Post-Brexit immigration policy: reconciling public perceptions with economic evidence

Existing research shows consistently high levels of concern among people in the UK over the scale of immigration and its impact on jobs, wages and services. At the same time, that same body of research does not provide much in the way of detail about the nature of these concerns. This is partly because much of the data is from opinion polls which say little about the priorities and perspectives that underlie the aggregate numbers. Moreover, very little research has been carried out on what new immigration policies the British public would like to see once the UK leaves the EU and free movement ends. Our research for this report aims to fill these gaps by providing evidence about how people use and understand information about economic impacts of immigration, and what they might wish to see from new, post-Brexit, policies

Mathematical Reasoning: Evaluation report and executive summary

The Mathematical Reasoning programme aims to improve the mathematical attainment of pupils in Year 2 by developing their understanding of the logical principles underlying maths. The programme was previously tested in an EEF-funded efficacy trial (Improving Numeracy and Literacy in Key Stage 1) which suggested that it had a positive impact. The efficacy trial examined the programme under developer-led conditions. This report describes a follow-up effectiveness trial which examined the impact of the programme under everyday conditions in a large number of schools and with less involvement from the original developer. Mathematical Reasoning lessons focus on developing pupils’ understanding of number and quantitative reasoning. They cover principles such as place value and the inverse relation between addition and subtraction. The programme consists of ten units delivered to pupils by their teachers as part of their usual mathematics lessons. It is designed to be taught over a 12- to 15-week period, with each unit taking approximately one hour. Learning is supported by online games, which can be used by pupils both at school and at home. The intervention was originally developed by a team at the University of Oxford, led by Professor Terezinha Nunes and Professor Peter Bryant. The National Centre for Excellence in the Teaching of Mathematics (NCETM) contributed to the development of the training model used in this trial and coordinated the delivery of the training through the network of Maths Hubs (partnerships of schools created to lead improvements to maths education). In this trial, the teacher training was delivered using a ‘train-the-trainers’ model through eight Maths Hubs. Each Maths Hub was asked to recruit two ‘Work Group Leads’. The University of Oxford programme developers trained these Work Group Leads who then trained the teachers in participating schools to deliver the programme. To prepare them to train the teachers, Work Group Leads received an initial day of training, used the materials in their own teaching, and then received a further two days’ training. Teachers delivering the programme then received one day of training from a Work Group Lead as well as a visit from the Work Group Lead during programme delivery. They were also able to seek additional support directly from the Work Group Lead or ask questions through an online Maths Hub community. The impact of the programme on maths attainment was evaluated using a randomised controlled trial involving 160 schools. Schools were randomly allocated either to receive Mathematical Reasoning or to be in the control group, the latter having the opportunity to take part in the programme in the following school year. A process evaluation used observations of training sessions, teacher interviews, lesson observations, and an online survey of treatment and control schools to examine implementation and the factors influencing impact. The trial began in August 2015 and analysis and reporting of the trial completed in December 2018. The project was co-funded by the Worshipful Company of Actuaries

Developing a Simplified Consent Form for Biobanking

BACKGROUND: Consent forms have lengthened over time and become harder for participants to understand. We sought to demonstrate the feasibility of creating a simplified consent form for biobanking that comprises the minimum information necessary to meet ethical and regulatory requirements. We then gathered preliminary data concerning its content from hypothetical biobank participants. METHODOLOGY/PRINCIPAL FINDINGS: We followed basic principles of plain-language writing and incorporated into a 2-page form (not including the signature page) those elements of information required by federal regulations and recommended by best practice guidelines for biobanking. We then recruited diabetes patients from community-based practices and randomized half (n = 56) to read the 2-page form, first on paper and then a second time on a tablet computer. Participants were encouraged to use "More information" buttons on the electronic version whenever they had questions or desired further information. These buttons led to a series of "Frequently Asked Questions" (FAQs) that contained additional detailed information. Participants were asked to identify specific sentences in the FAQs they thought would be important if they were considering taking part in a biorepository. On average, participants identified 7 FAQ sentences as important (mean 6.6, SD 14.7, range: 0-71). No one sentence was highlighted by a majority of participants; further, 34 (60.7%) participants did not highlight any FAQ sentences. CONCLUSIONS: Our preliminary findings suggest that our 2-page form contains the information that most prospective participants identify as important. Combining simplified forms with supplemental material for those participants who desire more information could help minimize consent form length and complexity, allowing the most substantively material information to be better highlighted and enabling potential participants to read the form and ask questions more effectively

