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| 1 | Risk factors for Barrett’s oesophagus and oesophageal adenocarcinoma:Results from the FINBAR study显示文摘AIM:To investigate risk factors associated with Barrett's oesophagus and oesophageal adenocarcinoma.METHODS:This all-Ireland population-based case-control study recruited 224 Barrett's oesophagus patients,227 oesophageal adenocarcinoma patients and 260 controls.All participants underwent a structured interview with information obtained about potential lifestyle and environmental risk factors.RESULTS:Gastro-oesophageal reflux was associated with Barrett's [OR 12.0(95% CI 7.64-18.7)] and oesophageal adenocarcinoma [OR 3.48(95% CI 2.25-5.41)].Oesophageal adenocarcinoma patients were more likely than controls to be ex-or current smokers [OR 1.72(95% CI 1.06-2.81)and OR 4.84(95% CI 2.72-8.61)respectively] and to have a high body mass index [OR 2.69(95% CI 1.62-4.46)].No significant associations were observed between these risk factors and Barrett's oesophagus.Fruit but not vegetables were negatively associated with oesophageal adenocarcinoma [OR 0.50(95% CI 0.30-0.86)].CONCLUSION:A high body mass index,a diet low in fruit and cigarette smoking may be involved in the progression from Barrett's oesophagus to oesophageal adenocarcinoma. | Lesley A Anderson RG Peter Watson Seamus J Murphy Brian T Johnston Harry Comber Jim Mc Guigan John V Reynolds Liam J Murray | 2007 | World Journal of Gastroenterology2007，13，10： | 5 |
| 2 | The Association Between Alcohol and Reflux Esophagitis, Barrett’s Esophagus, and Esophageal Adenocarcinoma显示文摘 | Lesley A. Anderson Marie M. Cantwell R.G. Peter Watson Brian T. Johnston Seamus J. Murphy Heather R. Ferguson Jim McGuigan Harry Comber John V. Reynolds Liam J. Murray | 2009 | Gastroenterology2009，，3： | 1 |
| 3 | High-performance solutions of geographically weighted regression in R显示文摘As an established spatial analytical tool,Geographically Weighted Regression(GWR)has been applied across a variety of disciplines.However,its usage can be challenging for large datasets,which are increasingly prevalent in today’s digital world.In this study,we propose two high-performance R solutions for GWR via Multi-core Parallel(MP)and Compute Unified Device Architecture(CUDA)techniques,respectively GWR-MP and GWR-CUDA.We compared GWR-MP and GWR-CUDA with three existing solutions available in Geographically Weighted Models(GWmodel),Multi-scale GWR(MGWR)and Fast GWR(FastGWR).Results showed that all five solutions perform differently across varying sample sizes,with no single solution a clear winner in terms of computational efficiency.Specifically,solutions given in GWmodel and MGWR provided acceptable computational costs for GWR studies with a relatively small sample size.For a large sample size,GWR-MP and FastGWR provided coherent solutions on a Personal Computer(PC)with a common multi-core configuration,GWR-MP provided more efficient computing capacity for each core or thread than FastGWR.For cases when the sample size was very large,and for these cases only,GWR-CUDA provided the most efficient solution,but should note its I/O cost with small samples.In summary,GWR-MP and GWR-CUDA provided complementary high-performance R solutions to existing ones,where for certain data-rich GWR studies,they should be preferred. | Binbin Lu Yigong Hu Daisuke Murakami Chris Brunsdon Alexis Comber Martin Charlton Paul Harris | 2022 | Geo-Spatial Information Science2022，25，4： | 1 |
| 4 | Convergence of decreasing male and increasing female incidence rates in major tobacco-related cancers in Europe in 1988–2010显示文摘 | Joannie Lortet-Tieulent Elisenda Renteria Linda Sharp Elisabete Weiderpass Harry Comber Paul Baas Freddie Bray Jan Willem Coebergh Isabelle Soerjomataram | 2013 | European Journal of Cancer2013，，： | 1 |
| 5 | When multi-functional landscape meets Critical Zone science:advancing multi-disciplinary research for sustainable human well-being显示文摘Environmental degradation has become one of the major obstacles to sustainable development and human well-being internationally. Scientific efforts are being made to understand the mechanism of environmental degradation and sustainability. Critical Zone(CZ) science and research on the multi-functional landscape are emerging fields in Earth science that can contribute to such scientific efforts. This paper reviews the progress, similarities and current status of these two scientific research fields, and identifies a number of opportunities for their synergistic integration through functional and multi-functional approaches,process-based monitoring, mechanistic analyses and dynamic modeling, global long-term and networked monitoring and systematic modeling supported by scaling and deep coupling. These approaches proposed in this paper have the potential to support sustainable human well-being by strengthening a functional orientation that consolidates multi-functional landscape research and CZ science. This is a key challenge for sustainable development and human well-being in the twenty-first century. | Ying Luo Yihe Lü Bojie Fu Paul Harris Lianhai Wu Alexis Comber | 2019 | National Science Review2019，6，2： | 0 |
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