495 research outputs found

    Ethanolic Extract of Aconiti Brachypodi Radix Attenuates Nociceptive Pain Probably Via Inhibition of Voltage-Dependent Na+ Channel

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    Aconiti Brachypodi Radix, belonging to the genus of Aconitum (Family Ranunculaceae), are used clinically as anti-rheumatic, anti-inflammatory and anti-nociceptive in traditional medicine of China. However, its mechanism and influence on nociceptive threshold are unknown and need further investigation. The analgesic effects of ethanolic extract of Aconiti Brachypodi Radix (EABR) were thus studied in vivo and in vitro. Three pain models in mice were used to assess the effect of EABR on nociceptive threshold. In vitro study was conducted to clarify the modulation of the extract on the tetrodotoxin-sensitive (TTX-S) sodium currents in rat’s dorsal root ganglion (DRG) neurons using whole-cell patch clamp technique. The results showed that EABR (5-20 mg/kg, i.g.) could produce dose-dependent analgesic effect on hot-plate tests as well as writhing response induced by acetic acid. In addition, administration of 2.5-10 mg/kg EABR (i.g.) caused significant decrease in pain responses in the first and second phases of formalin test without altering the PGE2 production in the hind paw of the mice. Moreover, EABR (10 μg/ml -1 mg/ml) could suppress TTX-S voltage-gated sodium currents in a dose-dependent way, indicating the underlying electrophysiological mechanism of the analgesic effect of the folk plant medicine. Collectively, our results indicated that EABR has analgesic property in three pain models and useful influence on TTX-S sodium currents in DRG neurons, suggesting that the interference with pain messages caused by the modulation of EABR on TTX-S sodium currents in DRG neurones may explain some of its analgesic effect

    A computational study on altered theta-gamma coupling during learning and phase coding

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    There is considerable interest in the role of coupling between theta and gamma oscillations in the brain in the context of learning and memory. Here we have used a neural network model which is capable of producing coupling of theta phase to gamma amplitude firstly to explore its ability to reproduce reported learning changes and secondly to memory-span and phase coding effects. The spiking neural network incorporates two kinetically different GABAA receptor-mediated currents to generate both theta and gamma rhythms and we have found that by selective alteration of both NMDA receptors and GABAA,slow receptors it can reproduce learning-related changes in the strength of coupling between theta and gamma either with or without coincident changes in theta amplitude. When the model was used to explore the relationship between theta and gamma oscillations, working memory capacity and phase coding it showed that the potential storage capacity of short term memories, in terms of nested gamma-subcycles, coincides with the maximal theta power. Increasing theta power is also related to the precision of theta phase which functions as a potential timing clock for neuronal firing in the cortex or hippocampus

    Using electric current to surpass the microstructure breakup limit

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    The elongated droplets and grains can break up into smaller ones. This process is driven by the interfacial free energy minimization, which gives rise to a breakup limit. We demonstrated in this work that the breakup limit can be overpassed drastically by using electric current to interfere. Electric current free energy is dependent on the microstructure configuration. The breakup causes the electric current free energy to reduce in some cases. This compensates the increment of interfacial free energy during breaking up and enables the processing to achieve finer microstructure. With engineering practical electric current parameters, our calculation revealed a significant increment of the obtainable number of particles, showing electric current a powerful microstructure refinement technology. The calculation is validated by our experiments on the breakup of Fe3C-plates in Fe matrix. Furthermore, there is a parameter range that electric current can drive spherical particles to split into smaller ones

    Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example

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    © The Author(s) 2017 This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Most agronomic traits of interest for crop improvement (including seed yield) are highly complex quantitative traits controlled by numerous genetic loci, which brings challenges for comprehensively capturing associated markers/ genes. We propose that multiple trait interactions underlie complex traits such as seed yield, and that considering these component traits and their interactions can dissect individual quantitative trait loci (QTL) effects more effectively and improve yield predictions. Using a segregating rapeseed (Brassica napus) population, we analyzed a large set of trait data generated in 19 independent experiments to investigate correlations between seed yield and other complex traits, and further identified QTL in this population with a SNP-based genetic bin map. A total of 1904 consensus QTL accounting for 22 traits, including 80 QTL directly affecting seed yield, were anchored to the B. napus reference sequence. Through trait association analysis and QTL meta-analysis, we identified a total of 525 indivisible QTL that either directly or indirectly contributed to seed yield, of which 295 QTL were detected across multiple environments. A majority (81.5%) of the 525 QTL were pleiotropic. By considering associations between traits, we identified 25 yield-related QTL previously ignored due to contrasting genetic effects, as well as 31 QTL with minor complementary effects. Implementation of the 525 QTL in genomic prediction models improved seed yield prediction accuracy. Dissecting the genetic and phenotypic interrelationships underlying complex quantitative traits using this method will provide valuable insights for genomics-based crop improvement.Peer reviewedFinal Published versio

    Identification of miRNA from Porphyra yezoensis by High-Throughput Sequencing and Bioinformatics Analysis

