The c-kit Ligand, Stem Cell Factor, Can Enhance Innate Immunity Through Effects on Mast Cells

Mast cells are thought to contribute significantly to the pathology and mortality associated with anaphylaxis and other allergic disorders. However, studies using genetically mast cell–deficient WBB6F1-KitW/KitW-v and congenic wild-type (WBB6F1-+/+) mice indicate that mast cells can also promote health, by participating in natural immune responses to bacterial infection. We previously reported that repetitive administration of the c-kit ligand, stem cell factor (SCF), can increase mast cell numbers in normal mice in vivo. In vitro studies have indicated that SCF can also modulate mast cell effector function. We now report that treatment with SCF can significantly improve the survival of normal C57BL/6 mice in a model of acute bacterial peritonitis, cecal ligation and puncture (CLP). Experiments in mast cell–reconstituted WBB6F1-KitW/KitW-v mice indicate that this effect of SCF treatment reflects, at least in part, the actions of SCF on mast cells. Repetitive administration of SCF also can enhance survival in mice that genetically lack tumor necrosis factor (TNF)-α, demonstrating that the ability of SCF treatment to improve survival after CLP does not solely reflect effects of SCF on mast cell– dependent (or –independent) production of TNF-α. These findings identify c-kit and mast cells as potential therapeutic targets for enhancing innate immune responses

A novel synthesis and detection method for cap-associated adenosine modifications in mouse mRNA

A method is described for the detection of certain nucleotide modifications adjacent to the 5' 7-methyl guanosine cap of mRNAs from individual genes. The method quantitatively measures the relative abundance of 2'-O-methyl and N6,2'-O-dimethyladenosine, two of the most common modifications. In order to identify and quantitatify the amounts of N6,2'-O-dimethyladenosine, a novel method for the synthesis of modified adenosine phosphoramidites was developed. This method is a one step synthesis and the product can directly be used for the production of N6,2'-O-dimethyladenosine containing RNA oligonucleotides. The nature of the cap-adjacent nucleotides were shown to be characteristic for mRNAs from individual genes transcribed in liver and testis

The role of place branding and image in the development of sectoral clusters: the case of Dubai

This paper contextualizes how place branding and image influence the development of Dubai’s key sectoral clusters, including the key determinants of growth and success under the impression of Porter’s cluster theory. The approach is exploratory and of a qualitative inductive nature. Data was collected through conducting 21 semi-structured interviews with Dubai’s marketing/communication managers and stakeholders. Findings suggest that Dubai’s traditional clusters, namely, trading, tourism and logistics that have strong place branding and image show strong signs of success owing to Dubai’s geographical location (i.e., physical conditions). Among the new clusters, the financial sector is also benefitting from place branding. The results suggest that the success of traditional clusters have a positive spill over effect on the new clusters, in particular on construction and real estate. For policy makers it is worth to note that the recent success of the financial services cluster in Dubai will have positive impact on both, the traditional as well new clusters. The marketing and brand communication managers must consider the correlation and interplay of strength of activities amongst trading, tourism and logistics clusters and its implication while undertaking place branding for clients in their sector

Evaluation in artificial intelligence: From task-oriented to ability-oriented measurement

The final publication is available at Springer via http://dx.doi.org/ 10.1007/s10462-016-9505-7.The evaluation of artificial intelligence systems and components is crucial for the progress of the discipline. In this paper we describe and critically assess the different ways AI systems are evaluated, and the role of components and techniques in these systems. We first focus on the traditional task-oriented evaluation approach. We identify three kinds of evaluation: human discrimination, problem benchmarks and peer confrontation. We describe some of the limitations of the many evaluation schemes and competitions in these three categories, and follow the progression of some of these tests. We then focus on a less customary (and challenging) ability-oriented evaluation approach, where a system is characterised by its (cognitive) abilities, rather than by the tasks it is designed to solve. We discuss several possibilities: the adaptation of cognitive tests used for humans and animals, the development of tests derived from algorithmic information theory or more integrated approaches under the perspective of universal psychometrics. We analyse some evaluation tests from AI that are better positioned for an ability-oriented evaluation and discuss how their problems and limitations can possibly be addressed with some of the tools and ideas that appear within the paper. Finally, we enumerate a series of lessons learnt and generic guidelines to be used when an AI evaluation scheme is under consideration.I thank the organisers of the AEPIA Summer School On Artificial Intelligence, held in September 2014, for giving me the opportunity to give a lecture on 'AI Evaluation'. This paper was born out of and evolved through that lecture. The information about many benchmarks and competitions discussed in this paper have been contrasted with information from and discussions with many people: M. Bedia, A. Cangelosi, C. Dimitrakakis, I. GarcIa-Varea, Katja Hofmann, W. Langdon, E. Messina, S. Mueller, M. Siebers and C. Soares. Figure 4 is courtesy of F. Martinez-Plumed. Finally, I thank the anonymous reviewers, whose comments have helped to significantly improve the balance and coverage of the paper. This work has been partially supported by the EU (FEDER) and the Spanish MINECO under Grants TIN 2013-45732-C4-1-P, TIN 2015-69175-C4-1-R and by Generalitat Valenciana PROMETEOII2015/013.José Hernández-Orallo (2016). Evaluation in artificial intelligence: From task-oriented to ability-oriented measurement. 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The SPECTRUM Consortium : A new UK Prevention Research Partnership consortium focussed on the commercial determinants of health, the prevention of non-communicable diseases, and the reduction of health inequalities

