Cycling performance of Mn2O3 porous nanocubes and hollow spheres for lithium-ion batteries

Post presentationMn2O3 is a promising anode material for lithium ion battery. Two different kinds of structures of Mn2O3 were synthesized via solution processes, the Mn2O3 porous cubes and hollow spheres. Scanning electron microscope images and transmission electron microscopy images clearly show the structures. Electrochemical impedance spectroscopy and cyclic voltammetry measurements were used to characterize their electrochemical properties. As anode materials for lithium ion batteries, Mn2O3 porous cubes performed similarly as Mn2O3 hollow spheres. Both samples started with high initial capacities (1583.2 mAh/g and 1550.7 mAh/g) which were reduced to 173.3 mAh/g and 162.0 mAh/g at 100th cycle at a current density of 100 mA/g. The decrease is likely due to morphology destruction the materials in charging and discharging process.published_or_final_versio

ChIP-BIT: Bayesian inference of target genes using a novel joint probabilistic model of ChIP-seq profiles.

Chromatin immunoprecipitation with massively parallel DNA sequencing (ChIP-seq) has greatly improved the reliability with which transcription factor binding sites (TFBSs) can be identified from genome-wide profiling studies. Many computational tools are developed to detect binding events or peaks, however the robust detection of weak binding events remains a challenge for current peak calling tools. We have developed a novel Bayesian approach (ChIP-BIT) to reliably detect TFBSs and their target genes by jointly modeling binding signal intensities and binding locations of TFBSs. Specifically, a Gaussian mixture model is used to capture both binding and background signals in sample data. As a unique feature of ChIP-BIT, background signals are modeled by a local Gaussian distribution that is accurately estimated from the input data. Extensive simulation studies showed a significantly improved performance of ChIP-BIT in target gene prediction, particularly for detecting weak binding signals at gene promoter regions. We applied ChIP-BIT to find target genes from NOTCH3 and PBX1 ChIP-seq data acquired from MCF-7 breast cancer cells. TF knockdown experiments have initially validated about 30% of co-regulated target genes identified by ChIP-BIT as being differentially expressed in MCF-7 cells. Functional analysis on these genes further revealed the existence of crosstalk between Notch and Wnt signaling pathways

Cost-effectiveness of initiating extrafine- or standard size-particle inhaled corticosteroid for asthma in two health-care systems: a retrospective matched cohort study

Data acquisition and analyses were funded by Teva Pharmaceuticals

Brain-Derived Neurotrophic Factor Gene Val66Met Polymorphism Modulates Reversible Cerebral Vasoconstriction Syndromes

BACKGROUND: Reversible cerebral vasoconstriction syndrome (RCVS) could be complicated by cerebral ischemic events. Hypothetical mechanisms of RCVS involve endothelial dysfunction and sympathetic overactivity, both of which were reported to be related to brain-derived neurotrophic factor (BDNF). The study investigated the association between functional BDNF Val66Met polymorphism and RCVS. METHODS: Patients with RCVS and controls were prospectively recruited and genotyped for the BDNF Val66Met polymorphism. Magnetic resonance angiography (MRA) and transcranial color-coded Doppler sonography were employed to evaluate cerebral vasoconstriction. Genotyping results, clinical parameters, vasoconstriction scores, mean flow velocities of the middle cerebral artery (V(MCA)), and Lindegaard indices were analyzed. Split-sample approach was employed to internally validate the data. PRINCIPAL FINDINGS: Ninety Taiwanese patients with RCVS and 180 age- and gender-matched normal controls of the same ethnicity completed the study. The genotype frequencies did not differ between patients and controls. Compared to patients with Met/Met homozygosity, patients with Val allele had higher mean vasoconstriction scores of all arterial segments (1.60±0.72 vs. 0.87±0.39, p<0.001), V(MCA) values (116.7±36.2 vs. 82.7±17.9 cm/s, p<0.001), and LI (2.41±0.91 vs. 1.89±0.41, p = 0.001). None of the Met/Met homozygotes, but 38.9% of the Val carriers, had V(MCA) values of >120 cm/s (p<0.001). Split-sample validation by randomization, age, entry time or residence of patients demonstrated concordant findings. CONCLUSIONS: Our findings link BDNF Val66Met polymorphism with the severity of RCVS for the first time and implicate possible pathogenic mechanisms for vasoconstriction in RCVS

