Nitrogen Response and Economics for Irrigated Corn in Nebraska

Nitrogen management recommendations may change as yield levels and efficiency of crop production increase. The mean yield with adequate nutrient availability in 32 irrigated corn (Zea mays L.) trials conducted across Nebraska to evaluate crop response to split-applied N was 14.8 Mg per ha. The mean economically optimal N rates (EONR) for irrigated corn varied with the fertilizer N to grain price ratio. At a fertilizer N:corn price ratio of 7, the EONR was 171, 122, and 93 kg per hectare, respectively, for cropping systems with corn following corn (CC), soybean (Glycine max L.) (CS), and drybean (Phaseolus vulgaris L.) (CD). At this price ratio the present University of Nebraska (UNL) recommendation procedure gave mean N recommendations that were 17.2, 0.3, and 68.1 kg per hectare higher than the mean EONR determined in this study for CC, CS, and CD, respectively. The UNL algorithm, adjusted for mean cropping system EONR gave more accurate prediction of site-year EONR than alternative N rate predictions for CC and CD with returns to applied N (RTN) of -$22 and -$13 per hectare compared with measured site-year EONR. Prediction of site-year EONR using mean EONR adjusted for soil organic matter was more accurate for CS than other methods with an RTN of -$6 per hectare compared with measured site-year EONR. Further research is needed to extend the results to: lower yield situations, alternatives to split application of N, and adjustment of EONR to protect against inadequate N in atypical seasons or for environmental protection

High-yielding corn response to applied phosphorus, potassium, and sulfur in Nebraska

Nutrient management recommendations may change as yield levels and efficiency of crop production increase. Recommendations for P, K, and S were evaluated using results from 34 irrigated corn (Zea mays L.) trials conducted in diverse situations across Nebraska. The mean yield was 14.7 Mg ha–1 with adequate fertilizer applied. The median harvest index values were 0.52, 0.89, 0.15, and 0.56 for biomass, P, K, and S, respectively. Median grain yields were 372, 49, and 613 kg kg–1 of aboveground plant uptake of P, K, and S, respectively. The estimated critical Bray-1 P level for corn response to 20 kg P ha–1 was 20 mg kg–1 when the previous crop was corn compared with 10 mg kg–1 when corn followed soybean [Glycine max (L.) Merr.]. Soil test K was generally high with only three site-years <125 mg kg–1. Over all trials, application of 40 kg K ha–1 resulted in a 0.2 Mg ha–1 mean grain yield decrease. Application of 22 kg S ha–1 did not result in significant yield increase in any trial. Soil test results accounted for twice as much variation in nutrient uptake when soil organic matter (SOM) and pH were considered in addition to the soil test nutrient values. The results indicate a need to revise the current recommendation for P, to maintain the current K and S recommendations, and to use SOM and pH in addition to soil test nutrient values in estimating applied nutrient requirements for irrigated high yield corn production

Nitrogen Use Efficiency of Irrigated Corn for Three Cropping Systems in Nebraska

Nitrogen use efficiency (NUE) is of economic and environmental importance. Components of NUE were evaluated in 32 irrigated corn (Zea mays L.) trials conducted across Nebraska with different N rates and where the previous crop was either corn (CC), drybean (Phaseolus vulgaris L.) (CD), or soybean (Glycine max L.) (CS). The mean grain yield with adequate nutrient availability was 14.7 Mg ha–1 . When no N was applied, measured soil properties and irrigation water N accounted for <20% of the variation in plant N uptake (UN). Mean fertilizer N recovery in above-ground biomass was 74% at the lowest N rate compared with 40% at the highest N rate, a mean of 64% at the economically optimal N rate (EONR), and least with CD. Agronomic efficiency of fertilizer N averaged 29 kg grain kg-1 N at EONR and was also least with CD. Partial factor productivity of N averaged 100 kg grain kg-1 N at EONR, and was greater with CS compared with CC and CD. After harvest, residual soil nitrate-N (RSN) in the 0 to 1.2 m depth ranged from 21 to 121 kg ha-1 and increased with N rate. Mean RSN was 88, 59, and 59 kg ha-1 for CD, CC, and CS, respectively. High corn yields can be achieved with high NUE and low RSN by management to maximize profitability in consideration of yield potential, and by applying N at the right amount and time

Uncovering precision phenotype-biomarker associations in traumatic brain injury using topological data analysis