The main causes of non-communicable diseases (NCDs), health inequalities and health inequity include consumption of unhealthy commodities such as tobacco, alcohol and/or foods high in fat, salt and/or sugar. These exposures are preventable, but the commodities involved are highly profitable. The economic interests of 'Unhealthy Commodity Producers' (UCPs) often conflict with health goals but their role in determining health has received insufficient attention. In order to address this gap, a new research consortium has been established. This open letter introduces the SPECTRUM ( S haping Public h Ealth poli Cies To Reduce ineq Ualities and har M) Consortium: a multi-disciplinary group comprising researchers from 10 United Kingdom (UK) universities and overseas, and partner organisations including three national public health agencies in Great Britain (GB), five multi-agency alliances and two companies providing data and analytic support. Through eight integrated work packages, the Consortium seeks to provide an understanding of the nature of the complex systems underlying the consumption of unhealthy commodities, the role of UCPs in shaping these systems and influencing health and policy, the role of systems-level interventions, and the effectiveness of existing and emerging policies. Co-production is central to the Consortium's approach to advance research and achieve meaningful impact and we will involve the public in the design and delivery of our research. We will also establish and sustain mutually beneficial relationships with policy makers, alongside our partners, to increase the visibility, credibility and impact of our evidence. The Consortium's ultimate aim is to achieve meaningful health benefits for the UK population by reducing harm and inequalities from the consumption of unhealthy commodities over the next five years and beyond

Phase 3 trials of ixekizumab in moderate-to-severe plaque psoriasis

BACKGROUND Two phase 3 trials (UNCOVER-2 and UNCOVER-3) showed that at 12 weeks of treatment, ixekizumab, a monoclonal antibody against interleukin-17A, was superior to placebo and etanercept in the treatment of moderate-to-severe psoriasis. We report the 60-week data from the UNCOVER-2 and UNCOVER-3 trials, as well as 12-week and 60-week data from a third phase 3 trial, UNCOVER-1. METHODS We randomly assigned 1296 patients in the UNCOVER-1 trial, 1224 patients in the UNCOVER-2 trial, and 1346 patients in the UNCOVER-3 trial to receive subcutaneous injections of placebo (placebo group), 80 mg of ixekizumab every 2 weeks after a starting dose of 160 mg (2-wk dosing group), or 80 mg of ixekizumab every 4 weeks after a starting dose of 160 mg (4-wk dosing group). Additional cohorts in the UNCOVER-2 and UNCOVER-3 trials were randomly assigned to receive 50 mg of etanercept twice weekly. At week 12 in the UNCOVER-3 trial, the patients entered a long-term extension period during which they received 80 mg of ixekizumab every 4 weeks through week 60; at week 12 in the UNCOVER-1 and UNCOVER-2 trials, the patients who had a response to ixekizumab (defined as a static Physicians Global Assessment [sPGA] score of 0 [clear] or 1 [minimal psoriasis]) were randomly reassigned to receive placebo, 80 mg of ixekizumab every 4 weeks, or 80 mg of ixekizumab every 12 weeks through week 60. Coprimary end points were the percentage of patients who had a score on the sPGA of 0 or 1 and a 75% or greater reduction from baseline in Psoriasis Area and Severity Index (PASI 75) at week 12. RESULTS In the UNCOVER-1 trial, at week 12, the patients had better responses to ixekizumab than to placebo; in the 2-wk dosing group, 81.8% had an sPGA score of 0 or 1 and 89.1% had a PASI 75 response; in the 4-wk dosing group, the respective rates were 76.4% and 82.6%; and in the placebo group, the rates were 3.2% and 3.9% (P<0.001 for all comparisons of ixekizumab with placebo). In the UNCOVER-1 and UNCOVER-2 trials, among the patients who were randomly reassigned at week 12 to receive 80 mg of ixekizumab every 4 weeks, 80 mg of ixekizumab every 12 weeks, or placebo, an sPGA score of 0 or 1 was maintained by 73.8%, 39.0%, and 7.0% of the patients, respectively. Patients in the UNCOVER-3 trial received continuous treatment of ixekizumab from weeks 0 through 60, and at week 60, at least 73% had an sPGA score of 0 or 1 and at least 80% had a PASI 75 response. Adverse events reported during ixekizumab use included neutropenia, candidal infections, and inflammatory bowel disease. CONCLUSIONS In three phase 3 trials involving patients with psoriasis, ixekizumab was effective through 60 weeks of treatment. As with any treatment, the benefits need to be weighed against the risks of adverse events. The efficacy and safety of ixekizumab beyond 60 weeks of treatment are not yet known

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Sensitivity of Pine Island Glacier to observed ocean forcing

We present subannual observations (2009–2014) of a major West Antarctic glacier (Pine Island Glacier) and the neighboring ocean. Ongoing glacier retreat and accelerated ice flow were likely triggered a few decades ago by increased ocean-induced thinning, which may have initiated marine ice-sheet instability. Following a subsequent 60% drop in ocean heat content from early 2012 to late 2013, ice flow slowed, but by < 4%, with flow recovering as the ocean warmed to prior temperatures. During this cold-ocean period, the evolving glacier-bed/ice-shelf system was also in a geometry favorable to stabilization. However, despite a minor, temporary decrease in ice discharge, the basin-wide thinning signal did not change. Thus, as predicted by theory, once marine ice-sheet instability is underway, a single transient high-amplitude ocean cooling has only a relatively minor effect on ice flow. The long-term effects of ocean-temperature variability on ice flow, however, are not yet known

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders