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Inter‐individual variation in phenotypic traits has long been considered as "noise" rather than meaningful phenotypic variation, with biological studies almost exclusively generating and reporting average responses for populations and species' aver‐ age responses. Here, we compare the use of an individual approach in the investigation of extracellular acid-base regulation by the purple sea urchin Paracentrotus lividus challenged with elevated pCO2 and temperature conditions, with a more traditional approach which generates and formally compares mean values. We detected a high level of inter‐individual variation in acid-base regulation parameters both within and between treatments. Comparing individual and mean values for the first (apparent) dissociation constant of the coelomic fluid for individual sea urchins resulted in substantially different (calculated) acid-base parameters, and models with stronger statistical support. While the approach using means showed that coelomic pCO2 was influenced by seawater pCO2 and temperature combined, the individual approach indicated that it was in fact seawater temperature in isolation that had a significant effect on coelomic pCO2. On the other hand, coelomic [HCO3−] appeared to be primarily affected by seawater pCO2, and less by seawater temperature, irrespective of the approach adopted. As a consequence, we suggest that individual variation in physiological traits needs to be considered, and where appropriate taken into ac‐ count, in global change biology studies. It could be argued that an approach reliant on mean values is a "procedural error." It produces an artefact, that is, a population's mean phenotype. While this may allow us to conduct relatively simple statistical analyses, it will not in all cases reflect, or take into account, the degree of (physiological) diversity present in natural populations.

The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10^−8). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.

Salmonella Typhimurium ST313 causes invasive nontyphoidal Salmonella (iNTS) disease in sub-Saharan Africa, targeting susceptible HIV + , malarial or malnourished individuals. An in-depth genomic comparison between the ST313 isolate D23580, and the well-characterized ST19 isolate 4/74 that causes gastroenteritis across the globe, revealed extensive synteny. To understand how the 856 nucleotide variations generated phenotypic differences, we devised a large-scale experimental approach that involved the global gene expression analysis of strains D23580 and 4/74 grown in sixteen infection-relevant growth conditions. Comparison of transcriptional patterns identified virulence and metabolic genes that were differentially expressed between D23580 versus 4/74, many of which were validated by proteomics. We also uncovered the S. Typhimurium D23580 and 4/74 genes that showed expression differences during infection of murine macrophages. Our comparative transcriptomic data are presented in a new enhanced version of the Salmonella expression compendium SalComD23580: bioinf.gen.tcd.ie/cgi-bin/salcom_v2.pl . We discovered that the ablation of melibiose utilization was caused by 3 independent SNP mutations in D23580 that are shared across ST313 lineage 2, suggesting that the ability to catabolise this carbon source has been negatively selected during ST313 evolution. The data revealed a novel plasmid maintenance system involving a plasmid-encoded CysS cysteinyl-tRNA synthetase, highlighting the power of large-scale comparative multi-condition analyses to pinpoint key phenotypic differences between bacterial pathovariants.

The Stratosphere–troposphere Processes And their Role in Climate (SPARC) Quasi-Biennial Oscillation initiative (QBOi) aims to improve the fidelity of tropical stratospheric variability in general circulation and Earth system models by conducting coordinated numerical experiments and analysis. In the equatorial stratosphere, the QBO is the most conspicuous mode of variability. Five coordinated experiments have therefore been designed to (i) evaluate and compare the verisimilitude of modelled QBOs under present-day conditions, (ii) identify robustness (or alternatively the spread and uncertainty) in the simulated QBO response to commonly imposed changes in model climate forcings (e.g. a doubling of CO2 amounts), and (iii) examine model dependence of QBO predictability. This paper documents these experiments and the recommended output diagnostics. The rationale behind the experimental design and choice of diagnostics is presented. To facilitate scientific interpretation of the results in other planned QBOi studies, consistent descriptions of the models performing each experiment set are given, with those aspects particularly relevant for simulating the QBO tabulated for easy comparison.

Aquistore is a deep saline CO2 storage research and demonstration project located near Estevan, Saskatchewan where CO2 is transported via pipeline and injected into a sandstone reservoir ∼3200 m below the surface. A pre-injection time-lapse analysis performed on two sparse 3D seismic datasets was used to characterise the background time-lapse signal-to-noise level at the storage site. The time-lapse analysis revealed that the lowest global nRMS was 0.07 which was taken to represent the level above which CO2 would be detectable in the reservoir. We investigate the conditions under which the injected CO2 can be detected above the defined minimum noise level through Gassmann fluid substitution and 3D seismic forward modelling. Additionally, Wave Unix was used to simulate the seismic response of the reservoir due to the injected CO2 by generating the synthetic surface reflection seismic data from an explosive surface P-wave source. We generated noise-free synthetic seismograms for the baseline model as well as for the 2-phase fluid replacement of brine with CO2 for CO2 concentrations up to 100% within the target zone – the monitors. The baseline and monitor traces from the 3D seismic survey at Aquistore are used as the noise traces in this study, and were added to their respective baseline and monitor synthetic traces. The nRMS within the reservoir was then computed for the noisy baseline and various noisy monitor surveys and was used in the assessment of the limitation to the detection of the injected CO2 in the reservoir under the background noise level at the site. We are able to conclude that the time-lapse repeatability will not limit the ability to monitor the CO2 induced changes in the reservoir at the Aquistore storage site.

