Dimethyl 3,3′-diphenyl-2,2′-[(S)-thio­phene-2,5-diylbis(carbonyl­aza­nedi­yl)]dipropano­ate

The asymmetric unit of the title compound, C26H26N2O6S, contains two independent mol­ecules; each has twofold symmetry with the S atom and the mid-point of the C—C bond of the thio­phene ring located on a twofold rotation axis. In the two mol­ecules, the terminal benzene rings are oriented at dihedral angles of 65.8 (3) and 63.5 (3)° with respect to the central thio­phene rings. The meth­oxy­carbonyl group of one mol­ecule is disordered over two positions with site-occupancy factors of 0.277 (12) and 0.723 (12). Inter­molecular N—H⋯O hydrogen bonding is present in the crystal structure

5 GHz TMRT observations of 71 pulsars

We present integrated pulse profiles at 5~GHz for 71 pulsars, including eight millisecond pulsars (MSPs), obtained using the Shanghai Tian Ma Radio Telescope (TMRT). Mean flux densities and pulse widths are measured. For 19 normal pulsars and one MSP, these are the first detections at 5~GHz and for a further 19, including five MPSs, the profiles have a better signal-to-noise ratio than previous observations. Mean flux density spectra between 400~MHz and 9~GHz are presented for 27 pulsars and correlations of power-law spectral index are found with characteristic age, radio pseudo-luminosity and spin-down luminosity. Mode changing was detected in five pulsars. The separation between the main pulse and interpulse is shown to be frequency independent for six pulsars but a frequency dependence of the relative intensity of the main pulse and interpulse is found. The frequency dependence of component separations is investigated for 20 pulsars and three groups are found: in seven cases the separation between the outmost leading and trailing components decreases with frequency, roughly in agreement with radius-to-frequency mapping; in eleven cases the separation is nearly constant; in the remain two cases the separation between the outmost components increases with frequency. We obtain the correlations of pulse widths with pulsar period and estimate the core widths of 23 multi-component profiles and conal widths of 17 multi-component profiles at 5.0~GHz using Gaussian fitting and discuss the width-period relationship at 5~GHz compared with the results at at 1.0~GHz and 8.6~GHz.Comment: 46 pages, 14 figures, 8 Tables, accepted by Ap

Embedded Palmprint Recognition System Using OMAP 3530

We have proposed in this paper an embedded palmprint recognition system using the dual-core OMAP 3530 platform. An improved algorithm based on palm code was proposed first. In this method, a Gabor wavelet is first convolved with the palmprint image to produce a response image, where local binary patterns are then applied to code the relation among the magnitude of wavelet response at the ccentral pixel with that of its neighbors. The method is fully tested using the public PolyU palmprint database. While palm code achieves only about 89% accuracy, over 96% accuracy is achieved by the proposed G-LBP approach. The proposed algorithm was then deployed to the DSP processor of OMAP 3530 and work together with the ARM processor for feature extraction. When complicated algorithms run on the DSP processor, the ARM processor can focus on image capture, user interface and peripheral control. Integrated with an image sensing module and central processing board, the designed device can achieve accurate and real time performance

Reduced expression of SMAD4 in gliomas correlates with progression and survival of patients

<p>Abstract</p> <p>Background</p> <p>To examine the expression of SMAD4 at gene and protein levels in glioma samples with different WHO grades and its association with survival.</p> <p>Methods</p> <p>Two hundreds fifty-two glioma specimens and 42 normal control tissues were collected. Immunochemistry assay, quantitative real-time PCR and Western blot analysis were carried out to investigate the expression of SMAD4. Kaplan-Meier method and Cox's proportional hazards model were used in survival analysis.</p> <p>Results</p> <p>Immunohistochemistry showed that SMAD4 expression was decreased in glioma. SMAD4 mRNA and protein levels were both lower in glioma compared to control on real-time PCR and Western blot analysis (both P < 0.001). In addition, its expression levels decrease from grade I to grade IV glioma according to the results of real-time PCR, immunohistochemistry analysis and Western blot. Moreover, the survival rate of SMAD4-positive patients was higher than that of SMAD4-negative patients. We further confirmed that the loss of SMAD4 was a significant and independent prognostic indicator in glioma by multivariate analysis.</p> <p>Conclusions</p> <p>Our data provides convincing evidence for the first time that the reduced expression of SMAD4 at gene and protein levels is correlated with poor outcome in patients with glioma. SMAD4 may play an inhibitive role during the development of glioma and may be a potential prognosis predictor of glioma.</p

