What factors are associated with ambulance use for non-emergency problems in children?:A systematic mapping review and qualitative synthesis

Objective To explore what factors are associated with ambulance use for non-emergency problems in children. Methods This study is a systematic mapping review and qualitative synthesis of published journal articles and grey literature. Searches were conducted on the following databases, for articles published between January 1980 and July 2020: MEDLINE, EMBASE, PsycINFO, CINAHL and AMED. A Google Scholar and a Web of Science search were undertaken to identify reports or proceedings not indexed in the above. Book chapters and theses were searched via the OpenSigle, EThOS and DART databases. A literature advisory group, including experts in the field, were contacted for relevant grey literature and unpublished reports. The inclusion criteria incorporated articles published in the English language reporting findings for the reasons behind why there are so many calls to the ambulance service for non-urgent problems in children. Data extraction was divided into two stages: extraction of data to generate a broad systematic literature € map', and extraction of data from highly relevant papers using qualitative methods to undertake a focused qualitative synthesis. An initial table of themes associated with reasons for non-emergency calls to the ambulance for children formed the € thematic map' element. The uniting feature running through all of the identified themes was the determination of € inappropriateness' or € appropriateness' of an ambulance call out, which was then adopted as the concept of focus for our qualitative synthesis. Results There were 27 articles used in the systematic mapping review and 17 in the qualitative synthesis stage of the review. Four themes were developed in the systematic mapping stage: socioeconomic status/geographical location, practical reasons, fear of consequences and parental education. Three analytical themes were developed in the qualitative synthesis stage including practicalities and logistics of obtaining care, arbitrary scoring system and retrospection. Conclusions There is a lack of public and caregiver understanding about the use of ambulances for paediatrics. There are factors that appear specific to choosing ambulance care for children that are not so prominent in adults (fever, reassurance, fear of consequences). Future areas for attention to decrease ambulance activation for paediatric low-acuity reports were highlighted as: identifying strategies for helping caregivers to mitigate perceived risk, increasing availability of primary care, targeted education to particular geographical areas, education to first-time parents with infants and providing alternate means of transportation. PROSPERO registration number CRD42019160395

Association mapping of seed quality traits using the Canadian flax (Linum usitatissimum L.) core collection

KEY MESSAGE: The identification of stable QTL for seed quality traits by association mapping of a diverse panel of linseed accessions establishes the foundation for assisted breeding and future fine mapping in linseed. ABSTRACT: Linseed oil is valued for its food and non-food applications. Modifying its oil content and fatty acid (FA) profiles to meet market needs in a timely manner requires clear understanding of their quantitative trait loci (QTL) architectures, which have received little attention to date. Association mapping is an efficient approach to identify QTL in germplasm collections. In this study, we explored the quantitative nature of seed quality traits including oil content (OIL), palmitic acid, stearic acid, oleic acid, linoleic acid (LIO) linolenic acid (LIN) and iodine value in a flax core collection of 390 accessions assayed with 460 microsatellite markers. The core collection was grown in a modified augmented design at two locations over 3 years and phenotypic data for all seven traits were obtained from all six environments. Significant phenotypic diversity and moderate to high heritability for each trait (0.73–0.99) were observed. Most of the candidate QTL were stable as revealed by multivariate analyses. Nine candidate QTL were identified, varying from one for OIL to three for LIO and LIN. Candidate QTL for LIO and LIN co-localized with QTL previously identified in bi-parental populations and some mapped nearby genes known to be involved in the FA biosynthesis pathway. Fifty-eight percent of the QTL alleles were absent (private) in the Canadian cultivars suggesting that the core collection possesses QTL alleles potentially useful to improve seed quality traits. The candidate QTL identified herein will establish the foundation for future marker-assisted breeding in linseed. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00122-014-2264-4) contains supplementary material, which is available to authorized users

Why gender matters for biodiversity conservation

Addressing gender inequality in biodiversity conservation is fundamental to meeting the goals and targets of the Convention on Biological Diversity’s (CBD) Post-2020 Global Biodiversity Framework, and building synergies with the Sustainable Development Goals. There are positive outcomes for nature, equity and sustainability, and for overall community wellbeing when women access and control biodiversity and natural resources, can benefit equally from nature, and participate meaningfully in biodiversity-related decision making. This briefing provides evidence of the value of integrating gender into conservation interventions, suggesting that Parties to the CBD should therefore prioritise the gender-responsive implementation of the Post-2020 Global Biodiversity Framework, using the Gender Plan of Action as a guiding mechanism. It identifies key avenues for effective action on the ground, based on evidence from successful interventions

