The Off-Shell Electromagnetic T-matrix: momentum-dependent scattering from spherical inclusions with both dielectric and magnetic contrast

The momentum- and frequency-dependent T-matrix operator for the scattering of electromagnetic waves by a dielectric/conducting and para- or diamagnetic sphere is derived as a Mie-type series, and presented in a compact form emphasizing various symmetry properties, notably the unitarity identity. This result extends to magnetic properties one previously obtained for purely dielectric contrasts by other authors. Several situations useful to spatially-dispersive effective-medium approximations to one-body order are examined. Partial summation of the Mie series is achieved in the case of elastic scattering.Comment: 22 pages. Preprint of a paper to appear in `Waves in Complex And Random Media' ((c) Taylor and Francis, 2011

Underwater Leidenfrost nanochemistry for creation of size-tailored zinc peroxide cancer nanotherapeutics

The dynamic underwater chemistry seen in nature is inspiring for the next generation of eco-friendly nanochemistry. In this context, green synthesis of size-tailored nanoparticles in a facile and scalable manner via a dynamic process is an interesting challenge. Simulating the volcano-induced dynamic chemistry of the deep ocean, here we demonstrate the Leidenfrost dynamic chemistry occurring in an underwater overheated confined zone as a new tool for customized creation of nanoclusters of zinc peroxide. The hydrodynamic nature of the phenomenon ensures eruption of the nanoclusters towards a much colder region, giving rise to growth of monodisperse, size-tailored nanoclusters. Such nanoparticles are investigated in terms of their cytotoxicity on suspension and adherent cells to prove their applicability as cancer nanotherapeutics. Our research can pave the way for employment of the dynamic green nanochemistry in facile, scalable fabrication of size-tailored nanoparticles for biomedical applications.Peer reviewe

Microarray-based gene set analysis: a comparison of current methods

BACKGROUND: The analysis of gene sets has become a popular topic in recent times, with researchers attempting to improve the interpretability and reproducibility of their microarray analyses through the inclusion of supplementary biological information. While a number of options for gene set analysis exist, no consensus has yet been reached regarding which methodology performs best, and under what conditions. The goal of this work was to examine the performance characteristics of a collection of existing gene set analysis methods, on both simulated and real microarray data sets. Of particular interest was the potential utility gained through the incorporation of inter-gene correlation into the analysis process. RESULTS: Each of six gene set analysis methods was applied to both simulated and publicly available microarray data sets. Overall, the various methodologies were all found to be better at detecting gene sets that moved from non-active (i.e., genes not expressed) to active states (or vice versa), rather than those that simply changed their level of activity. Methods which incorporate correlation structures were found to provide increased ability to detect altered gene sets in some settings. CONCLUSION: Based on the results obtained through the analysis of simulated data, it is clear that the performance of gene set analysis methods is strongly influenced by the features of the data set in question, and that methods which incorporate correlation structures into the analysis process tend to achieve better performance, relative to methods which rely on univariate test statistics

Efficient Strict-Binning Particle-in-Cell Algorithm for Multi-Core SIMD Processors

International audienceParticle-in-Cell (PIC) codes are widely used for plasma simulations. On recent multi-core hardware, performance of these codes is often limited by memory bandwidth. We describe a multi-core PIC algorithm that achieves close-to-minimal number of memory transfers with the main memory, while at the same time exploiting SIMD instructions for numerical computations and exhibiting a high degree of OpenMP-level parallelism. Our algorithm keeps particles sorted by cell at every time step, and represents particles from a same cell using a linked list of fixed-capacity arrays, called chunks. Chunks support either sequential or atomic insertions, the latter being used to handle fast-moving particles. To validate our code, called Pic-Vert, we consider a 3d electrostatic Landau-damping simulation as well as a 2d3v transverse instability of magnetized electron holes. Performance results on a 24-core Intel Sky-lake hardware confirm the effectiveness of our algorithm, in particular its high throughput and its ability to cope with fast moving particles

