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585). Trait culling was more effective to overcome collinearity. Mass of grains, number of nodes, and number of pods are promising for indirect selection for oil content.Social media has become an emerging alternative to opinion polls for public opinion collection, while it is still posing many challenges as a passive data source, such as structurelessness, quantifiability, and representativeness. [https://www.selleckchem.com/products/pamapimod-r-1503-ro4402257.html Pamapimod] Social media data with geotags provide new opportunities to unveil the geographic locations of users expressing their opinions. This paper aims to answer two questions 1) whether quantifiable measurement of public opinion can be obtained from social media and 2) whether it can produce better or complementary measures compared to opinion polls. This research proposes a novel approach to measure the relative opinion of Twitter users towards public issues in order to accommodate more complex opinion structures and take advantage of the geography pertaining to the public issues. To ensure that this new measure is technically feasible, a modeling framework is developed including building a training dataset by adopting a state-of-the-art approach and devising a new deep learning method called Opinion-Oriented Word Embedding. With a case study of tweets on the 2016 U.S. presidential election, we demonstrate the predictive superiority of our relative opinion approach and we show how it can aid visual analytics and support opinion predictions. Although the relative opinion measure is proved to be more robust than polling, our study also suggests that the former can advantageously complement the latter in opinion prediction.Introduction Depression is a global burden that is exacerbated by smoking. The association between depression and chronic smoking is well-known; however, existing findings contain possible confounding between nicotine dependence (ND), a latent construct measuring addiction, and objective smoking behavior. The current study examines the possible unique role of ND in explaining depression, independently of smoking behavior. Methods A nationally-representative sample of current adult daily smokers was drawn by pooling three independent, cross-sectional, biennial waves (spanning 2011-16) of the National Health and Nutrition Examination Survey (NHANES). The association between ND (operationally defined as time to first cigarette (TTFC) after waking) and the amount of depression symptoms was examined after adjusting for both current and lifetime smoking behaviors (cigarettes per day and years of smoking duration) and sociodemographic factors (gender, age, race, education and income to poverty ratio). Results Earlier TTFC was associated with more depression symptoms, such that those smoking within 5 minutes of waking had an approximately 1.6-fold higher depression score (PRR = 1.576, 95% CI = 1.324-1.687) relative to those who smoke more than 1 hour after waking. This relationship remained significant after adjusting for current and lifetime smoking behavior as well as sociodemographic factors (PRR = 1.370, 95% CI = 1.113, 1.687). Conclusions The latent construct of ND, as assessed by TTFC, may be associated with an additional risk for depression symptoms, beyond that conveyed by smoking behavior alone. This finding can be used for more refined risk prediction for depression among smokers.Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a novel coronavirus that has caused a worldwide pandemic of the human respiratory illness COVID-19, resulting in a severe threat to public health and safety. Analysis of the genetic tree suggests that SARS-CoV-2 belongs to the same Betacoronavirus group as severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV). Although the route for viral transmission remains a mystery, SARS-CoV-2 may have originated in an animal reservoir, likely that of bat. The clinical features of COVID-19, such as fever, cough, shortness of breath, and fatigue, are similar to those of many acute respiratory infections. There is currently no specific treatment for COVID-19, but antiviral therapy combined with supportive care is the main strategy. Here, we summarize recent progress in understanding the epidemiological, virological, and clinical characteristics of COVID-19 and discuss potential targets with existing drugs for the treatment of this emerging zoonotic disease.Human IgE-binding monocytes are identified as allergic disease mediators, but it is unknown whether IgE-binding monocytes promote or prevent an allergic response. We identified IgE-binding monocytes in equine peripheral blood as IgE+/MHCIIhigh/CD14low cells that bind IgE through an FcεRI αɣ variant. IgE-binding monocytes were analyzed monthly in Culicoides hypersensitive horses and nonallergic horses living together with natural exposure to Culicoides midges. The phenotype and frequency of IgE-binding monocytes remained consistent in all horses regardless of Culicoides exposure. All horses upregulated IgE-binding monocyte CD16 expression following initial Culicoides exposure. Serum total IgE concentration and monocyte surface IgE densities were positively correlated in all horses. We also demonstrated that IgE-binding monocytes produce IL-10, but not IL-4, IL-17A, or IFN-γ, following IgE crosslinking. In conclusion, we have characterized horse IgE-binding monocytes for the first time and further studies of these cells may provide important connections between regulation and cellular mechanisms of IgE-mediated diseases.Background The variable course of autosomal dominant polycystic kidney disease (ADPKD), and the advent of renoprotective treatment require early risk stratification. We applied urinary metabolomics to explore differences associated with estimated glomerular filtration rate (eGFR; CKD-EPI equation) and future eGFR decline. Methods Targeted, quantitative metabolic profiling (1H NMR-spectroscopy) was performed on baseline spot urine samples obtained from 501 patients with ADPKD. The discovery cohort consisted of 338 patients (56% female, median values for age 46 [IQR 38 to 52] years, eGFR 62 [IQR 45 to 85] ml/min/1.73m2, follow-up time 2.5 [range 1 to 3] years, and annual eGFR slope -3.3 [IQR -5.3 to -1.3] ml/min/1.73m2/year). An independent cohort (n = 163) was used for validation. Multivariate modelling and linear regression were used to analyze the associations between urinary metabolites and eGFR, and eGFR decline over time. Results Twenty-nine known urinary metabolites were quantified from the spectra using a semi-automatic quantification routine.