128 research outputs found

    Emergent Phenomena Induced by Spin-Orbit Coupling at Surfaces and Interfaces

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    Spin-orbit coupling (SOC) describes the relativistic interaction between the spin and momentum degrees of freedom of electrons, and is central to the rich phenomena observed in condensed matter systems. In recent years, new phases of matter have emerged from the interplay between SOC and low dimensionality, such as chiral spin textures and spin-polarized surface and interface states. These low-dimensional SOC-based realizations are typically robust and can be exploited at room temperature. Here we discuss SOC as a means of producing such fundamentally new physical phenomena in thin films and heterostructures. We put into context the technological promise of these material classes for developing spin-based device applications at room temperature

    Association of HLA class I with severe acute respiratory syndrome coronavirus infection

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    BACKGROUND: The human leukocyte antigen (HLA) system is widely used as a strategy in the search for the etiology of infectious diseases and autoimmune disorders. During the Taiwan epidemic of severe acute respiratory syndrome (SARS), many health care workers were infected. In an effort to establish a screening program for high risk personal, the distribution of HLA class I and II alleles in case and control groups was examined for the presence of an association to a genetic susceptibly or resistance to SARS coronavirus infection. METHODS: HLA-class I and II allele typing by PCR-SSOP was performed on 37 cases of probable SARS, 28 fever patients excluded later as probable SARS, and 101 non-infected health care workers who were exposed or possibly exposed to SARS coronavirus. An additional control set of 190 normal healthy unrelated Taiwanese was also used in the analysis. RESULTS: Woolf and Haldane Odds ratio (OR) and corrected P-value (Pc) obtained from two tails Fisher exact test were used to show susceptibility of HLA class I or class II alleles with coronavirus infection. At first, when analyzing infected SARS patients and high risk health care workers groups, HLA-B*4601 (OR = 2.08, P = 0.04, Pc = n.s.) and HLA-B*5401 (OR = 5.44, P = 0.02, Pc = n.s.) appeared as the most probable elements that may be favoring SARS coronavirus infection. After selecting only a "severe cases" patient group from the infected "probable SARS" patient group and comparing them with the high risk health care workers group, the severity of SARS was shown to be significantly associated with HLA-B*4601 (P = 0.0008 or Pc = 0.0279). CONCLUSIONS: Densely populated regions with genetically related southern Asian populations appear to be more affected by the spreading of SARS infection. Up until recently, no probable SARS patients were reported among Taiwan indigenous peoples who are genetically distinct from the Taiwanese general population, have no HLA-B* 4601 and have high frequency of HLA-B* 1301. While increase of HLA-B* 4601 allele frequency was observed in the "Probable SARS infected" patient group, a further significant increase of the allele was seen in the "Severe cases" patient group. These results appeared to indicate association of HLA-B* 4601 with the severity of SARS infection in Asian populations. Independent studies are needed to test these results

    Antiferromagnetic spintronics

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    Antiferromagnetic materials are magnetic inside, however, the direction of their ordered microscopic moments alternates between individual atomic sites. The resulting zero net magnetic moment makes magnetism in antiferromagnets invisible on the outside. It also implies that if information was stored in antiferromagnetic moments it would be insensitive to disturbing external magnetic fields, and the antiferromagnetic element would not affect magnetically its neighbors no matter how densely the elements were arranged in a device. The intrinsic high frequencies of antiferromagnetic dynamics represent another property that makes antiferromagnets distinct from ferromagnets. The outstanding question is how to efficiently manipulate and detect the magnetic state of an antiferromagnet. In this article we give an overview of recent works addressing this question. We also review studies looking at merits of antiferromagnetic spintronics from a more general perspective of spin-ransport, magnetization dynamics, and materials research, and give a brief outlook of future research and applications of antiferromagnetic spintronics.Comment: 13 pages, 7 figure

    Equal Graph Partitioning on Estimated Infection Network as an Effective Epidemic Mitigation Measure

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    Controlling severe outbreaks remains the most important problem in infectious disease area. With time, this problem will only become more severe as population density in urban centers grows. Social interactions play a very important role in determining how infectious diseases spread, and organization of people along social lines gives rise to non-spatial networks in which the infections spread. Infection networks are different for diseases with different transmission modes, but are likely to be identical or highly similar for diseases that spread the same way. Hence, infection networks estimated from common infections can be useful to contain epidemics of a more severe disease with the same transmission mode. Here we present a proof-of-concept study demonstrating the effectiveness of epidemic mitigation based on such estimated infection networks. We first generate artificial social networks of different sizes and average degrees, but with roughly the same clustering characteristic. We then start SIR epidemics on these networks, censor the simulated incidences, and use them to reconstruct the infection network. We then efficiently fragment the estimated network by removing the smallest number of nodes identified by a graph partitioning algorithm. Finally, we demonstrate the effectiveness of this targeted strategy, by comparing it against traditional untargeted strategies, in slowing down and reducing the size of advancing epidemics

    Evolutionary Repercussions of Avian Culling on Host Resistance and Influenza Virulence

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    Keeping pandemic influenza at bay is a global health priority. Of particular concern is the continued spread of the influenza subtype H5N1 in avian populations and the increasing frequency of transmission to humans. To decrease this threat, mass culling is the principal strategy for eradicating influenza in avian populations. Although culling has a crucial short-term epidemiological benefit, evolutionary repercussions on reservoir hosts and on the viral population have not been considered.To explore the epidemiological and evolutionary repercussions of mass avian culling, we combine population genetics and epidemiological influenza dynamics in a mathematical model parameterized by clinical, epidemiological, and poultry data. We model the virulence level of influenza and the selection on a dominant allele that confers resistance against influenza [1, 2] in a poultry population. Our findings indicate that culling impedes the evolution of avian host resistance against influenza. On the pathogen side of the coevolutionary race between pathogen and host, culling selects for heightened virulence and transmissibility of influenza.Mass culling achieves a short-term benefit at the expense of long-term detriments: a more genetically susceptible host population, ultimately greater mortality, and elevated influenza virulence

