635 research outputs found

    Thermal evolution history after collision of North China plate with Yangtze plate

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    对采自苏北一胶南一大别高压变质构造混杂岩带的片麻岩、糜棱岩和郑庐断裂带上的片麻岩中9个钾长石进行了40Ar-39Ar 年龄测定和多重扩散域(MDD)模式处理, 9个样品的热演化史表明上述地区存在5个不同的快速冷却时段, 并就其可能的构造含义, 提出了华北与扬子板块碰撞后的折返历史过程。40Ar-39Ar analyses and MDD(multiple diffusion domain)model treatements were performed for 9 K-feldspar samples. They were collected from gneiss and mylonite of North Jiangsu-Jiaonan-Dabie tectonic melange belt and Tancheng-Lujiang fault zone. The thermal evolution history exhibits five fast ccoling stages found in these samples.In relation with their possible tectonic implications a recovery process after the collision of the North China plate with the Yangtze plate is suggested here.published_or_final_versio

    Nanorod Photocatalysts for C-O Cross-Coupling Reactions

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    Carbon-heteroatom cross-coupling reactions are significant for numerous industrial chemical processes, in particular for the synthesis of pharmaceuticals, agrochemicals, and biologically active compounds. Photocatalyst/transition metal dual catalytic systems pave a new avenue for organic cross-coupling reactions. Specifically, the use of semiconductor nanoparticles as heterogeneous light sensitizers is highly beneficial for industrial-scale applications owing to their low-cost production, tunable photophysical properties, facile separation, high photostability, and recyclability. Here, CdSe@CdS nanorod photocatalysts are combined with a Ni complex catalyst for the promotion of selective light-induced C-O cross-coupling reactions between aryl halides and alkyl carboxylic acids. This efficient dual photocatalytic system displays a high yield (similar to 96 %), with an impressive turnover number (TON) of over 3x10(6), and within a relatively short reaction time as a result of high turnover frequency (TOF) of similar to 56 s(-1). In addition, the nanorod photocatalysts harness light with improved solar to product efficiency compared to alternative systems, signaling towards potential solar-powered chemistry. A reaction mechanism involving energy transfer from the nanorods to the Ni complex is proposed and discussed, along with specific benefits of the seeded rod morphology

    European Sea Bass (Dicentrarchus labrax) immune status and disease resistance are impaired by arginine dietary supplementation

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    Infectious diseases and fish feeds management are probably the major expenses in the aquaculture business. Hence, it is a priority to define sustainable strategies which simultaneously avoid therapeutic procedures and reinforce fish immunity. Currently, one preferred approach is the use of immunostimulants which can be supplemented to the fish diets. Arginine is a versatile amino acid with important mechanisms closely related to the immune response. Aiming at finding out how arginine affects the innate immune status or improve disease resistance of European seabass (Dicentrarchus labrax) against vibriosis, fish were fed two arginine-supplemented diets (1% and 2% arginine supplementation). A third diet meeting arginine requirement level for seabass served as control diet. Following 15 or 29 days of feeding, fish were sampled for blood, spleen and gut to assess cell-mediated immune parameters and immune-related gene expression. At the same time, fish from each dietary group were challenged against Vibrio anguillarum and survival was monitored. Cell-mediated immune parameters such as the extracellular superoxide and nitric oxide decreased in fish fed arginine-supplemented diets. Interleukins and immune-cell marker transcripts were down-regulated by the highest supplementation level. Disease resistance data were in accordance with a generally depressed immune status, with increased susceptibility to vibriosis in fish fed arginine supplemented diets. Altogether, these results suggest a general inhibitory effect of arginine on the immune defences and disease resistance of European seabass. Still, further research will certainly clarify arginine immunomodulation pathways thereby allowing the validation of its potential as a prophylactic strategy.European Union's Seventh Framework Programme AQUAEXCEL (Aquaculture Infrastructures for Excellence in European Fish Research) [262336]; AQUAIMPROV [NORTE-07-0124-FEDER-000038]; North Portugal Regional Operational Programme (ON. 2 - O Novo Norte) , under the National Strategic Reference Framework, through the European Regional Development Fund; North Portugal Regional Operational Programme (ON. 2 - O Novo Norte), under the National Strategic Reference Framework through the COMPETE - Operational Competitiveness Programme; Fundacao para a Ciencia e Tecnologia; Fundacao para a Ciencia e Tecnologia [SFRH/BD/89457/2012, SFRH/BPD/77210/2011]; Generalitat Valenciana through the project REVIDPAQUA [ISIC/2012/003]; [PEst-C/MAR/LA0015/2013]; [UID/Multi/04423/2013]info:eu-repo/semantics/publishedVersio

