RESUMEN
Owing to the unusual geometry of kagome lattices-lattices made of corner-sharing triangles-their electrons are useful for studying the physics of frustrated, correlated and topological quantum electronic states1-9. In the presence of strong spin-orbit coupling, the magnetic and electronic structures of kagome lattices are further entangled, which can lead to hitherto unknown spin-orbit phenomena. Here we use a combination of vector-magnetic-field capability and scanning tunnelling microscopy to elucidate the spin-orbit nature of the kagome ferromagnet Fe3Sn2 and explore the associated exotic correlated phenomena. We discover that a many-body electronic state from the kagome lattice couples strongly to the vector field with three-dimensional anisotropy, exhibiting a magnetization-driven giant nematic (two-fold-symmetric) energy shift. Probing the fermionic quasi-particle interference reveals consistent spontaneous nematicity-a clear indication of electron correlation-and vector magnetization is capable of altering this state, thus controlling the many-body electronic symmetry. These spin-driven giant electronic responses go well beyond Zeeman physics and point to the realization of an underlying correlated magnetic topological phase. The tunability of this kagome magnet reveals a strong interplay between an externally applied field, electronic excitations and nematicity, providing new ways of controlling spin-orbit properties and exploring emergent phenomena in topological or quantum materials10-12.
RESUMEN
Leaf senescence is induced or accelerated when leaves are detached. However, the senescence process and expression pattern of senescence-associated genes (SAGs) when leaves are detached are not clearly understood. To detect senescence-associated physiological changes and SAG expression, wheat (Triticum aestivum L.) leaves were detached and treated with light, darkness, low temperature (4 °C), jasmonic acid (JA), abscisic acid (ABA), and salicylic acid (SA). The leaf phenotypes, chlorophyll content, delayed fluorescence (DF), and expression levels of two SAGs, namely, TaSAG3 and TaSAG5, were analyzed. Under these different treatments, the detached leaves turned yellow with different patterns and varying chlorophyll content. DF significantly decreased after the dark, ABA, JA and SA treatments. TaSAG3 and TaSAG5, which are expressed in natural senescent leaves, showed different expression patterns under various treatments. However, both TaSAG3 and TaSAG5 were upregulated after leaf detachment. Our results revealed senescence-associated physiological changes and molecular differences in leaves, which induced leaf senescence during different stress treatments.
Asunto(s)
Genes de Plantas , Hojas de la Planta/fisiología , Estrés Fisiológico , Triticum/fisiología , Ácido Abscísico , Clorofila/metabolismo , Frío , Ciclopentanos , Oscuridad , Oxilipinas , Ácido SalicílicoRESUMEN
BACKGROUND: Clouds and MapReduce have shown themselves to be a broadly useful approach to scientific computing especially for parallel data intensive applications. However they have limited applicability to some areas such as data mining because MapReduce has poor performance on problems with an iterative structure present in the linear algebra that underlies much data analysis. Such problems can be run efficiently on clusters using MPI leading to a hybrid cloud and cluster environment. This motivates the design and implementation of an open source Iterative MapReduce system Twister. RESULTS: Comparisons of Amazon, Azure, and traditional Linux and Windows environments on common applications have shown encouraging performance and usability comparisons in several important non iterative cases. These are linked to MPI applications for final stages of the data analysis. Further we have released the open source Twister Iterative MapReduce and benchmarked it against basic MapReduce (Hadoop) and MPI in information retrieval and life sciences applications. CONCLUSIONS: The hybrid cloud (MapReduce) and cluster (MPI) approach offers an attractive production environment while Twister promises a uniform programming environment for many Life Sciences applications. METHODS: We used commercial clouds Amazon and Azure and the NSF resource FutureGrid to perform detailed comparisons and evaluations of different approaches to data intensive computing. Several applications were developed in MPI, MapReduce and Twister in these different environments.
Asunto(s)
Biología Computacional/métodos , Programas Informáticos , Disciplinas de las Ciencias Biológicas , Análisis por Conglomerados , Minería de Datos , MetagenómicaRESUMEN
Neovasculogenesis induced by stem cell therapy is an innovative approach to improve critical limb ischemia (CLI) in diabetes. Mesenchymal stem cells (MSCs) are ideal candidates due to their angiogenic and immunomodulatory features. The aim of this study is to determine the therapeutic effects of human placenta-derived MSCs (P-MSCs) on diabetic CLI, with or without exogenous insulin administration, and the underlying mechanism of any effect. A series of in vitro experiments were performed to assess the stemness and vasculogenic activity of P-MSCs. P-MSCs were intramuscularly injected at two different doses with and without the administration of insulin. The efficacy of P-MSC transplantation was evaluated by ischemia damage score, ambulatory score, laser Doppler perfusion image (LDPI), capillary, and vascular density. In vivo imaging was applied to track the implanted P-MSCs. In vivo differentiation and in situ secretion of angiogenic cytokines were determined. In vitro experimental outcomes showed the differentiation potential and potent paracrine effect of P-MSCs. P-MSCs survived in vivo for at least 3 weeks and led to the acceleration of ischemia recovery, due to newly formed capillaries, increased arterioles, and secretion of various proangiogenic factors. P-MSCs participate in angiogenesis and vascularization directly through differentiation and cytokine expression.