Design and Testing of Cesium Atomic Concentration Detection System Based on TDLAS

In order to better build the Neutral Beam Injector with Negative Ion Source (NNBI), the pre-research on key technologies has been carried out for the Comprehensive Research Facility for Fusion Technology (CRAFT). Cesium seeding into negative-ion sources is a prerequisite to obtain the required negative hydrogen ion. The performance of ion source largely depends on the cesium conditions in the source. It is very necessary to quantitatively measure the amount of cesium in the source during the plasma on and off periods (vacuum stage). This article uses the absorption peak of cesium atoms near 852.1nm to build a cesium atom concentration detection system based on Tunable Diode Laser Absorption Spectroscopy (TDLAS) technology. The test experiment based on the cesium cell is carried out, obtained the variation curve of cesium concentration at different temperatures. The experimental results indicate that: the system detection range is within 5*10E6-2.5*10E7 pieces/cm3 and the system resolution better than 1*10E6 pieces/cm3.Comment: 8 pages,7 figures, the 20th International Symposium on Laser-Aided Plasma Diagnostic

An ABA triblock copolymer strategy for intrinsically stretchable semiconductors

A novel semiconductor-rubber-semiconductor (P3HT-PMA-P3HT) triblock copolymer has been designed and prepared according to the principle of thermoplastic elastomers. It behaves as a thermoplastic elastomer with a Young's modulus (E) of 6 MPa for an elongation at break of 140% and exhibits good electrical properties with a carrier mobility of 9 x 10(-4) cm(2) V-1 s(-1). This novel semiconductor may play an important role in low-cost and large-area stretchable electronics.open112223sciescopu

SUMO-2 promotes mRNA translation by enhancing interaction between eIF4E and eIF4G

Small ubiquitin-like modifier (SUMO) proteins regulate many important eukaryotic cellular processes through reversible covalent conjugation to target proteins. In addition to its many well-known biological consequences, like subcellular translocation of protein, subnuclear structure formation, and modulation of transcriptional activity, we show here that SUMO-2 also plays a role in mRNA translation. SUMO-2 promoted formation of the active eukaryotic initiation factor 4F (eIF4F) complex by enhancing interaction between Eukaryotic Initiation Factor 4E (eIF4E) and Eukaryotic Initiation Factor 4G (eIF4G), and induced translation of a subset of proteins, such as cyclinD1 and c-myc, which essential for cell proliferation and apoptosis. As expected, overexpression of SUMO-2 can partially cancel out the disrupting effect of 4EGI-1, a small molecule inhibitor of eIF4E/eIF4G interaction, on formation of the eIF4F complex, translation of the cap-dependent protein, cell proliferation and apoptosis. On the other hand, SUMO-2 knockdown via shRNA partially impaired cap-dependent translation and cell proliferation and promoted apoptosis. These results collectively suggest that SUMO-2 conjugation plays a crucial regulatory role in protein synthesis. Thus, this report might contribute to the basic understanding of mammalian protein translation and sheds some new light on the role of SUMO in this process. © 2014 Chen et al

Changing planar thin film growth into self-assembled island formation by adjusting experimental conditions

Illustrated in this paper are two examples of altering planar growth into self-assembled island formation by adapting experimental conditions. Partial oxidation, undersaturated solution and high temperature change Frank-Van der Merwe (FM) growth of Al0.3Ga0.7As in liquid phase epitaxy (LPE) into isolated island deposition. Low growth speed, high temperature and in situ annealing in molecular beam epitaxy (MBE) cause the origination of InAs/GaAs quantum dots (QDs) to happen while the film is still below critical thickness in Stranski-Krastanow (SK) mode. Sample morphologies are characterized by scanning electron microscopy (SEM) or atomic force microscopy (AFM). It is suggested that such achievements are of value not only to fundamental researches but also to spheres of device applications as well. (c) 2004 Elsevier B.V. All rights reserved

Using gene co-expression network analysis to predict biomarkers for chronic lymphocytic leukemia

<p>Abstract</p> <p>Background</p> <p>Chronic lymphocytic leukemia (CLL) is the most common adult leukemia. It is a highly heterogeneous disease, and can be divided roughly into indolent and progressive stages based on classic clinical markers. Immunoglobin heavy chain variable region (IgV_H) mutational status was found to be associated with patient survival outcome, and biomarkers linked to the IgV_H status has been a focus in the CLL prognosis research field. However, biomarkers highly correlated with IgV_H mutational status which can accurately predict the survival outcome are yet to be discovered.</p> <p>Results</p> <p>In this paper, we investigate the use of gene co-expression network analysis to identify potential biomarkers for CLL. Specifically we focused on the co-expression network involving ZAP70, a well characterized biomarker for CLL. We selected 23 microarray datasets corresponding to multiple types of cancer from the Gene Expression Omnibus (GEO) and used the frequent network mining algorithm CODENSE to identify highly connected gene co-expression networks spanning the entire genome, then evaluated the genes in the co-expression network in which ZAP70 is involved. We then applied a set of feature selection methods to further select genes which are capable of predicting IgV_H mutation status from the ZAP70 co-expression network.</p> <p>Conclusions</p> <p>We have identified a set of genes that are potential CLL prognostic biomarkers IL2RB, CD8A, CD247, LAG3 and KLRK1, which can predict CLL patient IgV_H mutational status with high accuracies. Their prognostic capabilities were cross-validated by applying these biomarker candidates to classify patients into different outcome groups using a CLL microarray datasets with clinical information.</p

