Atypical focal cortical dysplasia in a patient with Cowden syndrome

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Effect of biochars pyrolyzed in N2 and CO2, and feedstock on microbial community in metal(loid)s contaminated soils

Little is known about the effects of applying amendments on soil for immobilizing metal(loid)s on the soil microbial community. Alterations in the microbial community were examined after incubation of treated contaminated soils. One soil was contaminated with Pb and As, a second soil with Cd and Zn. Red pepper stalk (RPS) and biochars produced from RPS in either N2 atmosphere (RPSN) or CO2 atmosphere (RPSC) were applied at a rate of 2.5% to the two soils and incubated for 30 days. Bacterial communities of control and treated soils were characterized by sequencing 16S rRNA genes using the Illumina MiSeq sequencing. In both soils, bacterial richness increased in the amended soils, though somewhat differently between the treatments. Evenness values decreased significantly, and the final overall diversities were reduced. The neutralization of pH, reduced available concentrations of Pb or Cd, and supplementation of available carbon and surface area could be possible factors affecting the community changes. Biochar amendments caused the soil bacterial communities to become more similar than those in the not amended soils. The bacterial community structures at the phylum and genus levels showed that amendment addition might restore the normal bacterial community of soils, and cause soil bacterial communities in contaminated soils to normalize and stabilize

The integrated DL_POLY/DL_FIELD/DL_ANALYSER software platform for molecular dynamics simulations for exploration of the synthonic interactions in saturated benzoic acid/hexane solutions

Three separately developed software Molecular Dynamics packages at Daresbury Laboratory, namely DL_FIELD (DL_F), DL_POLY and DL_ANALYSER, have been integrated to form an efficient computational infrastructure to investigate the detailed solution chemistry of saturated benzoic acid in hexane solutions. These software capabilities are demonstrated, in combination with the Synthonic Engineering tools and density functional theory (DFT) calculations, to assess the extent that the solute-solute intermolecular synthonic interactions in solution mirrors the synthons in the crystal structure. The results show that the majority of the COOH groups are forming OH … O H-bonds, which are a combination of classic OH … O homo-dimers and three membered H-bonding clusters. The formation of pi-pi stacking interactions is observed, but in far fewer numbers than observed for the OH … O interactions. The DFT simulations of the IR spectra of the multiple benzoic acid aggregates extracted from the MD trajectories provides further in-depth analysis of previously published IR data, by matching simulated peaks to the experimental peaks, hence identifying the exact bonding modes that are responsible for such peaks. This study demonstrates the value of a multi-scale and multi-technique approach to exploring the molecular transition pathway from solution to crystal structure

Ginkgo biloba extract (EGb761) inhibits mitochondria-dependent caspase pathway and prevents apoptosis in hypoxia-reoxygenated cardiomyocytes

Background: EGb761 is a standard extract from the leaves of Ginkgo biloba (Yinxing) containing ginkgo-flavone glycosides and terpenoid. The flavonoid components of EGb761 scavenge free radicals and protect myocardia from ischemia-reperfusion injury. The present study aims to determine the effects of the active compounds of EGb761 on mitochondria-dependent caspase pathway.Methods: Cardiomyocytes were exposed to 24 hours of hypoxia and four hours of reoxygenation, and pretreated with EGb761, bilobalide and quertcetin. By using immunoblot, immunofluorescent, biochemical and flow cytometry techniques, we compared the effects of EGb761 and its representative constituents including quercetin and bilobalides on regulating mitochondria-dependent caspases signal pathway and apoptotic cell death in the hypoxia-reoxygenated cardiomyocytes.Results: Pretreatment with EGb761 significantly inhibited the release of cytochrome c from mitochondria, the expression of caspase-3, cleavage activities of caspases and attenuated apoptotic cell death. The effects of quercetin on the release of cytochrome c, the cleavage activities of caspases and cell death were similar to those of EGb761 but better than those of bilobalide.Conclusion: The antioxidant constituents of EGb761 such as quercetin contribute to the cardioprotective effects of EGb761 and inhibit the mitochondria-dependent caspase pathway. It is possible that the mitochondria-dependent caspase pathway may be one of the molecular targets of EGb761 against myocardial ischemia-reperfusion injury. © 2011 Shen et al; licensee BioMed Central Ltd.published_or_final_versio

A Deep Probabilistic Spatiotemporal Framework for Dynamic Graph Representation Learning with Application to Brain Disorder Identification

