Evidence for Braggoriton Excitations in Opal Photonic Crystals Infiltrated with Highly Polarizable Dyes

We studied angle-dependent reflectivity spectra of opal photonic crystals infiltrated with cyanine dyes, which are highly polarizable media with very large Rabi frequency. We show that when resonance conditions between the exciton-polariton of the infiltrated dye and Bragg frequencies exist, then the Bragg stop band decomposes into two reflectivity bands with a semi-transparent spectral range in between that is due to light propagation inside the gap caused by the existence of braggoriton excitations. These novel excitations result from the interplay interaction between the Bragg gap with spatial modulation origin and the polariton gap due to the excitons, and may lead to optical communication traffic inside the gap of photonic crystals via channel waveguiding.Comment: LaTex, 5 pages, 3 figures include

Coherent Umklapp Scattering of Light from Disordered Photonic Crystals

A theoretical study of the coherent light scattering from disordered photonic crystal is presented. In addition to the conventional enhancement of the reflected light intensity into the backscattering direction, the so called coherent backscattering (CBS), the periodic modulation of the dielectric function in photonic crystals gives rise to a qualitatively new effect: enhancement of the reflected light intensity in directions different from the backscattering direction. These additional coherent scattering processes, dubbed here {\em umklapp scattering} (CUS), result in peaks, which are most pronounced when the incident light beam enters the sample at an angle close to the the Bragg angle. Assuming that the dielectric function modulation is weak, we study the shape of the CUS peaks for different relative lengths of the modulation-induced Bragg attenuation compared to disorder-induced mean free path. We show that when the Bragg length increases, then the CBS peak assumes its conventional shape, whereas the CUS peak rapidly diminishes in amplitude. We also study the suppression of the CUS peak upon the departure of the incident beam from Bragg resonance: we found that the diminishing of the CUS intensity is accompanied by substantial broadening. In addition, the peak becomes asymmetric.Comment: LaTeX, 8 two-column pages, 6 figures include

Charged mobile complexes in magnetic fields: A novel selection rule for magneto-optical transitions

The implications of magnetic translations for internal optical transitions of charged mobile electron-hole ($e$--$h$) complexes and ions in a uniform magnetic field $B$ are discussed. It is shown that transitions of such complexes are governed by a novel exact selection rule. Internal intraband transitions of two-dimensional (2D) charged excitons $X^-$ in strong magnetic fields are considered as an illustrative example.Comment: 4 pages, 2 figure

Braggoriton--Excitation in Photonic Crystal Infiltrated with Polarizable Medium

Light propagation in a photonic crystal infiltrated with polarizable molecules is considered. We demonstrate that the interplay between the spatial dispersion caused by Bragg diffraction and polaritonic frequency dispersion gives rise to novel propagating excitations, or braggoritons, with intragap frequencies. We derive the braggoriton dispersion relation and show that it is governed by two parameters, namely, the strength of light-matter interaction and detuning between the Bragg frequency and that of the infiltrated molecules. We also study defect-induced states when the photonic band gap is divided into two subgaps by the braggoritonic branches and find that each defect creates two intragap localized states inside each subgap.Comment: LaTeX, 8 pages, 5 figure

Exome and whole genome sequencing of esophageal adenocarcinoma identifies recurrent driver events and mutational complexity

The incidence of esophageal adenocarcinoma (EAC) has risen 600% over the last 30 years. With a five-year survival rate of 15%, identification of new therapeutic targets for EAC is greatly important. We analyze the mutation spectra from whole exome sequencing of 149 EAC tumors/normal pairs, 15 of which have also been subjected to whole genome sequencing. We identify a mutational signature defined by a high prevalence of A to C transversions at AA dinucleotides. Statistical analysis of exome data identified significantly mutated 26 genes. Of these genes, four (TP53, CDKN2A, SMAD4, and PIK3CA) have been previously implicated in EAC. The novel significantly mutated genes include chromatin modifying factors and candidate contributors: SPG20, TLR4, ELMO1, and DOCK2. Functional analyses of EAC-derived mutations in ELMO1 reveal increased cellular invasion. Therefore, we suggest a new hypothesis about the potential activation of the RAC1 pathway to be a contributor to EAC tumorigenesis

Finding consistent disease subnetworks across microarray datasets

<p>Abstract</p> <p>Background</p> <p>While contemporary methods of microarray analysis are excellent tools for studying individual microarray datasets, they have a tendency to produce different results from different datasets of the same disease. We aim to solve this reproducibility problem by introducing a technique (SNet). SNet provides both quantitative and descriptive analysis of microarray datasets by identifying specific connected portions of pathways that are significant. We term such portions within pathways as “subnetworks”.</p> <p>Results</p> <p>We tested SNet on independent datasets of several diseases, including childhood ALL, DMD and lung cancer. For each of these diseases, we obtained two independent microarray datasets produced by distinct labs on distinct platforms. In each case, our technique consistently produced almost the same list of significant nontrivial subnetworks from two independent sets of microarray data. The gene-level agreement of these significant subnetworks was between 51.18% to 93.01%. In contrast, when the same pairs of microarray datasets were analysed using GSEA, t-test and SAM, this percentage fell between 2.38% to 28.90% for GSEA, 49.60% tp 73.01% for t-test, and 49.96% to 81.25% for SAM. Furthermore, the genes selected using these existing methods did not form subnetworks of substantial size. Thus it is more probable that the subnetworks selected by our technique can provide the researcher with more descriptive information on the portions of the pathway actually affected by the disease.</p> <p>Conclusions</p> <p>These results clearly demonstrate that our technique generates significant subnetworks and genes that are more consistent and reproducible across datasets compared to the other popular methods available (GSEA, t-test and SAM). The large size of subnetworks which we generate indicates that they are generally more biologically significant (less likely to be spurious). In addition, we have chosen two sample subnetworks and validated them with references from biological literature. This shows that our algorithm is capable of generating descriptive biologically conclusions.</p

