Crop Updates 2005 Oilseeds

This session covers fifteen papers from different authors: 1. ACKNOWLEDGEMENTS, Douglas Hamilton, FARMING SYSTEMS DEVELOPMENT OFFICER CROP AGRONOMY AND NUTRITION 2. Canola workshop at Crop Updates 2005, Oilseeds WA, John Duff, EXECUTIVE OFFICER OILSEEDS WA 3. Comparison of IT and TT canola varieties in geographic zones of WA, 2003-4, Graham Walton and Hasan Zaheer, Department of Agriculture 4. Farmer scale canola variety trials in WA, 2004, Graham Walton, John Duff, Neil Harris and Heather Cosgriff, Oilseeds WA 5. Oilseed crops for industrial uses, Margaret C. Campbell, Centre for Legumes in Mediterranean Agriculture (CLIMA), Graham Walton,Department of Agriculture 6. Weed control opportunities with GM canola, Bill Crabtree, Independent Consultant, Northam 7. Soil and tissue tests for the sulfur requirements of canola, R.F. Brennan and M.D.A. Bolland, Department of Agriculture 8. Tests to predict the potassium requirements of canola, R.F. Brennan and M.D.A. Bolland, Department of Agriculture 9. Genotypic variation in potassium efficiency of canola, P.M. Damon and Z. Rengel, Faculty of Natural and Agricultural Sciences, UWA 10. Atrazine contamination of groundwater in the agricultural region of Western Australia, Russell Speed1, Neil Rothnie2, John Simons1, Ted Spadek2 and John Moore1;1Department of Agriculture, 2Chemistry Centre (WA) PESTS AND DISEASES 11. Controlling aphids and Beet western yellows virus in canola using imidacloprid seed dressing, Brenda Coutts and Roger Jones; Department of Agriculture 12. Managing sclerotinia in canola, Neil Harris, Dovuro Seeds Western Australia 13. Slugs, the trail of destruction in canola, Neil Harris, Dovuro Seeds Western Australia 14. Blackleg risk assessment and strategies for risk management in canola during 2005 and beyond, Moin Salam, Ravjit Khanguraand Art Diggle, Department of Agriculture 15. Modelling: BRAT – Blackleg Risk Appraisal Tool, Moin Salam, Ravjit KhanguraDepartment of Agricultur

Getting our ducks in a row:The need for data utility comparisons of healthcare systems data for clinical trials

BACKGROUND: Better use of healthcare systems data, collected as part of interactions between patients and the healthcare system, could transform planning and conduct of randomised controlled trials. Multiple challenges to widespread use include whether healthcare systems data captures sufficiently well the data traditionally captured on case report forms. "Data Utility Comparison Studies" (DUCkS) assess the utility of healthcare systems data for RCTs by comparison to data collected by the trial. Despite their importance, there are few published UK examples of DUCkS.METHODS-AND-RESULTS: Building from ongoing and selected recent examples of UK-led DUCkS in the literature, we set out experience-based considerations for the conduct of future DUCkS. Developed through informal iterative discussions in many forums, considerations are offered for planning, protocol development, data, analysis and reporting, with comparisons at "patient-level" or "trial-level", depending on the item of interest and trial status.DISCUSSION: DUCkS could be a valuable tool in assessing where healthcare systems data can be used for trials and in which trial teams can play a leading role. There is a pressing need for trials to be more efficient in their delivery and research waste must be reduced. Trials have been making inconsistent use of healthcare systems data, not least because of an absence of evidence of utility. DUCkS can also help to identify challenges in using healthcare systems data, such as linkage (access and timing) and data quality. We encourage trial teams to incorporate and report DUCkS in trials and funders and data providers to support them.</p

Getting our ducks in a row:The need for data utility comparisons of healthcare systems data for clinical trials

BACKGROUND: Better use of healthcare systems data, collected as part of interactions between patients and the healthcare system, could transform planning and conduct of randomised controlled trials. Multiple challenges to widespread use include whether healthcare systems data captures sufficiently well the data traditionally captured on case report forms. "Data Utility Comparison Studies" (DUCkS) assess the utility of healthcare systems data for RCTs by comparison to data collected by the trial. Despite their importance, there are few published UK examples of DUCkS.METHODS-AND-RESULTS: Building from ongoing and selected recent examples of UK-led DUCkS in the literature, we set out experience-based considerations for the conduct of future DUCkS. Developed through informal iterative discussions in many forums, considerations are offered for planning, protocol development, data, analysis and reporting, with comparisons at "patient-level" or "trial-level", depending on the item of interest and trial status.DISCUSSION: DUCkS could be a valuable tool in assessing where healthcare systems data can be used for trials and in which trial teams can play a leading role. There is a pressing need for trials to be more efficient in their delivery and research waste must be reduced. Trials have been making inconsistent use of healthcare systems data, not least because of an absence of evidence of utility. DUCkS can also help to identify challenges in using healthcare systems data, such as linkage (access and timing) and data quality. We encourage trial teams to incorporate and report DUCkS in trials and funders and data providers to support them.</p