QTL Mapping of Combining Ability and Heterosis of Agronomic Traits in Rice Backcross Recombinant Inbred Lines and Hybrid Crosses

BACKGROUND: Combining ability effects are very effective genetic parameters in deciding the next phase of breeding programs. Although some breeding strategies on the basis of evaluating combining ability have been utilized extensively in hybrid breeding, little is known about the genetic basis of combining ability. Combining ability is a complex trait that is controlled by polygenes. With the advent and development of molecular markers, it is feasible to evaluate the genetic bases of combining ability and heterosis of elite rice hybrids through QTL analysis. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, we first developed a QTL-mapping method for dissecting combining ability and heterosis of agronomic traits. With three testcross populations and a BCRIL population in rice, biometric and QTL analyses were conducted for ten agronomic traits. The significance of general combining ability and special combining ability for most of the traits indicated the importance of both additive and non-additive effects on expression levels. A large number of additive effect QTLs associated with performance per se of BCRIL and general combining ability, and dominant effect QTLs associated with special combining ability and heterosis were identified for the ten traits. CONCLUSIONS/SIGNIFICANCE: The combining ability of agronomic traits could be analyzed by the QTL mapping method. The characteristics revealed by the QTLs for combining ability of agronomic traits were similar with those by multitudinous QTLs for agronomic traits with performance per se of BCRIL. Several QTLs (1-6 in this study) were identified for each trait for combining ability. It demonstrated that some of the QTLs were pleiotropic or linked tightly with each other. The identification of QTLs responsible for combining ability and heterosis in the present study provides valuable information for dissecting genetic basis of combining ability

Genetic dissection of heterosis using epistatic association mapping in a partial NCII mating design

Heterosis refers to the phenomenon in which an F1 hybrid exhibits enhanced growth or agronomic performance. However, previous theoretical studies on heterosis have been based on bi-parental segregating populations instead of F1 hybrids. To understand the genetic basis of heterosis, here we used a subset of F1 hybrids, named a partial North Carolina II design, to perform association mapping for dependent variables: original trait value, general combining ability (GCA), specific combining ability (SCA) and mid-parental heterosis (MPH). Our models jointly fitted all the additive, dominance and epistatic effects. The analyses resulted in several important findings: 1) Main components are additive and additive-by-additive effects for GCA and dominance-related effects for SCA and MPH, and additive-by-dominant effect for MPH was partly identified as additive effect; 2) the ranking of factors affecting heterosis was dominance > dominance-by-dominance > over-dominance > complete dominance; and 3) increasing the proportion of F1 hybrids in the population could significantly increase the power to detect dominance-related effects, and slightly reduce the power to detect additive and additive-by-additive effects. Analyses of cotton and rapeseed datasets showed that more additive-by-additive QTL were detected from GCA than from trait phenotype, and fewer QTL were from MPH than from other dependent variables

Spatial and seasonal distributions of carbonaceous aerosols over China

Author name used in this publication: S. C. LeeAuthor name used in this publication: S. H. Qi2007-2008 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Proteomics analysis of serum protein profiling in pancreatic cancer patients by DIGE: up-regulation of mannose-binding lectin 2 and myosin light chain kinase 2

<p>Abstract</p> <p>Background</p> <p>Pancreatic cancer has significant morbidity and mortality worldwide. Good prognosis relies on an early diagnosis. The purpose of this study was to develop techniques for identifying cancer biomarkers in the serum of patients with pancreatic cancer.</p> <p>Methods</p> <p>Serum samples from five individuals with pancreatic cancer and five individuals without cancer were compared. Highly abundant serum proteins were depleted by immuno-affinity column. Differential protein analysis was performed using 2-dimensional differential in-gel electrophoresis (2D-DIGE).</p> <p>Results</p> <p>Among these protein spots, we found that 16 protein spots were differently expressed between the two mixtures; 8 of these were up-regulated and 8 were down-regulated in cancer. Mass spectrometry and database searching allowed the identification of the proteins corresponding to the gel spots. Up-regulation of mannose-binding lectin 2 and myosin light chain kinase 2, which have not previously been implicated in pancreatic cancer, were observed. In an independent series of serum samples from 16 patients with pancreatic cancer and 16 non-cancer-bearing controls, increased levels of mannose-binding lectin 2 and myosin light chain kinase 2 were confirmed by western blot.</p> <p>Conclusions</p> <p>These results suggest that affinity column enrichment and DIGE can be used to identify proteins differentially expressed in serum from pancreatic cancer patients. These two proteins 'mannose-binding lectin 2 and myosin light chain kinase 2' might be potential biomarkers for the diagnosis of the pancreatic cancer.</p