Swiss Distance University of Applied Sciences

Active travel (walking or cycling for transport) is considered the most sustainable form of personal transport. Yet its net effects on mobility-related CO2 emissions are complex and under-researched. Here we collected travel activity data in seven European cities and derived life cycle CO2 emissions across modes and purposes. Daily mobility-related life cycle CO2 emissions were 3.2 kgCO2 per person, with car travel contributing 70% and cycling 1%. Cyclists had 84% lower life cycle CO2 emissions than non-cyclists. Life cycle CO2 emissions decreased by −14% per additional cycling trip and decreased by −62% for each avoided car trip. An average person who ‘shifted travel modes’ from car to bike decreased life cycle CO2 emissions by 3.2 kgCO2/day. Promoting active travel should be a cornerstone of strategies to meet net zero carbon targets, particularly in urban areas, while also improving public health and quality of urban life.

Argonaute proteins are key players in microRNA (miRNA) processing and function. Next to their role as RISC effector proteins mediating target silencing, they actively participate in miRNA biogenesis and increase miRNA abundance by a yet unidentified mechanism. It has been hypothesized that this increase in steady-state miRNA levels might be due to a stabilizing effect of Argonaute proteins, but this has not been analyzed so far due to a lack of test systems. Here, we provide two approaches to estimate miRNA stability and factors affecting it: in cells lacking Ago2, endogenous miRNA guide strand degradation and half-lives can be assessed using Actinomycin D or α-Amanitin. In turn, miRNA passenger strands can serve as a model in wildtype cells to ascertain the impact of miRNA stability factors. We provide evidence that Argonaute proteins stabilize mature miRNAs in a slicing-independent manner. Transcriptional inhibition reveals reduced half-lives of multiple endogenous miRNA guide strands in cells lacking Ago2. This effect is reversible upon the reconstitution of Argonaute expression. Correspondingly, overexpression of Argonaute proteins decelerates miRNA degradation and increases miRNA half-life. Taken together, this study employs two model systems to identify factors altering miRNA stability and provides evidence how Argonaute proteins post-transcriptionally elevate mature miRNA levels via increasing miRNA stability.

Medical artificial intelligence (AI) systems have been remarkably successful, even outperforming human performance at certain tasks. There is no doubt that AI is important to improve human health in many ways and will disrupt various medical workflows in the future. Using AI to solve problems in medicine beyond the lab, in routine environments, we need to do more than to just improve the performance of existing AI methods. Robust AI solutions must be able to cope with imprecision, missing and incorrect information, and explain both the result and the process of how it was obtained to a medical expert. Using conceptual knowledge as a guiding model of reality can help to develop more robust, explainable, and less biased machine learning models that can ideally learn from less data. Achieving these goals will require an orchestrated effort that combines three complementary Frontier Research Areas: (1) Complex Networks and their Inference, (2) Graph causal models and counterfactuals, and (3) Verification and Explainability methods. The goal of this paper is to describe these three areas from a unified view and to motivate how information fusion in a comprehensive and integrative manner can not only help bring these three areas together, but also have a transformative role by bridging the gap between research and practical applications in the context of future trustworthy medical AI. This makes it imperative to include ethical and legal aspects as a cross-cutting discipline, because all future solutions must not only be ethically responsible, but also legally compliant.

Iron deficiency and iron deficiency anemia (IDA) are major public health problems worldwide, especially in young women. Oral iron supplementation can be an effective strategy to treat and prevent IDA, but guidelines vary. Some experts recommend doses of 150–200 mg elemental iron per day, with the dose split through the day. However, recent studies suggest this may not be an optimal regimen. The fraction of iron absorbed from high doses of oral iron is low, and unabsorbed iron can cause gut irritation, inflammation and dysbiosis, and these reduce compliance. In recent studies using serum hepcidin profiles and stable iron isotopes to quantify iron absorption in young women, we have shown that: (a) oral iron doses ≥60 mg in iron-deficient women, and doses ≥100 mg in women with IDA, stimulate an acute increase in hepcidin that persists 24 h after the dose, but subsides by 48 h; (b) therefore, to maximize fractional iron absorption, oral doses ≥60 mg should be given on alternate days; (c) the circadian increase in plasma hepcidin is augmented by a morning iron dose; therefore, iron doses should not be given in the afternoon or evening after a morning dose. If rate of Hb response is important, a pooled analysis of our data done for this review indicates that total iron absorption is also higher if twice the target daily iron dose is given on alternate days. In summary, these studies suggest changing from daily to alternate-day schedules and from divided to morning single doses increases iron absorption and may reduce side effects. Thus, providing morning doses of 60–120 mg iron as a ferrous salt given with ascorbic acid on alternate days may be an optimal oral dosing regimen for women with iron-deficiency and mild IDA.

