Showing papers by "Keele University published in 2020"

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

Abstract: Objective To review and appraise the validity and usefulness of published and preprint reports of prediction models for diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital with the disease. Design Living systematic review and critical appraisal by the COVID-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group. Data sources PubMed and Embase through Ovid, up to 1 July 2020, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020. Study selection Studies that developed or validated a multivariable covid-19 related prediction model. Data extraction At least two authors independently extracted data using the CHARMS (critical appraisal and data extraction for systematic reviews of prediction modelling studies) checklist; risk of bias was assessed using PROBAST (prediction model risk of bias assessment tool). Results 37 421 titles were screened, and 169 studies describing 232 prediction models were included. The review identified seven models for identifying people at risk in the general population; 118 diagnostic models for detecting covid-19 (75 were based on medical imaging, 10 to diagnose disease severity); and 107 prognostic models for predicting mortality risk, progression to severe disease, intensive care unit admission, ventilation, intubation, or length of hospital stay. The most frequent types of predictors included in the covid-19 prediction models are vital signs, age, comorbidities, and image features. Flu-like symptoms are frequently predictive in diagnostic models, while sex, C reactive protein, and lymphocyte counts are frequent prognostic factors. Reported C index estimates from the strongest form of validation available per model ranged from 0.71 to 0.99 in prediction models for the general population, from 0.65 to more than 0.99 in diagnostic models, and from 0.54 to 0.99 in prognostic models. All models were rated at high or unclear risk of bias, mostly because of non-representative selection of control patients, exclusion of patients who had not experienced the event of interest by the end of the study, high risk of model overfitting, and unclear reporting. Many models did not include a description of the target population (n=27, 12%) or care setting (n=75, 32%), and only 11 (5%) were externally validated by a calibration plot. The Jehi diagnostic model and the 4C mortality score were identified as promising models. Conclusion Prediction models for covid-19 are quickly entering the academic literature to support medical decision making at a time when they are urgently needed. This review indicates that almost all pubished prediction models are poorly reported, and at high risk of bias such that their reported predictive performance is probably optimistic. However, we have identified two (one diagnostic and one prognostic) promising models that should soon be validated in multiple cohorts, preferably through collaborative efforts and data sharing to also allow an investigation of the stability and heterogeneity in their performance across populations and settings. Details on all reviewed models are publicly available at https://www.covprecise.org/. Methodological guidance as provided in this paper should be followed because unreliable predictions could cause more harm than benefit in guiding clinical decisions. Finally, prediction model authors should adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guideline. Systematic review registration Protocol https://osf.io/ehc47/, registration https://osf.io/wy245. Readers’ note This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 3 of the original article published on 7 April 2020 (BMJ 2020;369:m1328). Previous updates can be found as data supplements (https://www.bmj.com/content/369/bmj.m1328/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.

Digital Twin: Enabling Technologies, Challenges and Open Research

Abstract: Digital Twin technology is an emerging concept that has become the centre of attention for industry and, in more recent years, academia. The advancements in industry 4.0 concepts have facilitated its growth, particularly in the manufacturing industry. The Digital Twin is defined extensively but is best described as the effortless integration of data between a physical and virtual machine in either direction. The challenges, applications, and enabling technologies for Artificial Intelligence, Internet of Things (IoT) and Digital Twins are presented. A review of publications relating to Digital Twins is performed, producing a categorical review of recent papers. The review has categorised them by research areas: manufacturing, healthcare and smart cities, discussing a range of papers that reflect these areas and the current state of research. The paper provides an assessment of the enabling technologies, challenges and open research for Digital Twins.

Calculating the sample size required for developing a clinical prediction model.

Abstract: Clinical prediction models aim to predict outcomes in individuals, to inform diagnosis or prognosis in healthcare. Hundreds of prediction models are published in the medical literature each year, yet many are developed using a dataset that is too small for the total number of participants or outcome events. This leads to inaccurate predictions and consequently incorrect healthcare decisions for some individuals. In this article, the authors provide guidance on how to calculate the sample size required to develop a clinical prediction model.

