How the Perceptions towards e-Retailer Image Affect the e-Consumer Behavior: Factors & Procedure Involved

In this research paper, the author highlighted three main elements that impacted online shoppers as an individual, in such security & privacy matters, individual behavior in relation with convenience and expectations and social influence which all will be further discussed.

Effect of a 6-month vegan low-carbohydrate (‘Eco-Atkins’) diet on cardiovascular risk factors and body weight in hyperlipidaemic adults: a randomised controlled trial

Objective: Low-carbohydrate diets may be useful for weight loss. Diets high in vegetable proteins and oils may reduce the risk of coronary heart disease. The main objective was to determine the longer term effect of a diet that was both low-carbohydrate and plant-based on weight loss and low-density lipoprotein cholesterol (LDL-C). Design, setting, participants A parallel design study of 39 overweight hyperlipidaemic men and postmenopausal women conducted at a Canadian university-affiliated hospital nutrition research centre from April 2005 to November 2006. Intervention Participants were advised to consume either a low-carbohydrate vegan diet or a high-carbohydrate lacto-ovo vegetarian diet for 6 months after completing 1-month metabolic (all foods provided) versions of these diets. The prescribed macronutrient intakes for the low-carbohydrate and high-carbohydrate diets were: 26% and 58% of energy from carbohydrate, 31% and 16% from protein and 43% and 25% from fat, respectively. Primary outcome Change in body weight. Results: 23 participants (50% test, 68% control) completed the 6-month ad libitum study. The approximate 4 kg weight loss on the metabolic study was increased to −6.9 kg on low-carbohydrate and −5.8 kg on high-carbohydrate 6-month ad libitum treatments (treatment difference (95% CI) −1.1 kg (−2.1 to 0.0), p=0.047). The relative LDL-C and triglyceride reductions were also greater on the low-carbohydrate treatment (treatment difference (95% CI) −0.49 mmol/L (−0.70 to −0.28), p<0.001 and −0.34 mmol/L (−0.57 to −0.11), p=0.005, respectively), as were the total cholesterol:HDL-C and apolipoprotein B:A1 ratios (−0.57 (−0.83, −0.32), p<0.001 and −0.05 (−0.09, −0.02), p=0.003, respectively). Conclusions: A self-selected low-carbohydrate vegan diet, containing increased protein and fat from gluten and soy products, nuts and vegetable oils, had lipid lowering advantages over a high-carbohydrate, low-fat weight loss diet, thus improving heart disease risk factors. Trial Registration clinicaltrials.gov (http://www.clinicaltrials.gov/), #NCT00256516

Factors Defining the Functional Oligomeric State of Escherichia coli DegP Protease

Escherichia coli DegP protein is a periplasmic protein that functions both as a protease and as a chaperone. In the absence of substrate, DegP oligomerizes as a hexameric cage but in its presence DegP reorganizes into 12 and 24-mer cages with large chambers that house the substrate for degradation or refolding. Here, we studied the factors that determine the oligomeric state adopted by DegP in the presence of substrate. Using size exclusion chromatography and electron microscopy, we found that the size of the substrate molecule is the main factor conditioning the oligomeric state adopted by the enzyme. Other factors such as temperature, a major regulatory factor of the activity of this enzyme, did not influence the oligomeric state adopted by DegP. In addition, we observed that substrate concentration exerted an effect only when large substrates (full-length proteins) were used. However, small substrate molecules (peptides) always triggered the same oligomeric state regardless of their concentration. These results clarify important aspects of the regulation of the oligomeric state of DegP

Identifying flares in rheumatoid arthritis: Reliability and construct validation of the OMERACT RA Flare Core Domain Set