Abstract Higher education institutions are increasingly interested in using adaptive learning as an innovative data-driven approach to teaching. The actual use of adaptive learning in courses remains, however, low. This is despite positive attitudes of institutional leaders towards its adoption and promising results of early studies on its effectiveness. This study examines the challenges that prevent higher education institutions from adopting adaptive learning concepts in teaching. We used a four-stage Delphi design to empirically identify, categorise, and prioritise the challenges of adaptive learning raised and rated by experts from two universities with different organisational and socioeconomic contexts, one from Switzerland and one from South Africa. Considering different contexts allowed us to include various perspectives on the research topic and thus broaden the view on the challenges of adaptive learning. Overall, three main dimensions related to technological, teaching and learning, and organisational challenges with eight corresponding categories were identified. Our findings revealed clear differences between the two universities regarding the emerged challenges and their rankings. These differences are linked to different socioeconomic backgrounds (South Africa and Switzerland) and organisational contexts (e.g., type of the university, teaching model, and implementation phase) of the universities. We conclude by proposing practical recommendations for institutional leaders and project implementers on the factors to be considered when implementing adaptive learning in higher education settings. These recommendations relate to the necessary infrastructure, institutional commitment, support and resources.

Urban green and blue spaces (UGBS) have the potential to improve public health and wellbeing, address health inequities, and provide co-benefits for the environment, economy, and society. To achieve these ambitions, researchers should engage with communities, practitioners, and policy makers in a virtuous circle of research, policy, implementation, and active citizenship using the principles of co-design, co-implementation, co-evaluation, and co-translation. This Viewpoint provides an integrated perspective on the challenges that hinder the delivery of health-enhancing UGBS and recommendations to address them. Our recommendations include: strengthening the evidence beyond cross-sectional research designs, strengthening the evidence base on UGBS intervention approaches, evaluating the effects on diverse population groups and communities, addressing inequities in the distribution and quality of UGBS, accelerating research on blue space, providing evidence for environmental effects, incorporating co-design approaches, developing innovative modelling methods, fostering whole-system evidence, harnessing political drivers, creating collaborations for sustainable UGBS action, and advancing evidence in low-income and middle-income countries. The full potential of UGBS as public health, social, economic, and environmental assets is yet to be realised. Acting on the research and translation recommendations will aid in addressing these challenges in collaboration with research, policy, practice, and communities.

BACKGROUND: Plasma ferritin is a widely used indicator to detect iron deficiency, but the threshold ferritin that defines iron deficiency remains uncertain. Our aim was to define the ferritin concentration at which the body begins to upregulate iron absorption from the diet; this could provide a functionally-defined threshold of incipient iron deficiency. We hypothesized this threshold ferritin concentration would correspond to the threshold hepcidin concentration at which iron absorption begins to increase. METHODS: = 1058) conducted from 2006 to 2019 in healthy women (age 18-50 years; mean±SD ferritin 33.7 ± 27.1 μg/L) that measured iron absorption from labeled test meals providing physiological amounts of iron. To fit relationships between iron absorption, ferritin and hepcidin, we used generalized additive modeling, and to identify thresholds, we estimated the first derivatives of the fitted trend to assess inflection points in these relationships. FINDINGS: Hepcidin increased linearly with increasing ferritin over the entire range of ferritin values. Iron absorption began to increase below a threshold hepcidin value of 3.09 (95%CI: 2.80, 3.38) nmol/l, above which iron absorption remained stable. Iron absorption began to increase below a threshold ferritin value of 51.1 (95%CI: 49.1, 53.1) µg/l, above which iron absorption remained stable. The latter two findings were internally consistent in that, in the relationship between hepcidin and ferritin, a hepcidin of ~3 nmol/l corresponded to a ferritin of ~51 µg/l. INTERPRETATION: Based on physiological upregulation of iron absorption, a threshold ferritin of <50 µg/L, corresponding to a threshold hepcidin of <3 nmol/l, indicates incipient iron deficiency in young women.