Applications of digital technology in COVID-19 pandemic planning and response

Abstract: Summary With high transmissibility and no effective vaccine or therapy, COVID-19 is now a global pandemic Government-coordinated efforts across the globe have focused on containment and mitigation, with varying degrees of success Countries that have maintained low COVID-19 per-capita mortality rates appear to share strategies that include early surveillance, testing, contact tracing, and strict quarantine The scale of coordination and data management required for effective implementation of these strategies has—in most successful countries—relied on adopting digital technology and integrating it into policy and health care This Viewpoint provides a framework for the application of digital technologies in pandemic management and response, highlighting ways in which successful countries have adopted these technologies for pandemic planning, surveillance, testing, contact tracing, quarantine, and health care

Global epidemiology of gout: prevalence, incidence, treatment patterns and risk factors.

Abstract: Gout is the most common inflammatory arthritis and occurs when hyperuricaemia, sustained elevation of serum urate levels resulting in supersaturation of body tissues with urate, leads to the formation and deposition of monosodium urate crystals in and around the joints. Recent reports of the prevalence and incidence of gout vary widely according to the population studied and methods employed but range from a prevalence of <1% to 6.8% and an incidence of 0.58–2.89 per 1,000 person-years. Gout is more prevalent in men than in women, with increasing age, and in some ethnic groups. Despite rising prevalence and incidence, suboptimal management of gout continues in many countries. Typically, only a third to half of patients with gout receive urate-lowering therapy, which is a definitive, curative treatment, and fewer than a half of patients adhere to treatment. Many gout risk factors exist, including obesity, dietary factors and comorbid conditions. As well as a firmly established increased risk of cardiovascular disease and chronic kidney disease in those with gout, novel associations of gout with other comorbidities have been reported, including erectile dysfunction, atrial fibrillation, obstructive sleep apnoea, osteoporosis and venous thromboembolism. Discrete patterns of comorbidity clustering in individuals with gout have been described. Increasing prevalence and incidence of obesity and comorbidities are likely to contribute substantially to the rising burden of gout. Gout is a chronic crystal deposition disorder in which sustained hyperuricaemia leads to formation and deposition of monosodium urate crystals in the joints. The prevalence and incidence of gout are increasing globally, which may be related to changes in the prevalence of gout risk factors (such as obesity) and comorbidities.

Evolutionary roads leading to low effective spins, high black hole masses, and O1/O2 rates for LIGO/Virgo binary black holes

Abstract: All ten LIGO/Virgo binary black hole (BH-BH) coalescences reported following the O1/O2 runs have near-zero effective spins. There are only three potential explanations for this. If the BH spin magnitudes are large, then: (i) either both BH spin vectors must be nearly in the orbital plane or (ii) the spin angular momenta of the BHs must be oppositely directed and similar in magnitude. Then there is also the possibility that (iii) the BH spin magnitudes are small. We consider the third hypothesis within the framework of the classical isolated binary evolution scenario of the BH-BH merger formation. We test three models of angular momentum transport in massive stars: A mildly efficient transport by meridional currents (as employed in the Geneva code), an efficient transport by the Tayler-Spruit magnetic dynamo (as implemented in the MESA code), and a very-efficient transport (as proposed by Fuller et al.) to calculate natal BH spins. We allow for binary evolution to increase the BH spins through accretion and account for the potential spin-up of stars through tidal interactions. Additionally, we update the calculations of the stellar-origin BH masses, including revisions to the history of star formation and to the chemical evolution across cosmic time. We find that we can simultaneously match the observed BH-BH merger rate density and BH masses and BH-BH effective spins. Models with efficient angular momentum transport are favored. The updated stellar-mass weighted gas-phase metallicity evolution now used in our models appears to be key for obtaining an improved reproduction of the LIGO/Virgo merger rate estimate. Mass losses during the pair-instability pulsation supernova phase are likely to be overestimated if the merger GW170729 hosts a BH more massive than 50âMâS. We also estimate rates of black hole-neutron star (BH-NS) mergers from recent LIGO/Virgo observations. If, in fact. angular momentum transport in massive stars is efficient, then any (electromagnetic or gravitational wave) observation of a rapidly spinning BH would indicate either a very effective tidal spin up of the progenitor star (homogeneous evolution, high-mass X-ray binary formation through case A mass transfer, or a spin-up of a Wolf-Rayet star in a close binary by a close companion), significant mass accretion by the hole, or a BH formation through the merger of two or more BHs (in a dense stellar cluster). (Less)