Crop Updates 2005 Oilseeds

This session covers fifteen papers from different authors: 1. ACKNOWLEDGEMENTS, Douglas Hamilton, FARMING SYSTEMS DEVELOPMENT OFFICER CROP AGRONOMY AND NUTRITION 2. Canola workshop at Crop Updates 2005, Oilseeds WA, John Duff, EXECUTIVE OFFICER OILSEEDS WA 3. Comparison of IT and TT canola varieties in geographic zones of WA, 2003-4, Graham Walton and Hasan Zaheer, Department of Agriculture 4. Farmer scale canola variety trials in WA, 2004, Graham Walton, John Duff, Neil Harris and Heather Cosgriff, Oilseeds WA 5. Oilseed crops for industrial uses, Margaret C. Campbell, Centre for Legumes in Mediterranean Agriculture (CLIMA), Graham Walton,Department of Agriculture 6. Weed control opportunities with GM canola, Bill Crabtree, Independent Consultant, Northam 7. Soil and tissue tests for the sulfur requirements of canola, R.F. Brennan and M.D.A. Bolland, Department of Agriculture 8. Tests to predict the potassium requirements of canola, R.F. Brennan and M.D.A. Bolland, Department of Agriculture 9. Genotypic variation in potassium efficiency of canola, P.M. Damon and Z. Rengel, Faculty of Natural and Agricultural Sciences, UWA 10. Atrazine contamination of groundwater in the agricultural region of Western Australia, Russell Speed1, Neil Rothnie2, John Simons1, Ted Spadek2 and John Moore1;1Department of Agriculture, 2Chemistry Centre (WA) PESTS AND DISEASES 11. Controlling aphids and Beet western yellows virus in canola using imidacloprid seed dressing, Brenda Coutts and Roger Jones; Department of Agriculture 12. Managing sclerotinia in canola, Neil Harris, Dovuro Seeds Western Australia 13. Slugs, the trail of destruction in canola, Neil Harris, Dovuro Seeds Western Australia 14. Blackleg risk assessment and strategies for risk management in canola during 2005 and beyond, Moin Salam, Ravjit Khanguraand Art Diggle, Department of Agriculture 15. Modelling: BRAT – Blackleg Risk Appraisal Tool, Moin Salam, Ravjit KhanguraDepartment of Agricultur

Validating a Proteomic Signature of Severe COVID-19

OBJECTIVES:. COVID-19 is a heterogenous disease. Biomarker-based approaches may identify patients at risk for severe disease, who may be more likely to benefit from specific therapies. Our objective was to identify and validate a plasma protein signature for severe COVID-19. DESIGN:. Prospective observational cohort study. SETTING:. Two hospitals in the United States. PATIENTS:. One hundred sixty-seven hospitalized adults with COVID-19. INTERVENTION:. None. MEASUREMENTS AND MAIN RESULTS:. We measured 713 plasma proteins in 167 hospitalized patients with COVID-19 using a high-throughput platform. We classified patients as nonsevere versus severe COVID-19, defined as the need for high-flow nasal cannula, mechanical ventilation, extracorporeal membrane oxygenation, or death, at study entry and in 7-day intervals thereafter. We compared proteins measured at baseline between these two groups by logistic regression adjusting for age, sex, symptom duration, and comorbidities. We used lead proteins from dysregulated pathways as inputs for elastic net logistic regression to identify a parsimonious signature of severe disease and validated this signature in an external COVID-19 dataset. We tested whether the association between corticosteroid use and mortality varied by protein signature. One hundred ninety-four proteins were associated with severe COVID-19 at the time of hospital admission. Pathway analysis identified multiple pathways associated with inflammatory response and tissue repair programs. Elastic net logistic regression yielded a 14-protein signature that discriminated 90-day mortality in an external cohort with an area under the receiver-operator characteristic curve of 0.92 (95% CI, 0.88–0.95). Classifying patients based on the predicted risk from the signature identified a heterogeneous response to treatment with corticosteroids (p = 0.006). CONCLUSIONS:. Inpatients with COVID-19 express heterogeneous patterns of plasma proteins. We propose a 14-protein signature of disease severity that may have value in developing precision medicine approaches for COVID-19 pneumonia