Greenhouse gas emissions from solid and liquid organic fertilizers applied to lettuce

Improper application of nitrogen (N) fertilizer and environmental factors can cause the loss of nitrous oxide (N2O) to the environment. Different types of fertilizers with different C/N ratios may have different effects on the environment. The focus of this study was to evaluate the effects of environmental factors and four organic fertilizers (feather meal, blood meal, fish emulsion, and cyano-fertilizer) applied at different rates (0, 28, 56, and 112 kg N ha−1) on N2O emissions and to track CO2 emissions from a lettuce field (Lactuca sativa L.). The study was conducted in 2013 and 2014 and compared preplant-applied solid fertilizers (feather meal and blood meal) and multiple applications of liquid fertilizers (fish emulsion and cyano-fertilizer). Three days a week, N2O and CO2 emissions were measured twice per day in 2013 and once per day in 2014 using a closed-static chamber, and gas samples were analyzed by gas chromatography. Preplant-applied solid fertilizers significantly increased cumulative N2O emissions as compared with control, but multiple applications of liquid fertilizers did not. Emission factors for N2O ranged from 0 to 0.1% for multiple applications of liquid fertilizers and 0.6 to 11% for preplant-applied solid fertilizers, which could be overestimated due to chamber placement over fertilizer bands. In 2014, solid fertilizers with higher C/N ratios (3.3–3.5) resulted in higher CO2 emissions than liquid fertilizers (C/N ratio, 0.9–1.5). Therefore, organic farmers should consider the use of multiple applications of liquid fertilizers as a means to reduce soil greenhouse gas emissions while maintaining high yields

An improved microarray image analysis architecture using mathematical morphology

DNA microarrays are now widely used to measure gene expression levels of healthy and cancerous cells. To allow further experiment for drug development to treat cancer, colour intensity from images of microarray spots need to be extracted as accurate as possible. The intensity extraction requires pre-requisite analysis stages including noise removal, and followed by location gridding. However, it remains as a challenging task for microarray analysis due to the variation of noise that infested the images. In this study, microarray analysis architecture using mathematical morphology was proposed, namely Mathematical Morphology Microarray Image Analysis (MaMIA).Firstly, in denoising stage, noise identification is conducted to identify and reverse the noise. Next, combinations of mathematical morphology were applied to the microarray and its pixel derivatives during the gridding stage. Raw microarrays used by MaMIA are available at Stanford Microarray Database (SMD), Gene Expression Omnibus (GEO) and from a dilution experiment (DILN). From comparisons with previous existing architectures, Optimal Multilevel Thresholding (OMTG) and Automated Robust MicroArray Data Analysis (ARMADA), MaMIA have proven to efficiently remove noise with highest value, 81.6657dB for Peak Signal to Noise Ratio (PSNR) and success identification of spots in cases of noises; with highest gridding accuracy level of 98.34%.Overall processing time, MaMIA architecture can perform gridding in less than 22 seconds, fastest as compared to its contender. This research have revealed the potential of analysing microarray by mainly using mathematical morphology operation, either applied on microarray or its pixel derivative

Atrasentan and renal events in patients with type 2 diabetes and chronic kidney disease (SONAR): a double-blind, randomised, placebo-controlled trial

Background: Short-term treatment for people with type 2 diabetes using a low dose of the selective endothelin A receptor antagonist atrasentan reduces albuminuria without causing significant sodium retention. We report the long-term effects of treatment with atrasentan on major renal outcomes. Methods: We did this double-blind, randomised, placebo-controlled trial at 689 sites in 41 countries. We enrolled adults aged 18–85 years with type 2 diabetes, estimated glomerular filtration rate (eGFR)25–75 mL/min per 1·73 m 2 of body surface area, and a urine albumin-to-creatinine ratio (UACR)of 300–5000 mg/g who had received maximum labelled or tolerated renin–angiotensin system inhibition for at least 4 weeks. Participants were given atrasentan 0·75 mg orally daily during an enrichment period before random group assignment. Those with a UACR decrease of at least 30% with no substantial fluid retention during the enrichment period (responders)were included in the double-blind treatment period. Responders were randomly assigned to receive either atrasentan 0·75 mg orally daily or placebo. All patients and investigators were masked to treatment assignment. The primary endpoint was a composite of doubling of serum creatinine (sustained for ≥30 days)or end-stage kidney disease (eGFR <15 mL/min per 1·73 m 2 sustained for ≥90 days, chronic dialysis for ≥90 days, kidney transplantation, or death from kidney failure)in the intention-to-treat population of all responders. Safety was assessed in all patients who received at least one dose of their assigned study treatment. The study is registered with ClinicalTrials.gov, number NCT01858532. Findings: Between May 17, 2013, and July 13, 2017, 11 087 patients were screened; 5117 entered the enrichment period, and 4711 completed the enrichment period. Of these, 2648 patients were responders and were randomly assigned to the atrasentan group (n=1325)or placebo group (n=1323). Median follow-up was 2·2 years (IQR 1·4–2·9). 79 (6·0%)of 1325 patients in the atrasentan group and 105 (7·9%)of 1323 in the placebo group had a primary composite renal endpoint event (hazard ratio [HR]0·65 [95% CI 0·49–0·88]; p=0·0047). Fluid retention and anaemia adverse events, which have been previously attributed to endothelin receptor antagonists, were more frequent in the atrasentan group than in the placebo group. Hospital admission for heart failure occurred in 47 (3·5%)of 1325 patients in the atrasentan group and 34 (2·6%)of 1323 patients in the placebo group (HR 1·33 [95% CI 0·85–2·07]; p=0·208). 58 (4·4%)patients in the atrasentan group and 52 (3·9%)in the placebo group died (HR 1·09 [95% CI 0·75–1·59]; p=0·65). Interpretation: Atrasentan reduced the risk of renal events in patients with diabetes and chronic kidney disease who were selected to optimise efficacy and safety. These data support a potential role for selective endothelin receptor antagonists in protecting renal function in patients with type 2 diabetes at high risk of developing end-stage kidney disease. Funding: AbbVie

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security