International Veterinary Epilepsy Task Force consensus proposal: Medical treatment of canine epilepsy in Europe

In Europe, the number of antiepileptic drugs (AEDs) licensed for dogs has grown considerably over the last years. Nevertheless, the same questions remain, which include, 1) when to start treatment, 2) which drug is best used initially, 3) which adjunctive AED can be advised if treatment with the initial drug is unsatisfactory, and 4) when treatment changes should be considered. In this consensus proposal, an overview is given on the aim of AED treatment, when to start long-term treatment in canine epilepsy and which veterinary AEDs are currently in use for dogs. The consensus proposal for drug treatment protocols, 1) is based on current published evidence-based literature, 2) considers the current legal framework of the cascade regulation for the prescription of veterinary drugs in Europe, and 3) reflects the authors’ experience. With this paper it is aimed to provide a consensus for the management of canine idiopathic epilepsy. Furthermore, for the management of structural epilepsy AEDs are inevitable in addition to treating the underlying cause, if possible

Automatic Diagnosis of Pathological Myopia from Heterogeneous Biomedical Data

10.1371/journal.pone.0065736PLoS ONE86

Routine pattern discovery and anomaly detection in individual travel behavior

Discovering patterns and detecting anomalies in individual travel behavior is a crucial problem in both research and practice. In this paper, we address this problem by building a probabilistic framework to model individual spatiotemporal travel behavior data (e.g., trip records and trajectory data). We develop a two-dimensional latent Dirichlet allocation (LDA) model to characterize the generative mechanism of spatiotemporal trip records of each traveler. This model introduces two separate factor matrices for the spatial dimension and the temporal dimension, respectively, and use a two-dimensional core structure at the individual level to effectively model the joint interactions and complex dependencies. This model can efficiently summarize travel behavior patterns on both spatial and temporal dimensions from very sparse trip sequences in an unsupervised way. In this way, complex travel behavior can be modeled as a mixture of representative and interpretable spatiotemporal patterns. By applying the trained model on future/unseen spatiotemporal records of a traveler, we can detect her behavior anomalies by scoring those observations using perplexity. We demonstrate the effectiveness of the proposed modeling framework on a real-world license plate recognition (LPR) data set. The results confirm the advantage of statistical learning methods in modeling sparse individual travel behavior data. This type of pattern discovery and anomaly detection applications can provide useful insights for traffic monitoring, law enforcement, and individual travel behavior profiling

Digital karyotyping reveals probable target genes at 7q21.3 locus in hepatocellular carcinoma

<p>Abstract</p> <p>Background</p> <p>Hepatocellular carcinoma (HCC) is a worldwide malignant liver tumor with high incidence in China. Subchromosomal amplifications and deletions accounted for major genomic alterations occurred in HCC. Digital karyotyping was an effective method for analyzing genome-wide chromosomal aberrations at high resolution.</p> <p>Methods</p> <p>A digital karyotyping library of HCC was constructed and 454 Genome Sequencer FLX System (Roche) was applied in large scale sequencing of the library. Digital Karyotyping Data Viewer software was used to analyze genomic amplifications and deletions. Genomic amplifications of genes detected by digital karyotyping were examined by real-time quantitative PCR. The mRNA expression level of these genes in tumorous and paired nontumorous tissues was also detected by real-time quantitative RT-PCR.</p> <p>Results</p> <p>A total of 821,252 genomic tags were obtained from the digital karyotyping library of HCC, with 529,162 tags (64%) mapped to unique loci of human genome. Multiple subchromosomal amplifications and deletions were detected through analyzing the digital karyotyping data, among which the amplification of 7q21.3 drew our special attention. Validation of genes harbored within amplicons at 7q21.3 locus revealed that genomic amplification of SGCE, PEG10, DYNC1I1 and SLC25A13 occurred in 11 (21%), 11 (21%), 11 (21%) and 23 (44%) of the 52 HCC samples respectively. Furthermore, the mRNA expression level of SGCE, PEG10 and DYNC1I1 were significantly up-regulated in tumorous liver tissues compared with corresponding nontumorous counterparts.</p> <p>Conclusions</p> <p>Our results indicated that subchromosomal region of 7q21.3 was amplified in HCC, and SGCE, PEG10 and DYNC1I1 were probable protooncogenes located within the 7q21.3 locus.</p