Anomaly Detection for IoT Time-Series Data: A Survey

Abstract: Anomaly detection is a problem with applications for a wide variety of domains; it involves the identification of novel or unexpected observations or sequences within the data being captured. The majority of current anomaly detection methods are highly specific to the individual use case, requiring expert knowledge of the method as well as the situation to which it is being applied. The Internet of Things (IoT) as a rapidly expanding field offers many opportunities for this type of data analysis to be implemented, however, due to the nature of the IoT, this may be difficult. This review provides a background on the challenges which may be encountered when applying anomaly detection techniques to IoT data, with examples of applications for the IoT anomaly detection taken from the literature. We discuss a range of approaches that have been developed across a variety of domains, not limited to IoT due to the relative novelty of this application. Finally, we summarize the current challenges being faced in the anomaly detection domain with a view to identifying potential research opportunities for the future.

Federated learning with hierarchical clustering of local updates to improve training on non-IID data

Abstract: Federated learning (FL) is a well established method for performing machine learning tasks over massively distributed data. However in settings where data is distributed in a non-iid (not independent and identically distributed) fashion - as is typical in real world situations - the joint model produced by FL suffers in terms of test set accuracy and/or communication costs compared to training on iid data. We show that learning a single joint model is often not optimal in the presence of certain types of non-iid data. In this work we present a modification to FL by introducing a hierarchical clustering step (FL+HC) to separate clusters of clients by the similarity of their local updates to the global joint model. Once separated, the clusters are trained independently and in parallel on specialised models. We present a robust empirical analysis of the hyperparameters for FL+HC for several iid and non-iid settings. We show how FL+HC allows model training to converge in fewer communication rounds (significantly so under some non-iid settings) compared to FL without clustering. Additionally, FL+HC allows for a greater percentage of clients to reach a target accuracy compared to standard FL. Finally we make suggestions for good default hyperparameters to promote superior performing specialised models without modifying the the underlying federated learning communication protocol.

Renewable energy communities under the 2019 European Clean Energy Package – Governance model for the energy clusters of the future?

Abstract: The recast of the European Union Renewable Energy Directive (RED II) entered into force in December 2018, followed by the Internal Electricity Market Directive (IEMD) and Regulation (IEMR) as part of the Clean Energy for all Europeans Package. The RED II, that the 28 Member States have until June 2021 to transpose into national law, defines “Renewable Energy Communities” (RECs), introduces a governance model for them and the possibility of energy sharing within the REC. It also provides an “enabling framework” to put RECs on equal footing with other market players and to promote and facilitate their development. This article defines "renewable energy clusters" that are comprised of complementarity of different energy sources, flexibility, interconnectivity of different actors and bi-directionality of energy flows. We argue that RECs and RE clusters are socio-technical mirrors of the same concept, necessary in a renewable energy transition. To test how these new rules will fare in practice, drawing on a secondary dataset of 67 best-practice cases of consumer (co-)ownership from 18 countries, each project is assessed using the criteria of cluster potential, and for the extent that they meet the RED II governance requirements of heterogeneity of members and of ownership structure. Nine cases were identified as having cluster potential all of which were in rural areas. Of these, five projects were found to be both RECs and RE clusters. The absence of the governance and heterogeneity criteria is observed in projects that fall short of the cluster elements of flexibility, bi-directionality and interconnectivity, while cluster elements occur where the governance and heterogeneity criteria are met. When transposing the new rules into national law we recommend careful attention to encourage complementarity of renewables, RECs in urban contexts and “regulatory sandboxes” for experimentation to find the range of optimal preferential conditions of the “enabling framework”.