Grains are the main energy and carbohydrate sources for human nutrition globally. Governmental and non-governmental authorities recommend whole grains as a healthy food choice. The role of contaminants in (whole) grains and how to mitigate any potential risk following their consumption has not been reported. With this narrative review, we shed light on the potential human health risk from contaminants in whole grains and elaborate strategies to mitigate such risk. We found that grains represent a significant source of food-borne contaminants, the main ones being; mycotoxins including (A) aflatoxin B1; (B) ochratoxin A; (C) fumonisin B1; (D) deoxynivalenol; (E) zearalenone; toxic metals like arsenic, cadmium and lead; as well as process contaminants such as acrylamide. Whole grains usually contain more contaminants than refined products. However, whole grains also provide more nutrients that may reduce the impact of these contaminants. Strict regulatory thresholds aim to minimize the risk of contaminants to public health. The consumer can further impact on the mitigation of any risk by eating a healthy diet filled with nutrient-dense foods such as whole grains and probiotics. The risk posed by contaminants from whole grains do not outweigh the known nutritional benefits of whole grain consumption.

BACKGROUND: Numerous digital health interventions have been developed for mental health promotion and intervention, including eating disorders. Efficacy of many interventions has been evaluated, yet knowledge about reasons for dropout and poor adherence is scarce. Most digital health intervention studies lack appropriate research design and methods to investigate individual engagement issues. User engagement and program usability are inextricably linked, making usability studies vital in understanding and improving engagement. OBJECTIVE: The aim of this study was to explore engagement and corresponding usability issues of the Healthy Body Image Program-a guided online intervention for individuals with body image concerns or eating disorders. The secondary aim was to demonstrate the value of usability research in order to investigate engagement. METHODS: We conducted an iterative usability study based on a mixed-methods approach, combining cognitive and semistructured interviews as well as questionnaires, prior to program launch. Two separate rounds of usability studies were completed, testing a total of 9 potential users. Thematic analysis and descriptive statistics were used to analyze the think-aloud tasks, interviews, and questionnaires. RESULTS: Participants were satisfied with the overall usability of the program. The average usability score was 77.5/100 for the first test round and improved to 83.1/100 after applying modifications for the second iteration. The analysis of the qualitative data revealed five central themes: layout, navigation, content, support, and engagement conditions. The first three themes highlight usability aspects of the program, while the latter two highlight engagement issues. An easy-to-use format, clear wording, the nature of guidance, and opportunity for interactivity were important issues related to usability. The coach support, time investment, and severity of users' symptoms, the program's features and effectiveness, trust, anonymity, and affordability were relevant to engagement. CONCLUSIONS: This study identified salient usability and engagement features associated with participant motivation to use the Healthy Body Image Program and ultimately helped improve the program prior to its implementation. This research demonstrates that improvements in usability and engagement can be achieved by testing and adjusting intervention design and content prior to program launch. The results are consistent with related research and reinforce the need for further research to identify usage patterns and effective means for reducing dropout. Digital health research should include usability studies prior to efficacy trials to help create more user-friendly programs that have a higher likelihood of "real-world" adoption.

BACKGROUND: Policy analysis is considered essential for achieving successful reforms in health promotion and public health. The only framework for physical activity (PA) policy analysis was developed at a time when the field of PA policy research was in its early stages. PA policy research has since grown, and our understanding of what elements need to be included in a comprehensive analysis of PA policy is now more refined. This study developed a new conceptual framework for PA policy analysis - the Comprehensive Analysis of Policy on Physical Activity (CAPPA) framework. METHODS: The development of the CAPPA framework was based on: (i) an extensive review of literature; (ii) an open discussion between the authors; (iii) three rounds of a Delphi process; and (iv) two-rounds of consultations with PA policy stakeholders. RESULTS: The CAPPA framework specifies 38 elements of a comprehensive analysis of PA policies in the following six categories, which comprise the building blocks of the framework: (i) purpose of analysis (including auditing and assessment of policies); (ii) policy level (including: international; national; subnational; local; and institutional policies); (iii) policy sector (including: health; sport; recreation and leisure; education; transport; environment; urban/rural planning and design; tourism; work and employment; public finance; and research sectors); (iv) type of policy (including: formal written policies; unwritten formal statements; written standards and guidelines; formal procedures; and informal policies); (v) stage of policy cycle (including: agenda setting; formulation; endorsement/legitimisation; implementation; evaluation; maintenance; termination; and succession); and (vi) scope of analysis (including availability; context; processes; actors; political will; content; and effects). Based on the CAPPA framework, we also proposed broad and inclusive definitions of PA policy and PA policy analysis. CONCLUSION: The CAPPA framework may be used to guide future studies related to PA policy and to provide a context for the analysis of its specific components. The framework could be used in the same way for sedentary behaviour policy research. Future research should examine the extent to which PA policy analysis has covered each of the elements specified in the CAPPA framework and analyse the elements for which evidence is lacking. Future studies should also determine whether the existing tools allow for auditing and assessment of all the CAPPA elements and develop new tools if needed to allow for a more comprehensive PA policy analysis.