Eukaryotic Evolutionary Transitions Are Associated with Extreme Codon Bias in Functionally-Related Proteins

Codon bias in the genome of an organism influences its phenome by changing the speed and efficiency of mRNA translation and hence protein abundance. We hypothesized that differences in codon bias, either between-species differences in orthologous genes, or within-species differences between genes, may play an evolutionary role. To explore this hypothesis, we compared the genome-wide codon bias in six species that occupy vital positions in the Eukaryotic Tree of Life. We acquired the entire protein coding sequences for these organisms, computed the codon bias for all genes in each organism and explored the output for relationships between codon bias and protein function, both within- and between-lineages. We discovered five notable coordinated patterns, with extreme codon bias most pronounced in traits considered highly characteristic of a given lineage. Firstly, the Homo sapiens genome had stronger codon bias for DNA-binding transcription factors than the Saccharomyces cerevisiae genome, whereas the opposite was true for ribosomal proteins – perhaps underscoring transcriptional regulation in the origin of complexity. Secondly, both mammalian species examined possessed extreme codon bias in genes relating to hair – a tissue unique to mammals. Thirdly, Arabidopsis thaliana showed extreme codon bias in genes implicated in cell wall formation and chloroplast function – which are unique to plants. Fourthly, Gallus gallus possessed strong codon bias in a subset of genes encoding mitochondrial proteins – perhaps reflecting the enhanced bioenergetic efficiency in birds that co-evolved with flight. And lastly, the G. gallus genome had extreme codon bias for the Ciliary Neurotrophic Factor – which may help to explain their spontaneous recovery from deafness. We propose that extreme codon bias in groups of genes that encode functionally related proteins has a pathway-level energetic explanation

Nucleotide and phylogenetic analyses of the Chlamydia trachomatis ompA gene indicates it is a hotspot for mutation

<p>Abstract</p> <p>Background</p> <p>Serovars of the human pathogen <it>Chlamydia trachomatis </it>occupy one of three specific tissue niches. Genomic analyses indicate that the serovars have a phylogeny congruent with their pathobiology and have an average substitution rate of less than one nucleotide per kilobase. In contrast, the gene that determines serovar specificity, <it>ompA</it>, has a phylogenetic association that is not congruent with tissue tropism and has a degree of nucleotide variability much higher than other genomic loci. The <it>ompA </it>gene encodes the major surface-exposed antigenic determinant, and the observed nucleotide diversity at the <it>ompA </it>locus is thought to be due to recombination and host immune selection pressure. The possible contribution of a localized increase in mutation rate, however, has not been investigated.</p> <p>Results</p> <p>Nucleotide diversity and phylogenetic relationships of the five constant and four variable domains of the <it>ompA </it>gene, as well as several loci surrounding <it>ompA</it>, were examined for each serovar. The loci flanking the <it>ompA </it>gene demonstrated that nucleotide diversity increased monotonically as <it>ompA </it>is approached and that their gene trees are not congruent with either <it>ompA </it>or tissue tropism. The variable domains of the <it>ompA </it>gene had a very high level of non-synonymous change, which is expected as these regions encode the surface-exposed epitopes and are under positive selection. However, the synonymous changes are clustered in the variable regions compared to the constant domains; if hitchhiking were to account for the increase in synonymous changes, these substitutions should be more evenly distributed across the gene. Recombination also cannot entirely account for this increase as the phylogenetic relationships of the constant and variable domains are congruent with each other.</p> <p>Conclusions</p> <p>The high number of synonymous substitutions observed within the variable domains of <it>ompA </it>appears to be due to an increased mutation rate within this region of the genome, whereas the increase in nucleotide substitution rate and the lack of phylogenetic congruence in the regions flanking <it>ompA </it>are characteristic motifs of gene conversion. Together, the increased mutation rate in the <it>ompA </it>gene, in conjunction with gene conversion and positive selection, results in a high degree of variability that promotes host immune evasion.</p