Accuracy of the Edinburgh Postnatal Depression Scale (EPDS) for screening to detect major depression among pregnant and postpartum women: systematic review and meta-analysis of individual participant data

Abstract: Objective To evaluate the Edinburgh Postnatal Depression Scale (EPDS) for screening to detect major depression in pregnant and postpartum women. Design Individual participant data meta-analysis. Data sources Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, and Web of Science (from inception to 3 October 2018). Eligibility criteria for selecting studies Eligible datasets included EPDS scores and major depression classification based on validated diagnostic interviews. Bivariate random effects meta-analysis was used to estimate EPDS sensitivity and specificity compared with semi-structured, fully structured (Mini International Neuropsychiatric Interview (MINI) excluded), and MINI diagnostic interviews separately using individual participant data. One stage meta-regression was used to examine accuracy by reference standard categories and participant characteristics. Results Individual participant data were obtained from 58 of 83 eligible studies (70%; 15 557 of 22 788 eligible participants (68%), 2069 with major depression). Combined sensitivity and specificity was maximised at a cut-off value of 11 or higher across reference standards. Among studies with a semi-structured interview (36 studies, 9066 participants, 1330 with major depression), sensitivity and specificity were 0.85 (95% confidence interval 0.79 to 0.90) and 0.84 (0.79 to 0.88) for a cut-off value of 10 or higher, 0.81 (0.75 to 0.87) and 0.88 (0.85 to 0.91) for a cut-off value of 11 or higher, and 0.66 (0.58 to 0.74) and 0.95 (0.92 to 0.96) for a cut-off value of 13 or higher, respectively. Accuracy was similar across reference standards and subgroups, including for pregnant and postpartum women. Conclusions An EPDS cut-off value of 11 or higher maximised combined sensitivity and specificity; a cut-off value of 13 or higher was less sensitive but more specific. To identify pregnant and postpartum women with higher symptom levels, a cut-off of 13 or higher could be used. Lower cut-off values could be used if the intention is to avoid false negatives and identify most patients who meet diagnostic criteria. Registration PROSPERO (CRD42015024785).

The 2019 coronavirus (SARS-CoV-2) surface protein (Spike) S1 Receptor Binding Domain undergoes conformational change upon heparin binding

Abstract: Many pathogens take advantage of the dependence of the host on the interaction of hundreds of extracellular proteins with the glycosaminoglycans heparan sulphate to regulate homeostasis and use heparan sulphate as a means to adhere and gain access to cells. Moreover, mucosal epithelia such as that of the respiratory tract are protected by a layer of mucin polysaccharides, which are usually sulphated. Consequently, the polydisperse, natural products of heparan sulphate and the allied polysaccharide, heparin have been found to be involved and prevent infection by a range of viruses including S-associated coronavirus strain HSR1. Here we use surface plasmon resonance and circular dichroism to measure the interaction between the SARS-CoV-2 Spike S1 protein receptor binding domain (SARS-CoV-2 S1 RBD) and heparin. The data demonstrate an interaction between the recombinant surface receptor binding domain and the polysaccharide. This has implications for the rapid development of a first-line therapeutic by repurposing heparin and for next-generation, tailor-made, GAG-based antivirals.

The anatomical basis for transcutaneous auricular vagus nerve stimulation.

Abstract: The array of end organ innervations of the vagus nerve, coupled with increased basic science evidence, has led to vagus nerve stimulation (VNS) being explored as a management option in a number of clinical disorders, such as heart failure, migraine and inflammatory bowel disease. Both invasive (surgically implanted) and non-invasive (transcutaneous) techniques of VNS exist. Transcutaneous VNS (tVNS) delivery systems rely on the cutaneous distribution of vagal afferents, either at the external ear (auricular branch of the vagus nerve) or at the neck (cervical branch of the vagus nerve), thus obviating the need for surgical implantation of a VNS delivery device and facilitating further investigations across a wide range of uses. The concept of electrically stimulating the auricular branch of the vagus nerve (ABVN), which provides somatosensory innervation to several aspects of the external ear, is relatively more recent compared with cervical VNS; thus, there is a relative paucity of literature surrounding its operation and functionality. Despite the increasing body of research exploring the therapeutic uses of auricular transcutaneous VNS (tVNS), a comprehensive review of the cutaneous, intracranial and central distribution of ABVN fibres has not been conducted to date. A review of the literature exploring the neuroanatomical basis of this neuromodulatory therapy is therefore timely. Our review article explores the neuroanatomy of the ABVN with reference to (1) clinical surveys examining Arnold's reflex, (2) cadaveric studies, (3) fMRI studies, (4) electrophysiological studies, (5) acupuncture studies, (6) retrograde tracing studies and (7) studies measuring changes in autonomic (cardiovascular) parameters in response to auricular tVNS. We also provide an overview of the fibre composition of the ABVN and the effects of auricular tVNS on the central nervous system. Cadaveric studies, of which a limited number exist in the literature, would be the 'gold-standard' approach to studying the cutaneous map of the ABVN; thus, there is a need for more such studies to be conducted. Functional magnetic resonance imaging (fMRI) represents a useful surrogate modality for discerning the auricular sites most likely innervated by the ABVN and the most promising locations for auricular tVNS. However, given the heterogeneity in the results of such investigations and the various limitations of using fMRI, the current literature lacks a clear consensus on the auricular sites that are most densely innervated by the ABVN and whether the brain regions secondarily activated by electrical auricular tVNS depend on specific parameters. At present, it is reasonable to surmise that the concha and inner tragus are suitable locations for vagal modulation. Given the therapeutic potential of auricular tVNS, there remains a need for the cutaneous map of the ABVN to be further refined and the effects of various stimulation parameters and stimulation sites to be determined.

Developments in medical education in response to the COVID-19 pandemic: A rapid BEME systematic review: BEME Guide No. 63.

Abstract: The novel coronavirus disease (COVID-19) was declared a pandemic in March 2020. This rapid systematic review synthesised published reports of medical educational developments in response to the pan...

Heparin Inhibits Cellular Invasion by SARS-CoV-2: Structural Dependence of the Interaction of the Spike S1 Receptor-Binding Domain with Heparin.

Abstract: The dependence of development and homeostasis in animals on the interaction of hundreds of extracellular regulatory proteins with the peri- and extracellular glycosaminoglycan heparan sulfate (HS) is exploited by many microbial pathogens as a means of adherence and invasion. Heparin, a widely used anticoagulant drug, is structurally similar to HS and is a common experimental proxy. Exogenous heparin prevents infection by a range of viruses, including S-associated coronavirus isolate HSR1. Here, we show that heparin inhibits severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) invasion of Vero cells by up to 80% at doses achievable through prophylaxis and, particularly relevant, within the range deliverable by nebulisation. Surface plasmon resonance and circular dichroism spectroscopy demonstrate that heparin and enoxaparin, a low-molecular-weight heparin which is a clinical anticoagulant, bind and induce a conformational change in the spike (S1) protein receptor-binding domain (S1 RBD) of SARS-CoV-2. A library of heparin derivatives and size-defined fragments were used to probe the structural basis of this interaction. Binding to the RBD is more strongly dependent on the presence of 2-O or 6-O sulfate groups than on N-sulfation and a hexasaccharide is the minimum size required for secondary structural changes to be induced in the RBD. It is likely that inhibition of viral infection arises from an overlap between the binding sites of heparin/HS on S1 RBD and that of the angiotensin-converting enzyme 2. The results suggest a route for the rapid development of a first-line therapeutic by repurposing heparin and its derivatives as antiviral agents against SARS-CoV-2 and other members of the Coronaviridae.

COVID-19 pandemic and admission rates for and management of acute coronary syndromes in England

Abstract: BACKGROUND: Several countries affected by the COVID-19 pandemic have reported a substantial drop in the number of patients attending the emergency department with acute coronary syndromes and a reduced number of cardiac procedures. We aimed to understand the scale, nature, and duration of changes to admissions for different types of acute coronary syndrome in England and to evaluate whether in-hospital management of patients has been affected as a result of the COVID-19 pandemic. METHODS: We analysed data on hospital admissions in England for types of acute coronary syndrome from Jan 1, 2019, to May 24, 2020, that were recorded in the Secondary Uses Service Admitted Patient Care database. Admissions were classified as ST-elevation myocardial infarction (STEMI), non-STEMI (NSTEMI), myocardial infarction of unknown type, or other acute coronary syndromes (including unstable angina). We identified revascularisation procedures undertaken during these admissions (ie, coronary angiography without percutaneous coronary intervention [PCI], PCI, and coronary artery bypass graft surgery). We calculated the numbers of weekly admissions and procedures undertaken; percentage reductions in weekly admissions and across subgroups were also calculated, with 95% CIs. FINDINGS: Hospital admissions for acute coronary syndrome declined from mid-February, 2020, falling from a 2019 baseline rate of 3017 admissions per week to 1813 per week by the end of March, 2020, a reduction of 40% (95% CI 37-43). This decline was partly reversed during April and May, 2020, such that by the last week of May, 2020, there were 2522 admissions, representing a 16% (95% CI 13-20) reduction from baseline. During the period of declining admissions, there were reductions in the numbers of admissions for all types of acute coronary syndrome, including both STEMI and NSTEMI, but relative and absolute reductions were larger for NSTEMI, with 1267 admissions per week in 2019 and 733 per week by the end of March, 2020, a percent reduction of 42% (95% CI 38-46). In parallel, reductions were recorded in the number of PCI procedures for patients with both STEMI (438 PCI procedures per week in 2019 vs 346 by the end of March, 2020; percent reduction 21%, 95% CI 12-29) and NSTEMI (383 PCI procedures per week in 2019 vs 240 by the end of March, 2020; percent reduction 37%, 29-45). The median length of stay among patients with acute coronary syndrome fell from 4 days (IQR 2-9) in 2019 to 3 days (1-5) by the end of March, 2020. INTERPRETATION: Compared with the weekly average in 2019, there was a substantial reduction in the weekly numbers of patients with acute coronary syndrome who were admitted to hospital in England by the end of March, 2020, which had been partly reversed by the end of May, 2020. The reduced number of admissions during this period is likely to have resulted in increases in out-of-hospital deaths and long-term complications of myocardial infarction and missed opportunities to offer secondary prevention treatment for patients with coronary heart disease. The full extent of the effect of COVID-19 on the management of patients with acute coronary syndrome will continue to be assessed by updating these analyses. FUNDING: UK Medical Research Council, British Heart Foundation, Public Health England, Health Data Research UK, and the National Institute for Health Research Oxford Biomedical Research Centre.

Finding the 'right' GP: a qualitative study of the experiences of people with long-COVID.

Abstract: Background: An unknown proportion of people who had an apparently mild COVID-19 infection continue to suffer with persistent symptoms, including chest pain, shortness of breath, muscle and joint pains, headaches, cognitive impairment (‘brain fog’), and fatigue. Post-acute COVID-19 (‘long-COVID’) seems to be a multisystem disease, sometimes occurring after a mild acute illness; people struggling with these persistent symptoms refer to themselves as ‘long haulers’. Aim: To explore experiences of people with persisting symptoms following COVID-19 infection, and their views on primary care support received. Design & setting: Qualitative methodology, with semi-structured interviews to explore perspectives of people with persisting symptoms following suspected or confirmed COVID-19 infection. Participants were recruited via social media between July–August 2020. Method: Interviews were conducted by telephone or video call, digitally recorded, and transcribed with consent. Thematic analysis was conducted applying constant comparison techniques. People with experience of persisting symptoms contributed to study design and data analysis. Results: This article reports analysis of 24 interviews. The main themes include: the ‘hard and heavy work’ of enduring and managing symptoms and accessing care; living with uncertainty, helplessness and fear, particularly over whether recovery is possible; the importance of finding the 'right' GP (understanding, empathy, and support needed); and recovery and rehabilitation: what would help? Conclusion: This study will raise awareness among primary care professionals, and commissioners, of long-COVID and the range of symptoms people are experiencing. Patients require their GP to believe their symptoms and to demonstrate empathy and understanding. Ongoing support by primary care professionals during recovery and rehabilitation is crucial.