    Scoring docking conformations using predicted protein interfaces

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    BACKGROUND: Since proteins function by interacting with other molecules, analysis of protein-protein interactions is essential for comprehending biological processes. Whereas understanding of atomic interactions within a complex is especially useful for drug design, limitations of experimental techniques have restricted their practical use. Despite progress in docking predictions, there is still room for improvement. In this study, we contribute to this topic by proposing T-PioDock, a framework for detection of a native-like docked complex 3D structure. T-PioDock supports the identification of near-native conformations from 3D models that docking software produced by scoring those models using binding interfaces predicted by the interface predictor, Template based Protein Interface Prediction (T-PIP). RESULTS: First, exhaustive evaluation of interface predictors demonstrates that T-PIP, whose predictions are customised to target complexity, is a state-of-the-art method. Second, comparative study between T-PioDock and other state-of-the-art scoring methods establishes T-PioDock as the best performing approach. Moreover, there is good correlation between T-PioDock performance and quality of docking models, which suggests that progress in docking will lead to even better results at recognising near-native conformations. CONCLUSION: Accurate identification of near-native conformations remains a challenging task. Although availability of 3D complexes will benefit from template-based methods such as T-PioDock, we have identified specific limitations which need to be addressed. First, docking software are still not able to produce native like models for every target. Second, current interface predictors do not explicitly consider pairwise residue interactions between proteins and their interacting partners which leaves ambiguity when assessing quality of complex conformations

    Protein-Protein Interaction Site Predictions with Three-Dimensional Probability Distributions of Interacting Atoms on Protein Surfaces

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    Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI) sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins) and were tested on an independent dataset (consisting of 142 proteins). The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted correctly with the physicochemical complementarity features based on the non-covalent interaction data derived from protein interiors

    Genetic variations in APPL2 are associated with overweight and obesity in a Chinese population with normal glucose tolerance

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    <p>Abstract</p> <p>Background</p> <p>APPL1 and APPL2 are two adaptor proteins, which can mediate adiponectin signaling via binding to N terminus of adiponectin receptors in muscle cells. Genes encoding adiponectin and adiponectin receptors contribute to insulin resistance and the risk of obesity, and genetic variants of <it>APPL1 </it>are associated with body fat distribution. However, the association between genetic variations of <it>APPL2 </it>and metabolic traits remains unknown. In the current study, we aimed to test the impacts of <it>APPL2 </it>genetic variants on obesity in a Chinese population with normal glucose tolerance.</p> <p>Methods</p> <p>We genotyped six single nucleotide polymorphisms (SNPs) in <it>APPL2 </it>in 1,808 non-diabetic subjects. Overweight and obesity were defined by body mass index (BMI). Obesity-related anthropometric parameters were measured, including height, weight, waist circumference, hip circumference. BMI and waist-hip ratio (WHR) were calculated.</p> <p>Results</p> <p>We found significant evidence of association with overweight/obesity for rs2272495 and rs1107756. rs2272495 C allele and rs1107756 T allele both conferred a higher risk of being overweight and obese (OR 1.218, 95% CI 1.047-1.416, <it>p </it>= 0.011 for rs2272495; OR 1.166, 95% CI 1.014-1.341, <it>p </it>= 0.031 for rs1107756). After adjusting multiple comparisons, only the effect of rs2272495 on overweight/obesity remained to be significant (empirical <it>p </it>= 0.043). Moreover, we investigated the effects of these SNPs on obesity-related quantitative traits in all participants. rs2272495 was associated with BMI (<it>p </it>= 0.015), waist circumference (<it>p </it>= 0.006), hip circumference (<it>p </it>= 0.025) as well as WHR (<it>p </it>= 0.047) under a recessive model. Similar associations were found for rs1107756 except for WHR.</p> <p>Conclusion</p> <p>This study suggests that genetic variations in <it>APPL2 </it>are associated with overweight and obesity in Chinese population with normal glucose tolerance.</p

    Predicting protein-protein interface residues using local surface structural similarity

