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Precision modelling of the radio sky for 21-cm cosmology with LOFAR
No full textUnderstanding how the first stars and galaxies formed is one of the central goals of modern cosmology. A unique way to probe this early phase of the Universe is through the 21-cm spectral line emitted by neutral hydrogen during the Epoch of Reionization. Detecting this signal, however, is extremely challenging: it is buried beneath much brighter radio emission from our Galaxy and from distant extragalactic sources, and its extraction requires both sensitive instruments and careful data analysis. This thesis focuses on improving our ability to isolate the cosmological signal using observations from the Low Frequency Array (LOFAR). A central challenge lies in accurately modelling and removing bright radio sources, whose imperfect subtraction can obscure the faint 21-cm signal. Particular attention is given to the development of advanced methods that provide more accurate spectral and spatial source models. Using these techniques, this work demonstrates significant progress in reducing foreground contamination and improving the quality of the recovered cosmological signal. These improvements are achieved through detailed modelling of both bright sources within the field of view, such as 3C61.1 and 3C196, and bright off-axis sources, such as Cygnus A. In addition, this thesis presents the first results obtained from the 3C196 field, which represents a promising alternative to the traditionally studied North Celestial Pole field. Together, these results show that accurate sky modelling across different observational scenarios is a key step toward a robust detection of the faint cosmological signal from the early Universe
Effects of radiotherapy on synaptic density as assessed by [11C]UCB-J PET in the brains of patients with head and neck cancer
No full textNuclear imaging in transthyretin amyloid cardiomyopathy:Improving screening, diagnosis and follow-up
No full textThis thesis investigates how nuclear imaging can improve the diagnosis, monitoring of disease progression, and evaluation of treatment response in patients with a cardiac protein misfolding disease called transthyretin amyloid cardiomyopathy (ATTR-CM).The first part focuses on bone scintigraphy, a well-established, non-invasive diagnostic tool for ATTR-CM, and explores how additional clinical value can be extracted from this technique. The thesis shows that using a cardiac blood biomarker can help identify which patients truly need a bone scan, reducing unnecessary imaging without loss of diagnostic accuracy. It also demonstrates that bone scintigraphy contains more information than is currently used in routine practice: while clinical interpretation mainly focuses on cardiac uptake, extracardiac tracer uptake is also prognostically relevant and associated with patient outcomes. Furthermore, the thesis shows that in specific patient groups bone scintigraphy can allow an earlier diagnosis than is currently achieved and may also be useful for monitoring treatment response and disease progression.The second part of the thesis examines the role of positron emission tomography (PET) imaging in ATTR-CM. Although PET is not yet routinely used in clinical practice for this disease, several PET tracers show promise in distinguishing ATTR-CM from other forms of cardiomyopathy and amyloidosis. The thesis demonstrates that PET can be particularly valuable in selected patient groups in whom bone scintigraphy is less sensitive, thereby serving as a meaningful addition to current diagnostic strategies. Finally, the thesis describes an ongoing international multicenter study aimed at validating PET for both diagnosis and longitudinal disease monitoring in patients with ATTR-CM
Multi-omics to study chronic respiratory diseases and viral infections
No full textDespite recent advances, the underlying mechanisms of the development and progression of many chronic respiratory diseases remain to be elucidated. Factors such as heterogeneity and complexity of human diseases and difficulty interpreting large datasets hinder research into chronic respiratory diseases. Omics assesses the changes in specific biological entities, such as mRNA expression, epigenetics/epigenomics, genomics, proteomics, metagenomics and metabolomics, and provides valuable insights into the roles of these processes in chronic respiratory diseases. High-throughput omics at bulk, single-cell and spatial levels empower the exploration of disease-related changes through untargeted data-driven statistical methods. Multi-omics is the exploration and integration of multiple biological processes, which compared to a single-omics, can provide a substantially greater and more holistic overview of the pathogenic mechanisms that underpin complex diseases. Multi-omics analysis can comprehensively characterise the mechanisms that drive chronic respiratory diseases, capturing unique biological signatures and cellular interactions at different omics levels. Use of these methods has begun to identify key factors and biomarkers in chronic respiratory diseases. Here, we review current omics approaches and highlight recent advances in respiratory research achieved using multi-omics and integrative methods. Our review provides a valuable resource for researchers and clinicians in this area.</p
Towards understanding cyclic di-AMP metabolism
No full textBacteria rely on small signaling molecules to rapidly adapt to changes in their environment. One such molecule, cyclic di-AMP, has emerged over the past decade as an essential regulator of bacterial physiology. This thesis investigates how cyclic di-AMP is synthesized, broken down, and used by bacteria to maintain their viability in a dynamic external environment.Chapter 1 places cyclic di-AMP in a broader physiological context, showing that its primary role is to control bacterial cell volume. By regulating the movement of ions and small molecules across the cell membrane, cyclic di-AMP allows cells to maintain internal pressure and adapt to osmotic stress. The chapter then explores how other essential cell processes are connected to cyclic di-AMP signaling, for example, cell wall synthesis, DNA replication and the stringent response, and how they are connected to cell volume control.Chapter 2 focuses on the enzyme responsible for cyclic di-AMP synthesis, CdaA. Using a combination of biochemical and structural methods, chapter 2 demonstrates that CdaA may only synthesize cyclic di-AMP efficiently when membrane-embedded, where it forms an active complex.Chapter 3 examines how cyclic di-AMP is broken down. Chapter 3 focuses on NrnA and GdpP, enzymes that are required for breakdown of cyclic di-AMP to pApA (GdpP) and finally from pApA to AMP (NrnA). NrnA is an enzyme essential which maintains bacterial viability, but which does not directly degrade cyclic di-AMP. Instead, NrnA clears the potentially toxic accumulation of dinucleotide breakdown products, like pApA.Together, this thesis presents a clear and concise investigation into cyclic di-AMP signalling, followed by investigation of key cyclic di-AMP metabolic enzymes, and finishes by exploring the implications of cyclic di-AMP research in microbial physiology and future development of cyclic di-AMP-targeted antibacterial therapies