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    BACKGROUND: miRNAs are a class of non-coding, small RNAs that are approximately 22 nucleotides long and play important roles in the translational level regulation of gene expression by either directly binding or cleaving target mRNAs. The red alga, Porphyra yezoensis is one of the most important marine economic crops worldwide. To date, only a few miRNAs have been identified in green unicellar alga and there is no report about Porphyra miRNAs. METHODOLOGY/PRINCIPAL FINDINGS: To identify miRNAs in Porphyra yezoensis, a small RNA library was constructed. Solexa technology was used to perform high throughput sequencing of the library and subsequent bioinformatics analysis to identify novel miRNAs. Specifically, 180,557,942 reads produced 13,324 unique miRNAs representing 224 conserved miRNA families that have been identified in other plants species. In addition, seven novel putative miRNAs were predicted from a limited number of ESTs. The potential targets of these putative miRNAs were also predicted based on sequence homology search. CONCLUSIONS/SIGNIFICANCE: This study provides a first large scale cloning and characterization of Porphyra miRNAs and their potential targets. These miRNAs belong to 224 conserved miRNA families and 7 miRNAs are novel in Porphyra. These miRNAs add to the growing database of new miRNA and lay the foundation for further understanding of miRNA function in the regulation of Porphyra yezoensis development

    Identification of Genome-Wide Variations among Three Elite Restorer Lines for Hybrid-Rice

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    Rice restorer lines play an important role in three-line hybrid rice production. Previous research based on molecular tagging has suggested that the restorer lines used widely today have narrow genetic backgrounds. However, patterns of genetic variation at a genome-wide scale in these restorer lines remain largely unknown. The present study performed re-sequencing and genome-wide variation analysis of three important representative restorer lines, namely, IR24, MH63, and SH527, using the Solexa sequencing technology. With the genomic sequence of the Indica cultivar 9311 as the reference, the following genetic features were identified: 267,383 single-nucleotide polymorphisms (SNPs), 52,847 insertion/deletion polymorphisms (InDels), and 3,286 structural variations (SVs) in the genome of IR24; 288,764 SNPs, 59,658 InDels, and 3,226 SVs in MH63; and 259,862 SNPs, 55,500 InDels, and 3,127 SVs in SH527. Variations between samples were also determined by comparative analysis of authentic collections of SNPs, InDels, and SVs, and were functionally annotated. Furthermore, variations in several important genes were also surveyed by alignment analysis in these lines. Our results suggest that genetic variations among these lines, although far lower than those reported in the landrace population, are greater than expected, indicating a complicated genetic basis for the phenotypic diversity of the restorer lines. Identification of genome-wide variation and pattern analysis among the restorer lines will facilitate future genetic studies and the molecular improvement of hybrid rice

    Oxidative/Nitrative Stress and Inflammation Drive Progression of Doxorubicin-Induced Renal Fibrosis in Rats as Revealed by Comparing a Normal and a Fibrosis-Resistant Rat Strain

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    Chronic renal fibrosis is the final common pathway of end stage renal disease caused by glomerular or tubular pathologies. Genetic background has a strong influence on the progression of chronic renal fibrosis. We recently found that Rowett black hooded rats were resistant to renal fibrosis. We aimed to investigate the role of sustained inflammation and oxidative/nitrative stress in renal fibrosis progression using this new model. Our previous data suggested the involvement of podocytes, thus we investigated renal fibrosis initiated by doxorubicin-induced (5 mg/kg) podocyte damage. Doxorubicin induced progressive glomerular sclerosis followed by increasing proteinuria and reduced bodyweight gain in fibrosis-sensitive, Charles Dawley rats during an 8-week long observation period. In comparison, the fibrosis-resistant, Rowett black hooded rats had longer survival, milder proteinuria and reduced tubular damage as assessed by neutrophil gelatinase-associated lipocalin (NGAL) excretion, reduced loss of the slit diaphragm protein, nephrin, less glomerulosclerosis, tubulointerstitial fibrosis and matrix deposition assessed by periodic acid-Schiff, Picro-Sirius-red staining and fibronectin immunostaining. Less fibrosis was associated with reduced profibrotic transforming growth factor-beta, (TGF-beta1) connective tissue growth factor (CTGF), and collagen type I alpha 1 (COL-1a1) mRNA levels. Milder inflammation demonstrated by histology was confirmed by less monocyte chemotactic protein 1 (MCP-1) mRNA. As a consequence of less inflammation, less oxidative and nitrative stress was obvious by less neutrophil cytosolic factor 1 (p47phox) and NADPH oxidase-2 (p91phox) mRNA. Reduced oxidative enzyme expression was accompanied by less lipid peroxidation as demonstrated by 4-hydroxynonenal (HNE) and less protein nitrosylation demonstrated by nitrotyrosine (NT) immunohistochemistry and quantified by Western blot. Our results demonstrate that mediators of fibrosis, inflammation and oxidative/nitrative stress were suppressed in doxorubicin nephropathy in fibrosis-resistant Rowett black hooded rats underlying the importance of these pathomechanisms in the progression of renal fibrosis initiated by glomerular podocyte damage
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