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Drug–device combinations in rare diseases: Challenges and opportunities
Get PDFDrug–device combinations (DDCs) are therapeutic products that integrate drugs with medical devices to enhance treatment efficacy and/or safety. These combinations hold significant promise for rare diseases, which affect millions of patients globally, by improving drug delivery, targeting specific organs, and reducing side effects. However, the regulatory framework for DDCs remains complex and lacks specific incentives for rare diseases, unlike orphan drugs. This review examines regulatory approaches and case studies of DDCs in rare diseases, and highlights specific challenges and untapped opportunities. Moreover, the publication discusses recommendations to overcome these challenges through tailored policies and incentives to unlock the potential of DDCs in the context of rare diseases.</p
Author Correction: Ex vivo validation of magnetically actuated intravascular untethered robots in a clinical setting:Ex vivo validation of magnetically actuated intravascular untethered robots in a clinical setting (Communications Engineering, (2024), 3, 1, (68), 10.1038/s44172-024-00215-2)
Get PDFCorrection to: Communications Engineeringhttps://doi.org/10.1038/s44172-024-00215-2, published online 16 May 2024 In the version of the article initially published, Michiel Warlé was incorrectly associated with the Department of Physics, German University in Cairo, New Cairo, 11835, Egypt. The correct affiliation is: Department of Surgery, Division of Vascular and Transplant Surgery, Radboud University Medical Center Nijmegen, Nijmegen, Netherlands. This has now been corrected in both the PDF and HTML versions of the article.</p
Wireless mechanical and hybrid thrombus fragmentation of ex vivo endovascular thrombosis model in the iliac artery
Get PDFThis study investigates the efficacy of an untethered magnetic robot (UMR) for wireless mechanical and hybrid blood clot removal in ex vivo tissue environments. By integrating x-ray-guided wireless manipulation with UMRs, we aim to address challenges associated with precise and controlled blood clot intervention. The untethered nature and size of these robots enhance maneuverability and accessibility within complex vascular networks, potentially improving clot removal efficiency. We explore mechanical fragmentation, chemical lysis, and hybrid dissolution techniques that combine mechanical fragmentation with chemical lysis, highlighting their potential for targeted and efficient blood clot removal. Through experimental validation using an ex vivo endovascular thrombosis model within the iliac artery of a sheep, we demonstrate direct revascularization of a 13-mm-long, 1-day-old blood clot positioned inside the left common iliac artery. This was achieved by deploying a UMR into the abdominal aorta within 15 min. Additionally, both mechanical fragmentation and hybrid dissolution achieve a greater volume rate of change compared to no intervention (control) and chemical lysis alone. Mechanical fragmentation exhibits clot removal with a median of 0.87 mm3/min and a range of 2.81 mm3/min, while the hybrid approach demonstrates slower but more consistent clot removal, with a median of 0.45 mm3/min and a range of 0.23 mm3/min
Robust computer vision with applications to microscopic image analysis
Get PDFComputer vision models often struggle in real-world applications due to data distribution shifts caused by variations in imaging conditions, sensor errors, or stylistic differences. This performance drop is particularly concerning in high-stakes domains like healthcare and autonomous driving, motivating research into improving model robustness and generalization. This thesis explores model learning behavior and develops techniques to improve robustness against common corruptions such as noise and blur. The research first reviews existing robustness methods, e.g. data augmentation, and finds that simply increasing model and dataset size does not effectively improve generalization. Instead, a novel frequency augmentation approach is proposed, combined with traditional augmentation methods to better handle real-world corruptions. Further analysis reveals that models often rely on frequency shortcuts, exploiting small and specific sets of frequencies for predictions. This can harm out-of-distribution (OOD) performance. Methods are proposed to mitigate this learning bias without sacrificing in-distribution performance.The study also addresses real-world challenges in microscope image analysis, where blur degrades image quality. A disentanglement representation learning technique separates cell structures from blur artifacts, enabling sharper image reconstructions. Additionally, a novel plant protoplast dataset is introduced to advance research in automated cell analysis for agricultural applications.In conclusion, this work advances model robustness through innovative augmentation and representation learning techniques while uncovering critical insights into shortcut learning. Future directions include designing inherently robust architectures and training strategies to ensure reliable performance across diverse real-world scenarios.<br/