High-performance pipeline for MutMap and QTL-seq

[Summary] Bulked segregant analysis implemented in MutMap and QTL-seq is a powerful and efficient method to identify loci contributing to important phenotypic traits. However, the previous pipelines were not user-friendly to install and run. Here, we describe new pipelines for MutMap and QTL-seq. These updated pipelines are approximately 5–8 times faster than the previous pipeline, are easier for novice users to use, and can be easily installed through bioconda with all dependencies. [Availability] The new pipelines of MutMap and QTL-seq are written in Python and can be installed via bioconda. The source code and manuals are available online (MutMap: https://github.com/YuSugihara/MutMap, QTL-seq: https://github.com/YuSugihara/QTL-seq)

Comparative Analysis of Cadmium Uptake and Distribution in Flax

Non-Peer ReviewedHumans consume low quantities of cadmium (Cd), a non-nutritive and potentially toxic heavy metal, primarily via the dietary intake of grains. As part of a larger study designed to assist in the breeding of low Cd-accumulating flax varieties, we have conducted an experiment to determine physiological and developmental differences in Cd content in four flax cultivars (AC Emerson, Flanders, CDC Bethune, and AC McDuff). Our objective was to identify varietal differences in the uptake and distribution of Cd in various tissues among flax cultivars grown in naturally Cd-containing soil in a controlled environment. Cadmium concentration was dependent on the flax variety, developmental stage, and tissue type, as well as their interaction and our results suggest varietal differences in the mechanisms that determine Cd content in seeds. The results of this project, combined with those from genomics and field experiments, will support and accelerate the breeding of adapted flax varieties with low levels of Cd in the seed. Link to Video Presentation: https://youtu.be/0B49NbXL8g

Antibiotic prescribing in UK out-of-hours primary care services: a realist-informed scoping review of training and guidelines for healthcare professionals

Background: Antibiotic overuse has contributed to antimicrobial resistance, which is a global public health problem. In the UK, despite the fall in rates of antibiotic prescription since 2013, prescribing levels remain high in comparison with other European countries. Prescribing in out-of-hours (OOH) care provides unique challenges for prudent prescribing, for which professionals may not be prepared. Aim: To explore the guidance available to professionals on prescribing antibiotics for common infections in OOH primary care within the UK, with a focus on training resources, guidelines, and clinical recommendations. Design & setting: A realist-informed scoping review of peer-reviewed articles and grey literature. Method: The review focused on antibiotic prescribing OOH (for example, clinical guidelines and training videos). General prescribing guidance was searched whenever OOH-focused resources were unavailable. Electronic databases and websites of national agencies and professional societies were searched following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards. Findings were organised according to realist review components, that is, mechanisms, contexts, and outcomes. Results: In total, 46 clinical guidelines and eight training resources were identified. Clinical guidelines targeted adults and children, and included recommendations on prescription strategy, spectrum of the antibiotic prescribed, communication with patients, treatment duration, and decision-making processes. No clinical guidelines or training resources focusing specifically on OOH were found. Conclusion: The results highlight a lack of knowledge about whether existing resources address the challenges faced by OOH antibiotic prescribers. Further research is needed to explore the training needs of OOH health professionals, and whether further OOH-focused resources need to be developed given the rates of antibiotic prescribing in this setting

Predicting dementia from primary care records: a systematic review and meta-analysis

