predicting the pH-dependent charge of proteins and protein-ligand complexes, developed by Jensen and co-workers [Li et al., Proteins: Struct., Funct., Bioinf., 2005, 61, 704-721, Bas et al., Proteins: Struct., Funct., Bioinf., 2008, 73, 765-783]. The predicted change in conductance sensitivity based on this methodology is compared to previously published data on nano-BioFET sensors obtained by other groups. In addition, the conductance sensitivity dependence from various parameters is explored for a standard wire, representative of a typical experimental setup. In general, the experimental data can be reproduced with sufficient accuracy to help interpret them. The method has the potential for even more quantitative predictions when key experimental parameters (such as the charge carrier density of the nano-wire or receptor density on the device surface) can be determined (and reported) more accurately. © 2011 The Royal Society of Chemistry

Medications that relax the lower oesophageal sphincter and risk of oesophageal cancer : An analysis of two independent population-based databases

Acknowledgements We acknowledge collaboration with the Research Applications and Data Management Team lead by Ms Katie Wilde, University of Aberdeen in conducting our study. This research has been conducted using the UK Bio-bank Resource under application number 34374.Peer reviewedPostprin

Geographical and ecological analyses of multiple myeloma in Denmark:Identification of potential hotspot areas and impact of urbanisation

BACKGROUND: The aetiology of multiple myeloma (MM) is unknown but various environmental exposures are suspected as risk factors. We present the first paper analysing the geographical distribution of MM in Denmark at the municipal level to investigate variations that could be explained by environmental exposures.METHODS: Patients diagnosed with MM in Denmark during 2005-2020 were identified from nationwide registries and grouped into the 98 Danish municipalities based on residence. The age- and sex-standardised incidence rate (SIR) of each municipality was compared to the national incidence in a funnel plot with 95% control limits. Differences in SIRs of rural, suburban, and urban areas were evaluated with incidence rate ratios.RESULTS: In total, 5243 MM patients were included. Overall, we found a heterogeneous geographical distribution of MM and a potential hotspot in southern Denmark. This hotspot contains three municipalities with SIRs above the 95% control limit assuming considerably higher rate of MM compared to the national incidence rate. A significant higher SIR was found in rural areas compared to urban areas.CONCLUSION: The geographical distribution of MM in Denmark indicates that the risk of developing MM depends on place of residence probably due to environmental factors.</p