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Hands-on texture. Evaluating texture and target congruency in sensory play on children's food acceptance
No full textFood rejection is common in early childhood and may lead to insufficient intake of fruits, vegetables, and other essential nutrients. Food texture can play a major role in these rejections, as young children often refuse foods with challenging textures. Previous studies suggest that tactile exposure, such as sensory play with food or similar non-food materials, can increase children's willingness to try foods. However, it remains unclear whether these effects depend on familiarity with the specific texture, the specific food, or the combination. This study compared the effects of texture-based and target-based exposure on food acceptance in children aged 4-6 years. A total of 131 children from four Dutch elementary schools were randomly assigned to one of four conditions in a 2 x 2 factorial design: exposure to both the target fruit and its texture (passionfruit seeds), similar texture only (basil seeds), target fruit only (whole passionfruit), or neither (polystyrene foam balls). Acceptance of passionfruit seeds was rated on a 7-point behavioral scale ranging from 1 (physical refusal) to 7 (having an additional bite). Parents completed the Child Food Rejection Scale (CFRS) and the Touch subscale of the Sensory Profile (SPt). A 2x2 ANOVA revealed no significant differences in food acceptance between the four conditions. Overall, passionfruit elicited polarized responses, with approximately half of the children accepting and half refusing the fruit. Higher CFRS scores were associated with lower acceptance, indicating that children perceived as more food-rejective were less willing to accept the fruit. As the present single-session intervention did not significantly alter food acceptance, future studies could explore whether repeated or more naturalistic, mealtime-based sensory play interventions are more effective in promoting children's willingness to try challenging foods
Effectuation at work in universities:Using what is at hand to support social entrepreneurs
No full textUniversities play an important role in creating social impact through supporting social entrepreneurs. While existing literature primarily focuses on the educational aspect of nurturing social entrepreneurs, there is a gap in understanding the diverse and heterogeneous initiatives undertaken by universities. Recognizing the call for a nuanced exploration of universities' distinct approaches, we adopt an effectuation theory as an interpretive framework to investigate how universities, with varying scale and scope, support social entrepreneurs. Through 37 in-depth interviews and 5 focus group discussions at four universities, we offer an empirically grounded typology of four distinct support logics: embedded, auxiliary, opportunity-driven, and boundary-spanning. These categories reflect divergent institutional responses to uncertainty, internal capability, and stakeholder engagement. Our findings challenge the conventional narrative of homogeneity in university initiatives, emphasizing that support systems are shaped by a dynamic interaction of structural elements and individual decision-making processes. This research expands the theoretical discourse on university support for social entrepreneurs by bridging structure and agency and demonstrating how universities act as both integrators of resources and ecosystem enablers. By leveraging internal strengths and cultivating external partnerships, universities create multifaceted, adaptable support mechanisms that reflect the uniqueness of their institutional context and their contributions to the social entrepreneurship ecosystem. The study contributes to evolving debates on the university's roles in entrepreneurial ecosystems and provides a conceptual foundation for future theorization and comparative analysis. It offers actionable insights for university management, social entrepreneurs, and policymakers, advocating for a more nuanced understanding of the role universities play in creating social impact through entrepreneurial ecosystems
Loyalty and Multiple Voting Shares in Listed Companies in Belgium:Current Legal Framework and Policy Proposals
No full textIn this article, we analyse the legal framework for loyalty voting shares (LVS) in Belgium and the implications of the EU Directive on Multiple Voting Shares (MVS). We evaluate the limited uptake and practical use of LVS, highlighting their function as a control-enhancing tool for insiders. Based on proposals by a working group within the Belgian Centre for Company Law, we present a policy framework to implement MVS in Belgium, including safeguards for minority shareholders, a 1:20 maximum voting ratio, and the possibility of midstream adoption. We conclude that MVS provide a more flexible and effective governance mechanism than LVS to stimulate long-term ownership and listing activity in Belgium
PRevention Of sudden cardiac death aFter myocardial Infarction by Defibrillator im-plantation:Design and rationale of the PROFID EHRA randomized clinical trial
