684 resultados para Shangguan, Zhou, 1665-


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This paper examines the degree of commonalities present in the cyclical behavior of the eight largest metropolitan housing markets in Australia. Using two techniques originally in the business cycle literature we consider the degree of synchronization present and secondly decompose the series’ into their permanent and cyclical components. Both empirical approaches reveal similar results. Sydney and Melbourne are closely related to each other and are relatively segmented from the smaller metropolitan areas. In contrast, there is substantial evidence of commonalities in the cyclical behavior of the remaining cities, especially those on the Eastern and Southern coasts of Australia.

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The Eph receptor tyrosine kinases interact with their ephrin ligands on adjacent cells to facilitate contact-dependent cell communication. Ephrin B ligands are expressed on T cells and have been suggested to act as co-stimulatory molecules during T cell activation. There are no detailed reports of the expression and modulation of EphB receptors on dendritic cells, the main antigen presenting cells that interact with T cells. Here we show that mouse splenic dendritic cells (DC) and bone-marrow derived DCs (BMDC) express EphB2, a member of the EphB family. EphB2 expression is modulated by ligation of TLR4 and TLR9 and also by interaction with ephrin B ligands. Co-localization of EphB2 with MHC-II is also consistent with a potential role in T cell activation. However, BMDCs derived from EphB2 deficient mice were able to present antigen in the context of MHC-II and produce T cell activating cytokines to the same extent as intact DCs. Collectively our data suggest that EphB2 may contribute to DC responses, but that EphB2 is not required for T cell activation. This result may have arisen because DCs express other members of the EphB receptor family, EphB3, EphB4 and EphB6, all of which can interact with ephrin B ligands, or because EphB2 may be playing a role in another aspect of DC biology such as migration.

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The El Niño/Southern Oscillation (ENSO) is the leading mode of interannual climate variability. However, it is unclear how ENSO has responded to external forcing, particularly orbitally induced changes in the amplitude of the seasonal cycle during the Holocene. Here we present a reconstruction of seasonal and interannual surface conditions in the tropical Pacific Ocean from a network of high-resolution coral and mollusc records that span discrete intervals of the Holocene. We identify several intervals of reduced variance in the 2 to 7 yr ENSO band that are not in phase with orbital changes in equatorial insolation, with a notable 64% reduction between 5,000 and 3,000 years ago. We compare the reconstructed ENSO variance and seasonal cycle with that simulated by nine climate models that include orbital forcing, and find that the models do not capture the timing or amplitude of ENSO variability, nor the mid-Holocene increase in seasonality seen in the observations; moreover, a simulated inverse relationship between the amplitude of the seasonal cycle and ENSO-related variance in sea surface temperatures is not found in our reconstructions. We conclude that the tropical Pacific climate is highly variable and subject to millennial scale quiescent periods. These periods harbour no simple link to orbital forcing, and are not adequately simulated by the current generation of models.

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Partial budgeting was used to estimate the net benefit of blending Jersey milk in Holstein-Friesian milk for Cheddar cheese production. Jersey milk increases Cheddar cheese yield. However, the cost of Jersey milk is also higher; thus, determining the balance of profitability is necessary, including consideration of seasonal effects. Input variables were based on a pilot plant experiment run from 2012 to 2013 and industry milk and cheese prices during this period. When Jersey milk was used at an increasing rate with Holstein-Friesian milk (25, 50, 75, and 100% Jersey milk), it resulted in an increase of average net profit of 3.41, 6.44, 8.57, and 11.18 pence per kilogram of milk, respectively, and this additional profit was constant throughout the year. Sensitivity analysis showed that the most influential input on additional profit was cheese yield, whereas cheese price and milk price had a small effect. The minimum increase in yield, which was necessary for the use of Jersey milk to be profitable, was 2.63, 7.28, 9.95, and 12.37% at 25, 50, 75, and 100% Jersey milk, respectively. Including Jersey milk did not affect the quantity of whey butter and powder produced. Althoug further research is needed to ascertain the amount of additional profit that would be found on a commercial scale, the results indicate that using Jersey milk for Cheddar cheese making would lead to an improvement in profit for the cheese makers, especially at higher inclusion rates.

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Genome-wide association studies (GWAS) have been widely used in genetic dissection of complex traits. However, common methods are all based on a fixed-SNP-effect mixed linear model (MLM) and single marker analysis, such as efficient mixed model analysis (EMMA). These methods require Bonferroni correction for multiple tests, which often is too conservative when the number of markers is extremely large. To address this concern, we proposed a random-SNP-effect MLM (RMLM) and a multi-locus RMLM (MRMLM) for GWAS. The RMLM simply treats the SNP-effect as random, but it allows a modified Bonferroni correction to be used to calculate the threshold p value for significance tests. The MRMLM is a multi-locus model including markers selected from the RMLM method with a less stringent selection criterion. Due to the multi-locus nature, no multiple test correction is needed. Simulation studies show that the MRMLM is more powerful in QTN detection and more accurate in QTN effect estimation than the RMLM, which in turn is more powerful and accurate than the EMMA. To demonstrate the new methods, we analyzed six flowering time related traits in Arabidopsis thaliana and detected more genes than previous reported using the EMMA. Therefore, the MRMLM provides an alternative for multi-locus GWAS.

