Radiating dispersive shock waves in nonlocal optical media

We consider the step Riemann problem for the system of equations describing the propagation of a coherent light beam in nematic liquid crystals, which is a general system describing nonlinear wave propagation in a number of different physical applications. While the equation governing the light beam is of defocusing nonlinear Schr\"odinger equation type, the dispersive shock wave (DSW) generated from this initial condition has major differences from the standard DSW solution of the defocusing nonlinear Schr\"odinger equation. In particular, it is found that the DSW has positive polarity and generates resonant radiation which propagates ahead of it. Remarkably, the velocity of the lead soliton of the DSW is determined by the classical shock velocity. The solution for the radiative wavetrain is obtained using the WKB approximation. It is shown that for sufficiently small initial jumps the nematic DSW is asymptotically governed by a Korteweg-de Vries equation with fifth order dispersion, which explicitly shows the resonance generating the radiation ahead of the DSW. The constructed asymptotic theory is shown to be in good agreement with the results of direct numerical simulations.Comment: 22 pages, 6 figures; accepted for publication in Proc. Roy.Soc. London A (2016

Genome-wide copy number variation (CNV) in patients with autoimmune Addison's disease

<p>Abstract</p> <p>Background</p> <p>Addison's disease (AD) is caused by an autoimmune destruction of the adrenal cortex. The pathogenesis is multi-factorial, involving genetic components and hitherto unknown environmental factors. The aim of the present study was to investigate if gene dosage in the form of copy number variation (CNV) could add to the repertoire of genetic susceptibility to autoimmune AD.</p> <p>Methods</p> <p>A genome-wide study using the Affymetrix GeneChip^®Genome-Wide Human SNP Array 6.0 was conducted in 26 patients with AD. CNVs in selected genes were further investigated in a larger material of patients with autoimmune AD (n = 352) and healthy controls (n = 353) by duplex Taqman real-time polymerase chain reaction assays.</p> <p>Results</p> <p>We found that low copy number of <it>UGT2B28 </it>was significantly more frequent in AD patients compared to controls; conversely high copy number of <it>ADAM3A </it>was associated with AD.</p> <p>Conclusions</p> <p>We have identified two novel CNV associations to <it>ADAM3A </it>and <it>UGT2B28 </it>in AD. The mechanism by which this susceptibility is conferred is at present unclear, but may involve steroid inactivation (<it>UGT2B28</it>) and T cell maturation (<it>ADAM3A</it>). Characterization of these proteins may unravel novel information on the pathogenesis of autoimmunity.</p

Summer effects on body mass index (BMI) gain and growth patterns of American Indian children from kindergarten to first grade: a prospective study

<p>Abstract</p> <p>Background</p> <p>Overweight and obesity are highly prevalent among American Indian children, especially those living on reservations. There is little scientific evidence about the effects of summer vacation on obesity development in children. The purpose of this study was to investigate the effects of summer vacation between kindergarten and first grade on growth in height, weight, and body mass index (BMI) for a sample of American Indian children.</p> <p>Methods</p> <p>Children had their height and weight measured in four rounds of data collection (yielded three intervals: kindergarten, summer vacation, and first grade) as part of a school-based obesity prevention trial (Bright Start) in a Northern Plains Indian Reservation. Demographic variables were collected at baseline from parent surveys. Growth velocities (Z-score units/year) for BMI, weight, and height were estimated and compared for each interval using generalized linear mixed models.</p> <p>Results</p> <p>The children were taller and heavier than median of same age counterparts. Height Z-scores were positively associated with increasing weight status category. The mean weight velocity during summer was significantly less than during the school year. More rapid growth velocity in height during summer than during school year was observed. Obese children gained less adjusted-BMI in the first grade after gaining more than their counterparts during the previous two intervals. No statistically significant interval effects were found for height and BMI velocities.</p> <p>Conclusions</p> <p>There was no indication of a significant summer effect on children's BMI. Rather than seasonal or school-related patterns, the predominant pattern indicated by weight-Z and BMI-Z velocities might be related to age or maturation.</p> <p>Trial registration</p> <p>Bright Start: Obesity Prevention in American Indian Children Clinical Trial Govt ID# <a href="http://www.clinicaltrials.gov/ct2/show/NCT00123032">NCT00123032</a></p

Markov Chain Ontology Analysis (MCOA)

<p>Abstract</p> <p>Background</p> <p>Biomedical ontologies have become an increasingly critical lens through which researchers analyze the genomic, clinical and bibliographic data that fuels scientific research. Of particular relevance are methods, such as enrichment analysis, that quantify the importance of ontology classes relative to a collection of domain data. Current analytical techniques, however, remain limited in their ability to handle many important types of structural complexity encountered in real biological systems including class overlaps, continuously valued data, inter-instance relationships, non-hierarchical relationships between classes, semantic distance and sparse data.</p> <p>Results</p> <p>In this paper, we describe a methodology called Markov Chain Ontology Analysis (MCOA) and illustrate its use through a MCOA-based enrichment analysis application based on a generative model of gene activation. MCOA models the classes in an ontology, the instances from an associated dataset and all directional inter-class, class-to-instance and inter-instance relationships as a single finite ergodic Markov chain. The adjusted transition probability matrix for this Markov chain enables the calculation of eigenvector values that quantify the importance of each ontology class relative to other classes and the associated data set members. On both controlled Gene Ontology (GO) data sets created with Escherichia coli, Drosophila melanogaster and Homo sapiens annotations and real gene expression data extracted from the Gene Expression Omnibus (GEO), the MCOA enrichment analysis approach provides the best performance of comparable state-of-the-art methods.</p> <p>Conclusion</p> <p>A methodology based on Markov chain models and network analytic metrics can help detect the relevant signal within large, highly interdependent and noisy data sets and, for applications such as enrichment analysis, has been shown to generate superior performance on both real and simulated data relative to existing state-of-the-art approaches.</p

