Breaking research silos to achieve equitable precision medicine in rheumatology
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Engineering bone/cartilage organoids: strategy, progress, and application
The concept and development of bone/cartilage organoids are rapidly gaining momentum, providing opportunities for both fundamental and translational research in bone biology. Bone/cartilage organoids, essentially miniature bone/cartilage tissues grown in vitro, enable the study of complex cellular interactions, biological processes, and disease pathology in a representative and controlled environment. This review provides a comprehensive and up-to-date overview of the field, focusing on the strategies for bone/cartilage organoid construction strategies, progresses in the research, and potential applications. We delve into the significance of selecting appropriate cells, matrix gels, cytokines/inducers, and construction techniques. Moreover, we explore the role of bone/cartilage organoids in advancing our understanding of bone/cartilage reconstruction, disease modeling, drug screening, disease prevention, and treatment strategies. While acknowledging the potential of these organoids, we discuss the inherent challenges and limitations in the field and propose potential solutions, including the use of bioprinting for organoid induction, AI for improved screening processes, and the exploration of assembloids for more complex, multicellular bone/cartilage organoids models. We believe that with continuous refinement and standardization, bone/cartilage organoids can profoundly impact patient-specific therapeutic interventions and lead the way in regenerative medicine.
Efficient computation using spatial-photonic Ising machines with low-rank and circulant matrix constraints
Spatial-photonic Ising machines (SPIMs) have shown promise as an energy-efficient Ising machine, but currently can only solve a limited set of Ising problems. There is currently limited understanding on what experimental constraints may impact the performance of SPIM, and what computationally intensive problems can be efficiently solved by SPIM. Our results indicate that the performance of SPIMs is critically affected by the rank and precision of the coupling matrices. By developing and assessing advanced decomposition techniques, we expand the range of problems SPIMs can solve, overcoming the limitations of traditional Mattis-type matrices. Our approach accommodates a diverse array of coupling matrices, including those with inherently low ranks, applicable to complex NP-complete problems. We explore the practical benefits of the low-rank approximation in optimisation tasks, particularly in financial optimisation, to demonstrate the real-world applications of SPIMs. Finally, we evaluate the computational limitations imposed by SPIM hardware precision and suggest strategies to optimise the performance of these systems within these constraints.
Clinical practice recommendations for the diagnosis and management of X-linked hypophosphataemia
X-linked hypophosphataemia (XLH) is a rare metabolic bone disorder caused by pathogenic variants in the PHEX gene, which is predominantly expressed in osteoblasts, osteocytes and odontoblasts. XLH is characterized by increased synthesis of the bone-derived phosphaturic hormone fibroblast growth factor 23 (FGF23), which results in renal phosphate wasting with consecutive hypophosphataemia, rickets, osteomalacia, disproportionate short stature, oral manifestations, pseudofractures, craniosynostosis, enthesopathies and osteoarthritis. Patients with XLH should be provided with multidisciplinary care organized by a metabolic bone expert. Historically, these patients were treated with frequent doses of oral phosphate supplements and active vitamin D, which was of limited efficiency and associated with adverse effects. However, the management of XLH has evolved in the past few years owing to the availability of burosumab, a fully humanized monoclonal antibody that neutralizes circulating FGF23. Here, we provide updated clinical practice recommendations for the diagnosis and management of XLH to improve outcomes and quality of life in these patients.
Evolution, genetic diversity, and health
Human genetic diversity in today’s world has been shaped by evolutionary history, demographic shifts and environmental exposures, influencing complex traits, disease susceptibility and drug responses. Capturing this diversity is essential for advancing precision medicine and promoting equitable healthcare. Despite the great progress achieved with initiatives such as the human Pangenome and large biobanks that aim for a better representation of human diversity, important challenges remain. In this Perspective, we discuss the importance of diversity in clinical genomics through an evolutionary lens. We highlight progress and challenges and outline key clinical applications of diverse genetic data. We argue that diversifying both datasets and methodologies—integrating ancestral and environmental factors—is crucial for fully understanding the genetic basis of human health and disease.
Experimental benchmarking of quantum state overlap estimation strategies with photonic systems
Accurately estimating the overlap between quantum states is a fundamental task in quantum information processing. While various strategies using distinct quantum measurements have been proposed for overlap estimation, the lack of experimental benchmarks on estimation precision limits strategy selection in different situations. Here we compare the performance of four practical strategies for overlap estimation, including tomography-tomography, tomography-projection, Schur collective measurement and optical swap test using photonic quantum systems. We encode the quantum states on the polarization and path degrees of freedom of single photons. The corresponding measurements are performed by photon detection on certain modes following single-photon mode transformation or two-photon interference. We further propose an adaptive strategy with optimized precision in full-range overlap estimation. Our results shed new light on extracting the parameter of interest from quantum systems, prompting the design of efficient quantum protocols.
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