Near-infrared light-responsive nano- and micro-platforms for cancer combination therapy
No full textChapter 1 provides a historical overview of modern laser-enabled phototherapy in clinical oncology, tracing its evolution profoundly from ancient heliotherapy to cutting-edge nanoparticle (NP)-mediated approaches. Then it introduces the mechanisms of phototherapy, mainly photothermal therapy (PTT) and photodynamic therapy (PDT). Chapter 2 reviewed the immunotherapy platform based on porous silicon NPs (PSiNPs) and porous silica NPs. Owing to their high surface area, tunable porous structure, easy surface modification, intrinsic immunogenicity and biodegradability, they are promising carriers for antigen delivery. Chapter 3 introduces a biomimetic nanovaccine fabricated via coating NIR light-responsive, photothermal PSiNPs@Au NPs-cores with cancer cell membrane (CCM). This structure enables strong specific tumor immune activation while minimizing systemic inflammation due to the weak immunostimulatory PSiNPs@Au NPs-cores. Chapter 4 presents an injectable bimetallic microsphere depot fabricated via microfluidics and photocrosslinking, denoted as HTAI. Designed for staged release, the depot first released Fe3+ to introduce ferroptosis, catalytically generate O2, and cause redox stress to sensitize the tumor for following treatments. The incorporated Au NPs remained inside the HTAI microsphere depot to provide sustained photothermal potency under NIR laser irradiation. Chapter 5 introduces a nano-in-micro microsphere depot designed for aggressive triple negative breast cancer (TNBC) local treatment, called cPAG. The cPAG integrates high conductivity, NIR light-triggered photothermal heating (brought by Au@GelMA microspheres), O2 and ROS generation (catalyzed by loaded manganese oxide nanoflowers), and innate immunity activation (triggered by co-loaded agonist)
Sepsis as a complex syndrome:Are combined biomarkers the future of diagnosis and prognosis? Clinical perspective
No full textSepsis remains a major cause of mortality worldwide, driven by a dysregulated host response to infection that leads to life-threatening organ dysfunction. Despite advances in evidence-based medicine, early diagnosis and risk stratification remain significant challenges due to the complex, multifaceted nature of sepsis and substantial interindividual variability in clinical presentation. Current approaches relying on single biomarkers cannot provide comprehensive insights into disease progression, limiting their clinical utility in guiding timely and effective interventions. Given the limitations of current single biomarkers in capturing the complexity of sepsis, there is an urgent need for improved diagnostic approaches. While the discovery of novel biomarkers remains important, combining existing biomarkers may offer a pragmatic and effective strategy to improve diagnostic accuracy by leveraging the strengths of each to compensate for the limitations of other. In this clinical perspective, we highlight the potential of such combined biomarker strategies to enhance diagnostic accuracy, support identification of the infection source, and improve prognostic assessment across the clinical course and into long-term outcomes. We provide examples of key biomarkers and their synergistic potential, emphasizing the need for advanced analytical methods such as machine learning and multi-omics integration to enhance predictive accuracy. Shifting toward multi-component biomarker panels represents a critical step toward a more precise, personalized approach to sepsis management to reduce sepsis-related morbidity and mortality. We advocate for further research and validation efforts to facilitate the clinical implementation of combined biomarker models, ultimately transforming sepsis care.</p
What Can a Business School Do When Generative Artificial Intelligence Replaces Entry-Level Graduate Jobs?
No full textPurpose: To suggest how business schools can respond when generative AI automates routine, entry-level tasks and erodes early-career opportunities. The paper addresses a focused question: What can a business school do when graduates’ entry-level jobs are replaced or reconfigured by AI?Approach: This is a perspective article that synthesises recent empirical studies, labour-market evidence, and international policy guidance. Drawing on this integrative review, the paper develops a practical institutional blueprint for programme design, governance, and university-industry collaboration.Findings: The existing literature indicates that traditional “first-rung” roles are thinning in AI-exposed occupations while expectations for day-one fluency with AI-augmented workflows rise. To bridge this capability gap, the paper proposes a coordinated blueprint: (1) reframe curricula around human-AI complementarity; (2) redesign assessment to evaluate judgment, verification, and communication; (3) build experiential pipelines that replicate the developmental function of first jobs; (4) co-design early-career roles through university-industry collaboration; (5) invest in student well-being and ethical governance; (6) sustain staff development; and (7) address common concerns (academic integrity, equity of access). Collectively, these actions enable business schools to restore apprenticeship-style learning within and immediately after degree programmes.Originality: The paper links near-term labour-market disruption from generative AI to concrete, institution-level strategies in business education. It offers an actionable, literature-informed blueprint that moves schools beyond placement facilitation to co-creation of AI-era entry pathways, showing how higher education can rebuild the apprenticeship-like learning once provided by traditional entry-level jobs