Background: Non-technical errors, such as insufficient communication or leadership, are a major cause of medical failures during trauma resuscitation. Research on staffing variation among trauma teams on teamwork is still in their infancy. In this study, the extent of variation in trauma team staffing was assessed. Our hypothesis was that there would be a high variation in trauma team staffing. Methods: Trauma team composition of consecutive resuscitations of injured patients were evaluated using videos. All trauma team members that where part of a trauma team during a trauma resuscitation were identified and classified during a one-week period. Other outcomes were number of unique team members, number of new team members following the previous resuscitation and new team members following the previous resuscitation in the same shift (Day, Evening, Night). Results: All thirty-two analyzed resuscitations had a unique trauma team composition and 101 unique members were involved. A mean of 5.71 (SD 2.57) new members in teams of consecutive trauma resuscitations was found, which was two-third of the trauma team. Mean team members present during trauma resuscitation was 8.38 (SD 1.43). Most variation in staffing was among nurses (32 unique members), radiology technicians (22 unique members) and anesthetists (19 unique members). The least variation was among trauma surgeons (3 unique members) and ER physicians (3 unique members). Conclusion: We found an extremely high variation in trauma team staffing during thirty-two consecutive resuscitations at our level one trauma center which is incorporated in an academic teaching hospital. Further research is required to explore and prevent potential negative effects of staffing variation in trauma teams on teamwork, processes and patient related outcomes.
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In clinical practice, formal elements of art products are regularly used in art therapy observation to obtain insight into clients’ mental health and provide directions for further treatment. Due to the diversity of formal elements used in existing studies and the inconsistency in the interpretation, it is unclear which formal elements contribute to insight into clients’ mental health. In this qualitative study using Constructivist Grounded Theory, eight art therapists were interviewed in-depth to identify which formal elements they observe, how they describe mental health and how they associate formal elements with mental health. Findings of this study show that art therapists in this study observe the combination of movement, dynamic, contour and repetition (i.e., primary formal elements) with mixture of color, figuration and color saturation (i.e., secondary formal elements). Primary and secondary elements interacting together construct the structure and variation of the art product. Art therapists rarely interpret these formal elements in terms of symptoms or diagnosis. Instead, they use concepts such as balance and adaptability (i.e., self-management, openness, flexibility, and creativity). They associate balance, specifically being out of balance, with the severity of the clients’ problem and adaptability with clients’ strengths and resources. In the conclusion of the article we discuss the findings’ implications for practice and further research.
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PURPOSE: Several studies have reported seasonal variation in intake of food groups and certain nutrients. However, whether this could lead to a seasonal pattern of diet quality has not been addressed. We aimed to describe the seasonality of diet quality, and to examine the contribution of the food groups included in the dietary guidelines to this seasonality.METHODS: Among 9701 middle-aged and elderly participants of the Rotterdam Study, a prospective population-based cohort, diet was assessed using food-frequency questionnaires (FFQ). Diet quality was measured as adherence to the Dutch dietary guidelines, and expressed in a diet quality score ranging from 0 to 14 points. The seasonality of diet quality and of the food group intake was examined using cosinor linear mixed models. Models were adjusted for sex, age, cohort, energy intake, physical activity, body mass index, comorbidities, and education.RESULTS: Diet quality had a seasonal pattern with a winter-peak (seasonal variation = 0.10 points, December-peak) especially among participants who were men, obese and of high socio-economic level. This pattern was mostly explained by the seasonal variation in the intake of legumes (seasonal variation = 3.52 g/day, December-peak), nuts (seasonal variation = 0.78 g/day, January-peak), sugar-containing beverages (seasonal variation = 12.96 milliliters/day, June-peak), and dairy (seasonal variation = 17.52 g/day, June-peak).CONCLUSIONS: Diet quality varies seasonally with heterogeneous seasonality of food groups counteractively contributing to the seasonal pattern in diet quality. This seasonality should be considered in future research on dietary behavior. Also, season-specific recommendations and policies are required to improve diet quality throughout the year.
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Sea Lettuce, Ulva spp. is a versatile and edible green seaweed. Ulva spp is high in protein, carbohydrates and lipids (respectively 7%-33%; 33%-62% and 1%-3% on dry weight base [1, 2]) but variation in these components is high. Ulva has the potential to produce up to 45 tons DM/ha/year but 15 tons DM/ha/year is more realistic.[3, 4] This makes Ulva a possible valuable resource for food and other applications. Sea Lettuce is either harvested wild or cultivated in onshore land based aquaculture systems. Ulva onshore aquaculture is at present implemented only on a few locations in Europe on commercial scale because of limited knowledge about Ulva biology and its optimal cultivation systems but also because of its unfamiliarity to businesses and consumers. The objective of this project is to improve Ulva onshore aquaculture by selecting Ulva seed material, optimizing growth and biomass production by applying ecophysiological strategies for nutrient, temperature, microbiome and light management, by optimizing pond systems eg. attached versus free floating production and eventually protoype product development for feed, food and cosmetics.
Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).
Eggshell particles as bio-ceramic in sustainable bioplastic engineering – ESP-BIOPACK Plastics make our lives easier in many ways. However, if they are not properly disposed of, they end up in the environment. Recently, biodegradable biopolymers, such as polylactic acid (PLA) and polyhydroxy alkanoates (PHAs), have moved towards alternatives for applications such as sustainable packaging. The major limitations of these biopolymers are the high cost, which is due to the high cost of the starting materials and the small volumes, and the poor thermal and mechanical properties such as limited processability and low impact resistance. Attempts to modify PHAs have been researched in many ways, such as blending various biodegradable polymers or mixing inorganic mineral fillers. Eggshell (10 million tons per year by 2030) is a natural bio-ceramic mineral with a unique chemical composition of calcium carbonate (>95% calcite). So far it has been regarded as a zero-value waste product, but it could be a great opportunity as raw material to reduce the cost of biopolymers and to improve properties, including the decomposition process at the end-of-life. In this project, we aim to develop eggshell particles that serve as bio-fillers in biopolymers to lower the cost of the product, to improve mechanical properties and to facilitate the validation of end-of-life routes, therefore, economically enhance the wide applications of such. The developed bioplastic packaging materials will be applied in SME partner EGGXPERT’s cosmetics line but also in other packaging applications, such as e.g. biodegradable coffee capsules. To be able to realize the proposed idea, the partnership between Chemelot Innovation and Learning Labs (CHILL), EGGXPERT B.V. and the Research Centre Material Sciences of Zuyd University of Applied Sciences is needed to research the physical, mechanical and end-of-life influences of eggshell particles (ESP) in biopolymers such as PLA and PHA and optimize their performance.