Objective: To evaluate the reliability of concurrent flare identification using 3 methods (patient, rheumatologist and Disease Activity Score (DAS)28 criteria), and construct validity of candidate items representing the Outcome Measures in Rheumatology Clinical Trials (OMERACT) RA Flare Core Domain Set. Methods: Candidate flare questions and legacy measures were administered at consecutive visits to Canadian Early Arthritis Cohort (CATCH) patients between November 2011 and November 2014. The American College of Rheumatology (ACR) core set indicators were recorded. Concordance to identify flares was assessed using the agreement coefficient. Construct validity of flare questions was examined: convergent (Spearman's r); discriminant (mean differences between flaring/non-flaring patients); and consequential (proportions with prior treatment reductions and intended therapeutic change postflare). Results: The 849 patients were 75% female, 81% white, 42% were in remission/low disease activity (R/LDA), and 16-32% were flaring at the second visit. Agreement of flare status was low-strong (κ's 0.17-0.88) and inversely related to RA disease activity level. Flare domains correlated highly (r's≥0.70) with each other, patient global (r's≥0.66) and corresponding measures (r's 0.49-0.92); and moderately highly with MD and patient-reported joint counts (r's 0.29-0.62). When MD/patients agreed the patient was flaring, mean flare domain between-group differences were 2.1-3.0; 36% had treatment reductions prior to flare, with escalation planned in 61%. Conclusions: Flares are common in rheumatoid arthritis (RA) and are often preceded by treatment reductions. Patient/MD/DAS agreement of flare status is highest in patients worsening from R/LDA. OMERACT RA flare questions can discriminate between patients with/without flare and have strong evidence of construct and consequential validity. Ongoing work will identify optimal scoring and cut points to identify RA flares

Crop Updates 2004 - Cereals

This session covers twenty eight papers from different authors: PLENARY 1. Declining profitability in continuous cropping systems. Is more wheat the answer on Duplex soil? Dr Wal Anderson, Department of Agriculture 2. Disease implications of extending the wheat phase in low-medium rainfall areas, Dr Vivian Vanstone and Dr Robert Loughman, Department of Agriculture 3. Prolonged wheat phase on duplex soils – where do weeds set the boundary? Vanessa Stewart, Department of Agriculture WHEAT AGRONOMY 4. Management of small grain screenings in wheat, Dr Wal Anderson and Dr Darshan Sharma, Department of Agriculture 5. Agronomic responses of new wheat varieties, Christine Zaicou-Kunesch, Dr Darshan Sharma, Brenda Shackley, Dr Mohammad Amjad, Dr Wal Anderson and Steve Penny,Department of Agriculture 6. Managing wheat yield reduction from wide rows, Dr Mohammad Amjad and Dr Wal Anderson, Department of Agriculture 7. Row spacing and stubble effect on wheat yield and ryegrass seed set, Glen Riethmuller, Department of Agriculture 8. Grain protein management – lessons learnt on the south coast, Jeremy Lemon, Department of Agriculture 9. Unravelling the mysteries of optimum seed rates, Dr Wal Anderson, Dr Darshan Sharma, Brenda Shackley and Mario D’Antuono, Department of Agriculture 10. Agronomic features for growing better wheat – south east agricultural region 2003, Dr Mohammad Amjad, Veronika Reck and Ben Curtis, Department of Agriculture 11. Agronomic responses of new wheat varieties – great southern agricultural region 2003, Brenda Shackley and Judith Devenish, Department of Agriculture 12. Variety specific responses of new wheat varieties – central agricultural region 2003, Dr Darshan Sharma and Dr Wal Anderson, Department of Agriculture 13. Agronomic responses of new wheat varieties – northern agricultural region 2003, Christine Zaicou-Kunesch, Melaine Kupsch and Anne Smith, Department of Agriculture BARLEY AND OAT AGRONOMY 14. Gairdner for high rainfall – where does Baudin fit in? Blakely Paynter, Roslyn Jettnerand Leanne Schulz, Department of Agriculture 15. Oaten hay – varieties and agronomy, Blakely Paynter, Jocelyn Ball and Tom Sweeny, Department of Agriculture NUTRITION 16. In-furrow fungicide applications in liquid fertiliser, Dr Stephen Loss, CSBP Ltd 17. Elemental sulphur as a fertiliser source in Western Australia, Ashleigh Brooks1A, Justin Fuery2, Geoff Anderson3 and Prof Zed Rengel1,1UWA, 2Summit FertilizerFertilisers and 3Department of Agriculture 18. Genetic variation in potassium efficiency of barley, Paul Damon and Prof. Zed Rengel, Faculty of Natural and Agricultural Sciences, UWA 19. Managing protein through strategic N applications, Eddy Pol and Dr Stephen Loss, CSBP Ltd 20. Nitrogen management for wheat in high rainfall cropping areas, Narelle Hill1, Ray Tugwell1, Dr Wal Anderson1, Ron McTaggart1and Nathan Moyes2, 1Department of Agriculture and 2Landmark 21. Flag smut resistance in current WA wheat varieties, John Majewski and Dr Manisha Shankar, Department of Agriculture 22. Rust resistance update for wheat varieties in WA, Dr Manisha Shankar, John Majewski and Jamie Piotrowski, Department of Agriculture PESTS AND DISEASES 23. Stripe rust in WA – where was it and what can we learn from 2003? Dr Robert Loughman and Ciara Beard, Department of Agriculture 24. Foliar disease management – a key factor in the adoption of Baudin and Hamlin barley, Dr Kithsiri Jayasena, Dr Rob Loughman, Kazue Tanaka and Grey Poulish, Department of Agriculture 25. Validating aphid and virus risk forecasts for cereals, Dr Debbie Thackray, Rohan Prince and Dr Roger Jones, Department of Agriculture and Centre for Legumes in Mediterranean Agriculture HARVESTING 26. Swathing Gairdner barley at 30% moisture, Peter Nelson¹ and Nigel Metz², ¹Cooperative Bulk Handling and ² Fitzgerald Biosphere Group MODELLING 27. Development of a web based grower decision aid application for cereal growers, Dr Leisa Armstrong1, Yee Leong (Alex) Yung1and Dr Moin Salam2 1School of Computer and Information Science, Edith Cowan University; and 2Department of Agriculture 28. Wheat varieties updated in ‘Flowering Calculator’ – a model predicting flowering time, Brenda Shackley, Dr David Tennant, Dr Darshan Sharma and Christine Zaicou‑Kunesch, Department of Agricultur

