Computational prediction of samarium hydride at megabar pressure

Samarium hydrides, a group of physically viable lanthanide polyhydrides, have yet to be experimentally realized at high pressures. In this work, we combine the first-principles methods of density functional theory (DFT) with dynamical mean-field theory (DMFT) to explore the many-body correlations of samarium. We explore various stoichiometries of samarium hydrides via random structure searches across a range of pressures and report the SmH$_2$ with a layered hexagonal structure in the $P6/mmm$ space group to a theoretically stable phase at a high pressure of approximately 200 GPa.Comment: 6 pages, 5 figure

Health risk ranking of antibiotic resistance genes in the Yangtze River

Antibiotic resistance is an escalating global health concern, exacerbated by the pervasive presence of antibiotic resistance genes (ARGs) in natural environments. The Yangtze River, the world's third-longest river, traversing areas with intense human activities, presents a unique ecosystem for studying the impact of these genes on human health. Here, we explored ARGs in the Yangtze River, examining 204 samples from six distinct habitats of approximately 6000 km of the river, including free-living and particle-associated settings, surface and bottom sediments, and surface and bottom bank soils. Employing shotgun sequencing, we generated an average of 13.69 Gb reads per sample. Our findings revealed a significantly higher abundance and diversity of ARGs in water-borne bacteria compared to other habitats. A notable pattern of resistome coalescence was observed within similar habitat types. In addition, we developed a framework for ranking the risk of ARG and a corresponding method for calculating the risk index. Applying them, we identified water-borne bacteria as the highest contributors to health risks, and noted an increase in ARG risks in particle-associated bacteria correlating with heightened anthropogenic activities. Further analysis using a weighted ARG risk index pinpointed the Chengdu–Chongqing and Yangtze River Delta urban agglomerations as regions of elevated health risk. These insights provide a critical new perspective on ARG health risk assessment, highlighting the urgent need for strategies to mitigate the impact of ARGs on human health and to preserve the ecological and economic sustainability of the Yangtze River for future human use.</p

Health risk ranking of antibiotic resistance genes in the Yangtze River

Antibiotic resistance is an escalating global health concern, exacerbated by the pervasive presence of antibiotic resistance genes (ARGs) in natural environments. The Yangtze River, the world's third-longest river, traversing areas with intense human activities, presents a unique ecosystem for studying the impact of these genes on human health. Here, we explored ARGs in the Yangtze River, examining 204 samples from six distinct habitats of approximately 6000 km of the river, including free-living and particle-associated settings, surface and bottom sediments, and surface and bottom bank soils. Employing shotgun sequencing, we generated an average of 13.69 Gb reads per sample. Our findings revealed a significantly higher abundance and diversity of ARGs in water-borne bacteria compared to other habitats. A notable pattern of resistome coalescence was observed within similar habitat types. In addition, we developed a framework for ranking the risk of ARG and a corresponding method for calculating the risk index. Applying them, we identified water-borne bacteria as the highest contributors to health risks, and noted an increase in ARG risks in particle-associated bacteria correlating with heightened anthropogenic activities. Further analysis using a weighted ARG risk index pinpointed the Chengdu–Chongqing and Yangtze River Delta urban agglomerations as regions of elevated health risk. These insights provide a critical new perspective on ARG health risk assessment, highlighting the urgent need for strategies to mitigate the impact of ARGs on human health and to preserve the ecological and economic sustainability of the Yangtze River for future human use.</p

Effects of Coronal Magnetic Field Configuration on Particle Acceleration and Release during the Ground Level Enhancement Events in Solar Cycle 24

Ground level enhancements (GLEs) are extreme solar energetic particle (SEP) events that are of particular importance in space weather. In solar cycle 24, two GLEs were recorded on 2012 May 17 (GLE 71) and 2017 September 10 (GLE 72), respectively, by a range of advanced modern instruments. Here we conduct a comparative analysis of the two events by focusing on the effects of large-scale magnetic field configuration near active regions on particle acceleration and release. Although the active regions both located near the western limb, temporal variations of SEP intensities and energy spectra measured in-situ display different behaviors at early stages. By combining a potential field model, we find the CME in GLE 71 originated below the streamer belt, while in GLE 72 near the edge of the streamer belt. We reconstruct the CME shock fronts with an ellipsoid model based on nearly simultaneous coronagraph images from multi-viewpoints, and further derive the 3D shock geometry at the GLE onset. The highest-energy particles are primarily accelerated in the shock-streamer interaction regions, i.e., likely at the nose of the shock in GLE 71 and the eastern flank in GLE 72, due to quasi-perpendicular shock geometry and confinement of closed fields. Subsequently, they are released to the field lines connecting to near-Earth spacecraft when the shocks move through the streamer cusp region. This suggests that magnetic structures in the corona, especially shock-streamer interactions, may have played an important role in the acceleration and release of the highest-energy particles in the two events.Comment: Accepted for publication in Ap

Generative AI for Medical Imaging: extending the MONAI Framework

Recent advances in generative AI have brought incredible breakthroughs in several areas, including medical imaging. These generative models have tremendous potential not only to help safely share medical data via synthetic datasets but also to perform an array of diverse applications, such as anomaly detection, image-to-image translation, denoising, and MRI reconstruction. However, due to the complexity of these models, their implementation and reproducibility can be difficult. This complexity can hinder progress, act as a use barrier, and dissuade the comparison of new methods with existing works. In this study, we present MONAI Generative Models, a freely available open-source platform that allows researchers and developers to easily train, evaluate, and deploy generative models and related applications. Our platform reproduces state-of-art studies in a standardised way involving different architectures (such as diffusion models, autoregressive transformers, and GANs), and provides pre-trained models for the community. We have implemented these models in a generalisable fashion, illustrating that their results can be extended to 2D or 3D scenarios, including medical images with different modalities (like CT, MRI, and X-Ray data) and from different anatomical areas. Finally, we adopt a modular and extensible approach, ensuring long-term maintainability and the extension of current applications for future features

The gut microbiome dysbiosis and regulation by fecal microbiota transplantation: umbrella review

BackgroundGut microbiome dysbiosis has been implicated in various gastrointestinal and extra-gastrointestinal diseases, but evidence on the efficacy and safety of fecal microbiota transplantation (FMT) for therapeutic indications remains unclear.MethodsThe gutMDisorder database was used to summarize the associations between gut microbiome dysbiosis and diseases. We performed an umbrella review of published meta-analyses to determine the evidence synthesis on the efficacy and safety of FMT in treating various diseases. Our study was registered in PROSPERO (CRD42022301226).ResultsGut microbiome dysbiosis was associated with 117 gastrointestinal and extra-gastrointestinal. Colorectal cancer was associated with 92 dysbiosis. Dysbiosis involving Firmicutes (phylum) was associated with 34 diseases. We identified 62 published meta-analyses of FMT. FMT was found to be effective for 13 diseases, with a 95.56% cure rate (95% CI: 93.88–97.05%) for recurrent Chloridoids difficile infection (rCDI). Evidence was high quality for rCDI and moderate to high quality for ulcerative colitis and Crohn’s disease but low to very low quality for other diseases.ConclusionGut microbiome dysbiosis may be implicated in numerous diseases. Substantial evidence suggests FMT improves clinical outcomes for certain indications, but evidence quality varies greatly depending on the specific indication, route of administration, frequency of instillation, fecal preparation, and donor type. This variability should inform clinical, policy, and implementation decisions regarding FMT