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    Preconception health as a target for improved pregnancy outcomes:Where do we go from here?

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    Preconception health status, especially of women, but also of men, is known to influence pregnancy outcomes. Despite knowledge of the growing importance of preconception health, numerous challenges remain for conducting research in this population and delivering appropriate clinical care. The 2023 Global Pregnancy Collaboration annual workshop focused on exploring preconception health as it relates to adverse pregnancy outcomes. Here we summarize the proceedings and the current state of the science. We particularly focus on quantifying the exposome as a rich target for investigation of factors that increase the risk for and/ or contribute to preeclampsia and other adverse pregnancy outcomes. We conclude with recommendations for the scientific and clinical community to address knowledge gaps regarding the links between preconception health and adverse pregnancy outcomes.</p

    Heijblom, Bram

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    Abdi, Abdikafi Hassan

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    Professional identity development and sense of belonging of diverse students at the transition to higher education

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    Besides being a challenging educational transition, the transition to higher education can be conceived of as the start of professional identity development in professional fields. Research on the role of professional identity at the transition to higher education is however scarce. This study examines how background characteristics and sense of belonging affect professional identity and how professional identity relates to academic achievement and study commitment. Survey and student administration data were collected at two time points among first year students enrolled in law school (Nt1 = 198; Nt2 = 124). Results indicated that sense of belonging to law school was positively related to professional identity. No effect of sense of belonging was found on change in professional identity between the two timepoints. Students with a migration background reported a lower level of belongingness, but a higher level of professional identity. Analyses showed no relationship between professional identity and academic achievement. Professional identity was however positively related to commitment to law school, particularly for students with lower achievement. Overall, the findings suggest no major role of the transition to higher education in shaping students’ professional identity but do indicate that a strong professional identity supports study commitment, especially when students face academic difficulties

    Artificial intelligence and animal farming:a scenario of drivers, barriers, and impacts in 2032

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    In animal farming, there is the hope that artificial intelligence (AI) will improve efficiency and increase profits while providing solutions to reduce pollution and pesticide use and improve environmental sustainability, animal health and welfare. However, many are also concerned about AI’s ethical, legal, social, and economic impacts. These include the instrumentalisation of animals, bias caused by AI in how animals are portrayed, allowing the continuation of a harmful farming industry, and concerns around power asymmetries, data ownership, and copyright infringements. Therefore, there is a tension between the potential benefits and drawbacks of AI use in animal farming. This paper takes a forward-looking view of the benefits and challenges that AI may create in animal farming by the year 2032. Through several iterative rounds with stakeholders, this paper maps out a future scenario of AI in animal farming, identifying technological developments alongside potential drivers, barriers, and impacts. The scenario concludes with five recommendations for policymakers: 1. Initiate education programmes on AI in the sector; 2. Create ethical guidelines for AI in animal farming; 3. Science policy should be realistic and not only rely on technical solutions like AI; 4. Ensure public safety from harm caused by AI; 5. Implement better guidance on data-sharing in the sector.</p

    The critique of Human-centered artificial intelligence.:Why it is questionable and why it calls for a radical transformation of the human-artificial intelligence relation

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    While current research in the ethics of AI concentrates on methods and approaches to ensure that AI serves human goals—enabling human self-realization, enhancing human agency, increasing social capabilities, and cultivating societal cohesion, the anthropological dimension of the human-AI relation remains largely neglected in the ethics of AI debate, let alone critically reflected upon. The objective of this chapter is to engage in such a critical reflection on the presupposed understanding of the ‘human’ in the human-AI relation. We first reflect on ‘the human’ as it is self-evidently understood in the HcAI literature (Section The self-evident concept of the human in human-centered AI), on the fusion of human intelligence and artificial intelligence in the digital age (Section The fusion of human intelligence (HI) and artificial intelligence (AI)), and how this leads to the emergence of the homo virtualis (Section The emergence of the homo virtualis). Subsequently, we question the increasing congruency between HI and AI in the conceptualization of the human-AI relation (Section Questioning the convergence). We first reflect on the difference between HI and AI (Section The difference between HI and AI) and introduce critical issues in the human-AI relation that can be found at the level of the input, throughput, and output of the human-AI relation (Section Critical issues in the human-AI relation). We conclude the article with a proposal for a concept of HcAI that takes the fundamental difference between HI and AI as a point of departure and provides a research agenda for future research on the human-AI relation in the digital age (Section Discussion and Conclusion)

