Quantificational analysis of NPT-II protein from genetically modified Vitis vinifera L.

Widely distributed inhibitors in grapevine extracts make it difficult to improve analytical procedures for protein detection. In this study, acidity in grapevine extracts was one of the major factors inhibiting the detection of neomycin phosphotransferase II via enzyme-linked immunosorbent assay. Leaf and berry extracts with low pH (3.0 – 4.0) strongly inhibited NPT-II detection, while root and xylem sap extracts (normally pH 5.5 to 7.0) allowed the successful detection of NPT-II. The other inhibitory effect against the detection was successfully solved by heat treatment to samples extracted. Boiling leaf extract prior to ELISA, in conjunction with pH adjustment (to 7.0) was essential to improve NPT-II detection, whilewith berry extracts only pH adjustment was required. In the basis of above results, NPT-II protein contents in transgenic grapevine tissues possessing a NPT-II gene were successfully measured. The results here may be useful to help in evaluation of the bio-safety whether the transgenic grapevineswere released or contaminated on the grapevine cultivation area by NPT-II protein detection

Multi-Level Cross Residual Network for Lung Nodule Classification.

Computer-aided algorithm plays an important role in disease diagnosis through medical images. As one of the major cancers, lung cancer is commonly detected by computer tomography. To increase the survival rate of lung cancer patients, an early-stage diagnosis is necessary. In this paper, we propose a new structure, multi-level cross residual convolutional neural network (ML-xResNet), to classify the different types of lung nodule malignancies. ML-xResNet is constructed by three-level parallel ResNets with different convolution kernel sizes to extract multi-scale features of the inputs. Moreover, the residuals are connected not only with the current level but also with other levels in a crossover manner. To illustrate the performance of ML-xResNet, we apply the model to process ternary classification (benign, indeterminate, and malignant lung nodules) and binary classification (benign and malignant lung nodules) of lung nodules, respectively. Based on the experiment results, the proposed ML-xResNet achieves the best results of 85.88% accuracy for ternary classification and 92.19% accuracy for binary classification, without any additional handcrafted preprocessing algorithm

Ultrasound volume projection image quality selection by ranking from convolutional RankNet.

Periodic inspection and assessment are important for scoliosis patients. 3D ultrasound imaging has become an important means of scoliosis assessment as it is a real-time, cost-effective and radiation-free imaging technique. With the generation of a 3D ultrasound volume projection spine image using our Scolioscan system, a series of 2D coronal ultrasound images are produced at different depths with different qualities. Selecting a high quality image from these 2D images is the crucial task for further scoliosis measurement. However, adjacent images are similar and difficult to distinguish. To learn the nuances between these images, we propose selecting the best image automatically, based on their quality rankings. Here, the ranking algorithm we use is a pairwise learning-to-ranking network, RankNet. Then, to extract more efficient features of input images and to improve the discriminative ability of the model, we adopt the convolutional neural network as the backbone due to its high power of image exploration. Finally, by inputting the images in pairs into the proposed convolutional RankNet, we can select the best images from each case based on the output ranking orders. The experimental result shows that convolutional RankNet achieves better than 95.5% top-3 accuracy, and we prove that this performance is beyond the experience of a human expert

Developmental changes in the role of different metalinguistic awareness skills in Chinese reading acquisition from preschool to third grade

Copyright @ 2014 Wei et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.The present study investigated the relationship between Chinese reading skills and metalinguistic awareness skills such as phonological, morphological, and orthographic awareness for 101 Preschool, 94 Grade-1, 98 Grade-2, and 98 Grade-3 children from two primary schools in Mainland China. The aim of the study was to examine how each of these metalinguistic awareness skills would exert their influence on the success of reading in Chinese with age. The results showed that all three metalinguistic awareness skills significantly predicted reading success. It further revealed that orthographic awareness played a dominant role in the early stages of reading acquisition, and its influence decreased with age, while the opposite was true for the contribution of morphological awareness. The results were in stark contrast with studies in English, where phonological awareness is typically shown as the single most potent metalinguistic awareness factor in literacy acquisition. In order to account for the current data, a three-stage model of reading acquisition in Chinese is discussed.National Natural Science Foundation of China and Knowledge Innovation Program of the Chinese Academy of Sciences

Imaging Coulomb Islands in a Quantum Hall Interferometer

In the Quantum Hall regime, near integer filling factors, electrons should only be transmitted through spatially-separated edge states. However, in mesoscopic systems, electronic transmission turns out to be more complex, giving rise to a large spectrum of magnetoresistance oscillations. To explain these observations, recent models put forward that, as edge states come close to each other, electrons can hop between counterpropagating edge channels, or tunnel through Coulomb islands. Here, we use scanning gate microscopy to demonstrate the presence of quantum Hall Coulomb islands, and reveal the spatial structure of transport inside a quantum Hall interferometer. Electron islands locations are found by modulating the tunneling between edge states and confined electron orbits. Tuning the magnetic field, we unveil a continuous evolution of active electron islands. This allows to decrypt the complexity of high magnetic field magnetoresistance oscillations, and opens the way to further local scale manipulations of quantum Hall localized states