Structure-Based Predictive Models for Allosteric Hot Spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues

Impact of renal impairment on atrial fibrillation: ESC-EHRA EORP-AF Long-Term General Registry

Background: Atrial fibrillation (AF) and renal impairment share a bidirectional relationship with important pathophysiological interactions. We evaluated the impact of renal impairment in a contemporary cohort of patients with AF. Methods: We utilised the ESC-EHRA EORP-AF Long-Term General Registry. Outcomes were analysed according to renal function by CKD-EPI equation. The primary endpoint was a composite of thromboembolism, major bleeding, acute coronary syndrome and all-cause death. Secondary endpoints were each of these separately including ischaemic stroke, haemorrhagic event, intracranial haemorrhage, cardiovascular death and hospital admission. Results: A total of 9306 patients were included. The distribution of patients with no, mild, moderate and severe renal impairment at baseline were 16.9%, 49.3%, 30% and 3.8%, respectively. AF patients with impaired renal function were older, more likely to be females, had worse cardiac imaging parameters and multiple comorbidities. Among patients with an indication for anticoagulation, prescription of these agents was reduced in those with severe renal impairment, p&nbsp;&lt;.001. Over 24&nbsp;months, impaired renal function was associated with significantly greater incidence of the primary composite outcome and all secondary outcomes. Multivariable Cox regression analysis demonstrated an inverse relationship between eGFR and the primary outcome (HR 1.07 [95% CI, 1.01–1.14] per 10&nbsp;ml/min/1.73&nbsp;m2 decrease), that was most notable in patients with eGFR &lt;30&nbsp;ml/min/1.73&nbsp;m2 (HR 2.21 [95% CI, 1.23–3.99] compared to eGFR ≥90&nbsp;ml/min/1.73&nbsp;m2). Conclusion: A significant proportion of patients with AF suffer from concomitant renal impairment which impacts their overall management. Furthermore, renal impairment is an independent predictor of major adverse events including thromboembolism, major bleeding, acute coronary syndrome and all-cause death in patients with AF

Clinical complexity and impact of the ABC (Atrial fibrillation Better Care) pathway in patients with atrial fibrillation: a report from the ESC-EHRA EURObservational Research Programme in AF General Long-Term Registry

Background: Clinical complexity is increasingly prevalent among patients with atrial fibrillation (AF). The ‘Atrial fibrillation Better Care’ (ABC) pathway approach has been proposed to streamline a more holistic and integrated approach to AF care; however, there are limited data on its usefulness among clinically complex patients. We aim to determine the impact of ABC pathway in a contemporary cohort of clinically complex AF patients. Methods: From the ESC-EHRA EORP-AF General Long-Term Registry, we analysed clinically complex AF patients, defined as the presence of frailty, multimorbidity and/or polypharmacy. A K-medoids cluster analysis was performed to identify different groups of clinical complexity. The impact of an ABC-adherent approach on major outcomes was analysed through Cox-regression analyses and delay of event (DoE) analyses. Results: Among 9966 AF patients included, 8289 (83.1%) were clinically complex. Adherence to the ABC pathway in the clinically complex group reduced the risk of all-cause death (adjusted HR [aHR]: 0.72, 95%CI 0.58–0.91), major adverse cardiovascular events (MACEs; aHR: 0.68, 95%CI 0.52–0.87) and composite outcome (aHR: 0.70, 95%CI: 0.58–0.85). Adherence to the ABC pathway was associated with a significant reduction in the risk of death (aHR: 0.74, 95%CI 0.56–0.98) and composite outcome (aHR: 0.76, 95%CI 0.60–0.96) also in the high-complexity cluster; similar trends were observed for MACEs. In DoE analyses, an ABC-adherent approach resulted in significant gains in event-free survival for all the outcomes investigated in clinically complex patients. Based on absolute risk reduction at 1 year of follow-up, the number needed to treat for ABC pathway adherence was 24 for all-cause death, 31 for MACEs and 20 for the composite outcome. Conclusions: An ABC-adherent approach reduces the risk of major outcomes in clinically complex AF patients. Ensuring adherence to the ABC pathway is essential to improve clinical outcomes among clinically complex AF patients