Building pathway clusters from Random Forests classification using class votes

<p>Abstract</p> <p>Background</p> <p>Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bring biological insights into microarray studies. A variety of methods have been proposed to construct networks using gene expression data. Because individual pathways do not act in isolation, it is important to understand how different pathways coordinate to perform cellular functions. However, there are no published methods describing how to build pathway clusters that are closely related to traits of interest.</p> <p>Results</p> <p>We propose to build pathway clusters from pathway-based classification methods. The proposed methods allow researchers to identify clusters of pathways sharing similar functions. These pathways may or may not share genes. As an illustration, our approach is applied to three human breast cancer microarray data sets. We found that our methods yielded consistent and interpretable results for these three data sets. We further investigated one of the pathway clusters found using PubMatrix. We found that informative genes in the pathway clusters do have more publications with keywords, like estrogen receptor, compared with informative genes in other top pathways. In addition, using the shortest path analysis in GeneGo's MetaCore and Human Protein Reference Database, we were able to identify the links which connect the pathways without shared genes within the pathway cluster.</p> <p>Conclusion</p> <p>Our proposed pathway clustering methods allow bioinformaticians and biologists to investigate how informative genes within pathways are related to each other and understand possible crosstalk between pathways in a cluster. Therefore, building pathway clusters may lead to a better understanding of molecular mechanisms affecting a trait of interest, and help generate further biological hypotheses from gene expression data.</p

Use of Confocal Laser as Light Source Reveals Stomata-Autonomous Function

In most terrestrial plants, stomata open during the day to maximize the update of CO(2) for photosynthesis, but they close at night to minimize water loss. Blue light, among several environmental factors, controls this process. Stomata response to diverse stimuli seems to be dictated by the behaviour of neighbour stomata creating leaf areas of coordinated response. Here individual stomata of Arabidopsis leaves were illuminated with a short blue-light pulse by focusing a confocal argon laser. Beautifully, the illuminated stomata open their pores, whereas their dark-adapted neighbours unexpectedly experience no change. This induction of individual stomata opening by low fluence rates of blue light was disrupted in the phototropin1 phototropin2 (phot1 phot2) double mutant, which exhibits insensitivity of stomatal movements in blue-illuminated epidermal strips. The irradiation of all epidermal cells making direct contact with a given stoma in both wild type and phot1 phot2 plants does not trigger its movement. These results unravel the stoma autonomous function in the blue light response and illuminate the implication of PHOT1 and/or PHOT2 in such response. The micro spatial heterogeneity that solar blue light suffers in partially shaded leaves under natural conditions highlights the physiological significance of the autonomous stomatal behaviour

Single-Tissue and Cross-Tissue Heritability of Gene Expression Via Identity-by-Descent in Related or Unrelated Individuals

Family studies of individual tissues have shown that gene expression traits are genetically heritable. Here, we investigate cis and trans components of heritability both within and across tissues by applying variance-components methods to 722 Icelanders from family cohorts, using identity-by-descent (IBD) estimates from long-range phased genome-wide SNP data and gene expression measurements for ∼19,000 genes in blood and adipose tissue. We estimate the proportion of gene expression heritability attributable to cis regulation as 37% in blood and 24% in adipose tissue. Our results indicate that the correlation in gene expression measurements across these tissues is primarily due to heritability at cis loci, whereas there is little sharing of trans regulation across tissues. One implication of this finding is that heritability in tissues composed of heterogeneous cell types is expected to be more dominated by cis regulation than in tissues composed of more homogeneous cell types, consistent with our blood versus adipose results as well as results of previous studies in lymphoblastoid cell lines. Finally, we obtained similar estimates of the cis components of heritability using IBD between unrelated individuals, indicating that transgenerational epigenetic inheritance does not contribute substantially to the “missing heritability” of gene expression in these tissue types

Dietary behavior and knowledge of dental erosion among Chinese adults

<p>Abstract</p> <p>Objectives</p> <p>To study the dietary behavior and knowledge about dental erosion and self-reported symptoms that can be related to dental erosion among Chinese adults in Hong Kong.</p> <p>Methods</p> <p>Chinese adults aged 25-45 years were randomly selected from a list of registered telephone numbers generated by computer. A telephone survey was administered to obtain information on demographic characteristics, dietary habits, dental visits, and knowledge of and presence of self-reported symptoms that can be related to dental erosion.</p> <p>Results</p> <p>A total of 520 participants were interviewed (response rate, 75%; sampling error, ± 4.4%) and their mean age was 37. Most respondents (79%) had ever had caries, and about two thirds (64%) attended dental check-ups at least once a year. Respondents had a mean of 5.4 meals per day and 36% had at least 6 meals per day. Fruit (89%) and lemon tea/water (41%) were the most commonly consumed acidic food and beverage. When asked if they ever noticed changes in their teeth, most respondents (92%) said they had experienced change that can be related to erosion. However, many (71%) had never heard about dental erosion and 53% mixed up dental erosion with dental caries.</p> <p>Conclusion</p> <p>Hong Kong Chinese adults have frequent intake of food and many have experienced symptoms that can be related to dental erosion. Their level of awareness of and knowledge about dental erosion is generally low, despite most of them have regular dental check-ups. Dental health education is essential to help the public understand dental erosion and its damaging effects.</p