    The Effects of Tonic and Burst Spinal Cord Stimulation on Cortical Pain Processing and Their Interaction With Conditioned Pain Modulation

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    Introduction:Spinal cord stimulation (SCS) is an effective treatment for certain chronic pain conditions. Proposed mechanisms of SCS include modulation of the ascending lateral, ascending medial, and descending pain pathways. Conditioned pain modulation (CPM) evaluates the descending pathway by measuring ways a first painful stimulus is affected by a second painful stimulus. Objectives:We aim to increase insight into SCS mechanisms by exploring cortical activity in response to painful stimuli under various SCS paradigms and assessing how these responses are influenced by CPM. Materials and Methods:21 patients with persistent spinal pain syndrome type 2 treated with SCS underwent three sessions (under tonic, burst, and sham SCS) with a one-week interval. Using magnetoencephalography, we measured the cortical responses to painful electrical stimuli before , during , and after CPM . Cortical activity was analyzed in the time domain (evoked response) and time-frequency domain (beta event-related synchronization [ERS]). Results:Data from 14 patients qualified for analysis. Before CP M , the lowest amplitude of evoked responses occurred under tonic SCS, followed by sham SCS ( p &gt; 0.05). The lowest power of beta ERS occurred under sham SCS ( p &gt; 0.05). Pain ratings of the stimuli were statistically significantly reduced during CPM ( p &lt; 0.05). The amplitude of evoked responses was statistically significantly reduced in multiple regions during CPM under sham and burst SCS ( p &lt; 0.05). The power of beta ERS was reduced during CPM under tonic and burst SCS, whereas no reduction was observed under sham SCS ( p &gt; 0.05). Discussion:This exploratory study indicates that evoked and induced cortical responses reflect distinct mechanisms during CPM under SCS. Evoked responses, which primarily reflect bottom-up sensory processing, may be reduced by tonic SCS in the ascending lateral pathway areas before CPM . This reduction may suggest that tonic SCS suppresses input of the ascending lateral pathway, limiting additional inhibition by CPM. Beta ERS (induced response), which primarily reflects top-down modulation, decreased during CPM under tonic and burst SCS, suggesting engagement of the descending pain pathway.</p

    AI implementation in pediatric radiology for patient safety:a multi-society statement from the ACR, ESPR, SPR, SLARP, AOSPR, SPIN

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    Artificial intelligence (AI) has potential to revolutionize radiology, yet current solutions and guidelines are predominantly focused on adult populations, often overlooking the specific requirements of children. This is important because children differ significantly from adults in terms of physiology, developmental stages, and clinical needs, necessitating tailored approaches for the safe and effective integration of AI tools. This multi-society position statement systematically addresses four critical pillars of AI adoption: (1) regulation and purchasing, (2) implementation and integration, (3) interpretation and post-market surveillance, and (4) education. We propose pediatric-specific safety ratings, inclusion of datasets from diverse pediatric populations, quantifiable transparency metrics, and explainability of models to mitigate biases and ensure AI systems are appropriate for use in children. Risk assessment, dataset diversity, transparency, and cybersecurity are important steps in regulation and purchasing. For successful implementation, a phased strategy is recommended, involving early pilot testing, stakeholder engagement, and comprehensive post-market surveillance with continuous monitoring of defined performance benchmarks. Clear protocols for managing discrepancies and adverse incident reporting are essential to maintain trust and safety. Moreover, we emphasize the need for foundational AI literacy courses for all healthcare professionals which include pediatric safety considerations, alongside specialized training for those directly involved in pediatric imaging. Public and patient engagement is crucial to foster understanding and acceptance of AI in pediatric radiology. Ultimately, we advocate for a child-centered framework for AI integration, ensuring that the distinct needs of children are prioritized and that their safety, accuracy, and overall well-being are safeguarded.</p

    Bugler-Lamb, Aimée

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    Götz, Hannelore M.

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