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1. Bee populations and other pollinators face multiple, synergistically acting threats, which have led to population declines, loss of local species richness and pollination services, and extinctions. However, our understanding of the degree, distribution and causes of declines is patchy, in part due to inadequate monitoring systems, with the challenge of taxonomic identification posing a major logistical barrier. Pollinator conservation would benefit from a high-throughput identification pipeline. 2. We show that the metagenomic mining and resequencing of mitochondrial genomes (mitogenomics) can be applied successfully to bulk samples of wild bees. We assembled the mitogenomes of 48 UK bee species and then shotgun-sequenced total DNA extracted from 204 whole bees that had been collected in 10 pan-trap samples from farms in England and been identified morphologically to 33 species. Each sample data set was mapped against the 48 reference mitogenomes. 3. The morphological and mitogenomic data sets were highly congruent. Out of 63 total species detections in the morphological data set, the mitogenomic data set made 59 correct detections (93�7% detection rate) and detected six more species (putative false positives). Direct inspection and an analysis with species-specific primers suggested that these putative false positives were most likely due to incorrect morphological IDs. Read frequency significantly predicted species biomass frequency (R2 = 24�9%). Species lists, biomass frequencies, extrapolated species richness and community structure were recovered with less error than in a metabarcoding pipeline. 4. Mitogenomics automates the onerous task of taxonomic identification, even for cryptic species, allowing the tracking of changes in species richness and istributions. A mitogenomic pipeline should thus be able to contain costs, maintain consistently high-quality data over long time series, incorporate retrospective taxonomic revisions and provide an auditable evidence trail. Mitogenomic data sets also provide estimates of species counts within samples and thus have potential for tracking population trajectories.

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Water resources are under stress in many regions due to increasing demands and, in places, falling quality. Climate change has the potential to change the risks of water stress.1 The focus in this section is on strategic definitions of water stress, which are based on generalized indicators of the amount of water that is available and the demands on that resource. Operational definitions, on the other hand, are typically based on the reliability of the supply of appropriate quality water and are strongly determined by local conditions.

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This section of the report outlines the effect of different levels of climate change on exposure to river flood risk, at national and watershed scales.

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This section of the report summarises the effect of different levels of climate change on risk of drought.

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Soybean, an important source of vegetable oils and proteins for humans, has undergone significant phenotypic changes during domestication and improvement. However, there is limited knowledge about genes related to these domesticated and improved traits, such as flowering time, seed development, alkaline-salt tolerance, and seed oil content (SOC). In this study, more than 106,000 single nucleotide polymorphisms (SNPs) were identified by restriction site associated DNA sequencing of 14 wild, 153 landrace, and 119 bred soybean accessions, and 198 candidate domestication regions (CDRs) were identified via multiple genetic diversity analyses. Of the 1489 candidate domestication genes (CDGs) within these CDRs, a total of 330 CDGs were related to the above four traits in the domestication, gene ontology (GO) enrichment, gene expression, and pathway analyses. Eighteen, 60, 66, and 10 of the 330 CDGs were significantly associated with the above four traits, respectively. Of 134 traitassociated CDGs, 29 overlapped with previous CDGs, 11 were consistent with candidate genes in previous trait association studies, and 66 were covered by the domesticated and improved quantitative trait loci or their adjacent regions, having six common CDGs, such as one functionally characterized gene Glyma15 g17480 (GmZTL3). Of the 68 seed size (SS) and SOC CDGs, 37 were further confirmed by gene expression analysis. In addition, eight genes were found to be related to artificial selection during modern breeding. Therefore, this study provides an integrated method for efficiently identifying CDGs and valuable information for domestication and genetic research.

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The goal of the Palaeoclimate Modelling Intercomparison Project (PMIP) is to understand the response of the climate system to changes in different climate forcings and to feedbacks. Through comparison with observations of the environmental impacts of these climate changes, or with climate reconstructions based on physical, chemical or biological records, PMIP also addresses the issue of how well state-of-the-art models simulate climate changes. Palaeoclimate states are radically different from those of the recent past documented by the instrumental record and thus provide an out-of-sample test of the models used for future climate projections and a way to assess whether they have the correct sensitivity to forcings and feedbacks. Five distinctly different periods have been selected as focus for the core palaeoclimate experiments that are designed to contribute to the objectives of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). This manuscript describes the motivation for the choice of these periods and the design of the numerical experiments, with a focus upon their novel features compared to the experiments performed in previous phases of PMIP and CMIP as well as the benefits of common analyses of the models across multiple climate states. It also describes the information needed to document each experiment and the model outputs required for analysis and benchmarking.

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When allowed to choose between different macronutrients, most animals display a strong attraction toward carbohydrates compared with proteins. It remains uncertain, however, whether this food selection pattern depends primarily on the sensory properties intrinsic to each nutrient or, alternatively, metabolic signals can act independently of the hedonic value of sweetness to stimulate elevated sugar intake. Here we show that Trpm5(-/-) mice, which lack the cellular mechanisms required for sweet and several forms of L-amino acid taste transduction, develop a robust preference for D-glucose compared with isocaloric L-serine independently of the perception of sweetness. Moreover, a close relationship was found between glucose oxidation and taste-independent nutrient intake levels, with animals increasing intake as a function of glucose oxidation rates. Furthermore, microdialysis measurements revealed nutrient-specific dopaminergic responses in accumbens and dorsal striatum during intragastric infusions of glucose or serine. Specifically, intragastric infusions of glucose induced significantly higher levels of dopamine release compared with isocaloric serine in both ventral and dorsal striatum. Intragastric stimulation of dopamine release seemed to depend on glucose utilization, because administration of an anti-metabolic glucose analog resulted in lower dopamine levels in striatum, an effect that was reversed by intravenous glucose infusions. Together, our findings suggest that carbohydrate-specific preferences can develop independently of taste quality or caloric load, an effect associated with the ability of a given nutrient to regulate glucose metabolism and stimulate brain dopamine centers.