No full textBackground: Randomized clinical trials from over 20 years ago demonstrated that an implantable cardioverter defibrillator (ICD) improved survival for patients with severely reduced left ventricular ejection fraction (LVEF) after myocardial infarction (MI) compared with optimal medical therapy (OMT) alone. Since then advances in therapy have led to the reduction in the incidence of sudden cardiac death (SCD) in this population, whilst complication rates from ICD implantation are still substantial. Objectives: To determine whether OMT without ICD implantation is not inferior to OMT with ICD implantation with respect to all-cause mortality. Design: The PROFID EHRA trial is an investigator-driven, prospective, parallel-group, randomized, open-label, blinded outcome assessment (PROBE), multi-center, noninferiority trial without dedicated investigational medical device (Proof of Strategy Trial) with 2 groups with 1:1 randomization. PROFID-EHRA will recruit approximately 3,595 patients with documented history of MI at least 3 months prior, LVEF ≤35%, on OMT for at least 3 months, and with New York Heart Association class II or III, who will be randomized to OMT or OMT plus ICD, to collect 374 first primary outcome events within a median observation period of around 28 months from about 180 clinical sites in an estimated 13 countries. The primary outcome is time from randomization to the occurrence of all-cause death. Secondary outcomes include time from randomization to death from cardiovascular causes, to SCD, to first hospital readmission for cardiovascular causes after date of randomization, the average length of hospital stay during follow-up, and quality of life trajectories. Clinical Trial: Trials.gov</p
Administrative integration through agency governance:The role of Frontex, the EUAA and Europol
No full textCurrent Controversies and Challenges in Non-Oncogene-Addicted Synchronous Oligometastatic Non-Small Cell Lung Cancer:A Review
No full textIMPORTANCE: It has been stated that especially with the advancements in imaging, systemic therapy, and local radical treatment (LRT) that patients with synchronous oligometastatic disease (sOMD) can potentially benefit from curative-intent treatment. This statement is challenged by the results of the NRG-LU002 randomized phase 2/3 trial, showing no significant progression-free survival and overall survival improvements with the addition of LRT to maintenance systemic therapy in patients with oligometastatic non-small cell lung cancer (NSCLC) who achieved at least stable disease after induction systemic therapy (approximately 90% received an immunotherapy-based regimen). This Review discusses the current challenges and controversies in the treatment of non-oncogene-addicted sOMD. OBSERVATIONS: Whether LRT indeed can improve survival in a contemporary immunotherapy-based systemic treatment regimen is discussed as well as the optimal treatment sequence. Moreover, the NRG-LU002 trial also sparks debate of whether a true sOMD state exists. Genomic alterations, the tumor microenvironment of the primary tumor and metastasis, organotropism, and tumor heterogeneity can all influence metastatic potential, giving a biological explanation that there could be existence of a true sOMD state. However, as true sOMD cannot be distinguished from early-detected widespread metastatic disease with the current imaging modalities, it becomes difficult to select patients for a radical strategy and protect patients from futile treatment. CONCLUSIONS AND RELEVANCE: It remains under debate whether synchronous oligometastatic NSCLC represents a distinct biological entity or merely a probabilistic imaging finding. Biomarkers such as circulating tumor DNA, microRNA, and radiomics may improve patient selection but require further validation. Clinical trials should prioritize translational research to address these challenges
Varying Levels of Inflammatory Activity in Brain and Body of Patients with Persistent Fatigue and Difficulty Concentrating After COVID-19:A TSPO PET Study
No full textA significant number of patients report persistent fatigue and difficulty concentrating after infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a condition known as post-coronavirus disease 2019 (post-COVID) syndrome. The underlying mechanisms for these complaints remain poorly understood. Dysregulated immune and neurologic systems may play a role in the pathophysiology of post-COVID syndrome. A target providing direct information on immune activation is the 18-kDa translocator protein (TSPO), which is upregulated in activated microglia. The PET tracer N,N-diethyl-2-(2-(4-(2-fluoroethoxy)phenyl)5,7dimethylpyrazolo[1,5a]pyrimidin-3-yl)acetamide ([18F]DPA-714) binds with high affinity to TSPO and serves as a biomarker for neuroinflammation. We aimed to assess whole-body inflammatory activity with TSPO PET in individuals with and without persistent severe fatigue and difficulty concentrating 2 y after infection with SARS-CoV-2 as well as its association with complaint severity. Methods: In this cross-sectional cohort study, we evaluated 47 post-COVID individuals, 33 of whom had severe fatigue and difficulty concentrating (age, 50 ± 8 y; 27 ± 9 mo after initial infection) and 14 who did not have these complaints (age, 47 ± 9 y; 25 ± 10 mo after initial infection). All individuals were high-affinity binders according to their TSPO genotype and completed whole-body 60-min dynamic [18F]DPA-714 PET with arterial sampling, MRI, genotyping, and questionnaires. Tracer binding was quantified using binding potential for cerebral regions and inhibitory constant or total distribution volume for extracerebral regions. Parameters were compared between 33 individuals with persistent complaints (severe fatigue and difficulty concentrating) and 14 without, and associations between parameters were assessed. Results: We found globally increased cerebral [18F]DPA-714 binding in some individuals reporting persistent complaints when compared with individuals without these complaints. No group-level differences were found in extracerebral binding. Large variability in cerebral and extracerebral binding was observed among individuals. Cerebral and extracerebral binding levels were not correlated with each other or with complaint severity. Conclusion: Increased specific [18F]DPA-714 binding was found in some individuals with post-COVID syndrome, indicating the presence of an inflammatory subtype and further supporting the role of neuroinflammation in subtypes of post-COVID syndrome.</p
