Structural comparison of nickel electrodes and precursor phases

A summary of previous Raman spectroscopic results and a discussion of important structural differences in the various phases of active mass and active mass precurors are presented. Raman spectra provide unique signatures for these phases, and allow one to distinguish each phase, even when the compound is amorphous to X-rays (i.e., does not scatter X-rays because of a lack of order and/or small particle size). The structural changes incurred during formation, charge and discharge, cobalt addition, and aging will be discussed and related to electrode properties. Important structural differences include NiO2 layer stacking, nonstoichiometry (especially cation-deficit nonstoichiometry), disorder, dopant content, and water content. The results indicate that optimal nickel active mass is non-close packed and nonstoichiometric. The formation process transforms precursor phases into this structure. Therefore, the precursor disorder, or lack thereof, influences this final active mass structure and the rate of formation. Aging processes induce structural change which is believed to be detrimental. The role of cobalt addition can be appreciated in terms of structures favored or stabilized by the dopant. In recent work, the in situ Raman technique to characterize the critical structural parameters was developed. An in situ method relates structure, electrochemistry, and preparation. In situ Raman spectra of cells during charge and discharge, either during cyclic voltammetry or under constant current conditions were collected. With the structure-preparation knowledge and the in situ Raman tool, it will be possible to define the structure-property-preparation relations in more detail. This instrumentation has application to a variety of electrode systems

Design, simulation and experiment of particle dampers attached to a precision instrument in spacecraft

Aiming at attenuating the vibration of a precision instrument in spacecraft, multiple particle dampers are designed and their damping performances are evaluated. Firstly, the vibrating table test for the primary system under sin-swept excitation is conducted to acquire the vibration characteristic. Then enclosures attached to the installing bracket are designed and fabricated elaborately. Using discrete element-finite element (DE-FE) coupling algorithm, the effects of some system parameters (such as: mass ratio, particle material, numbers of dampers and cavity depth) are investigated to optimize the damping capacity of particle dampers. Furthermore, a series of experiments are conducted to verify the performance of particle dampers under dynamic load. The results indicate that the transfer functions of acceleration in Y and Z direction decrease at 22.58 % and 77.38 % respectively, while only 3.1 % mass of the primary system is attached

Differential Regulation of PDE5 Expression in Left and Right Ventricles of Feline Hypertrophy Models

Though long known to affect smooth muscle biology, recent studies indicate that phosphodiesterase 5 (PDE5) is also expressed in myocardium. Recognizing that the regulation of PDE5 in hypertrophy is not well understood, we assessed the response of PDE5 expression and the level of cGMP-dependent kinase I (cGKI) in the left and right ventricles of feline hypertrophy models.Using a cDNA library of feline aortic smooth muscle cells, we identified and cloned PDE5 cDNA for the first time in this species. The sequence shares 98% identity with its human orthologue at the amino acid level. E. coli expression of the cloned allele allowed selection of antibodies with appropriate specificity, facilitating the analysis of PDE5 expression in feline models created by selective proximal aortic (Ao) or pulmonary artery (PA) banding that resulted in hypertrophy of the left ventricle (LV) and right ventricle (RV), respectively. We demonstrated that PDE5 expression responded differentially with a decreased expression in the LV and an increased expression in the RV in the Ao-banded model. Similarly, in the PA-banded model, LV showed reduced expression while the RV expression was unaltered. In addition, the expression of cGKI was significantly decreased in the RV of Ao-banded group, correlating inversely with the increase in PDE5 expression.The differential regulation of PDE5 and cGKI expression suggests that the mechanisms involved in hypertrophy could be different in RV vs. LV. Reciprocal PDE5 and cGKI expression in the RV of Ao-banded model suggests functional significance for PDE5 up-regulation

Polymerase II Promoter Strength Determines Efficacy of microRNA Adapted shRNAs

Since the discovery of RNAi and microRNAs more than 10 years ago, much research has focused on the development of systems that usurp microRNA pathways to downregulate gene expression in mammalian cells. One of these systems makes use of endogenous microRNA pri-cursors that are expressed from polymerase II promoters where the mature microRNA sequence is replaced by gene specific duplexes that guide RNAi (shRNA-miRs). Although shRNA-miRs are effective in directing target mRNA knockdown and hence reducing protein expression in many cell types, variability of RNAi efficacy in cell lines has been an issue. Here we show that the choice of the polymerase II promoter used to drive shRNA expression is of critical importance to allow effective mRNA target knockdown. We tested the abundance of shRNA-miRs expressed from five different polymerase II promoters in 6 human cell lines and measured their ability to drive target knockdown. We observed a clear positive correlation between promoter strength, siRNA expression levels, and protein target knockdown. Differences in RNAi from the shRNA-miRs expressed from the various promoters were particularly pronounced in immune cells. Our findings have direct implications for the design of shRNA-directed RNAi experiments and the preferred RNAi system to use for each cell type

Discovery of Genetic Variation on Chromosome 5q22 Associated with Mortality in Heart Failure

Failure of the human heart to maintain sufficient output of blood for the demands of the body, heart failure, is a common condition with high mortality even with modern therapeutic alternatives. To identify molecular determinant

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Determination of PDE5 expression in feline hypertrophy models.

<p>Tissue homogenates from LV and RV of control, PA-banded and Ao-banded animal models were analyzed for PDE5 expression by immunoblotting. (a) Homogenates from LV samples. (b) Homogenate from RV samples. Samples from control, PA-banded and Ao-banded groups were indicated in the figure. <i>E. coli</i> extracts from strains carrying pT7-PDE5 and pSNAP-tag(T7) were used as positive and negative controls (shown as+and -). GAPDH levels in the same set of tissue samples were also determined by immunoblotting, and used for normalization of PDE5 levels. (c) Normalized average PDE level in LV tissues from each group (n = 4). (d) Normalized average PDE level in RV tissues from each group. The error bars indicate standard deviations. Student t-test p values that show statistical significance are indicated in the figure.</p

cGKI expression in feline hypertrophy models.

<p>Tissue homogenates from LV (a) and RV (b) of control, PA-banded and Ao-banded animal models were analyzed for cGKI expression by immunoblotting, as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0019922#pone-0019922-g005" target="_blank">Figure 5</a>. GAPDH levels in the same set of samples were used to normalize the cGKI levels. The normalized average cGKI levels in each group (n = 4) are shown in (c) for LV and (d) in RV. The error bars indicate standard deviations. Student t-test p values that show statistical significance are indicated in the figure.</p

Cardiac Morphology at 1 Month after Banding.

<p>Values are mean ± SEM.</p><p>Abbreviations: HW/BW-heart weight to body weight ratio; RV th-RV free wall thickness; IVS th-thickness of interventricular septum; PW th-thickness of left ventricular posterior wall; LVEDD-left ventricular end-diastolic dimension; LVFS-left ventricular fractional shortening; LV Mass-calculated left ventricular mass (see text for details).</p><p>*p<0.05 vs. Control.</p