OBJECTIVE: The objective of this study was to investigate the prevalence of eating disorder (ED) risk as well as associated psychopathology and health-related quality of life (HrQoL) in a large population sample of Austrian adolescents. METHOD: A sample of 3610 adolescents aged 10-18 years was recruited from 261 schools representative for the Austrian population. The SCOFF questionnaire was used to identify participants at risk for EDs, and the Youth Self-Report and KIDSCREEN were used to assess general psychopathology and HrQoL. RESULTS: In total, 30.9% of girls and 14.6% of boys were screened at risk for EDs. SCOFF scores were significantly associated with internalising and externalising behavioural problems as well as HrQoL after controlling for sex, age and body mass index. The SCOFF score further turned out to be an independent predictor of HrQoL. DISCUSSION: The high prevalence of ED risk among Austrian adolescents points out the need for prevention in this field. Variables indicating eating pathology should be included in general mental health screenings.

Imagine how flicking through your photo album and seeing a picture of a beach sunset brings back fond memories of a tasty cocktail you had that night. Computational models suggest that upon receiving a partial memory cue ('beach'), neurons in the hippocampus coordinate reinstatement of associated memories ('cocktail') in cortical target sites. Here, using human single neuron recordings, we show that hippocampal firing rates are elevated from ~ 500-1500 ms after cue onset during successful associative retrieval. Concurrently, the retrieved target object can be decoded from population spike patterns in adjacent entorhinal cortex (EC), with hippocampal firing preceding EC spikes and predicting the fidelity of EC object reinstatement. Prior to orchestrating reinstatement, a separate population of hippocampal neurons distinguishes different scene cues (buildings vs. landscapes). These results elucidate the hippocampal-entorhinal circuit dynamics for memory recall and reconcile disparate views on the role of the hippocampus in scene processing vs. associative memory.

Humor in the Values in Action (VIA) Classification of Strengths is conceptualized as a unipolar and unidimensional strength and is subsumed under the virtue of transcendence. Its scope is intentionally restricted to forms of humor that serve some moral good. The present study (N = 203) investigated the relation between five dimensions of humorous conduct, sense of humor, and the VIA-Inventory of Strengths (VIA-IS). Results show (1) that the VIA-humor correlated with socially warm and competent humor, and the sense of humor, all with a common basis in humanity. (2) Each humor style showed relations to strengths. Additionally, strengths related to the virtue of temperance were also related to not showing mean-spirited and earthy forms of humor. Hence, humor in the VIA-IS can be well-located in established humor taxonomies, but does not cover all of the virtue-related humorous behaviors. Further research is requested to investigate the role of virtue in humor.

&lt;p&gt;Flexibility in learning provides a student room for volitional control and an array of strategies and encourages persistence in the face of difficulties. Autonomy in and control over one’s learning process can be seen as a condition for self-regulated learning. There are a number of categories and dimensions for flexible learning; following professional publications, time, location, lesson content, pedagogy method, learning style, organization, and course requirements are all elements to consider. Using these categories and the dimensions of flexible learning, we developed and validated a questionnaire for an open and distance learning setting. This article reports on the results from a study investigating the relationship between flexible learning and self-regulated learning strategies. The results show the positive effects of flexible learning and its three factors, time management, teacher contact, and content, on self-regulated learning strategies (cognitive, metacognitive, and resource-based). Groups that have high flexibility in learning indicate that they use more learning strategies than groups with low flexibility.&lt;/p&gt;

Omega-3 fatty acids, specifically eicosapentanoic acid (EPA, 20:5n-3) and docosahexanoic acid (DHA, 22:6n-3) are receiving increasing attention in sports nutrition. While the usual focus is that of athletes, questions remain if the different training status between athletes and amateurs influences the response to EPA/DHA, and as to whether amateurs would benefit from EPA/DHA supplementation. We critically examine the efficacy of EPA/DHA on performance, recovery and injury/reduced risk of illness in athletes as well as amateurs. Relevant studies conducted in amateurs will not only broaden the body of evidence but shed more light on the effects of EPA/DHA in professionally trained vs. amateur populations. Overall, studies of EPA/DHA supplementation in sport performance are few and research designs rather diverse. Several studies suggest a potentially beneficial effect of EPA/DHA on performance by improved endurance capacity and delayed onset of muscle soreness, as well as on markers related to enhanced recovery and immune modulation. The majority of these studies are conducted in amateurs. While the evidence seems to broadly support beneficial effects of EPA/DHA supplementation for athletes and more so in amateurs, strong conclusions and clear recommendations about the use of EPA/DHA supplementation are currently hampered by inconsistent translation into clinical endpoints.

