34 research outputs found

    CropPol: a dynamic, open and global database on crop pollination

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    Seventy five percent of the world's food crops benefit from insect pollination. Hence, there has been increased interest in how global change drivers impact this critical ecosystem service. Because standardized data on crop pollination are rarely available, we are limited in our capacity to understand the variation in pollination benefits to crop yield, as well as to anticipate changes in this service, develop predictions, and inform management actions. Here, we present CropPol, a dynamic, open and global database on crop pollination. It contains measurements recorded from 202 crop studies, covering 3,394 field observations, 2,552 yield measurements (i.e. berry weight, number of fruits and kg per hectare, among others), and 47,752 insect records from 48 commercial crops distributed around the globe. CropPol comprises 32 of the 87 leading global crops and commodities that are pollinator dependent. Malus domestica is the most represented crop (32 studies), followed by Brassica napus (22 studies), Vaccinium corymbosum (13 studies), and Citrullus lanatus (12 studies). The most abundant pollinator guilds recorded are honey bees (34.22% counts), bumblebees (19.19%), flies other than Syrphidae and Bombyliidae (13.18%), other wild bees (13.13%), beetles (10.97%), Syrphidae (4.87%), and Bombyliidae (0.05%). Locations comprise 34 countries distributed among Europe (76 studies), Northern America (60), Latin America and the Caribbean (29), Asia (20), Oceania (10), and Africa (7). Sampling spans three decades and is concentrated on 2001-05 (21 studies), 2006-10 (40), 2011-15 (88), and 2016-20 (50). This is the most comprehensive open global data set on measurements of crop flower visitors, crop pollinators and pollination to date, and we encourage researchers to add more datasets to this database in the future. This data set is released for non-commercial use only. Credits should be given to this paper (i.e., proper citation), and the products generated with this database should be shared under the same license terms (CC BY-NC-SA). This article is protected by copyright. All rights reserved

    COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

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    Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≀ 18 years: 69, 48, 23; 85%), older adults (≄ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

    Surveillance of adult Aedes

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    Objective To determine the effectiveness of using sticky traps and the NS1 dengue antigen kit for the surveillance of Aedes mosquitoes for dengue control. methods Apartments were selected in a dengue-endemic area, and sticky traps were set to capture adult Aedes mosquitoes. NS1 dengue antigen kit was used to detect dengue antigen in mosquitoes, and positive mosquitoes were serotyped using real-time RT-PCR. results The sticky traps were effective in capturing Aedes aegypti, and a minimum of three traps per floor was sufficient. Multiple serotypes were found in individual mosquitoes. conclusion The sticky trap and the NS1 dengue antigen test kit can be used as surveillance tool in dengue control programmes. This proactive method will be better suited for control programmes than current reactive methods

    Imputation of genetic composition for missing pedigree data in Serrasalmidae using morphometric data

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    This study aimed to impute the genetic makeup of individual fishes of Serrasalmidae family on the basis of body weight and morphometric measurements. Eighty-three juveniles, belonging to the genetic groups Pacu, Pirapitinga, Tambaqui, Tambacu, Tambatinga, Patinga, Paqui and Piraqui, were separated into 16 water tanks in a recirculation system, with two tanks per genetic group, where they remained until they reached 495 days of age. They were then weighed and analyzed according to the following morphometric parameters: Standard Length (SL), Head Length (HL), Body Height (BH), and Body Width (BW). The identity of each fish was confirmed with two SNPs and two mitochondrial markers. Two analyses were performed: one for the validating the imputation and another for imputing a genetic composition of animals considered to be advanced hybrids (post F1). In both analyses, we used linear mixed models with a mixture of normal distributions to impute the genetic makeup of the fish based on phenotype. We applied the mixed models method, whereby the environmental effects were estimated by the Empirical Best Linear Unbiased Estimator (EBLUE) and genetic effects are considered random, obtaining the Empirical Best Linear Unbiased Predictor (EBLUP) from the general (GCA) and the specific (SCA) combining ability effects. The results showed that validation of the genetic makeup imputation based on body weight can be used because of the strong correlation between the observed and imputed genotype. The fish classified as advanced hybrids had a genetic composition with a high probability of belonging to known genotypes and there was consistency in genotype imputation according to the different characteristics used
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