The Vasculome of the Mouse Brain

The blood vessel is no longer viewed as passive plumbing for the brain. Increasingly, experimental and clinical findings suggest that cerebral endothelium may possess endocrine and paracrine properties – actively releasing signals into and receiving signals from the neuronal parenchyma. Hence, metabolically perturbed microvessels may contribute to central nervous system (CNS) injury and disease. Furthermore, cerebral endothelium can serve as sensors and integrators of CNS dysfunction, releasing measurable biomarkers into the circulating bloodstream. Here, we define and analyze the concept of a brain vasculome, i.e. a database of gene expression patterns in cerebral endothelium that can be linked to other databases and systems of CNS mediators and markers. Endothelial cells were purified from mouse brain, heart and kidney glomeruli. Total RNA were extracted and profiled on Affymetrix mouse 430 2.0 micro-arrays. Gene expression analysis confirmed that these brain, heart and glomerular preparations were not contaminated by brain cells (astrocytes, oligodendrocytes, or neurons), cardiomyocytes or kidney tubular cells respectively. Comparison of the vasculome between brain, heart and kidney glomeruli showed that endothelial gene expression patterns were highly organ-dependent. Analysis of the brain vasculome demonstrated that many functionally active networks were present, including cell adhesion, transporter activity, plasma membrane, leukocyte transmigration, Wnt signaling pathways and angiogenesis. Analysis of representative genome-wide-association-studies showed that genes linked with Alzheimer’s disease, Parkinson’s disease and stroke were detected in the brain vasculome. Finally, comparison of our mouse brain vasculome with representative plasma protein databases demonstrated significant overlap, suggesting that the vasculome may be an important source of circulating signals in blood. Perturbations in cerebral endothelial function may profoundly affect CNS homeostasis. Mapping and dissecting the vasculome of the brain in health and disease may provide a novel database for investigating disease mechanisms, assessing therapeutic targets and exploring new biomarkers for the CNS

Loop-Mediated Isothermal Amplification Assay Targeting the MOMP Gene for Rapid Detection of Chlamydia psittaci Abortus Strain

For rapid detection of the Chlamydia psittaci abortus strain, a loop-mediated isothermal amplification (LAMP) assay was developed and evaluated in this study. The primers for the LAMP assay were designed on the basis of the main outer membrane protein (MOMP) gene sequence of C. psittaci. Analysis showed that the assay could detect the abortus strain of C. psittaci with adequate specificity. The sensitivity of the test was the same as that of the nested-conventional PCR and higher than that of chick embryo isolation. Testing of 153 samples indicated that the LAMP assay could detect the genome of the C. psittaci abortus strain effectively in clinical samples. This assay is a useful tool for rapid diagnosis of C. psittaci infection in sheep, swine and cattle

Macrochirality of Self-Assembled and Co-assembled Supramolecular Structures of a Pair of Enantiomeric Peptides

Although macrochirality of peptides’ supramolecular structures has been found to play important roles in biological activities, how macrochirality is determined by the molecular chirality of the constituted amino acids is still unclear. Here, two chiral peptides, Ac-LKLHLHLQLKLLLVLFLFLALK-NH2 (KK-11) and Ac-DKDHDHDQDKDL DVDFDFDADK-NH2 (KKd-11), which were composed entirely of either L- or D-amino acids, were designed for studying the chiral characteristics of the supramolecular microstructures. It was found that monocomponent KK-11 or KKd-11 self-assembled into right- or left-handed helical nanofibrils, respectively. However, when they co-assembled with concentration ratios varied from 1:9 to 9:1, achiral nanowire-like structures were formed. Both circular dichroism and Fourier transform infrared spectra indicated that the secondary structures changed when the peptides co-assembled. MD simulations indicated that KK-11 or KKd-11 exhibited a strong propensity to self-assemble into right-handed or left-handed nanofibrils, respectively. However, when KK-11 and KKd-11 were both presented in a solution, they had a higher probability to co-assemble instead of self-sort. MD simulations indicated that, in their mixtures, they formed nanowires without handedness feature, a good agreement with experimental observation. Our results shed light on the molecular mechanisms of the macrochirality of peptide supramolecular microstructures

Multi-task Neural Network for Non-discrete Attribute Prediction in Knowledge Graphs

Many popular knowledge graphs such as Freebase, YAGO or DBPedia maintain a list of non-discrete attributes for each entity. Intuitively, these attributes such as height, price or population count are able to richly characterize entities in knowledge graphs. This additional source of information may help to alleviate the inherent sparsity and incompleteness problem that are prevalent in knowledge graphs. Unfortunately, many state-of-the-art relational learning models ignore this information due to the challenging nature of dealing with non-discrete data types in the inherently binary-natured knowledge graphs. In this paper, we propose a novel multi-task neural network approach for both encoding and prediction of non-discrete attribute information in a relational setting. Specifically, we train a neural network for triplet prediction along with a separate network for attribute value regression. Via multi-task learning, we are able to learn representations of entities, relations and attributes that encode information about both tasks. Moreover, such attributes are not only central to many predictive tasks as an information source but also as a prediction target. Therefore, models that are able to encode, incorporate and predict such information in a relational learning context are highly attractive as well. We show that our approach outperforms many state-of-the-art methods for the tasks of relational triplet classification and attribute value prediction.Comment: Accepted at CIKM 201