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Re-emerging and emerging viral diseases, for which no approved vaccines or therapeutics exist, pose a significant public health threat in affected areas of the world. Antiviral drugs that are broadly active against multiple pathogenic viruses are much needed. Our findings demonstrating robust protection conferred by treatment with 4′-fluorouridine (4′-FlU) in viral infection models for Oropouche fever, Rift Valley fever, and severe fever with thrombocytopenia syndrome support the continuing development of this promising broad-spectrum antiviral drug candidate for the treatment of these notable viral diseases.

This chapter briefly reviews the distributed shared‐memory and message‐passing models for network‐centric applications. It presents the advantages of message‐passing tools and their classification with respect to the application domain, programming model supported, communication model, portability, and adaptability. The chapter then describes hardware‐ and software‐based approaches to improving the performance of message‐passing tools. This is followed by an overview of existing message‐passing tools such as socket‐based message‐passing, p4, Parallel Virtual Machine (PVM), Message Passing Interface (MPI), Nexus, Madeleine, and Active Messages. The chapter then describes the design of ACS (Adaptive Communication Systems), a multi‐threaded message‐passing tool, and presents an experimental evaluation of ACS and three different message‐passing tools (p4, PVM, and MPI) with respect to primitives and application performance.

This chapter contains sections titled: Introduction Inductive and transductive methods Overview of classification and prediction methods Classification by decision tree Prediction by decision tree Classification by discriminant analysis Prediction by linear regression Classification by logistic regression Developments in logistic regression Bayesian methods Classification and prediction by neural networks Classification by support vector machines Prediction by genetic algorithms Improving the performance of a predictive model Bootstrapping and ensemble methods Using classification and prediction methods

The majority of psychological treatment research is dedicated to investigating the effectiveness of cognitive behavioural therapy (CBT) across different conditions, population and contexts. We aimed to summarise the current systematic review evidence and evaluate the consistency of CBT's effect across different conditions. We included reviews of CBT randomised controlled trials in any: population, condition, format, context, with any type of comparator and published in English. We searched DARE, Cochrane, MEDLINE, EMBASE, PsycINFO, CINAHL, CDAS, and OpenGrey between 1992 and January 2019. Reviews were quality assessed, their data extracted and summarised. The effects upon health-related quality of life (HRQoL) were pooled, within-condition groups. If the across-condition heterogeneity was I 2 < 75%, we pooled effects using a random-effect panoramic meta-analysis. We summarised 494 reviews (221 128 participants), representing 14/20 physical and 13/20 mental conditions (World Health Organisation's International Classification of Diseases). Most reviews were lower-quality (351/494), investigated face-to-face CBT (397/494), and in adults (378/494). Few reviews included trials conducted in Asia, South America or Africa (45/494). CBT produced a modest benefit across-conditions on HRQoL (standardised mean difference 0.23; 95% confidence intervals 0.14–0.33, I 2 = 32%). The effect's associated prediction interval −0.05 to 0.50 suggested CBT will remain effective in conditions for which we do not currently have available evidence. While there remain some gaps in the completeness of the evidence base, we need to recognise the consistent evidence for the general benefit which CBT offers.

After 8 years, an update of central nervous system (CNS) tumors was published in 2016 after 2007. First time ever, molecular markers along with histology have been used in classification of any tumor. Major changes are seen in glioma and medulloblastoma groups. Few entities have been added such as diffuse midline glioma, H3 K27M-mutant, RELA fusion-positive ependymoma, embryonal tumor with multilayered rosettes, C19MC-altered, and hybrid nerve sheath tumors. Few variants and patterns that no longer have diagnostic and/or biological relevance and have been deleted such as glioblastoma cerebri, protoplasmic and fibrillary astrocytoma, and cellular ependymoma. Other changes include deletion of term “primitive neuroectodermal tumor,” addition of criterion of brain invasion in atypical meningioma, separation of melanotic schwannoma from other schwannoma, and combination of solitary fibrous tumors and hemangiopericytoma as one entity. There is also expansion of entities in nerve sheath tumors and hematopoietic/lymphoid tumors of the CNS. In this review article, we tried to review CNS tumors 2016 classification update in a simplified manner; comparing the differences between 2016 and 2007 CNS tumors classifications with brief description of important molecular markers and finally utility as well as challenges of this classification.

