Monitoring Soil Quality to Assess the Sustainability of Harvesting Corn Stover

Harvesting feedstock for biofuel production must not degrade soil, water, or air resources. Our objective is to provide an overview of field research being conducted to quantify effects of harvesting corn (Zea mays L.) stover as a bioenergy feedstock. Coordinated field studies are being conducted near Ames, IA; St. Paul and Morris, MN; Mead, NE; University Park, PA; Florence, SC; and Brookings, SD., as part of the USDA-ARS Renewable Energy Assessment Project (REAP). A baseline soil quality assessment was made using the Soil Management Assessment Framework (SMAF). Corn grain and residue yield for two different stover harvest rates (∼50% and ∼90%) are being measured. Available soil data remains quite limited but sufficient for an initial SMAF analysis that confirms total organic carbon (TOC) is a soil quality indicator that needs to be closely monitored closely to quantify crop residue removal effects. Overall, grain yields averaged 9.7 and 11.7 Mg ha−1 (155 and 186 bu acre−1) in 2008 and 2009, values that are consistent with national averages for both years. The average amount of stover collected for the 50% treatment was 2.6 and 4.2 Mg ha−1 for 2008 and 2009, while the 90% treatment resulted in an average removal of 5.4 and 7.4 Mg ha−1, respectively. Based on a recent literature review, both stover harvest scenarios could result in a gradual decline in TOC. However, the literature value has a large standard error, so continuation of this long-term multi-location study for several years is warranted

Adjuvant bevacizumab for melanoma patients at high risk of recurrence: survival analysis of the AVAST-M trial

Background: Bevacizumab is a recombinant humanised monoclonal antibody to vascular endothelial growth factor shown to improve survival in advanced solid cancers. We evaluated the role of adjuvant bevacizumab in melanoma patients at high risk of recurrence. Patients and methods: Patients with resected AJCC stage IIB, IIC and III cutaneous melanoma were randomised to receive either adjuvant bevacizumab (7.5?mg/kg i.v. 3 weekly for 1?year) or standard observation. The primary end point was detection of an 8% difference in 5-year overall survival (OS) rate; secondary end points included disease-free interval (DFI) and distant metastasis-free interval (DMFI). Tumour and blood were analysed for prognostic and predictive markers. Results: Patients (n=1343) recruited between 2007 and 2012 were predominantly stage III (73%), with median age 56?years (range 18-88?years). With 6.4-year median follow-up, 515 (38%) patients had died [254 (38%) bevacizumab; 261 (39%) observation]; 707 (53%) patients had disease recurrence [336 (50%) bevacizumab, 371 (55%) observation]. OS at 5?years was 64% for both groups [hazard ratio (HR) 0.98; 95% confidence interval (CI) 0.82-1.16, P?=?0.78). At 5?years, 51% were disease free on bevacizumab versus 45% on observation (HR 0.85; 95% CI 0.74-0.99, P?=?0.03), 58% were distant metastasis free on bevacizumab versus 54% on observation (HR 0.91; 95% CI 0.78-1.07, P?=?0.25). Forty four percent of 682 melanomas assessed had a BRAFV600 mutation. In the observation arm, BRAF mutant patients had a trend towards poorer OS compared with BRAF wild-type patients (P?=?0.06). BRAF mutation positivity trended towards better OS with bevacizumab (P?=?0.21). Conclusions: Adjuvant bevacizumab after resection of high-risk melanoma improves DFI, but not OS. BRAF mutation status may predict for poorer OS untreated and potential benefit from bevacizumab. Clinical Trial Information: ISRCTN 81261306; EudraCT Number: 2006-005505-64

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries