Upregulation of the microRNA cluster at the Dlk1-Dio3 locus in lung adenocarcinoma.

Mice in which lung epithelial cells can be induced to express an oncogenic Kras(G12D) develop lung adenocarcinomas in a manner analogous to humans. A myriad of genetic changes accompany lung adenocarcinomas, many of which are poorly understood. To get a comprehensive understanding of both the transcriptional and post-transcriptional changes that accompany lung adenocarcinomas, we took an omics approach in profiling both the coding genes and the non-coding small RNAs in an induced mouse model of lung adenocarcinoma. RNAseq transcriptome analysis of Kras(G12D) tumors from F1 hybrid mice revealed features specific to tumor samples. This includes the repression of a network of GTPase-related genes (Prkg1, Gnao1 and Rgs9) in tumor samples and an enrichment of Apobec1-mediated cytosine to uridine RNA editing. Furthermore, analysis of known single-nucleotide polymorphisms revealed not only a change in expression of Cd22 but also that its expression became allele specific in tumors. The most salient finding, however, came from small RNA sequencing of the tumor samples, which revealed that a cluster of ∼53 microRNAs and mRNAs at the Dlk1-Dio3 locus on mouse chromosome 12qF1 was markedly and consistently increased in tumors. Activation of this locus occurred specifically in sorted tumor-originating cancer cells. Interestingly, the 12qF1 RNAs were repressed in cultured Kras(G12D) tumor cells but reactivated when transplanted in vivo. These microRNAs have been implicated in stem cell pleuripotency and proteins targeted by these microRNAs are involved in key pathways in cancer as well as embryogenesis. Taken together, our results strongly imply that these microRNAs represent key targets in unraveling the mechanism of lung oncogenesis

Phosphorylation of chemoattractant receptors is not essential for chemotaxis or termination of G-protein-mediated responses

In several G-protein-coupled signaling systems, ligand-induced receptor phosphorylation by specific kinases is suggested to lead to desensitization via mechanisms including receptor/G-protein uncoupling, receptor internalization, and receptor down-regulation. We report here that elimination of phosphorylation of a chemoattractant receptor of Dictyostelium, either by site-directed substitution of the serines or by truncation of the C-terminal cytoplasmic domain, completely prevented agonist-induced loss of ligand binding but did not impair the adaptation of several receptor-mediated responses including the activation of adenylyl and guanylyl cyclases and actin polymerization, In addition, the phosphorylation deficient receptors were capable of mediating chemotaxis, aggregation, and differentiation. We propose that for chemoattractant receptors agonist-induced phosphorylation regulates surface binding activity but other phosphorylation-independent mechanisms mediate response adaptation

Controlling molecular conformation for highly efficient and stable deep-blue copolymer light-emitting diodes

We report a novel approach to the achievement of deep-blue, high-efficiency, and long-lived solution processed polymer light-emitting diodes (PLEDs) via a simple molecular-level conformation change whereby we introduce rigid β-phase segments into a 95% fluorene - 5% arylamine copolymer emission layer (EML). The arylamine moieties at low density act as efficient exciton formation sites in PLEDs whilst the conformational change alters the nature of the dominant luminescence from a broad, charge-transfer like emission to a significantly blue-shifted and highly vibronically structured, excitonic emission. As a consequence, we observe a significant improvement in Commission International de L'Eclairage (CIE) (x, y) co-ordinates from (0.149, 0.175) to (0.145, 0.123) whilst maintaining high efficiency and improving stability. We achieve peak luminous efficiency, η = 3.60 cd/A and luminous power efficiency, ηw = 2.44 lm/W; values that represent state of the art performance for single copolymer deep-blue PLEDs. These values are five-fold better than for otherwise-equivalent, β-phase poly(9,9-dioctylfluorene) (PFO) EML PLEDs (0.70 cd/A and 0.38 lm/W). This report represents the first demonstration of the use of molecular conformation as a vector to control the optoelectronic properties of a fluorene copolymer; previous examples have been confined to homopolymers

Closing the sea surface mixed layer temperature budget from in situ observations alone: Operation Advection during BoBBLE