Recent applications of pattern recognition techniques on brain connectome classification using functional connectivity (FC) neglect the non-Euclidean topology and causal dynamics of brain connectivity across time. In this paper, a deep probabilistic spatiotemporal framework developed based on variational Bayes (DSVB) is proposed to learn time-varying topological structures in dynamic brain FC networks for autism spectrum disorder (ASD) identification. The proposed framework incorporates a spatial-aware recurrent neural network to capture rich spatiotemporal patterns across dynamic FC networks, followed by a fully-connected neural network to exploit these learned patterns for subject-level classification. To overcome model overfitting on limited training datasets, an adversarial training strategy is introduced to learn graph embedding models that generalize well to unseen brain networks. Evaluation on the ABIDE resting-state functional magnetic resonance imaging dataset shows that our proposed framework significantly outperformed state-of-the-art methods in identifying ASD. Dynamic FC analyses with DSVB learned embeddings reveal apparent group difference between ASD and healthy controls in network profiles and switching dynamics of brain states

Cross-domain Transfer Learning and State Inference for Soft Robots via a Semi-supervised Sequential Variational Bayes Framework

Recently, data-driven models such as deep neural networks have shown to be promising tools for modelling and state inference in soft robots. However, voluminous amounts of data are necessary for deep models to perform effectively, which requires exhaustive and quality data collection, particularly of state labels. Consequently, obtaining labelled state data for soft robotic systems is challenged for various reasons, including difficulty in the sensorization of soft robots and the inconvenience of collecting data in unstructured environments. To address this challenge, in this paper, we propose a semi-supervised sequential variational Bayes (DSVB) framework for transfer learning and state inference in soft robots with missing state labels on certain robot configurations. Considering that soft robots may exhibit distinct dynamics under different robot configurations, a feature space transfer strategy is also incorporated to promote the adaptation of latent features across multiple configurations. Unlike existing transfer learning approaches, our proposed DSVB employs a recurrent neural network to model the nonlinear dynamics and temporal coherence in soft robot data. The proposed framework is validated on multiple setup configurations of a pneumatic-based soft robot finger. Experimental results on four transfer scenarios demonstrate that DSVB performs effective transfer learning and accurate state inference amidst missing state labels. The data and code are available at https://github.com/shageenderan/DSVB.Comment: Accepted at the International Conference on Robotics and Automation (ICRA) 202

Effects of Erxian decoction, a Chinese medicinal formulation, on serum lipid profile in a rat model of menopause

<p>Abstract</p> <p>Background</p> <p>The prevalence and risk of cardiovascular disease increase after menopause in correlation with the progression of abnormality in the serum lipid profile and the deprivation of estrogen. <it>Erxian </it>decoction (EXD), a Chinese medicinal formulation for treating menopausal syndrome, stimulates ovarian estrogen biosynthesis. This study investigates whether EXD improves the serum lipid profile in a menopausal rat model.</p> <p>Methods</p> <p>Twenty-month-old female Sprague Dawley rats were treated with EXD and its constituent fractions. Premarin was administered for comparison. After eight weeks of treatment, rats were sacrificed and the serum levels of total cholesterol, triglyceride, high-density-lipoprotein cholesterol and low-density-lipoprotein cholesterol were determined. The hepatic protein levels of 3-hydroxy-3-methyl-glutaryl-CoA reductase and low-density-lipoprotein receptor were assessed with Western blot.</p> <p>Results</p> <p>The serum levels of total cholesterol and low-density-lipoprotein cholesterol were significantly lower in the EXD-treated group than in the constituent fractions of EXD or premarin groups. However, the serum levels of triglyceride and high-density-lipoprotein cholesterol were not significantly different from the control groups. Results from Western blot suggest that EXD significantly down-regulated the protein level of 3-hydroxy-3-methyl-glutaryl-CoA reductase and up-regulated low-density-lipoprotein receptor. <b>Conclusion </b>EXD improves serum lipid profile in a menopausal rat model through the suppression of the serum levels of total cholesterol and low-density-lipoprotein cholesterol, possibly through the down-regulation of the 3-hydroxy-3-methyl-glutaryl-CoA and up-regulation of the low-density-lipoprotein receptor.</p

Time-variant 1D photonic crystals using flowing microdroplets

Author name used in this publication: Chi Wah Leung2012-2013 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Investigation of interface states in single-negative metamaterial layered structures based on the phase properties

Author name used in this publication: Chi Wah Leung2013-2014 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe