Algebraic conformal quantum field theory in perspective

Conformal quantum field theory is reviewed in the perspective of Axiomatic, notably Algebraic QFT. This theory is particularly developped in two spacetime dimensions, where many rigorous constructions are possible, as well as some complete classifications. The structural insights, analytical methods and constructive tools are expected to be useful also for four-dimensional QFT.Comment: Review paper, 40 pages. v2: minor changes and references added, so as to match published versio

The role of the RACK1 ortholog Cpc2p in modulating pheromone-induced cell cycle arrest in fission yeast

The detection and amplification of extracellular signals requires the involvement of multiple protein components. In mammalian cells the receptor of activated C kinase (RACK1) is an important scaffolding protein for signal transduction networks. Further, it also performs a critical function in regulating the cell cycle by modulating the G1/S transition. Many eukaryotic cells express RACK1 orthologs, with one example being Cpc2p in the fission yeast Schizosaccharomyces pombe. In contrast to RACK1, Cpc2p has been described to positively regulate, at the ribosomal level, cells entry into M phase. In addition, Cpc2p controls the stress response pathways through an interaction with Msa2p, and sexual development by modulating Ran1p/Pat1p. Here we describe investigations into the role, which Cpc2p performs in controlling the G protein-mediated mating response pathway. Despite structural similarity to Gβ-like subunits, Cpc2p appears not to function at the G protein level. However, upon pheromone stimulation, cells overexpressing Cpc2p display substantial cell morphology defects, disorientation of septum formation and a significantly protracted G1 arrest. Cpc2p has the potential to function at multiple positions within the pheromone response pathway. We provide a mechanistic interpretation of this novel data by linking Cpc2p function, during the mating response, with its previous described interactions with Ran1p/Pat1p. We suggest that overexpressing Cpc2p prolongs the stimulated state of pheromone-induced cells by increasing ste11 gene expression. These data indicate that Cpc2p regulates the pheromone-induced cell cycle arrest in fission yeast by delaying cells entry into S phase

A two-domain elevator mechanism for sodium/proton antiport

Sodium/proton (Na+/H+) antiporters, located at the plasma membrane in every cell, are vital for cell homeostasis1. In humans, their dysfunction has been linked to diseases, such as hypertension, heart failure and epilepsy, and they are well-established drug targets2. The best understood model system for Na+/H+ antiport is NhaA from Escherichia coli1, 3, for which both electron microscopy and crystal structures are available4, 5, 6. NhaA is made up of two distinct domains: a core domain and a dimerization domain. In the NhaA crystal structure a cavity is located between the two domains, providing access to the ion-binding site from the inward-facing surface of the protein1, 4. Like many Na+/H+ antiporters, the activity of NhaA is regulated by pH, only becoming active above pH 6.5, at which point a conformational change is thought to occur7. The only reported NhaA crystal structure so far is of the low pH inactivated form4. Here we describe the active-state structure of a Na+/H+ antiporter, NapA from Thermus thermophilus, at 3 Å resolution, solved from crystals grown at pH 7.8. In the NapA structure, the core and dimerization domains are in different positions to those seen in NhaA, and a negatively charged cavity has now opened to the outside. The extracellular cavity allows access to a strictly conserved aspartate residue thought to coordinate ion binding1, 8, 9 directly, a role supported here by molecular dynamics simulations. To alternate access to this ion-binding site, however, requires a surprisingly large rotation of the core domain, some 20° against the dimerization interface. We conclude that despite their fast transport rates of up to 1,500 ions per second3, Na+/H+ antiporters operate by a two-domain rocking bundle model, revealing themes relevant to secondary-active transporters in general

Garden and landscape-scale correlates of moths of differing conservation status: significant effects of urbanization and habitat diversity