Prediction and Testing of Biological Networks Underlying Intestinal Cancer

Colorectal cancer progresses through an accumulation of somatic mutations, some of which reside in so-called “driver” genes that provide a growth advantage to the tumor. To identify points of intersection between driver gene pathways, we implemented a network analysis framework using protein interactions to predict likely connections – both precedented and novel – between key driver genes in cancer. We applied the framework to find significant connections between two genes, Apc and Cdkn1a (p21), known to be synergistic in tumorigenesis in mouse models. We then assessed the functional coherence of the resulting Apc-Cdkn1a network by engineering in vivo single node perturbations of the network: mouse models mutated individually at Apc (Apc1638N+/−) or Cdkn1a (Cdkn1a−/−), followed by measurements of protein and gene expression changes in intestinal epithelial tissue. We hypothesized that if the predicted network is biologically coherent (functional), then the predicted nodes should associate more specifically with dysregulated genes and proteins than stochastically selected genes and proteins. The predicted Apc-Cdkn1a network was significantly perturbed at the mRNA-level by both single gene knockouts, and the predictions were also strongly supported based on physical proximity and mRNA coexpression of proteomic targets. These results support the functional coherence of the proposed Apc-Cdkn1a network and also demonstrate how network-based predictions can be statistically tested using high-throughput biological data

Augmented serum level of major histocompatibility complex class I-related chain A (MICA) protein and reduced NKG2D expression on NK and T cells in patients with cervical cancer and precursor lesions

<p>Abstract</p> <p>Background</p> <p>Cervical cancer is the second most common cancer in women worldwide. NK and cytotoxic T cells play an important role in the elimination of virus-infected and tumor cells through NKG2D activating receptors, which can promote the lysis of target cells by binding to the major histocompatibility complex class I-related chain A (MICA) proteins. Increased serum levels of MICA have been found in patients with epithelial tumors. The aim of this study was to compare the levels of soluble MICA (sMICA) and NKG2D-expressing NK and T cells in blood samples from patients with cervical cancer or precursor lesions with those from healthy donors.</p> <p>Methods</p> <p>Peripheral blood with or without heparin was collected to obtain mononuclear cells or sera, respectively. Serum sMICA levels were measured by ELISA and NKG2D-expressing immune cells were analyzed by flow cytometry. Also, a correlation analysis was performed to associate sMICA levels with either NKG2D expression or with the stage of the lesion.</p> <p>Results</p> <p>Significant amounts of sMICA were detected in sera from nearly all patients. We found a decrease in the number of NKG2D-expressing NK and T cells in both cervical cancer and lesion groups when compared to healthy donors. Pearson analysis showed a negative correlation between sMICA and NKG2D-expressing T cells; however, we did not find a significant correlation when the analysis was applied to sMICA and NKG2D expression on NK cells.</p> <p>Conclusion</p> <p>Our results show for the first time that high sMICA levels are found in sera from patients with both cervical cancer and precursor lesions when compared with healthy donors. We also observed a diminution in the number of NKG2D-expressing NK and T cells in the patient samples; however, a significant negative correlation between sMICA and NKG2D expression was only seen in T cells.</p

A Genetically Hard-Wired Metabolic Transcriptome in Plasmodium falciparum Fails to Mount Protective Responses to Lethal Antifolates

Genome sequences of Plasmodium falciparum allow for global analysis of drug responses to antimalarial agents. It was of interest to learn how DNA microarrays may be used to study drug action in malaria parasites. In one large, tightly controlled study involving 123 microarray hybridizations between cDNA from isogenic drug-sensitive and drug-resistant parasites, a lethal antifolate (WR99210) failed to over-produce RNA for the genetically proven principal target, dihydrofolate reductase-thymidylate synthase (DHFR-TS). This transcriptional rigidity carried over to metabolically related RNA encoding folate and pyrimidine biosynthesis, as well as to the rest of the parasite genome. No genes were reproducibly up-regulated by more than 2-fold until 24 h after initial drug exposure, even though clonal viability decreased by 50% within 6 h. We predicted and showed that while the parasites do not mount protective transcriptional responses to antifolates in real time, P. falciparum cells transfected with human DHFR gene, and adapted to long-term WR99210 exposure, adjusted the hard-wired transcriptome itself to thrive in the presence of the drug. A system-wide incapacity for changing RNA levels in response to specific metabolic perturbations may contribute to selective vulnerabilities of Plasmodium falciparum to lethal antimetabolites. In addition, such regulation affects how DNA microarrays are used to understand the mode of action of antimetabolites

Rationale and design of the multiethnic Pharmacogenomics in Childhood Asthma consortium

AIM: International collaboration is needed to enable large-scale pharmacogenomics studies in childhood asthma. Here, we describe the design of the Pharmacogenomics in Childhood Asthma (PiCA) consortium. MATERIALS & METHODS: Investigators of each study participating in PiCA provided data on the study characteristics by answering an online questionnaire. RESULTS: A total of 21 studies, including 14,227 children/young persons (58% male), from 12 different countries are currently enrolled in the PiCA consortium. Fifty six percent of the patients are Caucasians. In total, 7619 were inhaled corticosteroid users. Among patients from 13 studies with available data on asthma exacerbations, a third reported exacerbations despite inhaled corticosteroid use. In the future pharmacogenomics studies within the consortium, the pharmacogenomics analyses will be performed separately in each center and the results will be meta-analyzed. CONCLUSION: PiCA is a valuable platform to perform pharmacogenetics studies within a multiethnic pediatric asthma population