Physicochemical analysis of rotavirus segment 11 supports a 'modified panhandle' structure and not the predicted alternative tRNA-like structure (TRLS)

.Rotaviruses are a major cause of acute gastroenteritis, which is often fatal in infants. The viral genome consists of 11 double-stranded RNA segments, but little is known about their cis-acting sequences and structural elements. Covariation studies and phylogenetic analysis exploring the potential structure of RNA11 of rotaviruses suggested that, besides the previously predicted "modified panhandle" structure, the 5' and 3' termini of one of the isoforms of the bovine rotavirus UKtc strain may interact to form a tRNA-like structure (TRLS). Such TRLSs have been identified in RNAs of plant viruses, where they are important for enhancing replication and packaging. However, using tRNA mimicry assays (in vitro aminoacylation and 3'- adenylation), we found no biochemical evidence for tRNA-like functions of RNA11. Capping, synthetic 3' adenylation and manipulation of divalent cation concentrations did not change this finding. NMR studies on a 5'- and 3'-deletion construct of RNA11 containing the putative intra-strand complementary sequences supported a predominant panhandle structure and did not conform to a cloverleaf fold despite the strong evidence for a predicted structure in this conserved region of the viral RNA. Additional viral or cellular factors may be needed to stabilise it into a form with tRNA-like properties

Effect of screening of the electron-phonon interaction on the temperature of Bose-Einstein condensation of intersite bipolarons

Here we consider an interacting electron-phonon system within the framework of extended Holstein-Hubbard model at strong enough electron-phonon interaction limit in which (bi)polarons are the essential quasiparticles of the system. It is assumed that the electron-phonon interaction is screened and its potential has Yukawa-type analytical form. An effect of screening of the electron-phonon interaction on the temperature of Bose-Einstein condensation of the intersite bipolarons is studied for the first time. It is revealed that the temperature of Bose-Einstein condensation of intersite bipolarons is higher in the system with the more screened electron-phonon interaction.Comment: 6 pages, 4 figure

A Duplication CNV That Conveys Traits Reciprocal to Metabolic Syndrome and Protects against Diet-Induced Obesity in Mice and Men

The functional contribution of CNV to human biology and disease pathophysiology has undergone limited exploration. Recent observations in humans indicate a tentative link between CNV and weight regulation. Smith-Magenis syndrome (SMS), manifesting obesity and hypercholesterolemia, results from a deletion CNV at 17p11.2, but is sometimes due to haploinsufficiency of a single gene, RAI1. The reciprocal duplication in 17p11.2 causes Potocki-Lupski syndrome (PTLS). We previously constructed mouse strains with a deletion, Df(11)17, or duplication, Dp(11)17, of the mouse genomic interval syntenic to the SMS/PTLS region. We demonstrate that Dp(11)17 is obesity-opposing; it conveys a highly penetrant, strain-independent phenotype of reduced weight, leaner body composition, lower TC/LDL, and increased insulin sensitivity that is not due to alteration in food intake or activity level. When fed with a high-fat diet, Dp(11)17/+ mice display much less weight gain and metabolic change than WT mice, demonstrating that the Dp(11)17 CNV protects against metabolic syndrome. Reciprocally, Df(11)17/+ mice with the deletion CNV have increased weight, higher fat content, decreased HDL, and reduced insulin sensitivity, manifesting a bona fide metabolic syndrome. These observations in the deficiency animal model are supported by human data from 76 SMS subjects. Further, studies on knockout/transgenic mice showed that the metabolic consequences of Dp(11)17 and Df(11)17 CNVs are not only due to dosage alterations of Rai1, the predominant dosage-sensitive gene for SMS and likely also PTLS. Our experiments in chromosome-engineered mouse CNV models for human genomic disorders demonstrate that a CNV can be causative for weight/metabolic phenotypes. Furthermore, we explored the biology underlying the contribution of CNV to the physiology of weight control and energy metabolism. The high penetrance, strain independence, and resistance to dietary influences associated with the CNVs in this study are features distinct from most SNP–associated metabolic traits and further highlight the potential importance of CNV in the etiology of both obesity and MetS as well as in the protection from these traits

Graphene plasmonics

Two rich and vibrant fields of investigation, graphene physics and plasmonics, strongly overlap. Not only does graphene possess intrinsic plasmons that are tunable and adjustable, but a combination of graphene with noble-metal nanostructures promises a variety of exciting applications for conventional plasmonics. The versatility of graphene means that graphene-based plasmonics may enable the manufacture of novel optical devices working in different frequency ranges, from terahertz to the visible, with extremely high speed, low driving voltage, low power consumption and compact sizes. Here we review the field emerging at the intersection of graphene physics and plasmonics.Comment: Review article; 12 pages, 6 figures, 99 references (final version available only at publisher's web site