The conservation and sustainable use of marine resources is a highlighted goal on a growing number of national and international policy agendas. Unfortunately, efforts to assess progress, as well as to strategically plan and prioritize new marine conservation measures, have been hampered by the lack of a detailed, comprehensive biogeographic system to classify the oceans. Here we report on a new global system for coastal and shelf areas: the Marine Ecoregions of the World, or MEOW, a nested system of 12 realms, 62 provinces, and 232 ecoregions. This system provides considerably better spatial resolution than earlier global systems, yet it preserves many common elements and can be cross-referenced to many regional biogeographic classifications. The designation of terrestrial ecoregions has revolutionized priority setting and planning for terrestrial conservation; we anticipate similar benefits from the use of a coherent and credible marine system.

Genomic technologies offer the promise of a comprehensive understanding of cancer. These technologies are being used to characterize tumours at the molecular level, and several clinical successes have shown that such information can guide the design of drugs targeted to a relevant molecule. One of the main barriers to further progress is identifying the biological indicators, or biomarkers, of cancer that predict who will benefit from a particular targeted therapy.

During the past several decades, high numbers of gelatinous Zooplankton species have been reported in many estuarine and coastal ecosystems. Coupled with media-driven public perception, a paradigm has evolved in which the global ocean ecosystems are thought to he heading toward being dominated by “nuisance” jellyfish. We question this current paradigm by presenting a broad overview of gelatinous Zooplankton in a historical context to develop the hypothesis that population changes reflect the human-mediated alteration of global ocean ecosystems. To this end, we synthesize information related to the evolutionary context of contemporary gelatinous Zooplankton blooms, the human frame of reference for changes in gelatinous Zooplankton populations, and whether sufficient data are available to have established the paradigm. We conclude that the current paradigm in which it is believed that there has been a global increase in gelatinous Zooplankton is unsubstantiated, and we develop a strategy for addressing the critical questions about long-term, human-related changes in the sea as they relate to gelatinous Zooplankton blooms.

The scientific literature contains an abundance of prediction models for hospital readmissions. However, no review has yet synthesized their predictors across various patient populations. Therefore, our aim was to examine predictors of hospital readmissions across 13 patient populations. An overview of systematic reviews was combined with a meta-analytical approach. Two thousand five hundred four different predictors were categorized using common ontologies to pool and examine their odds ratios and frequencies of use in prediction models across and within different patient populations. Twenty-eight systematic reviews with 440 primary studies were included. Numerous predictors related to prior use of healthcare services (odds ratio; 95% confidence interval: 1.64; 1.42–1.89), diagnoses (1.41; 1.31–1.51), health status (1.35; 1.20–1.52), medications (1.28; 1.13–1.44), administrative information about the index hospitalization (1.23; 1.14–1.33), clinical procedures (1.20; 1.07–1.35), laboratory results (1.18; 1.11–1.25), demographic information (1.10; 1.06–1.14), and socioeconomic status (1.07; 1.02–1.11) were analyzed. Diagnoses were frequently used (in 37.38%) and displayed large effect sizes across all populations. Prior use of healthcare services showed the largest effect sizes but were seldomly used (in 2.57%), whereas demographic information (in 13.18%) was frequently used but displayed small effect sizes. Diagnoses and patients’ prior use of healthcare services showed large effects both across and within different populations. These results can serve as a foundation for future prediction modeling.

The World Register of Marine Species is an over 90% complete open-access inventory of all marine species names. Here we illustrate the scale of the problems with species names, synonyms, and their classification, and describe how WoRMS publishes online quality assured information on marine species. Within WoRMS, over 100 global, 12 regional and 4 thematic species databases are integrated with a common taxonomy. Over 240 editors from 133 institutions and 31 countries manage the content. To avoid duplication of effort, content is exchanged with 10 external databases. At present WoRMS contains 460,000 taxonomic names (from Kingdom to subspecies), 368,000 species level combinations of which 215,000 are currently accepted marine species names, and 26,000 related but non-marine species. Associated information includes 150,000 literature sources, 20,000 images, and locations of 44,000 specimens. Usage has grown linearly since its launch in 2007, with about 600,000 unique visitors to the website in 2011, and at least 90 organisations from 12 countries using WoRMS for their data management. By providing easy access to expert-validated content, WoRMS improves quality control in the use of species names, with consequent benefits to taxonomy, ecology, conservation and marine biodiversity research and management. The service manages information on species names that would otherwise be overly costly for individuals, and thus minimises errors in the application of nomenclature standards. WoRMS' content is expanding to include host-parasite relationships, additional literature sources, locations of specimens, images, distribution range, ecological, and biological data. Species are being categorised as introduced (alien, invasive), of conservation importance, and on other attributes. These developments have a multiplier effect on its potential as a resource for biodiversity research and management. As a consequence of WoRMS, we are witnessing improved communication within the scientific community, and anticipate increased taxonomic efficiency and quality control in marine biodiversity research and management.