Sea surface temperature (SST) is a fundamental driver of tropical weather systems such as monsoon rainfall and tropical cyclones. However, understanding of the factors that control SST variability is lacking, especially during the monsoons when in situ observations are sparse. Here we use a ground-breaking observational approach to determine the controls on the SST variability in the southern Bay of Bengal. We achieve this through the first full closure of the ocean mixed layer energy budget derived entirely from in situ observations during the Bay of Bengal Boundary Layer Experiment (BoBBLE). Locally measured horizontal advection and entrainment contribute more significantly than expected to SST evolution and thus oceanic variability during the observation period. These processes are poorly resolved by state-of-the-art climate models, which may contribute to poor representation of monsoon rainfall variability. The novel techniques presented here provide a blueprint for future observational experiments to quantify the mixed layer heat budget on longer time scales and to evaluate these processes in models

H_2 emission arises outside photodissociation regions in ultra-luminous infrared galaxies

Ultra-luminous infrared galaxies are among the most luminous objects in the local universe and are thought to be powered by intense star formation. It has been shown that in these objects the rotational spectral lines of molecular hydrogen observed at mid-infrared wavelengths are not affected by dust obscuration, leaving unresolved the source of excitation of this emission. Here I report an analysis of archival Spitzer Space Telescope data on ultra-luminous infrared galaxies and demonstrate that star formation regions are buried inside optically thick clouds of gas and dust, so that dust obscuration affects star-formation indicators but not molecular hydrogen. I thereby establish that the emission of H_2 is not co-spatial with the buried starburst activity and originates outside the obscured regions. This is rather surprising in light of the standard view that H_2 emission is directly associated with star-formation activity. Instead, I propose that H_2 emission in these objects traces shocks in the surrounding material, which are in turn excited by interactions with nearby galaxies, and that powerful large-scale shocks cooling by means of H_2 emission may be much more common than previously thought. In the early universe, a boost in H_2 emission by this process may speed up the cooling of matter as it collapsed to form the first stars and galaxies and would make these first structures more readily observable.Comment: Main text and supplemental information, 21 pages including 6 figures, 2 table

Using Neural Networks for Relation Extraction from Biomedical Literature

Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems. The primary comprehensive source of these relations is biomedical literature. Several relation extraction approaches have been proposed to identify relations between concepts in biomedical literature, namely, using neural networks algorithms. The use of multichannel architectures composed of multiple data representations, as in deep neural networks, is leading to state-of-the-art results. The right combination of data representations can eventually lead us to even higher evaluation scores in relation extraction tasks. Thus, biomedical ontologies play a fundamental role by providing semantic and ancestry information about an entity. The incorporation of biomedical ontologies has already been proved to enhance previous state-of-the-art results.Comment: Artificial Neural Networks book (Springer) - Chapter 1

A Novel Three-Phase Model of Brain Tissue Microstructure

We propose a novel biologically constrained three-phase model of the brain microstructure. Designing a realistic model is tantamount to a packing problem, and for this reason, a number of techniques from the theory of random heterogeneous materials can be brought to bear on this problem. Our analysis strongly suggests that previously developed two-phase models in which cells are packed in the extracellular space are insufficient representations of the brain microstructure. These models either do not preserve realistic geometric and topological features of brain tissue or preserve these properties while overestimating the brain's effective diffusivity, an average measure of the underlying microstructure. In light of the highly connected nature of three-dimensional space, which limits the minimum diffusivity of biologically constrained two-phase models, we explore the previously proposed hypothesis that the extracellular matrix is an important factor that contributes to the diffusivity of brain tissue. Using accurate first-passage-time techniques, we support this hypothesis by showing that the incorporation of the extracellular matrix as the third phase of a biologically constrained model gives the reduction in the diffusion coefficient necessary for the three-phase model to be a valid representation of the brain microstructure

Neonatal-onset multisystem inflammatory disease responsive to interleukin-1 beta inhibition