Moths are abundant and ubiquitous in vegetated terrestrial environments and are pollinators, important herbivores of wild plants, and food for birds, bats and rodents. In recent years, many once abundant and widespread species have shown sharp declines that have been cited by some as indicative of a widespread insect biodiversity crisis. Likely causes of these declines include agricultural intensification, light pollution, climate change, and urbanization; however, the real underlying cause(s) is still open to conjecture. We used data collected from the citizen science Garden Moth Scheme (GMS) to explore the spatial association between the abundance of 195 widespread British species of moth, and garden habitat and landscape features, to see if spatial habitat and landscape associations varied for species of differing conservation status. We found that associations with habitat and landscape composition were species-specific, but that there were consistent trends in species richness and total moth abundance. Gardens with more diverse and extensive microhabitats were associated with higher species richness and moth abundance; gardens near to the coast were associated with higher richness and moth abundance; and gardens in more urbanized locations were associated with lower species richness and moth abundance. The same trends were also found for species classified as increasing, declining and vulnerable under IUCN (World Conservation Union) criteria

Within- and across-breed genomic prediction using whole-genome sequence and single nucleotide polymorphism panels

International audienceBackground Currently, genomic prediction in cattle is largely based on panels of about 54k single nucleotide polymorphisms (SNPs). However with the decreasing costs of and current advances in next-generation sequencing technologies, whole-genome sequence (WGS) data on large numbers of individuals is within reach. Availability of such data provides new opportunities for genomic selection, which need to be explored.MethodsThis simulation study investigated how much predictive ability is gained by using WGS data under scenarios with QTL (quantitative trait loci) densities ranging from 45 to 132 QTL/Morgan and heritabilities ranging from 0.07 to 0.30, compared to different SNP densities, with emphasis on divergent dairy cattle breeds with small populations. The relative performances of best linear unbiased prediction (SNP-BLUP) and of a variable selection method with a mixture of two normal distributions (MixP) were also evaluated. Genomic predictions were based on within-population, across-population, and multi-breed reference populations.ResultsThe use of WGS data for within-population predictions resulted in small to large increases in accuracy for low to moderately heritable traits. Depending on heritability of the trait, and on SNP and QTL densities, accuracy increased by up to 31 %. The advantage of WGS data was more pronounced (7 to 92 % increase in accuracy depending on trait heritability, SNP and QTL densities, and time of divergence between populations) with a combined reference population and when using MixP. While MixP outperformed SNP-BLUP at 45 QTL/Morgan, SNP-BLUP was as good as MixP when QTL density increased to 132 QTL/Morgan.ConclusionsOur results show that, genomic predictions in numerically small cattle populations would benefit from a combination of WGS data, a multi-breed reference population, and a variable selection method

Deregressed EBV as the response variable yield more reliable genomic predictions than traditional EBV in pure-bred pigs

<p>Abstract</p> <p>Background</p> <p>Genomic selection can be implemented by a multi-step procedure, which requires a response variable and a statistical method. For pure-bred pigs, it was hypothesised that deregressed estimated breeding values (EBV) with the parent average removed as the response variable generate higher reliabilities of genomic breeding values than EBV, and that the normal, thick-tailed and mixture-distribution models yield similar reliabilities.</p> <p>Methods</p> <p>Reliabilities of genomic breeding values were estimated with EBV and deregressed EBV as response variables and under the three statistical methods, genomic BLUP, Bayesian Lasso and MIXTURE. The methods were examined by splitting data into a reference data set of 1375 genotyped animals that were performance tested before October 2008, and 536 genotyped validation animals that were performance tested after October 2008. The traits examined were daily gain and feed conversion ratio.</p> <p>Results</p> <p>Using deregressed EBV as the response variable yielded 18 to 39% higher reliabilities of the genomic breeding values than using EBV as the response variable. For daily gain, the increase in reliability due to deregression was significant and approximately 35%, whereas for feed conversion ratio it ranged between 18 and 39% and was significant only when MIXTURE was used. Genomic BLUP, Bayesian Lasso and MIXTURE had similar reliabilities.</p> <p>Conclusions</p> <p>Deregressed EBV is the preferred response variable, whereas the choice of statistical method is less critical for pure-bred pigs. The increase of 18 to 39% in reliability is worthwhile, since the reliabilities of the genomic breeding values directly affect the returns from genomic selection.</p