    Assessing population genetic structure via the maximisation of genetic distance

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    <p>Abstract</p> <p>Background</p> <p>The inference of the hidden structure of a population is an essential issue in population genetics. Recently, several methods have been proposed to infer population structure in population genetics.</p> <p>Methods</p> <p>In this study, a new method to infer the number of clusters and to assign individuals to the inferred populations is proposed. This approach does not make any assumption on Hardy-Weinberg and linkage equilibrium. The implemented criterion is the maximisation (via a <it>simulated annealing </it>algorithm) of the averaged genetic distance between a predefined number of clusters. The performance of this method is compared with two Bayesian approaches: STRUCTURE and BAPS, using simulated data and also a real human data set.</p> <p>Results</p> <p>The simulations show that with a reduced number of markers, BAPS overestimates the number of clusters and presents a reduced proportion of correct groupings. The accuracy of the new method is approximately the same as for STRUCTURE. Also, in Hardy-Weinberg and linkage disequilibrium cases, BAPS performs incorrectly. In these situations, STRUCTURE and the new method show an equivalent behaviour with respect to the number of inferred clusters, although the proportion of correct groupings is slightly better with the new method. Re-establishing equilibrium with the randomisation procedures improves the precision of the Bayesian approaches. All methods have a good precision for <it>F</it><sub><it>ST </it></sub>≥ 0.03, but only STRUCTURE estimates the correct number of clusters for <it>F</it><sub><it>ST </it></sub>as low as 0.01. In situations with a high number of clusters or a more complex population structure, MGD performs better than STRUCTURE and BAPS. The results for a human data set analysed with the new method are congruent with the geographical regions previously found.</p> <p>Conclusion</p> <p>This new method used to infer the hidden structure in a population, based on the maximisation of the genetic distance and not taking into consideration any assumption about Hardy-Weinberg and linkage equilibrium, performs well under different simulated scenarios and with real data. Therefore, it could be a useful tool to determine genetically homogeneous groups, especially in those situations where the number of clusters is high, with complex population structure and where Hardy-Weinberg and/or linkage equilibrium are present.</p

    A sequence-based genetic linkage map as a reference for Brassica rapa pseudochromosome assembly

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    <p>Abstract</p> <p>Background</p> <p><it>Brassica rapa </it>is an economically important crop and a model plant for studies concerning polyploidization and the evolution of extreme morphology. The multinational <it>B. rapa </it>Genome Sequencing Project (BrGSP) was launched in 2003. In 2008, next generation sequencing technology was used to sequence the <it>B. rapa </it>genome. Several maps concerning <it>B. rapa </it>pseudochromosome assembly have been published but their coverage of the genome is incomplete, anchoring approximately 73.6% of the scaffolds on to chromosomes. Therefore, a new genetic map to aid pseudochromosome assembly is required.</p> <p>Results</p> <p>This study concerns the construction of a reference genetic linkage map for <it>Brassica rapa</it>, forming the backbone for anchoring sequence scaffolds of the <it>B. rapa </it>genome resulting from recent sequencing efforts. One hundred and nineteen doubled haploid (DH) lines derived from microspore cultures of an F1 cross between a Chinese cabbage (<it>B. rapa </it>ssp. <it>pekinensis</it>) DH line (Z16) and a rapid cycling inbred line (L144) were used to construct the linkage map. PCR-based insertion/deletion (InDel) markers were developed by re-sequencing the two parental lines. The map comprises a total of 507 markers including 415 InDels and 92 SSRs. Alignment and orientation using SSR markers in common with existing <it>B. rapa </it>linkage maps allowed ten linkage groups to be identified, designated A01-A10. The total length of the linkage map was 1234.2 cM, with an average distance of 2.43 cM between adjacent marker loci. The lengths of linkage groups ranged from 71.5 cM to 188.5 cM for A08 and A09, respectively. Using the developed linkage map, 152 scaffolds were anchored on to the chromosomes, encompassing more than 82.9% of the <it>B. rapa </it>genome. Taken together with the previously available linkage maps, 183 scaffolds were anchored on to the chromosomes and the total coverage of the genome was 88.9%.</p> <p>Conclusions</p> <p>The development of this linkage map is vital for the integration of genome sequences and genetic information, and provides a useful resource for the international <it>Brassica </it>research community.</p

    Trends in parameterization, economics and host behaviour in influenza pandemic modelling: a review and reporting protocol.

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    BACKGROUND: The volume of influenza pandemic modelling studies has increased dramatically in the last decade. Many models incorporate now sophisticated parameterization and validation techniques, economic analyses and the behaviour of individuals. METHODS: We reviewed trends in these aspects in models for influenza pandemic preparedness that aimed to generate policy insights for epidemic management and were published from 2000 to September 2011, i.e. before and after the 2009 pandemic. RESULTS: We find that many influenza pandemics models rely on parameters from previous modelling studies, models are rarely validated using observed data and are seldom applied to low-income countries. Mechanisms for international data sharing would be necessary to facilitate a wider adoption of model validation. The variety of modelling decisions makes it difficult to compare and evaluate models systematically. CONCLUSIONS: We propose a model Characteristics, Construction, Parameterization and Validation aspects protocol (CCPV protocol) to contribute to the systematisation of the reporting of models with an emphasis on the incorporation of economic aspects and host behaviour. Model reporting, as already exists in many other fields of modelling, would increase confidence in model results, and transparency in their assessment and comparison
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