Filter Results
4339 results
A new Mn(II) complex {[Mn5(CH3COO)2(L)2(DMF)8](DMF)}n (1), (H4L = 3,5-bis(3′,5′-dicarboxylphenyl)-1H-1,2,3-triazole), has been synthesized and structurally characterized. The complex 1 have pentanuclear Mn(II) core, where the two sides of metal centers (Mn2 and Mn3) have trigonal bipyramidal arrangement and the middle metal center (Mn1) have octahedral environment utilizing two O atoms from adjacent bridging bidentate carboxylate groups and four O atoms from four coordinated DMF molecules. The planar arrangement of pentanuclear Mn(II) atoms are linked by L linkage to generate two dimensional sheet. The magnetic property of the compound indicates χM T value for the five Mn(II) unit to be 21.3 cm3 K mol−1 at 300 K, which is close to the spin-only value (21.9 cm3 K mol−1) for the pentamer having S = 5/2. Also, the Hirshfeld surface analyses have been performed which indicated the absence of weak Mn···Mn interaction thereby corroborating the results of observed magnetic properties.
Data Types:
  • Image
  • Tabular Data
  • Document
  • Text
Chromatographic background drift correction, which influences peak detection and time shift alignment results, is a critical stage in chromatographic data analysis. In this study, an automatic background drift correction methodology was developed. Local minimum values in a chromatogram were initially detected and organized as a new baseline vector. Iterative optimization was then employed to recognize outliers, which belong to the chromatographic peaks, in this vector, and update the outliers in the baseline until convergence. The optimized baseline vector was finally expanded into the original chromatogram, and linear interpolation was employed to estimate background drift in the chromatogram. The principle underlying the proposed method was confirmed using a complex gas chromatographic dataset. Finally, the proposed approach was applied to eliminate background drift in liquid chromatography quadrupole time-of-flight samples used in the metabolic study of Escherichia coli samples. The proposed method was comparable with three classical techniques: morphological weighted penalized least squares, moving window minimum value strategy and background drift correction by orthogonal subspace projection. The proposed method allows almost automatic implementation of background drift correction, which is convenient for practical use.
Data Types:
  • Image
  • Tabular Data
  • Text
  • File Set
Superoxide dismutases (SODs) are scavengers of superoxide radicals, one of the main reactive oxygen species (ROS) in the cell. SOD-based ROS scavenging system constitutes the frontline defense against intra- and extracellular ROS, but the roles of SODs in the important cereal pathogen Fusarium graminearum are not very clear. There are five SOD genes in F. graminearum genome, encoding cytoplasmic Cu-Zn SOD1 and MnSOD3, mitochondrial MnSOD2 and FeSOD4, and extracellular CuSOD5. Previous studies reported that the expression of SOD1 increased during infection of wheat coleoptiles and florets. In this work we showed that the recombinant SOD1 protein had the superoxide dismutase activity in vitro, and that the SOD1-mRFP fusion protein localized in the cytoplasm of F. graminearum. The Δsod1 mutants had slightly reduced hyphal growth and markedly increased sensitivity to the intracellular ROS generator menadione. The conidial germination under extracellular oxidative stress was significantly delayed in the mutants. Wheat floret infection assay showed that the Δsod1 mutants had a reduced pathogenicity. Furthermore, the Δsod1 mutants had a significant reduction in production of deoxynivalenol mycotoxin. Our results indicate that the cytoplasmic Cu-Zn SOD1 affects fungal growth probably depending on detoxification of intracellular superoxide radicals, and that SOD1-mediated deoxynivalenol production contributes to the virulence of F. graminearum in wheat head infection.