Introduction Possible dementia is usually identified in primary care by general practitioners (GPs) who refer to specialists for diagnosis. Only two-thirds of dementia cases are currently recorded in primary care, so increasing the proportion of cases diagnosed is a strategic priority for the UK and internationally. Clinical entities in the primary care record may indicate risk of developing dementia, and could be combined in a predictive model to help find patients who are missing a diagnosis. We conducted a meta-analysis to identify clinical entities with potential for use in such a predictive model for dementia in primary care. Methods and Findings We conducted a systematic search in PubMed, Web of Science and primary care database bibliographies. We included cohort or case-control studies which used routinely collected primary care data, to measure the association between any clinical entity and dementia. Meta-analyses were performed to pool odds ratios. A sensitivity analysis assessed the impact of non-independence of cases between studies. From a sift of 3836 papers, 20 studies, all European, were eligible for inclusion, comprising >1 million patients. 75 clinical entities were assessed as risk factors for all cause dementia, Alzheimer’s (AD) and Vascular dementia (VaD). Data included were unexpectedly heterogeneous, and assumptions were made about definitions of clinical entities and timing as these were not all well described. Meta-analysis showed that neuropsychiatric symptoms including depression, anxiety, and seizures, cognitive symptoms, and history of stroke, were positively associated with dementia. Cardiovascular risk factors such as hypertension, heart disease, dyslipidaemia and diabetes were positively associated with VaD and negatively with AD. Sensitivity analyses showed similar results. Conclusions These findings are of potential value in guiding feature selection for a risk prediction tool for dementia in primary care. Limitations include findings being UK-focussed. Further predictive entities ascertainable from primary care data, such as changes in consulting patterns, were absent from the literature and should be explored in future studies

Quantification of Low-level GM Seed Presence in Canadian Commercial Flax Stocks

Detection and quantification of the prevalence of genetically modified (GM) organism contamination in seed exports is a critical element of regulatory compliance. While the procedures to reliably detect high levels of GM contamination are well understood, no comparable statistical approaches are available for the quantification of levels of GM prevalence below the established detection rate of standard tests. Presented is a simple statistical approach based on simulation modeling for the quantification of low levels of GM contamination. The approach can be modified to match any sampling regime and can account for rates of false positive and negative assay results. The application of this method is demonstrated using the low level of contamination in Canadian commercial flax stocks by the GM flax variety "Triffid." We show that rates of GM contamination in commercial flax stocks ranged between 1 GM seed per million and 1 seed per hundred thousand. A simulation model was used to determine whether the observed rates of positive tests are within the range expected from false positive rates of the test. We showed that for the majority of categories of grain or seed, the very low level of GM prevalence still remains outside that which is to be expected based on false positives returned or by chance alone. These results indicate a pervasive low-level presence of GM construct in the Canadian commercial flax system

Using the General Linear Mixed Model (GLMM) to Predict Yield of New Flax Cultivars

Non-Peer ReviewedTraditional approaches to analyzing data generated in plant breeding programs involve the use of ANOVA and an overall average of genotypic performance across environments and/or years. This approach, in some cases, is an oversimplification as it does not handle the unbalanced data that generally accompanies multi-environment and multi-year data well, nor does it allow for heterogeneity of variance. Typically new entries with fewer site years of data are susceptible to large sways in mean values when the check cultivars they are compared to experience unusual values due to the environment. Use of a generalized linear mixed model (GLMM) to predict means using all available information across locations and years results in more accurate comparisons and prediction of superior genotypes. Firstly, the need for a complex modelling system and the benefits of using GLMM will be illustrated using yield of flax cultivars in multi-environment trials. Moreover, using wheat and flax as examples, we will compare the traditional statistical approaches and the mixed model. We will conduct a brief demonstration on the use of R and ASReml software to generate predicted means using a GLMM. Importantly use of the GLMM gives a more representative trait mean for new cultivars, and thus, more accurate comparisons regarding potential performance in commercial fields

Optimal models in the yield analysis of new flax cultivars

Multi-environment trials (MET) are conducted to evaluate the performance of cultivars. In a combined analysis the mixed model is superior to analysis of variance (ANOVA) for evaluating and comparing cultivars and dealing with an unbalanced data structure. This study seeks to identify the optimal models using the Saskatchewan Variety Performance Group (SVPG) post-registration regional trial data for flax. Yield data were collected for 15 entries in post-registration tests conducted in Saskatchewan from 2007 to 2016 (except 2011) and 16 mixed models with homogeneous or heterogeneous residual errors were compared. A compound symmetry model with heterogeneous residual error (CSR) had the best fit, with a normal distribution of residuals and a mean of zero fitted to the trial data for each year. The compound symmetry model with homogeneous residual error (CS) and a model extending the CSR to higher dimensions (DIAGR) were the next best models in most cases. Five hundred random samples from a two-stage sampling method were produced to determine the optimal models suitable for various environments. The CSR model was superior to other models for 396 of 500 samples (79.2%). The top three models CSR, CS, and DIAGR had higher statistical power and could be used to access the yield stability of the new flax cultivars. Optimal mixed models are recommended for future data analysis of new flax cultivars in regional tests.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author