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    <p>Abstract</p> <p>Background</p> <p>Identification of the residues in protein-protein interaction sites has a significant impact in problems such as drug discovery. Motivated by the observation that the set of interface residues of a protein tend to be conserved even among remote structural homologs, we introduce <it>PrISE</it>, a family of local structural similarity-based computational methods for predicting protein-protein interface residues.</p> <p>Results</p> <p>We present a novel representation of the surface residues of a protein in the form of structural elements. Each structural element consists of a central residue and its surface neighbors. The <it>PrISE </it>family of interface prediction methods uses a representation of structural elements that captures the atomic composition and accessible surface area of the residues that make up each structural element. Each of the members of the <it>PrISE </it>methods identifies for each structural element in the query protein, a collection of <it>similar </it>structural elements in its repository of structural elements and weights them according to their similarity with the structural element of the query protein. <it>PrISE<sub>L </sub></it>relies on the similarity between structural elements (i.e. local structural similarity). <it>PrISE<sub>G </sub></it>relies on the similarity between protein surfaces (i.e. general structural similarity). <it>PrISE<sub>C</sub></it>, combines local structural similarity and general structural similarity to predict interface residues. These predictors label the central residue of a structural element in a query protein as an interface residue if a weighted majority of the structural elements that are similar to it are interface residues, and as a non-interface residue otherwise. The results of our experiments using three representative benchmark datasets show that the <it>PrISE<sub>C </sub></it>outperforms <it>PrISE<sub>L </sub></it>and <it>PrISE<sub>G</sub></it>; and that <it>PrISE<sub>C </sub></it>is highly competitive with state-of-the-art structure-based methods for predicting protein-protein interface residues. Our comparison of <it>PrISE<sub>C </sub></it>with <it>PredUs</it>, a recently developed method for predicting interface residues of a query protein based on the known interface residues of its (global) structural homologs, shows that performance superior or comparable to that of <it>PredUs </it>can be obtained using only local surface structural similarity. <it>PrISE<sub>C </sub></it>is available as a Web server at <url>http://prise.cs.iastate.edu/</url></p> <p>Conclusions</p> <p>Local surface structural similarity based methods offer a simple, efficient, and effective approach to predict protein-protein interface residues.</p

    Response Properties of the Auditory Telencephalon in Songbirds Change with Recent Experience and Season

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    The caudomedial nidopallium (NCM) is a telencephalic auditory area that is selectively activated by conspecific vocalizations in zebra finches and canaries. We recently demonstrated that temporal and spectral dynamics of auditory tuning in NCM differ between these species [1]. In order to determine whether these differences reflect recent experience, we exposed separate groups of each species and sex to different housing conditions. Adult birds were housed either in an aviary with conspecifics (NORM), with heterospecifics (canary subjects in a zebra finch aviary, and vice versa: (CROSS)), or in isolation (ISO) for 9 days prior to testing. We then recorded extracellular multi-unit electrophysiological responses to simple pure tone stimuli (250–5000 Hz) in awake birds from each group and analyzed auditory tuning width using methods from our earlier studies. Relative to NORM birds, tuning was narrower in CROSS birds, and wider in ISO birds. The trend was greater in canaries, especially females. The date of recording was also included as a covariate in ANCOVAs that analyzed a larger set of the canary data, including data from birds tested outside of the breeding season, and treated housing condition and sex as independent variables. These tests show that tuning width was narrower early in the year and broader later. This effect was most pronounced in CROSS males. The degree of the short-term neural plasticity described here differs across sexes and species, and may reflect differences in NCM's anatomical and functional organization related to species differences in song characteristics, adult plasticity and/or social factors. More generally, NCM tuning is labile and may be modulated by recent experience to reflect the auditory processing required for behavioral adaptation to the current acoustic, social or seasonal context

    Downgrading MELD Improves the Outcomes after Liver Transplantation in Patients with Acute-on-Chronic Hepatitis B Liver Failure

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    Background: High score of model for end-stage liver diseases (MELD) before liver transplantation (LT) indicates poor prognosis. Artificial liver support system (ALSS) has been proved to effectively improve liver and kidney functions, and thus reduce the MELD score. We aim to evaluate whether downgrading MELD score could improve patient survival after LT. Methodology/Principal Findings: One hundred and twenty-six LT candidates with acute-on-chronic hepatitis B liver failure and MELD score 30wereincludedinthisprospectivestudy.Ofthe126patients,42receivedemergencyLTwithin72h(ELTgroup)andtheother84weregivenALSSassalvagetreatment.Ofthe84patients,33werefoundtohavereducedMELDscore(,30)onthedayofLT(DGMgroup),51underwentLTwithpersistenthighMELDscore(NDGMgroup).Themedianwaitingtimeforadonorwas10forDGMgroupand9.5daysforNDGMgroup.InNDGMgroupthereisasignificantlyhigheroverallmortality(43.130 were included in this prospective study. Of the 126 patients, 42 received emergency LT within 72 h (ELT group) and the other 84 were given ALSS as salvage treatment. Of the 84 patients, 33 were found to have reduced MELD score (,30) on the day of LT (DGM group), 51 underwent LT with persistent high MELD score (N-DGM group). The median waiting time for a donor was 10 for DGM group and 9.5 days for N-DGM group. In N-DGM group there is a significantly higher overall mortality (43.1%) than that in ELT group (16.7%) and DGM group (15.2%). N-DGM (vs. ECT and DGM) was the only independent risk factor of overall mortality (P = 0.003). Age.40 years and the interval from last ALSS to LT.48 h were independent negative influence factors of downgrading MELD. Conclusions/Significance: Downgrading MELD for liver transplant candidates with MELD score 30 was effective i
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