A systematic review on the possible relationship between bilingualism, cognitive decline, and the onset of dementia

A systematic review was conducted to investigate whether bilingualism has a protective effect against cognitive decline in aging and can protect against dementia. We searched the Medline, ScienceDirect, Scopus, and ERIC databases with a cut-off date of 31 March 2019, thereby following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) protocol. Our search resulted in 34 eligible studies. Mixed results were found with respect to the protective effect of bilingualism against cognitive decline. Several studies showed a protective effect whereas other studies failed to find it. Moreover, evidence for a delay of the onset of dementia of between 4 and 5.5 years in bilingual individuals compared to monolinguals was found in several studies, but not in all. Methodological differences in the set-up of the studies seem to explain these mixed results. Lifelong bilingualism is a complex individual process, and many factors seem to influence this and need to be further investigated. This can be best achieved through large longitudinal studies with objective behavioral and neuroimaging measurements. In conclusion, although some evidence was found for a cognitive reserve-enhancing effect of lifelong bilingualism and protection against dementia, to date, no firm conclusions can be drawn

Organizational culture, team climate and diabetes care in small office-based practices

Contains fulltext : 71456.pdf ( ) (Open Access)BACKGROUND: Redesigning care has been proposed as a lever for improving chronic illness care. Within primary care, diabetes care is the most widespread example of restructured integrated care. Our goal was to assess to what extent important aspects of restructured care such as multidisciplinary teamwork and different types of organizational culture are associated with high quality diabetes care in small office-based general practices. METHODS: We conducted cross-sectional analyses of data from 83 health care professionals involved in diabetes care from 30 primary care practices in the Netherlands, with a total of 752 diabetes mellitus type II patients participating in an improvement study. We used self-reported measures of team climate (Team Climate Inventory) and organizational culture (Competing Values Framework), and measures of quality of diabetes care and clinical patient characteristics from medical records and self-report. We conducted multivariate analyses of the relationship between culture, climate and HbA1c, total cholesterol, systolic blood pressure and a sum score on process indicators for the quality of diabetes care, adjusting for potential patient- and practice level confounders and practice-level clustering. RESULTS: A strong group culture was negatively associated to the quality of diabetes care provided to patients (beta = -0.04; p = 0.04), whereas a more 'balanced culture' was positively associated to diabetes care quality (beta = 5.97; p = 0.03). No associations were found between organizational culture, team climate and clinical patient outcomes. CONCLUSION: Although some significant associations were found between high quality diabetes care in general practice and different organizational cultures, relations were rather marginal. Variation in clinical patient outcomes could not be attributed to organizational culture or teamwork. This study therefore contributes to the discussion about the legitimacy of the widespread idea that aspects of redesigning care such as teamwork and culture can contribute to higher quality of care. Future research should preferably combine quantitative and qualitative methods, focus on possible mediating or moderating factors and explore the use of instruments more sensitive to measure such complex constructs in small office-based practices

Bridging the Gap between Field Experiments and Machine Learning: The EC H2020 B-GOOD Project as a Case Study towards Automated Predictive Health Monitoring of Honey Bee Colonies.

Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies' exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony's health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project's data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping

Data from: Early detection of phytophthora using hyperspectral imaging pot-tuber experiment

In this experiment 3 x 15 potato plants were inoculated with phytophthora infestance and imaged with a hyperspectral camera. Along with that the plants where observed by an expert

Data from: Early detection of phytophthora using hyperspectral imaging pot-tuber experiment

In this experiment 3 x 15 potato plants were inoculated with phytophthora infestance and imaged with a hyperspectral camera. Along with that the plants where observed by an expert.</p

Data from: Early detection of phytophthora using hyperspectral imaging pot-tuber experiment

In this experiment 3 x 15 potato plants were inoculated with phytophthora infestance and imaged with a hyperspectral camera. Along with that the plants where observed by an expert.</p

Gapless genome assembly of the potato and tomato early blight pathogen alternaria solani