The global burden of adolescent and young adult cancer in 2019 : a systematic analysis for the Global Burden of Disease Study 2019

Background In estimating the global burden of cancer, adolescents and young adults with cancer are often overlooked, despite being a distinct subgroup with unique epidemiology, clinical care needs, and societal impact. Comprehensive estimates of the global cancer burden in adolescents and young adults (aged 15-39 years) are lacking. To address this gap, we analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, with a focus on the outcome of disability-adjusted life-years (DALYs), to inform global cancer control measures in adolescents and young adults. Methods Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15-39 years to define adolescents and young adults. Findings There were 1.19 million (95% UI 1.11-1.28) incident cancer cases and 396 000 (370 000-425 000) deaths due to cancer among people aged 15-39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59.6 [54.5-65.7] per 100 000 person-years) and high-middle SDI countries (53.2 [48.8-57.9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14.2 [12.9-15.6] per 100 000 person-years) and middle SDI (13.6 [12.6-14.8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23.5 million (21.9-25.2) DALYs to the global burden of disease, of which 2.7% (1.9-3.6) came from YLDs and 97.3% (96.4-98.1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally. Interpretation Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Rationale, Design and Baseline Characteristics of Participants in the Cardiovascular Outcomes for People Using Anticoagulation Strategies (COMPASS) Trial

Long-term aspirin prevents vascular events but is only modestly effective. Rivaroxaban alone or in combination with aspirin might be more effective than aspirin alone for vascular prevention in patients with stable coronary artery disease (CAD) or peripheral artery disease (PAD). Rivaroxaban as well as aspirin increase upper gastrointestinal (GI) bleeding and this might be prevented by proton pump inhibitor therapy. Cardiovascular Outcomes for People Using Anticoagulation Strategies (COMPASS) is a double-blind superiority trial comparing rivaroxaban 2.5 mg twice daily combined with aspirin 100 mg once daily or rivaroxaban 5 mg twice daily vs aspirin 100 mg once daily for prevention of myocardial infarction, stroke, or cardiovascular death in patients with stable CAD or PAD. Patients not taking a proton pump inhibitor were also randomized, using a partial factorial design, to pantoprazole 40 mg once daily or placebo. The trial was designed to have at least 90% power to detect a 20% reduction in each of the rivaroxaban treatment arms compared with aspirin and to detect a 50% reduction in upper GI complications with pantoprazole compared with placebo. Between February 2013 and May 2016, we recruited 27,395 participants from 602 centres in 33 countries; 17,598 participants were included in the pantoprazole vs placebo comparison. At baseline, the mean age was 68.2 years, 22.0% were female, 90.6% had CAD, and 27.3% had PAD. COMPASS will provide information on the efficacy and safety of rivaroxaban, alone or in combination with aspirin, in the long-term management of patients with stable CAD or PAD, and on the efficacy and safety of pantoprazole in preventing upper GI complications in patients receiving antithrombotic therapy

Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019: A Systematic Analysis for the Global Burden of Disease Study 2019.

