Reviews

Tolkien, Race and Cultural History: From Fairies to Hobbits. Dimitra Fimi. Reviewed by Jason Fisher. Charles Williams and his Contemporaries. Suzanne Bray and Richard Sturch, eds. Reviewed by Joe R. Christopher. In the Land of Invented Languages: Esperanto Rock Stars, Klingon Poets, Loglan Lovers, and the Mad Dreamers who Tried to Build a Perfect Language. Arika Okrent. Reviewed by Harley J. Sims. Millennial Mythmaking: Essays on the Power of Science Fiction and Fantasy Literature, Films and Games. John Perlich & David Whitt, eds. Reviewed by Priscilla Hobbs Middle-earth Minstrel: Essays on Music in Tolkien. Bradford Lee Eden, ed. Reviewed by Emily A. Moniz. Harry Potter & Imagination: The Way Between Two Worlds. Travis Prinzi. Reviewed by David D. Oberhelman. Fastitocalon: Studies in Fantasticism Ancient to Modern: Immortals and the Undead. Eds. Thomas Honneger and Fanfan Chen. Reviewed by Janet Brennan Croft. Theodor Seuss Geisel [sic]. Donald E. Pease. Reviewed by Joe R. Christopher

The gene-rich genome of the scallop Pecten maximus.

BACKGROUND: The king scallop, Pecten maximus, is distributed in shallow waters along the Atlantic coast of Europe. It forms the basis of a valuable commercial fishery and plays a key role in coastal ecosystems and food webs. Like other filter feeding bivalves it can accumulate potent phytotoxins, to which it has evolved some immunity. The molecular origins of this immunity are of interest to evolutionary biologists, pharmaceutical companies, and fisheries management. FINDINGS: Here we report the genome assembly of this species, conducted as part of the Wellcome Sanger 25 Genomes Project. This genome was assembled from PacBio reads and scaffolded with 10X Chromium and Hi-C data. Its 3,983 scaffolds have an N50 of 44.8 Mb (longest scaffold 60.1 Mb), with 92% of the assembly sequence contained in 19 scaffolds, corresponding to the 19 chromosomes found in this species. The total assembly spans 918.3 Mb and is the best-scaffolded marine bivalve genome published to date, exhibiting 95.5% recovery of the metazoan BUSCO set. Gene annotation resulted in 67,741 gene models. Analysis of gene content revealed large numbers of gene duplicates, as previously seen in bivalves, with little gene loss, in comparison with the sequenced genomes of other marine bivalve species. CONCLUSIONS: The genome assembly of P. maximus and its annotated gene set provide a high-quality platform for studies on such disparate topics as shell biomineralization, pigmentation, vision, and resistance to algal toxins. As a result of our findings we highlight the sodium channel gene Nav1, known to confer resistance to saxitoxin and tetrodotoxin, as a candidate for further studies investigating immunity to domoic acid

World radiocommunication conference 12 : implications for the spectrum eco-system

Spectrum allocation is once more a key issue facing the global telecommunications industry. Largely overlooked in current debates, however, is the World Radiocommunication Conference (WRC). Decisions taken by WRC shape the future roadmap of the telecommunications industry, not least because it has the ability to shape the global spectrum allocation framework. In the debates of WRC-12 it is possible to identify three main issues: enhancement of the international spectrum regulatory framework, regulatory measures required to introduce Cognitive Radio Systems (CRS) technologies; and, additional spectrum allocation to mobile service. WRC-12 eventually decided not to change the current international radio regulations with regard to the first two issues and agreed to the third issue. The main implications of WRC-12 on the spectrum ecosystem are that most of actors are not in support of the concept of spectrum flexibility associated with trading and that the concept of spectrum open access is not under consideration. This is explained by the observation that spectrum trading and spectrum commons weaken state control over spectrum and challenge the main principles and norms of the international spectrum management regime. In addition, the mobile allocation issue has shown the lack of conformity with the main rules of the regime: regional spectrum allocation in the International Telecommunication Union (ITU) three regions, and the resistance to the slow decision making procedures. In conclusion, while the rules and decision-making procedures of the international spectrum management regime were challenged in the WRC-12, the main principles and norms are still accepted by the majority of countries

Hypergraph models of biological networks to identify genes critical to pathogenic viral response

Background: Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way relationships present among genes and proteins in biological systems. Hypergraphs are generalizations of graphs that naturally model multi-way relationships and have shown promise in modeling systems such as protein complexes and metabolic reactions. In this paper we seek to understand how hypergraphs can more faithfully identify, and potentially predict, important genes based on complex relationships inferred from genomic expression data sets. Results: We compiled a novel data set of transcriptional host response to pathogenic viral infections and formulated relationships between genes as a hypergraph where hyperedges represent significantly perturbed genes, and vertices represent individual biological samples with specific experimental conditions. We find that hypergraph betweenness centrality is a superior method for identification of genes important to viral response when compared with graph centrality. Conclusions: Our results demonstrate the utility of using hypergraphs to represent complex biological systems and highlight central important responses in common to a variety of highly pathogenic viruses

A Network Integration Approach to Predict Conserved Regulators Related to Pathogenicity of Influenza and SARS-CoV Respiratory Viruses