Research priorities for the COVID-19 pandemic and beyond: A call to action for psychological science.

Abstract: The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) that has caused the coronavirus disease 2019 (COVID-19) pandemic represents the greatest international biopsychosocial emergency the world has faced for a century, and psychological science has an integral role to offer in helping societies recover. The aim of this paper is to set out the shorter- and longer-term priorities for research in psychological science that will (a) frame the breadth and scope of potential contributions from across the discipline; (b) enable researchers to focus their resources on gaps in knowledge; and (c) help funders and policymakers make informed decisions about future research priorities in order to best meet the needs of societies as they emerge from the acute phase of the pandemic. The research priorities were informed by an expert panel convened by the British Psychological Society that reflects the breadth of the discipline; a wider advisory panel with international input; and a survey of 539 psychological scientists conducted early in May 2020. The most pressing need is to research the negative biopsychosocial impacts of the COVID-19 pandemic to facilitate immediate and longer-term recovery, not only in relation to mental health, but also in relation to behaviour change and adherence, work, education, children and families, physical health and the brain, and social cohesion and connectedness. We call on psychological scientists to work collaboratively with other scientists and stakeholders, establish consortia, and develop innovative research methods while maintaining high-quality, open, and rigorous research standards.

A male-biased sex-distorter gene drive for the human malaria vector Anopheles gambiae

Abstract: Only female insects transmit diseases such as malaria, dengue and Zika; therefore, control methods that bias the sex ratio of insect offspring have long been sought. Genetic elements such as sex-chromosome drives can distort sex ratios to produce unisex populations that eventually collapse, but the underlying molecular mechanisms are unknown. We report a male-biased sex-distorter gene drive (SDGD) in the human malaria vector Anopheles gambiae. We induced super-Mendelian inheritance of the X-chromosome-shredding I-PpoI nuclease by coupling this to a CRISPR-based gene drive inserted into a conserved sequence of the doublesex (dsx) gene. In modeling of invasion dynamics, SDGD was predicted to have a quicker impact on female mosquito populations than previously developed gene drives targeting female fertility. The SDGD at the dsx locus led to a male-only population from a 2.5% starting allelic frequency in 10–14 generations, with population collapse and no selection for resistance. Our results support the use of SDGD for malaria vector control.

Self-assembled poly-catenanes from supramolecular toroidal building blocks.

Abstract: Mechanical interlocking of molecules (catenation) is a nontrivial challenge in modern synthetic chemistry and materials science1,2. One strategy to achieve catenation is the design of pre-annular molecules that are capable of both efficient cyclization and of pre-organizing another precursor to engage in subsequent interlocking3–9. This task is particularly difficult when the annular target is composed of a large ensemble of molecules, that is, when it is a supramolecular assembly. However, the construction of such unprecedented assemblies would enable the visualization of nontrivial nanotopologies through microscopy techniques, which would not only satisfy academic curiosity but also pave the way to the development of materials with nanotopology-derived properties. Here we report the synthesis of such a nanotopology using fibrous supramolecular assemblies with intrinsic curvature. Using a solvent-mixing strategy, we kinetically organized a molecule that can elongate into toroids with a radius of about 13 nanometres. Atomic force microscopy on the resulting nanoscale toroids revealed a high percentage of catenation, which is sufficient to yield ‘nanolympiadane’10, a nanoscale catenane composed of five interlocked toroids. Spectroscopic and theoretical studies suggested that this unusually high degree of catenation stems from the secondary nucleation of the precursor molecules around the toroids. By modifying the self-assembly protocol to promote ring closure and secondary nucleation, a maximum catenation number of 22 was confirmed by atomic force microscopy. Nanoscale toroids with a high percentage of poly-catenation and radii of up to about 13 nm are kinetically organized using fibrous supramolecular assemblies with intrinsic curvature and a solvent-mixing strategy.

Invasion Biology, Ecology, and Management of Western Flower Thrips.