Latent Growth Curve Models (LGCM) have become a standard technique to model change over time. Prediction and explanation of inter-individual differences in change are major goals in lifespan research. The major determinants of statistical power to detect individual differences in change are the magnitude of true inter-individual differences in linear change (LGCM slope variance), design precision, alpha level, and sample size. Here, we show that design precision can be expressed as the inverse of effective error. Effective error is determined by instrument reliability and the temporal arrangement of measurement occasions. However, it also depends on another central LGCM component, the variance of the latent intercept and its covariance with the latent slope. We derive a new reliability index for LGCM slope variance – effective curve reliability (ECR) – by scaling slope variance against effective error, which is interpretable as a standardized effect size index. We demonstrate how effective error, ECR, and statistical power for a likelihood ratio test of zero slope variance formally relate to each other and how they function as indices of statistical power. We also provide a computational approach to derive ECR for arbitrary intercept-slope covariance. With practical use cases, we argue for the complementary utility of the proposed indices of a study’s sensitivity to detect slope variance when making a priori longitudinal design decisions or communicating study designs.

We argue that, starting from a sophisticated understanding of "digital," we should develop a corresponding notion of "education" suitable to meet the challenges of the ongoing digital transformation. The central task for higher education institutions is to model the complex networks of digital skills (critical thinking, media literacy, cross-cultural competence, etc.) as a foundation for creating contextualized learning scenarios in the disciplines. The crucial success factor is the reunification of the classroom with the real world.

The International Breakfast Research Initiative (IBRI) set out to derive nutritional recommendations for a balanced breakfast using a standardized analysis of national nutrition surveys from Canada, Denmark, France, Spain, UK and the US. In all countries, the frequency of breakfast consumption by age was high and U-shaped with children and older adults having a higher frequency of breakfast consumption. Breakfast contributed 16% to 21% of daily energy intake. In all countries, breakfast was a carbohydrate- and nutrient-rich meal, providing more carbohydrates (including sugars), thiamin, riboflavin, folate, calcium, potassium, and magnesium, and less vitamin A, fats and sodium relative to its contribution to daily energy intakes. Breakfast consumers were stratified by tertiles of the Nutrient Rich Foods (NRF) index, used as a measure of diet quality. Breakfast intakes associated with the top tertile of NRF, along with the Codex Alimentarius international food standards and World Health Organization (WHO) diet guidelines, were used to derive the proposed nutrient recommendations. The goal was to preserve the nutrient density of existing breakfasts, while addressing concerns regarding added sugars, saturated fats, dietary fiber, and vitamin D. This initiative is unique in seeking to derive nutrient recommendations for a specific meal using the observed nutritional profile of such meal.

Food systems have been identified as significant contributors to the global environmental emergency. However, there is no universally agreed-upon definition of what constitutes a planetary healthy, sustainable diet. In our study, we investigated the association between the EAT-Lancet reference diet, a diet within the planetary boundaries, and incident cancer, incident major cardiovascular events, and all-cause mortality. Higher adherence to the EAT-Lancet reference diet was associated with lower incident cancer risk (hazard ratio [HR]continuous: 0.99; 95% confidence interval [CI]: 0.98–0.99]) and lower all-cause mortality (HR continuous: 0.98; 95% CI: 0.98–0.99), while mostly null associations were detected for major cardiovascular event risk (HR continuous: 1.00; 95% CI: 0.98–1.01). Stratified analyses using potentially modifiable risk factors led to similar results. Our findings, in conjunction with the existing literature, support that adoption of the EAT-Lancet reference diet could have a benefit for the prevention of non-communicable diseases.

In recent years, many applications are using various forms of deep learning models. Such methods are usually based on traditional learning paradigms requiring the consistency of properties among the feature spaces of the training and test data and also the availability of large amounts of training data, e.g., for performing supervised learning tasks. However, many real-world data do not adhere to such assumptions. In such situations transfer learning can provide feasible solutions, e.g., by simultaneously learning from data-rich source data and data-sparse target data to transfer information for learning a target task. In this paper, we survey deep transfer learning models with a focus on applications to text data. First, we review the terminology used in the literature and introduce a new nomenclature allowing the unequivocal description of a transfer learning model. Second, we introduce a visual taxonomy of deep learning approaches that provides a systematic structure to the many diverse models introduced until now. Furthermore, we provide comprehensive information about text data that have been used for studying such models because only by the application of methods to data, performance measures can be estimated and models assessed.