BACKGROUND:Neonatal-onset multisystem inflammatory disease is characterized by fever, urticarial rash, aseptic meningitis, deforming arthropathy, hearing loss, and mental retardation. Many patients have mutations in the cold-induced autoinflammatory syndrome 1 (CIAS1) gene, encoding cryopyrin, a protein that regulates inflammation.METHODS:We selected 18 patients with neonatal-onset multisystem inflammatory disease (12 with identifiable CIAS1 mutations) to receive anakinra, an interleukin-1-receptor antagonist (1 to 2 mg per kilogram of body weight per day subcutaneously). In 11 patients, anakinra was withdrawn at three months until a flare occurred. The primary end points included changes in scores in a daily diary of symptoms, serum levels of amyloid A and C-reactive protein, and the erythrocyte sedimentation rate from baseline to month 3 and from month 3 until a disease flare.RESULTS:All 18 patients had a rapid response to anakinra, with disappearance of rash. Diary scores improved (P<0.001) and serum amyloid A (from a median of 174 mg to 8 mg per liter), C-reactive protein (from a median of 5.29 mg to 0.34 mg per deciliter), and the erythrocyte sedimentation rate decreased at month 3 (all P<0.001), and remained low at month 6. Magnetic resonance imaging showed improvement in cochlear and leptomeningeal lesions as compared with baseline. Withdrawal of anakinra uniformly resulted in relapse within days; retreatment led to rapid improvement. There were no drug-related serious adverse events.CONCLUSIONS:Daily injections of anakinra markedly improved clinical and laboratory manifestations in patients with neonatal-onset multisystem inflammatory disease, with or without CIAS1 mutations

Overstating the evidence - double counting in meta-analysis and related problems

Background: The problem of missing studies in meta-analysis has received much attention. Less attention has been paid to the more serious problem of double counting of evidence. Methods: Various problems in overstating the precision of results from meta-analyses are described and illustrated with examples, including papers from leading medical journals. These problems include, but are not limited to, simple double-counting of the same studies, double counting of some aspects of the studies, inappropriate imputation of results, and assigning spurious precision to individual studies. Results: Some suggestions are made as to how the quality and reliability of meta-analysis can be improved. It is proposed that the key to quality in meta-analysis lies in the results being transparent and checkable. Conclusions: Existing quality check lists for meta-analysis do little to encourage an appropriate attitude to combining evidence and to statistical analysis. Journals and other relevant organisations should encourage authors to make data available and make methods explicit. They should also act promptly to withdraw meta-analyses when mistakes are found

CSI-OMIM - Clinical Synopsis Search in OMIM

<p>Abstract</p> <p>Background</p> <p>The OMIM database is a tool used daily by geneticists. Syndrome pages include a Clinical Synopsis section containing a list of known phenotypes comprising a clinical syndrome. The phenotypes are in free text and different phrases are often used to describe the same phenotype, the differences originating in spelling variations or typing errors, varying sentence structures and terminological variants.</p> <p>These variations hinder searching for syndromes or using the large amount of phenotypic information for research purposes. In addition, negation forms also create false positives when searching the textual description of phenotypes and induce noise in text mining applications.</p> <p>Description</p> <p>Our method allows efficient and complete search of OMIM phenotypes as well as improved data-mining of the OMIM phenome. Applying natural language processing, each phrase is tagged with additional semantic information using UMLS and MESH. Using a grammar based method, annotated phrases are clustered into groups denoting similar phenotypes. These groups of synonymous expressions enable precise search, as query terms can be matched with the many variations that appear in OMIM, while avoiding over-matching expressions that include the query term in a negative context. On the basis of these clusters, we computed pair-wise similarity among syndromes in OMIM. Using this new similarity measure, we identified 79,770 new connections between syndromes, an average of 16 new connections per syndrome. Our project is Web-based and available at <url>http://fohs.bgu.ac.il/s2g/csiomim</url></p> <p>Conclusions</p> <p>The resulting enhanced search functionality provides clinicians with an efficient tool for diagnosis. This search application is also used for finding similar syndromes for the candidate gene prioritization tool S2G.</p> <p>The enhanced OMIM database we produced can be further used for bioinformatics purposes such as linking phenotypes and genes based on syndrome similarities and the known genes in Morbidmap.</p