Cascading disasters:How the 2023 Türkiye-Syria earthquake was amplified by an atmospheric river
Get PDFStrong earthquakes in mountain landscapes can trigger widespread slope failures, initiating chains of multiple hydro-geomorphic hazards such as channel blockage, instability, flooding, and coarse sedimentation. These impacts disrupting ongoing response operations may be fueled and potentially amplified by extreme post-seismic precipitation delivered by atmospheric rivers (ARs), which can form continent-spanning corridors of concentrated moisture. Yet, such cases of ARs occurring in the aftermath of major earthquakes have remained unreported to the best of our knowledge. Here, we document the combined effects of seismic and precipitation extremes that perturbed the area struck by the February 6, 2023 Türkiye-Syrian earthquakes (Mw 7.8 and 7.6), the largest seismic sequence ever recorded in the region. Strong ground shaking triggered thousands of landslides and was followed, 36 days later, by an exceptionally strong AR bringing severe precipitation with up to 183 mm in 20 hour. This rainfall induced yet more landslides, debris flows, and flooding, disrupting recovery efforts, affecting earthquake victims and temporary settlement areas, and claiming more lives. This unprecedented disaster highlights the need to revise rapid hazard assessment protocols to account better for hazard cascades arising from tightly timed seismic and weather extremes
Radiation stability of two extraction chromatography resins containing aza-crown-based diglycolamides used for Am(III) uptake
No full textThe radiolytic stability of two extraction chromatography resins with multiple diglycolamide arms was investigated by exposing them to gamma radiation and carrying out uptake studies of Am(III) from acidic feeds. The resins contained aza-crown-based diglycolamide (DGA) ligands, viz., triaza-9-crown-3-N,N’,N”-trisdiglycolamide (TAM-3-DGA) and tetraaza-12-crown-4-N,N’,N”,N’”-tetrakisdiglycolamide (TAM-4-DGA), where the DGA moieties were grafted to the ‘N’ atoms of the macrocyclic ring. These two resins showed excellent performance for the separation of Am(III) from radioactive feed solutions and radiation stabilities were evaluated under a reasonably high gamma ray dose of 1000 kGy. The irradiated resins were employed to recover Am(III) from the acidic feeds in order to evaluate the radiation resistance of the sorbent. The irradiated resins yielded large distribution coefficients for the uptake of Am(III) in the acidity range of 0.5 M – 6 M HNO3. Different physicochemical properties of the irradiated resins vis-à-vis the pristine resins were evaluated to establish their radiation stabilities. Recycling possibility of the resins was ensured in 5 successive cycles of sorption and desorption. Column studies were carried out using an Am(III) tracer spiked feed containing Eu carrier. The results support the possible application of the two TAM-n-DGA resins (n = 3 or 4) for the separation of Am(III) from radioactive waste solutions without any issue of recycling and radiation stability.</p
Rethinking GIScience education in an age of disruptions
Get PDFGIS and GIScience education have continually evolved over the past three decades, responding to technological advances and societal issues. Today, the content and context in which GIScience is taught continue to be impacted by these disruptions, notably from technology through artificial intelligence (AI) and society through the myriad environmental and social challenges facing the planet. These disruptions create a new landscape for training within the discipline that is affecting not only what is taught in GIScience courses but also who is taught, why it is being taught, and how it is taught. The aim of this paper is to structure a direction for developing and delivering GIScience education that, amid these disruptions, can generate a capable workforce and the next generation of leaders for the discipline. We present a framework for understanding the various emphases of GIScience education and use it to discuss how the content, audience, and purpose are changing. We then discuss how pedagogical strategies and practices can change how GIScience concepts and skills are taught to train more creative, inclusive, and empathetic learners. Specifically, we focus on how GIScience pedagogy should (1) center on problem-based learning, (2) be open and accelerate open science, and (3) cultivate ethical reasoning and practices. We conclude with remarks on how the principles of GIScience education can extend beyond disciplinary boundaries for holistic spatial training across academia