Respiratory infections stemming from influenza viruses and the Severe Acute Respiratory Syndrome corona virus (SARS-CoV) represent a serious public health threat as emerging pandemics. Despite efforts to identify the critical interactions of these viruses with host machinery, the key regulatory events that lead to disease pathology remain poorly targeted with therapeutics. Here we implement an integrated network interrogation approach, in which proteome and transcriptome datasets from infection of both viruses in human lung epithelial cells are utilized to predict regulatory genes involved in the host response. We take advantage of a novel "crowd-based" approach to identify and combine ranking metrics that isolate genes/proteins likely related to the pathogenicity of SARS-CoV and influenza virus. Subsequently, a multivariate regression model is used to compare predicted lung epithelial regulatory influences with data derived from other respiratory virus infection models. We predicted a small set of regulatory factors with conserved behavior for consideration as important components of viral pathogenesis that might also serve as therapeutic targets for intervention. Our results demonstrate the utility of integrating diverse 'omic datasets to predict and prioritize regulatory features conserved across multiple pathogen infection models

The role of EGFR in influenza pathogenicity: Multiple network-based approaches to identify a key regulator of non-lethal infections

Despite high sequence similarity between pandemic and seasonal influenza viruses, there is extreme variation in host pathogenicity from one viral strain to the next. Identifying the underlying mechanisms of variability in pathogenicity is a critical task for understanding influenza virus infection and effective management of highly pathogenic influenza virus disease. We applied a network-based modeling approach to identify critical functions related to influenza virus pathogenicity using large transcriptomic and proteomic datasets from mice infected with six influenza virus strains or mutants. Our analysis revealed two pathogenicity-related gene expression clusters; these results were corroborated by matching proteomics data. We also identified parallel downstream processes that were altered during influenza pathogenesis. We found that network bottlenecks (nodes that bridge different network regions) were highly enriched in pathogenicity-related genes, while network hubs (highly connected network nodes) were significantly depleted in these genes. We confirmed that this trend persisted in a distinct virus: Severe Acute Respiratory Syndrome Coronavirus (SARS). The role of epidermal growth factor receptor (EGFR) in influenza pathogenesis, one of the bottleneck regulators with corroborating signals across transcript and protein expression data, was tested and validated in additional mouse infection experiments. We demonstrate that EGFR is important during influenza infection, but the role it plays changes for lethal versus non-lethal infections. Our results show that by using association networks, bottleneck genes that lack hub characteristics can be used to predict a gene’s involvement in influenza virus pathogenicity. We also demonstrate the utility of employing multiple network approaches for analyzing host response data from viral infections

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Comparative genome analysis of lignin biosynthesis gene families across the plant kingdom

<p>Abstract</p> <p>Background</p> <p>As a major component of plant cell wall, lignin plays important roles in mechanical support, water transport, and stress responses. As the main cause for the recalcitrance of plant cell wall, lignin modification has been a major task for bioenergy feedstock improvement. The study of the evolution and function of lignin biosynthesis genes thus has two-fold implications. First, the lignin biosynthesis pathway provides an excellent model to study the coordinative evolution of a biochemical pathway in plants. Second, understanding the function and evolution of lignin biosynthesis genes will guide us to develop better strategies for bioenergy feedstock improvement.</p> <p>Results</p> <p>We analyzed lignin biosynthesis genes from fourteen plant species and one symbiotic fungal species. Comprehensive comparative genome analysis was carried out to study the distribution, relatedness, and family expansion of the lignin biosynthesis genes across the plant kingdom. In addition, we also analyzed the comparative synteny map between rice and sorghum to study the evolution of lignin biosynthesis genes within the <it>Poaceae </it>family and the chromosome evolution between the two species. Comprehensive lignin biosynthesis gene expression analysis was performed in rice, poplar and <it>Arabidopsis</it>. The representative data from rice indicates that different fates of gene duplications exist for lignin biosynthesis genes. In addition, we also carried out the biomass composition analysis of nine <it>Arabidopsis </it>mutants with both MBMS analysis and traditional wet chemistry methods. The results were analyzed together with the genomics analysis.</p> <p>Conclusion</p> <p>The research revealed that, among the species analyzed, the complete lignin biosynthesis pathway first appeared in moss; the pathway is absent in green algae. The expansion of lignin biosynthesis gene families correlates with substrate diversity. In addition, we found that the expansion of the gene families mostly occurred after the divergence of monocots and dicots, with the exception of the C4H gene family. Gene expression analysis revealed different fates of gene duplications, largely confirming plants are tolerant to gene dosage effects. The rapid expansion of lignin biosynthesis genes indicated that the translation of transgenic lignin modification strategies from model species to bioenergy feedstock might only be successful between the closely relevant species within the same family.</p

Investigating Instructor Talk in Novel Contexts: Widespread Use, Unexpected Categories, and an Emergent Sampling Strategy.

Instructor Talk-noncontent language used by instructors in classrooms-is a recently defined and promising variable for better understanding classroom dynamics. Having previously characterized the Instructor Talk framework within the context of a single course, we present here our results surrounding the applicability of the Instructor Talk framework to noncontent language used by instructors in novel course contexts. We analyzed Instructor Talk in eight additional biology courses in their entirety and in 61 biology courses using an emergent sampling strategy. We observed widespread use of Instructor Talk with variation in the amount and category type used. The vast majority of Instructor Talk could be characterized using the originally published Instructor Talk framework, suggesting the robustness of this framework. Additionally, a new form of Instructor Talk-Negatively Phrased Instructor Talk, language that may discourage students or distract from the learning process-was detected in these novel course contexts. Finally, the emergent sampling strategy described here may allow investigation of Instructor Talk in even larger numbers of courses across institutions and disciplines. Given its widespread use, potential influence on students in learning environments, and ability to be sampled, Instructor Talk may be a key variable to consider in future research on teaching and learning in higher education