ВИЧ-ИНФЕКЦИЯ И ВИЧ-АССОЦИИРОВАННЫЙ ТУБЕРКУЛЕЗ У ДЕТЕЙ УКРАИНЫ

The article presents data on the epidemiology of HIV infection and co-infection with HIV/TB in children in Ukraine. Along with the increasing number of HIV-infected women of reproductive age and their children, it is mentioned the growth of tuberculosis among HIV-infected children. The problems of adequate monitoring and management of these patients, in particular with regard to the prevention of tuberculosis among them are described. There are made conclusions about the need to improve the delivery system of TB care for children born by HIV-infected mothers.В статье представлены данные об эпидемиологической ситуации по ВИЧ-инфекции и ко-инфекции ВИЧ/туберкулез у детей на Украине. Наряду с увеличением числа ВИЧ-инфицированных женщин детородного возраста и рожденных ими детей отмечен рост заболеваемости туберкулезом среди ВИЧ-инфицированных детей. Освещаются вопросы адекватного наблюдения и ведения этой категории пациентов, в частности трудности профилактики у них туберкулеза. Сделаны выводы о необходимости совершенствования системы оказания противотуберкулезной помощи детям, рожденным от ВИЧ-инфицированных матерей

Network-Based Pipeline for Analyzing MS Data: An Application toward Liver Cancer

10.1021/pr1010845Journal of Proteome Research1052261-2272JPRO

Integrated genomic analyses of ovarian carcinoma

A catalogue of molecular aberrations that cause ovarian cancer is critical for developing and deploying therapies that will improve patients’ lives. The Cancer Genome Atlas project has analysed messenger RNA expression, microRNA expression, promoter methylation and DNA copy number in 489 high-grade serous ovarian adenocarcinomas and the DNA sequences of exons from coding genes in 316 of these tumours. Here we report that high-grade serous ovarian cancer is characterized by TP53 mutations in almost all tumours (96%); low prevalence but statistically recurrent somatic mutations in nine further genes including NF1, BRCA1, BRCA2, RB1 and CDK12; 113 significant focal DNA copy number aberrations; and promoter methylation events involving 168 genes. Analyses delineated four ovarian cancer transcriptional subtypes, three microRNA subtypes, four promoter methylation subtypes and a transcriptional signature associated with survival duration, and shed new light on the impact that tumours with BRCA1/2 (BRCA1 or BRCA2) and CCNE1 aberrations have on survival. Pathway analyses suggested that homologous recombination is defective in about half of the tumours analysed, and that NOTCH and FOXM1 signalling are involved in serous ovarian cancer pathophysiology.National Institutes of Health (U.S.) (Grant U54HG003067)National Institutes of Health (U.S.) (Grant U54HG003273)National Institutes of Health (U.S.) (Grant U54HG003079)National Institutes of Health (U.S.) (Grant U24CA126543)National Institutes of Health (U.S.) (Grant U24CA126544)National Institutes of Health (U.S.) (Grant U24CA126546)National Institutes of Health (U.S.) (Grant U24CA126551)National Institutes of Health (U.S.) (Grant U24CA126554)National Institutes of Health (U.S.) (Grant U24CA126561)National Institutes of Health (U.S.) (Grant U24CA126563)National Institutes of Health (U.S.) (Grant U24CA143882)National Institutes of Health (U.S.) (Grant U24CA143731)National Institutes of Health (U.S.) (Grant U24CA143835)National Institutes of Health (U.S.) (Grant U24CA143845)National Institutes of Health (U.S.) (Grant U24CA143858)National Institutes of Health (U.S.) (Grant U24CA144025)National Institutes of Health (U.S.) (Grant U24CA143866)National Institutes of Health (U.S.) (Grant U24CA143867)National Institutes of Health (U.S.) (Grant U24CA143848)National Institutes of Health (U.S.) (Grant U24CA143843)National Institutes of Health (U.S.) (Grant R21CA135877

Biomedical Discovery Acceleration, with Applications to Craniofacial Development

The profusion of high-throughput instruments and the explosion of new results in the scientific literature, particularly in molecular biomedicine, is both a blessing and a curse to the bench researcher. Even knowledgeable and experienced scientists can benefit from computational tools that help navigate this vast and rapidly evolving terrain. In this paper, we describe a novel computational approach to this challenge, a knowledge-based system that combines reading, reasoning, and reporting methods to facilitate analysis of experimental data. Reading methods extract information from external resources, either by parsing structured data or using biomedical language processing to extract information from unstructured data, and track knowledge provenance. Reasoning methods enrich the knowledge that results from reading by, for example, noting two genes that are annotated to the same ontology term or database entry. Reasoning is also used to combine all sources into a knowledge network that represents the integration of all sorts of relationships between a pair of genes, and to calculate a combined reliability score. Reporting methods combine the knowledge network with a congruent network constructed from experimental data and visualize the combined network in a tool that facilitates the knowledge-based analysis of that data. An implementation of this approach, called the Hanalyzer, is demonstrated on a large-scale gene expression array dataset relevant to craniofacial development. The use of the tool was critical in the creation of hypotheses regarding the roles of four genes never previously characterized as involved in craniofacial development; each of these hypotheses was validated by further experimental work