Materials and flow fields of bipolar plates in polymer electrolyte membrane water electrolysis:A review
Get PDFHydrogen serves as an efficient energy vector with advantages such as high energy density, greenness, and cleanliness. Hydrogen generation from water electrolysis with renewable energy is an effective approach for achieving renewable energy consumption and green hydrogen energy production. Polymer electrolyte membrane water electrolysis (PEMWE) is capable of presenting the merits of high current density, high productivity, superior gas purity, low energy consumption and high safety. The development of PEMWE is an important part of achieving the coupling of renewable energy, electric energy and hydrogen energy. As a crucial component of PEMWE, bipolar plates (BPs) constitute the mechanical support of the whole cell and provide a channel for electron transport and material supply. These channels determine the electrochemical and hydrodynamic response of a PEMWE. This work reviews the latest developments and applications of BPs, with a focus on the challenges of flow field structure and material fabrication. The specific content covers the BP matrix, types of surface layers, and effect of flow field design on mass transfer. Extended-term growth and feasibility studies of BPs, which can provide a reference and guidance for the configuration of high-behavior flow fields in PEMWEs in the long run, are envisioned.</p
Modelling the impact of ecosystem fragmentation on ecosystem services in the degraded Ethiopian highlands
Get PDFHumans shape landscapes to optimise food, fibre, and fuel production. These modifications often fragment ecosystems and degrade ecological functions over time, particularly regulating and cultural ecosystem services (ES). Understanding how ecosystem fragmentation influences the temporal dynamics of ES is critical for biodiversity conservation and sustainable management under global environmental and climate change. Despite its importance, the role of fragmentation patterns in shaping ES over time remains underexplored. This study addresses this gap by assessing how fragmentation metrics—ecosystem area, perimeter-area ratio, and patch proximity—impact four key ES (wetland grass biomass, microclimate heat stress regulation, crop pollination, and nature-based tourism) in the degraded Ethiopian highlands. Using spatial generalized additive models (GAMs), we combined fragmentation metrics with relevant biophysical variables to model ES patterns for 2020 and extrapolated back to 2000 with year-specific remote sensing-based predictors. Our results reveal substantial temporal declines in all four ES driven by both linear and non-linear effects of ecosystem fragmentation. Over two decades, reductions in ecosystem area (25 %), increases in the perimeter-area ratio (15 %), and declines in patch proximity (30 %) were strongly associated with significant losses in all four ES. Ecosystem fragmentation not only reduces ES supply but also alters their spatial and temporal distribution. Therefore, incorporating fragmentation dynamics into ES modelling is crucial for accurate and comprehensive assessments of ES distribution. By demonstrating a novel temporal perspective on the relationship between landscape configuration and ES, our findings provide robust, data-driven insights for landscape planning and the development of sustainable conservation strategies in fragmented landscapes.</p
Foreword to the Special Issue“Exploring the Potential of Urban Remote Sensing”
Get PDFUrban growth and decline, changing urban patterns, densification, conversion, or deconstruction of the built landscape, gain, loss or alteration of natural space, socioeconomic inequalities, variabilities of structural types within and across cities, efficiency of land consumption, causes and effects of the urban heat island, environmental burdens of air pollution, impacts of natural hazards on urban assets and people, or projected effects of climate change; these manifold and crucial topics in the urban domain are all issues in a long list that could be continued almost indefinitely. All these and many other issues are omnipresent in today's cities on our planet.</p