Background: Traumatic brain injury (TBI) is a complex disorder that is traditionally stratified based on clinical signs and symptoms. Recent imaging and molecular biomarker innovations provide unprecedented opportunities for improved TBI precision medicine, incorporating patho-anatomical and molecular mechanisms. Complete integration of these diverse data for TBI diagnosis and patient stratification remains an unmet challenge. Methods and findings: The Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) Pilot multicenter study enrolled 586 acute TBI patients and collected diverse common data elements (TBI-CDEs) across the study population, including imaging, genetics, and clinical outcomes. We then applied topology-based data-driven discovery to identify natural subgroups of patients, based on the TBI-CDEs collected. Our hypothesis was two-fold: 1) A machine learning tool known as topological data analysis (TDA) would reveal data-driven patterns in patient outcomes to identify candidate biomarkers of recovery, and 2) TDA-identified biomarkers would significantly predict patient outcome recovery after TBI using more traditional methods of univariate statistical tests. TDA algorithms organized and mapped the data of TBI patients in multidimensional space, identifying a subset of mild TBI patients with a specific multivariate phenotype associated with unfavorable outcome at 3 and 6 months after injury. Further analyses revealed that this patient subset had high rates of post-traumatic stress disorder (PTSD), and enrichment in several distinct genetic polymorphisms associated with cellular responses to stress and DNA damage (PARP1), and in striatal dopamine processing (ANKK1, COMT, DRD2). Conclusions: TDA identified a unique diagnostic subgroup of patients with unfavorable outcome after mild TBI that were significantly predicted by the presence of specific genetic polymorphisms. Machine learning methods such as TDA may provide a robust method for patient stratification and treatment planning targeting identified biomarkers in future clinical trials in TBI patients

Inequalities in health and community-oriented social work: lessons from Cuba?

Social justice is, as the World Health Organization Commission on Social Determinants of Health (WHO CSDH, 2008) reminds us, ‘a matter of life and death’. While the stark differences in mortality rates and life expectancy between rich and poor countries might be the most obvious example of this, it is also true that ‘Within countries, the differences in life chances are dramatic and are seen in all countries – even the richest’ (WHO CSDH, 2008: 26). As the Commission demonstrates, the roots of these inequities lie in social conditions, suggesting an important role for social work in this area. Unfortunately, the Commission says very little about the type of social work that might be appropriate: nevertheless, the report does provide fresh impetus to the debate about what social workers might contribute to tackling health inequalities. In this article, we suggest that a community-oriented approach to social work is required. In making a case for this, we review the progress of the government’s drive to reduce inequalities in England,1 arguing that this has, thus far, been largely unsuccessful because it has primarily been pursued through health-care services, while addressing the wider (social) determinants of health has been a secondary consideration. In contrast, we offer the example of Cuban community-oriented social work (COSW) which has helped maintain population health at a level that stands comparison with much wealthier nations, despite the hardships and inequalities which followed economic collapse in the 1990s. In many ways the Cuban situation is unusual, perhaps unique, so we are not arguing that Cuban social work methods can be readily transferred. Rather, we suggest that, in the neglected field of tackling health inequalities, social workers can learn from the general approach taken in Cuba. To establish the context of this discussion, we begin by defining key concepts: COSW itself, health inequalities and inequity, the health gap and the health gradient

Toward an internally consistent astronomical distance scale

Accurate astronomical distance determination is crucial for all fields in astrophysics, from Galactic to cosmological scales. Despite, or perhaps because of, significant efforts to determine accurate distances, using a wide range of methods, tracers, and techniques, an internally consistent astronomical distance framework has not yet been established. We review current efforts to homogenize the Local Group's distance framework, with particular emphasis on the potential of RR Lyrae stars as distance indicators, and attempt to extend this in an internally consistent manner to cosmological distances. Calibration based on Type Ia supernovae and distance determinations based on gravitational lensing represent particularly promising approaches. We provide a positive outlook to improvements to the status quo expected from future surveys, missions, and facilities. Astronomical distance determination has clearly reached maturity and near-consistency.Comment: Review article, 59 pages (4 figures); Space Science Reviews, in press (chapter 8 of a special collection resulting from the May 2016 ISSI-BJ workshop on Astronomical Distance Determination in the Space Age

Apolipoprotein E epsilon 4 (APOE-ε4) genotype is associated with decreased 6-month verbal memory performance after mild traumatic brain injury

Introduction: The apolipoprotein E (APOE) ε4 allele associates with memory impairment in neurodegenerative diseases. Its association with memory after mild traumatic brain injury (mTBI) is unclear. Methods: mTBI patients (Glasgow Coma Scale score 13–15, no neurosurgical intervention, extracranial Abbreviated Injury Scale score ≤1) aged ≥18 years with APOE genotyping results were extracted from the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study. Cohorts determined by APOE-ε4(+/−) were assessed for associations with 6-month verbal memory, measured by California Verbal Learning Test, Second Edition (CVLT-II) subscales: Immediate Recall Trials 1–5 (IRT), Short-Delay Free Recall (SDFR), Short-Delay Cued Recall (SDCR), Long-Delay F

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types