The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.Funding/Support: The Institute for Health Metrics and Evaluation received funding from the Bill & Melinda Gates Foundation and the American Lebanese Syrian Associated Charities. Dr Aljunid acknowledges the Department of Health Policy and Management of Kuwait University and the International Centre for Casemix and Clinical Coding, National University of Malaysia for the approval and support to participate in this research project. Dr Bhaskar acknowledges institutional support from the NSW Ministry of Health and NSW Health Pathology. Dr Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, which is funded by the German Federal Ministry of Education and Research. Dr Braithwaite acknowledges funding from the National Institutes of Health/ National Cancer Institute. Dr Conde acknowledges financial support from the European Research Council ERC Starting Grant agreement No 848325. Dr Costa acknowledges her grant (SFRH/BHD/110001/2015), received by Portuguese national funds through Fundação para a Ciência e Tecnologia, IP under the Norma Transitória grant DL57/2016/CP1334/CT0006. Dr Ghith acknowledges support from a grant from Novo Nordisk Foundation (NNF16OC0021856). Dr Glasbey is supported by a National Institute of Health Research Doctoral Research Fellowship. Dr Vivek Kumar Gupta acknowledges funding support from National Health and Medical Research Council Australia. Dr Haque thanks Jazan University, Saudi Arabia for providing access to the Saudi Digital Library for this research study. Drs Herteliu, Pana, and Ausloos are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. Dr Hugo received support from the Higher Education Improvement Coordination of the Brazilian Ministry of Education for a sabbatical period at the Institute for Health Metrics and Evaluation, between September 2019 and August 2020. Dr Sheikh Mohammed Shariful Islam acknowledges funding by a National Heart Foundation of Australia Fellowship and National Health and Medical Research Council Emerging Leadership Fellowship. Dr Jakovljevic acknowledges support through grant OI 175014 of the Ministry of Education Science and Technological Development of the Republic of Serbia. Dr Katikireddi acknowledges funding from a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the Medical Research Council (MC_UU_00022/2), and the Scottish Government Chief Scientist Office (SPHSU17). Dr Md Nuruzzaman Khan acknowledges the support of Jatiya Kabi Kazi Nazrul Islam University, Bangladesh. Dr Yun Jin Kim was supported by the Research Management Centre, Xiamen University Malaysia (XMUMRF/2020-C6/ITCM/0004). Dr Koulmane Laxminarayana acknowledges institutional support from Manipal Academy of Higher Education. Dr Landires is a member of the Sistema Nacional de Investigación, which is supported by Panama’s Secretaría Nacional de Ciencia, Tecnología e Innovación. Dr Loureiro was supported by national funds through Fundação para a Ciência e Tecnologia under the Scientific Employment Stimulus–Institutional Call (CEECINST/00049/2018). Dr Molokhia is supported by the National Institute for Health Research Biomedical Research Center at Guy’s and St Thomas’ National Health Service Foundation Trust and King’s College London. Dr Moosavi appreciates NIGEB's support. Dr Pati acknowledges support from the SIAN Institute, Association for Biodiversity Conservation & Research. Dr Rakovac acknowledges a grant from the government of the Russian Federation in the context of World Health Organization Noncommunicable Diseases Office. Dr Samy was supported by a fellowship from the Egyptian Fulbright Mission Program. Dr Sheikh acknowledges support from Health Data Research UK. Drs Adithi Shetty and Unnikrishnan acknowledge support given by Kasturba Medical College, Mangalore, Manipal Academy of Higher Education. Dr Pavanchand H. Shetty acknowledges Manipal Academy of Higher Education for their research support. Dr Diego Augusto Santos Silva was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil Finance Code 001 and is supported in part by CNPq (302028/2018-8). Dr Zhu acknowledges the Cancer Prevention and Research Institute of Texas grant RP210042