Developmental Contexts and Features of Elite Academy Footoall Players: Coach and Player Perspectives

Player profiling can reap many benefits; through reflective coach-athlete dialogue that produces a profile the athlete has a raised awareness of their own development, while the coach has an opportunity to understand the athlete's viewpoint. In this study, we explored how coaches and players perceived the development features of an elite academy footballer and the contexts in which these features are revealed, in order to develop a player profile to be used for mentoring players. Using a Delphi polling technique, coaches and players experienced a number of ‘rounds’ of expressing their opinions regarding player development contexts and features, ultimately reduced into a consensus. Players and coaches had differing priorities on the key contexts of player development. These contexts, when they reflect the consensus between players and coaches were heavily dominated by ability within the game and training. Personal, social, school, and lifestyle contexts featured less prominently. Although ‘discipline’ was frequently mentioned as an important player development feature, coaches and players disagreed on the importance of ‘training’

Individuals living with lupus: findings from the LUPUS UK Members Survey 2014

Systemic lupus erythematosus (SLE) is a complex and unpredictable disease which varies greatly among patients and has a significant impact on an individual’s daily living and quality of life. A better understanding of the patients’ experiences with the disease is vital to the effective management of the disease. LUPUS UK, a national UK-registered charity supporting people with systemic and discoid lupus, conducted a UK-wide survey of individuals living with lupus in order to provide foundation information to support and identify gaps needing further research. An anonymous survey was sent to 5660 LUPUS UK members in order to obtain demographic, diagnosis, symptom and treatment information. A total of 2527 surveys were returned by 2371 females (mean age 56.9 years, SD 13.6) and 156 males, (mean age 60.9 years, SD 15.7). Individuals reported a mean (SD) time to diagnosis from the first symptom of 6.4 (9.5) years, with 47% (n ¼ 1186) initially being given a different diagnosis prior to lupus. Fatigue/weakness (91%, n ¼ 2299) and joint pain/swelling (77.4%, n ¼ 1957) were the most common symptoms that interfere with daily activities, while 73% (n ¼ 1836) noted having some problems that make them unable to carry out their usual daily activities. Thirty-two per cent (n ¼ 806) were also seeking support beyond traditional pharmacological treatments, such as acupuncture and massage. This study highlights the range and frequency of symptoms difficult to live with on a daily basis and support areas needing further research to improve patients’ well-being

Innovation in the time of SARS-CoV-2: A collaborative journey between NHS clinicians, engineers, academics and industry.

During the pandemic healthcare faced great pressure on the availability of protective equipment. This paper describes the entire novel innovative process of design optimisation, production and deployment of face-visors to NHS frontline workers during SARS-CoV-2 pandemic. The described innovative journey spans collaboration between clinicians and academic colleagues for design to the implementation with industry partners of a face-visor for use in a healthcare setting. It identifies the enablers and barriers to development along with the strategies employed to produce a certified reusable, adjustable, high volume and locally produced face-visor. The article also explores aspects of value, scalability, spread and sustainability all of which are essential features of innovation

Higher resources decrease fluctuating selection during host-parasite coevolution

This is the final version of the article. Available from the publisher via the DOI in this record.We still know very little about how the environment influences coevolutionary dynamics. Here, we investigated both theoretically and empirically how nutrient availability affects the relative extent of escalation of resistance and infectivity (arms race dynamic; ARD) and fluctuating selection (fluctuating selection dynamic; FSD) in experimentally coevolving populations of bacteria and viruses. By comparing interactions between clones of bacteria and viruses both within- and between-time points, we show that increasing nutrient availability resulted in coevolution shifting from FSD, with fluctuations in average infectivity and resistance ranges over time, to ARD. Our model shows that range fluctuations with lower nutrient availability can be explained both by elevated costs of resistance (a direct effect of nutrient availability), and reduced benefits of resistance when population sizes of hosts and parasites are lower (an indirect effect). Nutrient availability can therefore predictably and generally affect qualitative coevolutionary dynamics by both direct and indirect (mediated through ecological feedbacks) effects on costs of resistance.This work was funded by NERC (UK). ABu was supported by the Royal Society and ABe by a the Leverhulme Trust Early Career Fellowship

Deletion of the Polycomb-Group Protein EZH2 Leads to Compromised Self-Renewal and Differentiation Defects in Human Embryonic Stem Cells

Through the histone methyltransferase EZH2, the Polycomb complex PRC2 mediates H3K27me3 and is associated with transcriptional repression. PRC2 regulates cell-fate decisions in model organisms; however, its role in regulating cell differentiation during human embryogenesis is unknown. Here, we report the characterization of $\small \textit{EZH2}$-deficient human embryonic stem cells (hESCs). H3K27me3 was lost upon $\small \textit{EZH2}$ deletion, identifying an essential requirement for EZH2 in methylating H3K27 in hESCs, in contrast to its non-essential role in mouse ESCs. Developmental regulators were derepressed in $\small \textit{EZH2}$-deficient hESCs, and single-cell analysis revealed an unexpected acquisition of lineage-restricted transcriptional programs. $\small \textit{EZH2}$-deficient hESCs show strongly reduced self-renewal and proliferation, thereby identifying a more severe phenotype compared to mouse ESCs. $\small \textit{EZH2}$-deficient hESCs can initiate differentiation toward developmental lineages; however, they cannot fully differentiate into mature specialized tissues. Thus, $\small \textit{EZH2}$ is required for stable ESC self-renewal, regulation of transcriptional programs, and for late-stage differentiation in this model of early human development.Wellcome Trust (Grant ID: WT093736), Biotechnology and Biological Sciences Research Council (Grant ID: BBS/E/B/000C0402), Medical Research Council (DTG Studentships, Grant ID: MR/J003808/1

DNAscan: personal computer compatible NGS analysis, annotation and visualisation.