Data Types:
  • Image
  • Tabular Data
  • Document
  • Text
The visible spectrum of CD has been investigated at high resolution between 24,500 and 27,500cm−1 using a high accuracy dispersive optical spectroscopy technique. The CD molecules were produced and excited in a stainless steel hollow-cathode lamp with two anodes and filled with a mixture of He buffer gas and CD4. The emission from the discharge was observed with a plane grating spectrograph and recorded by a photomultiplier tube. The 0–0, 1–0 and 1–1 bands of the B2Σ-–X2Π transition have been registered and measured, while 2–0 and 2–1 absorption bands (Herzberg and Johns, 1969) have been reanalyzed. The current data were elaborated with help of recent X2Π ground state parameters reported by Zachwieja et al. (2012) from investigation of the A2Δ–X2Π transition. This way, the improved spectroscopic constants for the B2Σ- state of CD have been provided as follows: νe=26,050.787(11)cm−1, ωe=1653.019(25)cm−1, ωexe=123.899(12)cm−1, Be=7.08296(32)cm−1, αe=0.30741(84)cm−1, and γe=-0.10727(42)cm−1.
Data Types:
  • Image
  • Tabular Data
  • Text
MicroRNAs (miRNAs) are a class of endogenous, non-coding small RNAs that serve as important post-transcriptional gene expression regulators and play important roles in the silkworm (Bombyx mori) development, growth, and viral immunity. However, information on the diversity of these regulatory RNAs in the middle silk gland (MSG) of naked pupa (Nd) mutant silkworms is limited. In this study, by using Solexa high-throughput sequencing technology, we identified and compared small RNA libraries from the MSG of wild-type silkworm P50(MSG-P50) and the Nd mutant (MSG-Nd), respectively. A total of 272 conserved and 333 novel miRNAs were identified, in which 141 ones showed significantly different expression patterns between MSG-P50 and MSG-Nd, and 10 ones were randomly selected and validated by stem-loop quantitative reverse-transcription polymerase chain reaction (qRT-PCR). In addition, potential targets were predicted for differentially expressed miRNAs based on sequence complementation between miRNAs and their target genes. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation revealed miRNAs that actively participate in various life processes and three pathways associated with protein synthesis including endoplasmic reticulum pathway, ribosome pathway, and ribosome biogenesis in eukaryotes, were significantly disrupted in MSG-Nd. This is the first comprehensive description of miRNAs in the silkworm MSG. Overall, the results provide useful information for future studies on miRNAs and suggest that the fibroin synthetic deficiency in the posterior silk gland impairs the sericin secretion process in MSG.
Data Types:
  • Image
  • Tabular Data
  • Text
It has become important for ethanol producers to hedge input and output price risks. The purpose of this paper is to analyze an ethanol-producing firm's strategy to reduce price risks for inputs and outputs. Corn is the primary input, and the outputs are ethanol, corn oil, distillers' dried grains (DDGs), and renewable identification numbers (RINs). A theoretical model is developed including margins and risk is measured using value at risk (VaR). An empirical model is developed and extended to VaR using copulas to analyze the marginal distribution and dependence structure for input and output prices on margins. Efficient frontier curves analyzing VaR with and without copula are discussed. The results compare varying risk-strategy measures for long corn, short corn, and combining short and long corn. Sensitivity analyses are conducted for functional changes in the margin as a result of ethanol price changes.
Data Types:
  • Image
  • Tabular Data
  • Document
  • Text
Regulatory single nucleotide polymorphisms (rSNPs) in human genomes are thought to be responsible for phenotypic differences, including susceptibility to diseases and treatment outcomes, even they do not change any gene product. However, a genome-wide search for rSNPs has not been properly addressed so far. In this work, a computational method for rSNP identification is proposed. As background SNPs far outnumber rSNPs, an ensemble method is applied to handle imbalanced data, which firstly converts an unbalanced dataset into several balanced ones and then models for every balanced dataset. Two major types of features are extracted, that are sequence based features and allele-specific based features. Then random forest is applied to build the recognition model for each balanced dataset. Finally, ensemble strategies are adopted to combine the result of each model together. We have tested our method on a set of experimentally verified rSNPs, and leave-one-out cross-validation results showed that our method can achieve accuracy with sensitivity of 73.8%, specificity of 71.8% and the area under ROC curve (AUC) is 0.756. In addition, our method is threshold free and doesn’t rely on data of regulatory elements, thus it will have better adaptability when facing different data scenarios. The original data and the source matlab codes involved are available at https://sourceforge.net/projects/rsnpdect/.