Arm-hand training strategies and therapy dose dimensions during the subacute rehabilitation of people with cervical spinal cord injury:a longitudinal observational study
No full textSTUDY DESIGN: Longitudinal observational study.OBJECTIVES: To explore motor training strategies, therapy dosage, and motivation in subacute arm-hand rehabilitation for individuals with cervical spinal cord injury and their change over a 6-month rehabilitation period.SETTING: Three rehabilitation centers in Belgium and the Netherlands.METHODS: Individuals with lesions between C1-Th1 and AIS A-D were included between 4-8 weeks post-injury and observed for three weeks with an eight-week interval. Regular arm-hand training sessions, with at least 25% arm-hand training, were analyzed. Motor training strategies, therapy dosage, and motivation were collected by two trained observers, video recordings and patient-reported outcome measures.RESULTS: 240 Sessions from thirteen participants (mean age 54.4 ± 12.9; C1-C5; AIS B-D) were included. Analytical training showed the highest active arm-hand use (30.3%), followed by skill training (26.6%). Of the 15 task-oriented components, only multiple movement planes, functional movements, and feedback were used in ≥60% of sessions. Actual session time averaged 78.3% of the planned duration. During the arm-hand session, 52.1% of the time involved active time. Skill training showed the lowest number of repetitions (MED: 66.5). Participants reported low physical fatigue (4/10) and difficulty (4/10) but high motivation (7/10). Limited changes in training variables were observed over six months.CONCLUSION: Our findings reveal a gap between clinical practice and evidence-based guidelines for arm-hand training. Despite its importance, skill training and key task-oriented components are underused. Low perceived difficulty and intensity, contrasted with high motivation, suggest the potential to increase therapy doses for better rehabilitation outcomes.</p
EFLM checklist for the assessment of AI/ML studies in laboratory medicine:enhancing general medical AI frameworks for laboratory-specific applications
No full textThe integration of artificial intelligence (AI) and machine learning (ML) into laboratory medicine shows promise for advancing diagnostic, prognostic, and decision-support tools; however, routine clinical implementation remains limited and heterogeneous. Laboratory data presents unique methodological and semantic complexities - method dependency, analyte-specific variation, and contextual sensitivity-not adequately addressed by general-purpose AI reporting guidelines. To bridge this gap, the EFLM Committee on Digitalisation and Artificial Intelligence (C-AI) proposes an expanded checklist to support assessment of requirements and recommendations for the development of AI/ML models based on laboratory data. Building upon the widely adopted ChAMAI checklist (Checklist for assessment of medical AI), our proposal introduces six additional items, each grounded in the CRoss Industry Standard Process for Data Mining (CRISP-DM) framework and tailored to the specificities of laboratory workflows. These extensions address: (1) explicit documentation of laboratory data characteristics; (2) consideration of biological and analytical variability; (3) the role of metadata and peridata in contextualizing results; (4) analyte harmonization and standardization practices; (5) rigorous external validation with attention to dataset similarity; and (6) the implementation of FAIR data principles for transparency and reproducibility. Together, these recommendations aim to foster robust, interpretable, and generalizable AI systems that are fit for deployment in clinical laboratory settings. By incorporating these laboratory-aware considerations into model development pipelines, researchers and practitioners can enhance both the scientific rigor and practical applicability of AI tools. We advocate for the adoption of this extended checklist by developers, reviewers, and regulators to promote trustworthy and reproducible AI in laboratory medicine
Exploring the Limitations of Layer Synchronization in Spiking Neural Networks
No full textNeural-network processing in machine learning applications relies on layer synchronization. This is practiced even in artificial Spiking Neural Networks (SNNs), which are touted as consistent with neurobiology, in spite of processing in the brain being in fact asynchronous. A truly asynchronous system however would allow all neurons to evaluate concurrently their threshold and emit spikes upon receiving any presynaptic current. Omitting layer synchronization is potentially beneficial, for latency and energy efficiency, but asynchronous execution of models previously trained with layer synchronization may entail a mismatch in network dynamics and performance. We present and quantify this problem, and show that models trained with layer synchronization either perform poorly in absence of the synchronization, or fail to benefit from any energy and latency reduction, when such a mechanism is in place. We then explore a potential solution direction, based on a generalization of backpropagation-based training that integrates knowledge about an asynchronous execution scheduling strategy, for learning models suitable for asynchronous processing. We experiment with 2 asynchronous neuron execution scheduling strategies in datasets that encode spatial and temporal information, and we show the potential of asynchronous processing to use less spikes (up to 50%), complete inference faster (up to 2x), and achieve competitive or even better accuracy (up to ~10% higher). Our exploration affirms that asynchronous event-based AI processing can be indeed more efficient, but we need to rethink how we train our SNN models to benefit from it. (Source code available at: https://github.com/RoelMK/asynctorch)