Ionomics is a novel multidisciplinary field that uses advanced techniques to investigate the composition and distribution of all minerals and trace elements in a living organism and their variations under diverse physiological and pathological conditions. It involves both high-throughput elemental profiling technologies and bioinformatic methods, providing opportunities to study the molecular mechanism underlying the metabolism, homeostasis, and cross-talk of these elements. While much effort has been made in exploring the ionomic traits relating to plant physiology and nutrition, the use of ionomics in the research of serious diseases is still in progress. In recent years, a number of ionomic studies have been carried out for a variety of complex diseases, which offer theoretical and practical insights into the etiology, early diagnosis, prognosis, and therapy of them. This review aims to give an overview of recent applications of ionomics in the study of complex diseases and discuss the latest advances and future trends in this area. Overall, disease ionomics may provide substantial information for systematic understanding of the properties of the elements and the dynamic network of elements involved in the onset and development of diseases. 相似文献
Ceramics with mullite whiskers were prepared from coal fly ash and Al2O3 raw materials, with AlF3 used as an additive. The phase structures and microstructures of the ceramics were identified via X-ray diffraction and scanning electron microscopy, respectively. The results show that pickling of coal fly ash is an effective method for enhancing the flexural strength of ceramics. Sintering temperature and AlF3 addition were also key factors influencing the creation of ideal ceramics. The ceramic made from pickled coal fly ash, 6?wt% AlF3, and sintered at 1200?°C, exhibited the highest flexural strength of 59.1?MPa, and had a bulk density of 1.32?g/cm3 and porosity of 26.8%. The results show that ceramic materials made under these conditions are ideal candidates for manufacturing ceramic proppants for the exploitation of unconventional oil and gas resources. 相似文献
Large scale wireless sensor networks raise many challenges in the design of efficient and effective routing algorithm due to their complexity and hardware constraints. However, the scalability challenge may be mitigated from a macroscopic perspective. One example is the distributed De la Garza iteration (DDLGI) algorithm for global routing load-balancing, based on a set of partial differential equations iteratively solved by the De la Garza method. We theoretically analyze the parallelism of DDLGI and illustrate that the region of interest may impact the degree of parallelism and error. Furthermore, though DDLGI always converges, the slow convergence and long-range information exchange problems may lead to excess energy consumption in communication. Thus, we propose various enhanced De la Garza routing (E-DLGR) algorithms to alleviate the energy consumption problem by which nodes may exchange less information and only need to exchange information with closer nodes to complete each iteration. Our theoretical analysis and simulation results show that the proposed E-DLGR algorithms may have less transmission overhead, thus further reducing energy consumption, and converge faster while still maintaining adequate accuracy.
Strength of Materials - A metallographic method, dilatometry, and X-ray diffraction were applied to investigate the effects of undercooling and holding time on bainitic transformation,... 相似文献