Data Types:
  • Image
  • Tabular Data
  • Text
Microclimatic conditions influence fungal growth, yet accurate descriptions of the relationships between the occurrence of fungi and microclimate (especially temperature) are lacking for dead wood in natural conditions. Here, we studied the occurrence of fungal fruit bodies on 2 m long segments of both standing and lying trunks of Norway spruce (Picea abies). The fungal assemblages were associated with properties of the segments related to the progression in wood decay, causes of tree death, and temperature and moisture conditions. Fluctuations in the temperature of wood decreased with increasing water content, and both water content and temperature stability increased with diameter and with the progression in wood decay. Red-listed species differed in their relations to both wood and microclimate parameters, which highlights the importance of the simultaneous presence of various wood types for the occurrence of rare and threatened species.
Data Types:
  • Image
  • Tabular Data
  • Document
  • Text
The flora in China is highly endemic. Decisions about conservation and management of biodiversity based on hotspots and conservation gaps of endemic seed plant species diversity in China are essential. In this paper, based on a species distribution data set with 12,824 Chinese endemic plants, we measured Chinese endemic seed plant diversity using five indices: endemic species richness (ER), weighted endemism (WE), phylogenetic diversity (PD), phylogenetic endemism (PE), and biogeographically weighted evolutionary distinctiveness (BED). Five percent of China's total land area with the highest biodiversity was used to identify hotspots for each index. In total, 19 hotspots covering 7.96% of China's total land area were identified. Most hotspots are located in mountainous areas, mainly in the Qinling Mountains and further south or in the Hengduan Mountains and to the east in China. Nine hotspots are identified with all five indices. These hotspots include the Hengduan Mountains, the Xishuangbanna Region, the Qinling Mountains, southwest Chongqing, and five mountainous areas (located in east Chongqing and west Hubei; in east Yunnan and west Guangxi; in north Guangxi, southeast Guizhou and southwest Hunan; in north Guangdong and south Hunan; and in southeast Tibet, respectively). Furthermore, we detected conservation gaps for hotspots of Chinese endemic seed flora by overlaying national nature reserves with the identified hotspots, and we designated priority conservation gaps for hotspots by overlaying global biodiversity hotspots with conservation gaps for hotspots. Most hotspots for Chinese endemic seed plant species are badly protected. Only 26.48% of the hotspot areas of Chinese endemic seed plant species were covered by nature reserves. We suggest that it is essential to pay more attention to herbaceous plants in biodiversity conservation, and to promote a network function of nature reserves within these hotspots in China.
Data Types:
  • Image
  • Tabular Data
  • Document
  • Text
We present an efficient, automated workflow for validating model chemistries in computational quantum chemistry by integrating several open-source web and semantic technologies within a discipline-specific context. We combine a range of open-source functionalities to (i) canonicalize the outputs of standard, popular computational chemistry software; (ii) store and index data within a central networked repository; (iii) query the data against a range of relevant properties; and (iv) compute robust statistical measures of model accuracy. Our workflow is tested by committing data from 10,304 ab initio potential energy surface calculations to a central repository and subsequently applying nested queries and analytics. Specifically, we investigate the performance of 44 different model chemistries (coupled with polarized, double-zeta basis sets) at reproducing CCSD(T)/CBS(D,T) potential energy surfaces of eight different Lewis acid/base pairs, whose dative bonds are known to be challenging to model for many electronic structure theories.
Data Types:
  • Image
  • Tabular Data
  • Text
  • File Set
7