Objectives To report (1) the injury incidence in recreational runners in preparation for a 8-km or 16-km running event and (2) which factors were associated withan increased injury risk. Methods Prospective cohort study in Amsterdam, the Netherlands. Participants (n=5327) received a baseline survey to determine event distance (8 km or 16 km), main sport, running experience, previous injuries, recent overuse injuries and personal characteristics. Three days after the race, they received a follow-up survey to determine duration of training period, running distance per week, training hours, injuries during preparation and use oftechnology. Univariate and multivariate regression models were applied to examine potential risk factors for injuries. Results 1304 (24.5%) participants completed both surveys. After excluding participants with current health problems, no signed informed consent, missing or incorrect data, we included 706 (13.3%) participants. In total, 142 participants (20.1%) reported an injury during preparation for the event. Univariate analyses (OR: 1.7, 95% CI 1.1 to 2.4) and multivariate analyses (OR: 1.7, 95% CI 1.1 to 2.5) showed that injury history was a significant risk factor for running injuries (Nagelkerke R-square=0.06). Conclusion An injury incidence for recreational runners in preparation for a running event was 20%. A previous injury was the only significant risk factor for runningrelated injuries.
Abstract: Since the first Oxford Survey of Childhood Cancer’s results were published, people have become more aware of the risks associated with prenatal exposure from diagnostic x rays. As a result, it has since been the subject of many studies. In this review, the results of recent epidemiological studies are summarized. The current international guidelines for diagnostic x-ray examinations were compared to the review. All epidemiological studies starting from 2007 and all relevant international guidelines were included. Apart from one study that involved rhabdomyosarcoma, no statistically significant associations were found between prenatal exposure to x rays and the development of cancer during 2007–2020. Most of the studies were constrained in their design due to too small a cohort or number of cases, minimal x-ray exposure, and/or data obtained from the exposed mothers instead of medical reports. In one of the studies, computed tomography exposure was also included, and this requires more and longer follow-up in successive studies. Most international guidelines are comparable, provide risk coefficients that are quite conservative, and discourage abdominal examinations of pregnant women.
Both because of the shortcomings of existing risk assessment methodologies, as well as newly available tools to predict hazard and risk with machine learning approaches, there has been an emerging emphasis on probabilistic risk assessment. Increasingly sophisticated AI models can be applied to a plethora of exposure and hazard data to obtain not only predictions for particular endpoints but also to estimate the uncertainty of the risk assessment outcome. This provides the basis for a shift from deterministic to more probabilistic approaches but comes at the cost of an increased complexity of the process as it requires more resources and human expertise. There are still challenges to overcome before a probabilistic paradigm is fully embraced by regulators. Based on an earlier white paper (Maertens et al., 2022), a workshop discussed the prospects, challenges and path forward for implementing such AI-based probabilistic hazard assessment. Moving forward, we will see the transition from categorized into probabilistic and dose-dependent hazard outcomes, the application of internal thresholds of toxicological concern for data-poor substances, the acknowledgement of user-friendly open-source software, a rise in the expertise of toxicologists required to understand and interpret artificial intelligence models, and the honest communication of uncertainty in risk assessment to the public.
In line with European sustainability goals, small and medium sized enterprises (SMEs) in the Dutch automotive aftermarket face the challenge of maintaining competitiveness while transitioning to circular business models. These models, supported by EU policies such as the Circular Economy Action Plan and the European Green Deal, drive innovation in product lifecycle management, recycling, and sustainability. However, as SMEs adapt to these changes, they must also navigate the growing competition from imported Chinese electric vehicles (EVs), which bring both opportunities and risks. Logistics plays a critical role in this transition, as optimizing supply chains, enhancing resource efficiency, and minimizing waste are essential for achieving circularity. Will the Chinese car manufacturers move their value chain to Europe? Or will they further localize in aftersales businesses? Either scenario would affect a chain of SMEs in automotive aftermarket. Focusing on the auto parts SMEs in the Brainport region, this research examines how SMEs can stay competitive by leveraging logistics strategies to support circular practices, and navigate the challenges posed by the influx of Chinese EVs while remaining resilient and adaptable in the automotive aftermarket value chain. Together with our consortium partners, we help the regional SMEs in the automotive aftermarket with: 1. Mapping out logistical challenges and objectives, 2. Risk mitigation and demand planning, 3. Strategic supply chain development. Involving Fontys International Business graduation projects on data analysis, this project combines quantitative and qualitative insights to examine the transition of automotive aftermarket to an EV-dominated future. The SMEs in our consortium network are drive to adapt to the evolving landscape by investing in new measures. Through scenario assessment, we help them with scenario strategies in circular transition. For a broader impact, this project brings SMEs, branch and public organizations together and presents shared responsibilities in creating a resilient supply chain.
The composition of diets and supplements given to bovine cattle are constantly evolving. These changes are driven by the social call for a more sustainable beef and dairy production, interests to influence the nutritional value of bovine products for human consumption, and to increase animal health. These adaptations can introduce (new) compounds in the beef and milk supply chain. Currently, the golden standard to study transfer of compounds from feed or veterinary medicine to cows and consequences for human health is performing animal studies, which are time consuming, costly and thus limited. Although animal studies are increasingly debated for ethical reasons, cows are still in the top 10 list of most used animals for animal experiments in Europe. There is, however, no widely applicable alternative modelling tool available to rapidly predict transfer of compounds, apart from individual components like cattle kinetic models and simple in vitro kinetic assays. Therefore, this project aims to develop a first-of-a-kind generic bovine kinetic modelling platform that predicts the transfer of compounds from medicine/supplements and feed to bovine tissues. This will provide new tools for the efficacy and safety evaluation of veterinary medicine and feed and facilitates a rapid evaluation of human health effects of bovine origin food products, thereby contributing to an increased safety in the cattle production chain and supporting product innovations, all without animal testing. This will be accomplished by integrating existing in silico and in vitro techniques into a generic bovine modelling platform and further developing state-of-the-art in vitro bovine organoid cell culturing systems. The platform can be used world-wide by stakeholders involved in the cattle industry (feed-/veterinary medicine industry, regulators, risk assessors). The project partners involve a strong combination of academia, knowledge institutes, small and medium enterprises, industry, branche-organisations and Proefdiervrij, all driven by their pursuit for animal free innovations.
Possibly, the aviation sector’s decarbonization challenge (see Dutch knowledge key in international climate study for tourism | CELTH) has profound implications for the ability of aviation-de-pendent outbound tour operators to attract capital and with that their ability to maintain or trans-form their current business portfolio (understood here as the current product offers and approximate carbon footprints, business models, and ownership structures present in this economic do-main). Knowledge about these (possible) investment risks and their business and policy implications is lacking. This project therefore addresses this knowledge gap by means of the following research questions.1. What is the current business portfolio of Dutch outbound tour operators?a. To what extend do Dutch outbound tour operators depend on aviation in terms of product offer and turnover?b. What is the relative carbon footprint share of aviation-based products compared to the total outbound product offer and turnover of Dutch outbound tour operators?2. What are investment risks of this business portfolio as indicated by investors?a. How do investors evaluate investment risks in relation to climate change mitigation and de-carbonisation?b. What are investment risks of the business portfolio of Dutch outbound tour operators?c. What are the reflections on and implications of these investment risks from the perspective of policymakers and tour operators?