BACKGROUND: Next Generation Sequencing (NGS) is a commonly used technology for studying the genetic basis of biological processes and it underpins the aspirations of precision medicine. However, there are significant challenges when dealing with NGS data. Firstly, a huge number of bioinformatics tools for a wide range of uses exist, therefore it is challenging to design an analysis pipeline. Secondly, NGS analysis is computationally intensive, requiring expensive infrastructure, and many medical and research centres do not have adequate high performance computing facilities and cloud computing is not always an option due to privacy and ownership issues. Finally, the interpretation of the results is not trivial and most available pipelines lack the utilities to favour this crucial step. RESULTS: We have therefore developed a fast and efficient bioinformatics pipeline that allows for the analysis of DNA sequencing data, while requiring little computational effort and memory usage. DNAscan can analyse a whole exome sequencing sample in 1 h and a 40x whole genome sequencing sample in 13 h, on a midrange computer. The pipeline can look for single nucleotide variants, small indels, structural variants, repeat expansions and viral genetic material (or any other organism). Its results are annotated using a customisable variety of databases and are available for an on-the-fly visualisation with a local deployment of the gene.iobio platform. DNAscan is implemented in Python. Its code and documentation are available on GitHub: https://github.com/KHP-Informatics/DNAscan . Instructions for an easy and fast deployment with Docker and Singularity are also provided on GitHub. CONCLUSIONS: DNAscan is an extremely fast and computationally efficient pipeline for analysis, visualization and interpretation of NGS data. It is designed to provide a powerful and easy-to-use tool for applications in biomedical research and diagnostic medicine, at minimal computational cost. Its comprehensive approach will maximise the potential audience of users, bringing such analyses within the reach of non-specialist laboratories, and those from centres with limited funding available

The two-hour orbit of a binary millisecond X-ray pulsar

Typical radio pulsars are magnetized neutron stars that are born rapidly rotating and slow down as they age on time scales of 10 to 100 million years. However, millisecond radio pulsars spin very rapidly even though many are billions of years old. The most compelling explanation is that they have been "spun up" by the transfer of angular momentum during accretion of material from a companion star in so-called low-mass X-ray binary systems, LMXBs. (LMXBs consist of a neutron star or black hole accreting from a companion less than one solar mass.) The recent detection of coherent X-ray pulsations with a millisecond period from a suspected LMXB system appears to confirm this link. Here we report observations showing that the orbital period of this binary system is two hours, which establishes it as an LMXB. We also find an apparent modulation of the X-ray flux at the orbital period (at the two per cent level), with a broad minimum when the pulsar is behind this low-mass companion star. This system seems closely related to the "black widow" millisecond radio pulsars, which are evaporating their companions through irradiation. It may appear as an eclipsing radio pulsar during periods of X-ray quiescence.Comment: 4 pages with 1 figure. Style files included. Fig. 2 deleted and text revised. To appear in Nature. Press embargo until 18:00 GMT on 1998 July 2

A physics-based machine learning technique rapidly reconstructs the wall-shear stress and pressure fields in coronary arteries

With the global rise of cardiovascular disease including atherosclerosis, there is a high demand or accurate diagnostic tools that can be used during a short consultation. In view of pathology, abnormal blood flow patterns have been demonstrated to be strong predictors of atherosclerotic lesion incidence, location, progression, and rupture. Prediction of patient-specific blood flow patterns can hence enable fast clinical diagnosis. However, the current state of art for the technique is by employing 3D-imaging-based Computational Fluid Dynamics (CFD). The high computational cost renders these methods impractical. In this work, we present a novel method to expedite the reconstruction of 3D pressure and shear stress fields using a combination of a reduced-order CFD modelling technique together with non-linear regression tools from the Machine Learning (ML) paradigm. Specifically, we develop a proof-of-concept automated pipeline that uses randomised perturbations of an atherosclerotic pig coronary artery to produce a large dataset of unique mesh geometries with variable blood flow. A total of 1407 geometries were generated from seven reference arteries and were used to simulate blood flow using the CFD solver Abaqus. This CFD dataset was then post-processed using the mesh-domain common-base Proper Orthogonal Decomposition (cPOD) method to obtain Eigen functions and principal coefficients, the latter of which is a product of the individual mesh flow solutions with the POD Eigenvectors. Being a data-reduction method, the POD enables the data to be represented using only the ten most significant modes, which captures cumulatively greater than 95% of variance of flow features due to mesh variations. Next, the node coordinate data of the meshes were embedded in a two-dimensional coordinate system using the t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm. The reduced dataset for t-SNE coordinates and corresponding vector of POD coefficients were then used to train a Random Forest Regressor (RFR) model. The same methodology was applied to both the volumetric pressure solution and the wall shear stress. The predicted pattern of blood pressure, and shear stress in unseen arterial geometries were compared with the ground truth CFD solutions on 'unseen' meshes. The new method was able to reliably reproduce the 3D coronary artery haemodynamics in less than 10 seconds