The Genetic Interpretation of Area under the ROC Curve in Genomic Profiling

Genome-wide association studies in human populations have facilitated the creation of genomic profiles which combine the effects of many associated genetic variants to predict risk of disease. The area under the receiver operator characteristic (ROC) curve is a well established measure for determining the efficacy of tests in correctly classifying diseased and non-diseased individuals. We use quantitative genetics theory to provide insight into the genetic interpretation of the area under the ROC curve (AUC) when the test classifier is a predictor of genetic risk. Even when the proportion of genetic variance explained by the test is 100%, there is a maximum value for AUC that depends on the genetic epidemiology of the disease, i.e. either the sibling recurrence risk or heritability and disease prevalence. We derive an equation relating maximum AUC to heritability and disease prevalence. The expression can be reversed to calculate the proportion of genetic variance explained given AUC, disease prevalence, and heritability. We use published estimates of disease prevalence and sibling recurrence risk for 17 complex genetic diseases to calculate the proportion of genetic variance that a test must explain to achieve AUC = 0.75; this varied from 0.10 to 0.74. We provide a genetic interpretation of AUC for use with predictors of genetic risk based on genomic profiles. We provide a strategy to estimate proportion of genetic variance explained on the liability scale from estimates of AUC, disease prevalence, and heritability (or sibling recurrence risk) available as an online calculator

Access to primary care for socio-economically disadvantaged older people in rural areas: a qualitative study

Objective: We aim to explore the barriers to accessing primary care for socio-economically disadvantaged older people in rural areas. Methods: Using a community recruitment strategy, fifteen people over 65 years, living in a rural area, and receiving financial support were recruited for semi-structured interviews. Four focus groups were held with rural health professionals. Interviews and focus groups were audio-recorded and transcribed. Thematic analysis was used to identify barriers to primary care access. Findings: Older people’s experience can be understood within the context of a patient perceived set of unwritten rules or social contract – an individual is careful not to bother the doctor in return for additional goodwill when they become unwell. However, most found it difficult to access primary care due to engaged telephone lines, availability of appointments, interactions with receptionists; breaching their perceived social contract. This left some feeling unwelcome, worthless or marginalised, especially those with high expectations of the social contract or limited resources, skills and/or desire to adapt to service changes Health professionals’ described how rising demands and expectations coupled with service constraints had necessitated service development, such as fewer home visits, more telephone consultations, triaging calls and modifying the appointment system. Conclusion: Multiple barriers to accessing primary care exist for this group. As primary care is re-organised to reduce costs, commissioners and practitioners must not lose sight of the perceived social contract and models of care that form the basis of how many older people interact with the service

Predicting the start week of respiratory syncytial virus outbreaks using real time weather variables

<p>Abstract</p> <p>Background</p> <p>Respiratory Syncytial Virus (RSV), a major cause of bronchiolitis, has a large impact on the census of pediatric hospitals during outbreak seasons. Reliable prediction of the week these outbreaks will start, based on readily available data, could help pediatric hospitals better prepare for large outbreaks.</p> <p>Methods</p> <p>Naïve Bayes (NB) classifier models were constructed using weather data from 1985-2008 considering only variables that are available in real time and that could be used to forecast the week in which an RSV outbreak will occur in Salt Lake County, Utah. Outbreak start dates were determined by a panel of experts using 32,509 records with ICD-9 coded RSV and bronchiolitis diagnoses from Intermountain Healthcare hospitals and clinics for the RSV seasons from 1985 to 2008.</p> <p>Results</p> <p>NB models predicted RSV outbreaks up to 3 weeks in advance with an estimated sensitivity of up to 67% and estimated specificities as high as 94% to 100%. Temperature and wind speed were the best overall predictors, but other weather variables also showed relevance depending on how far in advance the predictions were made. The weather conditions predictive of an RSV outbreak in our study were similar to those that lead to temperature inversions in the Salt Lake Valley.</p> <p>Conclusions</p> <p>We demonstrate that Naïve Bayes (NB) classifier models based on weather data available in real time have the potential to be used as effective predictive models. These models may be able to predict the week that an RSV outbreak will occur with clinical relevance. Their clinical usefulness will be field tested during the next five years.</p