Sirtuin 3, a New Target of PGC-1α, Plays an Important Role in the Suppression of ROS and Mitochondrial Biogenesis

Sirtuin 3 (SIRT3) is one of the seven mammalian sirtuins, which are homologs of the yeast Sir2 gene. SIRT3 is the only sirtuin with a reported association with the human life span. Peroxisome proliferator-activated receptor gamma coactivator-1alpha (PGC-1alpha) plays important roles in adaptive thermogenesis, gluconeogenesis, mitochondrial biogenesis and respiration. PGC-1alpha induces several key reactive oxygen species (ROS)-detoxifying enzymes, but the molecular mechanism underlying this is not well understood.Here we show that PGC-1alpha strongly stimulated mouse Sirt3 gene expression in muscle cells and hepatocytes. Knockdown of PGC-1alpha led to decreased Sirt3 gene expression. PGC-1alpha activated the mouse SIRT3 promoter, which was mediated by an estrogen-related receptor (ERR) binding element (ERRE) (-407/-399) mapped to the promoter region. Chromatin immunoprecipitation and electrophoretic mobility shift assays confirmed that ERRalpha bound to the identified ERRE and PGC-1alpha co-localized with ERRalpha in the mSirt3 promoter. Knockdown of ERRalpha reduced the induction of Sirt3 by PGC-1alpha in C(2)C(12) myotubes. Furthermore, Sirt3 was essential for PGC-1alpha-dependent induction of ROS-detoxifying enzymes and several components of the respiratory chain, including glutathione peroxidase-1, superoxide dismutase 2, ATP synthase 5c, and cytochrome c. Overexpression of SIRT3 or PGC-1alpha in C(2)C(12) myotubes decreased basal ROS level. In contrast, knockdown of mSIRT3 increased basal ROS level and blocked the inhibitory effect of PGC-1alpha on cellular ROS production. Finally, SIRT3 stimulated mitochondrial biogenesis, and SIRT3 knockdown decreased the stimulatory effect of PGC-1alpha on mitochondrial biogenesis in C(2)C(12) myotubes.Our results indicate that Sirt3 functions as a downstream target gene of PGC-1alpha and mediates the PGC-1alpha effects on cellular ROS production and mitochondrial biogenesis. Thus, SIRT3 integrates cellular energy metabolism and ROS generation. The elucidation of the molecular mechanisms of SIRT3 regulation and its physiological functions may provide a novel target for treating ROS-related disease

Heading Down the Wrong Pathway: on the Influence of Correlation within Gene Sets

<p>Abstract</p> <p>Background</p> <p>Analysis of microarray experiments often involves testing for the overrepresentation of pre-defined sets of genes among lists of genes deemed individually significant. Most popular gene set testing methods assume the independence of genes within each set, an assumption that is seriously violated, as extensive correlation between genes is a well-documented phenomenon.</p> <p>Results</p> <p>We conducted a meta-analysis of over 200 datasets from the Gene Expression Omnibus in order to demonstrate the practical impact of strong gene correlation patterns that are highly consistent across experiments. We show that a common independence assumption-based gene set testing procedure produces very high false positive rates when applied to data sets for which treatment groups have been randomized, and that gene sets with high internal correlation are more likely to be declared significant. A reanalysis of the same datasets using an array resampling approach properly controls false positive rates, leading to more parsimonious and high-confidence gene set findings, which should facilitate pathway-based interpretation of the microarray data.</p> <p>Conclusions</p> <p>These findings call into question many of the gene set testing results in the literature and argue strongly for the adoption of resampling based gene set testing criteria in the peer reviewed biomedical literature.</p