Recent FDA guidance on adaptive clinical trial designs defines bias as "a systematic tendency for the estimate of treatment effect to deviate from its true value", and states that it is desirable to obtain and report estimates of treatment effects that reduce or remove this bias. In many adaptive designs, the conventional end-of-trial point estimates of the treatment effects are prone to bias, because they do not take into account the potential and realised trial adaptations. While much of the methodological developments on adaptive designs have tended to focus on control of type I error rates and power considerations, in contrast the question of biased estimation has received less attention. This article addresses this issue by providing a comprehensive overview of proposed approaches to remove or reduce the potential bias in point estimation of treatment effects in an adaptive design, as well as illustrating how to implement them. We first discuss how bias can affect standard estimators and critically assess the negative impact this can have. We then describe and compare proposed unbiased and bias-adjusted estimators of treatment effects for different types of adaptive designs. Furthermore, we illustrate the computation of different estimators in practice using a real trial example. Finally, we propose a set of guidelines for researchers around the choice of estimators and the reporting of estimates following an adaptive design.

Commercial airlines began operations over polar routes in 1999 with a small number of proving flights. By 2014 the number had increased to in excess of 12,000 flights per year, and further increases are expected. For safe operations, the aircraft have to be able to communicate with air traffic control centres at all times. This is achieved by VHF links whilst within range of the widespread network of ground stations, and by HF radio in remote areas such as the Polar regions, the North Atlantic and Pacific where VHF ground infrastructure does not exist. Furthermore, the Russian side of the pole only has HF capability. This has created a demand for improved HF nowcasting and forecasting procedures to support the polar operations, which are the subject of this paper.

Commercial airlines began operations over polar routes in 1999 with a small number of proving flights. By 2014 the number had increased to in excess of 12,000 flights per year, and further increases are expected. For safe operations, the aircraft have to be able to communicate with air traffic control centres at all times. This is achieved by VHF links whilst within range of the widespread network of ground stations, and is by HF radio in remote areas such as the Polar regions, the North Atlantic and Pacific where VHF ground infrastructure does not exist. Furthermore, the Russian side of the pole only has HF capability. Researchers at the University of Leicester and at Lancaster University have developed various models (outlined below) that can be employed in HF radio propagation predictions. It is anticipated that these models will form the basis of an HF forecasting and nowcasting service for the airline industry. Propagation coverage predictions make use of numerical ray tracing to estimate the ray paths through a model ionosphere. Initially, a background ionospheric model is produced, which is then perturbed to include the various ionospheric features prevalent at high latitudes (in particular patches, arcs, auroral zone irregularities and the mid-latitude trough) that significantly affect the propagation of the radio signals. The approach that we are currently adopting is to start with the IRI and to perturb this based on measurements made near to the time and area of interest to form the basis of the background ionospheric model. This is then further perturbed to include features such as the convecting patches, the parameters of which may also be informed by measurements. A significant problem is the high variability of the high latitude ionosphere, and the relative scarcity of real-time measurements over the region. Real time measurements that we will use as the basis for perturbing the IRI include ionosonde soundings from, e.g. the GIRO database, and TEC measurements from the IGS network. Real-time modelling of HF radiowave absorption in the D-region ionosphere is also included. The geostationary GOES satellites provide real-time information on X-ray flux (causing shortwave fadeout during solar flares) and the flux of precipitating energetic protons which correlates strongly with Polar Cap Absorption (PCA). Real-time solar wind and interplanetary magnetic field measurements from the ACE or DSCOVR spacecraft provide geomagnetic index estimates used to model the location of both auroral absorption (on a probabilistic basis) and the proton rigidity cutoff boundary that defines the latitudinal extent of PCA during solar proton events (SPE). Empirical climatological models have been uniquely adapted to assimilate recent measurements of cosmic noise absorption (at 30 MHz) from a large array of riometers in Canada and Scandinavia. The model parameters are continuously optimised and updated to account for regional and temporal variations in ionospheric composition (and hence HF absorption rate (dB/km)) that can change significantly during the course of an SPE, for example. Real-time optimisation during SPE can also improve estimates of the proton rigidity cutoff and improve the modelled ionospheric response function absorption vs. zenith angle) at twilight.

The mid-Piacenzian is known as a period of relative warmth when compared to the present day. A comprehensive understanding of conditions during the Piacenzian serves as both a conceptual model and a source for boundary conditions as well as means of verification of global climate model experiments. In this paper we present the PRISM4 reconstruction, a paleoenvironmental reconstruction of the mid-Piacenzian ( ∼ 3 Ma) containing data for paleogeography, land and sea ice, sea-surface temperature, vegetation, soils, and lakes. Our retrodicted paleogeography takes into account glacial isostatic adjustments and changes in dynamic topography. Soils and lakes, both significant as land surface features, are introduced to the PRISM reconstruction for the first time. Sea-surface temperature and vegetation reconstructions are unchanged but now have confidence assessments. The PRISM4 reconstruction is being used as boundary condition data for the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2) experiments.