The Alternaria genus consists of saprophytic fungi as well as plant-pathogenic species that have significant economic impact. To date, the genomes of multiple Alternaria species have been sequenced. These studies have yielded valuable data for molecular studies on Alternaria fungi. However, most of the current Alternaria genome assemblies are highly fragmented, thereby hampering the identification of genes that are involved in causing disease. Here, we report a gapless genome assembly of A. solani, the causal agent of early blight in tomato and potato. The genome assembly is a significant step toward a better understanding of pathogenicity of A. solani.</p

Stepwise screening of candidate antagonists for biological control of Blumeria graminis f. sp. tritici

Antagonists for the biological control of Blumeria graminis f. sp. tritici were selected using a stepwise screening approach. Fungal colonizers of powdery mildew pustules were isolated from leaves of cereals and other plant species. Spore production, cold tolerance, drought tolerance and UV-B resistance as important characteristics for application of biocontrol candidates in the phyllosphere were tested in in vitro assays and preliminary risk assessments were conducted. Amongst 850 tested isolates 58% belonged to various taxonomical groups of Cladosporium. Only 3% belonged to species that have been reported in literature as antagonistic to powdery mildews. The stepwise screening approach allowed to reduce the number of candidate antagonists using screening criteria that can be tested reliably and cost-effectively in in vitro assays and by data mining from initially 1237 isolates down to 143 candidate antagonists belonging to 42 taxonomical groups. The potential of these isolates to reduce conidia production of B. graminis f. sp. tritici. in wheat was assessed in bioassays on potted winter wheat plants under controlled conditions. A set of ten superior isolates was subsequently tested in a series of trials on potted spring wheat plants under open field conditions. Isolates Tilletiopsis pallescens BC0441 and T. pallescens BC0850 significantly reduced the number of powdery mildew pustules per flag leaf by 30 to 62%. Slopes of the regression lines fitted to data on number of powdery mildew pustules during time were significantly reduced by the antagonists indicating that the powdery mildew epidemics were slowed down. Treatments with T. pallescens BC0441 and T. pallescens BC0850 also reduced leaf coverage with powdery mildew pustules in a small-scale field trial in spring wheat.</p

Gapless Genome Assembly of the Potato and Tomato Early Blight Pathogen Alternaria solani

The Alternaria genus consists of saprophytic fungi as well as plant-pathogenic species that have significant economic impact. To date, the genomes of multiple Alternaria species have been sequenced. These studies have yielded valuable data for molecular studies on Alternaria fungi. However, most of the current Alternaria genome assemblies are highly fragmented, thereby hampering the identification of genes that are involved in causing disease. Here, we report a gapless genome assembly of A. solani, the causal agent of early blight in tomato and potato. The genome assembly is a significant step toward a better understanding of pathogenicity of A. solani

Development and validation of IPM strategies for the cultivation of cisgenically modified late blight resistant potato

Potato late blight disease remains the primary stressor of commercial potato production across the EU, typically requiring >10 fungicide applications per growing season to offset crop losses. In response, the goal of this study was to test and validate a novel, more durable, control strategy for potato late blight. This IPM2.0 strategy is based on the principles of Integrated Pest Management (IPM) which sees the deployment of a late blight resistant potato genotype, a cisgenically modified, Desiree based resistant potato line here, in conjunction with pathogen population monitoring for virulence to the resistance genes (R genes) deployed and a “do not spray unless”, low input fungicide spray strategy. Field evaluations were completed in the Netherlands and in Ireland in 2013, 2014 and in Ireland in 2015. Comparators used in this study included the original but susceptible potato variety Desiree and the conventional but highly resistant variety Sarpo Mira. The novel IPM2.0 strategy was compared to local common practice (fungicide applications on a near weekly basis) and an untreated control. Overall, the IPM2.0 control strategy validated here reduced the average fungicide input by 80–90% without compromising control efficacy. Corresponding environmental side-effects were reduced proportionally. The results underline the pragmatic role host resistance can provide to commercial potato production systems and to society at large if employed as part of an integrated late blight control system