Abstract: Western flower thrips, Frankliniella occidentalis, first arose as an important invasive pest of many crops during the 1970s-1980s. The tremendous growth in international agricultural trade that developed then fostered the invasiveness of western flower thrips. We examine current knowledge regarding the biology of western flower thrips, with an emphasis on characteristics that contribute to its invasiveness and pest status. Efforts to control this pest and the tospoviruses that it vectors with intensive insecticide applications have been unsuccessful and have created significant problems because of the development of resistance to numerous insecticides and associated outbreaks of secondary pests. We synthesize information on effective integrated management approaches for western flower thrips that have developed through research on its biology, behavior, and ecology. We further highlight emerging topics regarding the species status of western flower thrips, as well as its genetics, biology, and ecology that facilitate its use as a model study organism and will guide development of appropriate management practices.

Deep Reinforcement Learning-Based Energy Storage Arbitrage With Accurate Lithium-Ion Battery Degradation Model

Abstract: Accurate estimation of battery degradation cost is one of the main barriers for battery participating on the energy arbitrage market. This paper addresses this problem by using a model-free deep reinforcement learning (DRL) method to optimize the battery energy arbitrage considering an accurate battery degradation model. Firstly, the control problem is formulated as a Markov Decision Process (MDP). Then a noisy network based deep reinforcement learning approach is proposed to learn an optimized control policy for storage charging/discharging strategy. To address the uncertainty of electricity price, a hybrid Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) model is adopted to predict the price for the next day. Finally, the proposed approach is tested on the historical U.K. wholesale electricity market prices. The results compared with model based Mixed Integer Linear Programming (MILP) have demonstrated the effectiveness and performance of the proposed framework.

International Society for Peritoneal Dialysis practice recommendations: Prescribing high-quality goal-directed peritoneal dialysis:

Abstract: Lay summary The International Society for Peritoneal Dialysis last published a guideline on prescribing peritoneal dialysis (PD) in 2006. This focused on clearance of toxins and used a measure of waste product removal by dialysis using urea as an example. This guideline suggested that a specific quantity of small solute removal was needed to achieve dialysis `adequacy'. It is now generally accepted, however, that the well-being of the person on dialysis is related to many different factors and not just removal of specific toxins. This guideline has been written with the focus on the person doing PD. It is proposed that dialysis delivery should be `goal-directed'. This involves discussions between the person doing PD and the care team (shared decision-making) to establish care goals for dialysis delivery. The aims of these care goals are (1) to allow the person doing PD to achieve his/her own life goals and (2) to promote the provision of high-quality dialysis care by the dialysis team.Key recommendations 1. PD should be prescribed using shared decision-making between the person doing PD and the care team. The aim is to establish realistic care goals that (1) maintain quality of life for the person doing PD as much as possible by enabling them to meet their life goals, (2) minimize symptoms and treatment burden while (3) ensuring high-quality care is provided. 2. The PD prescription should take into account the local country resources, the wishes and lifestyle considerations of people needing treatment, including those of their families/caregivers', especially if providing assistance in their care. 3. A number of assessments should be used to help ensure the delivery of high-quality PD care. a. Patient reported outcome measures - this is a measure of how a person doing PD is experiencing life and his/her feeling of well-being. It should take into account the person's symptoms, impact of the dialysis regimen on the person's life, mental health and social circumstances. b. Fluid status is an important part of dialysis delivery. Urine output and fluid removed by dialysis both contribute to maintaining good fluid status. Regular assessment of fluid status, including blood pressure and clinical examination, should be part of routine care. c. Nutrition status should be assessed regularly through evaluation of the patient's appetite, clinical examination, body weight measurements and blood tests (potassium, bicarbonate, phosphate, albumin). Dietary intake of potassium, phosphate, sodium, protein, carbohydrate and fat may need to be assessed and adjusted as well. d. Removal of toxins. This can be estimated using a calculation called Kt/Vurea and/or creatinine clearance. Both are measures of the amount of dialysis delivered. There is no high-quality evidence regarding the need or benefit associated with the achievement of a specific target value for these measures. 4. The amount of kidney function that continues to remove waste products and the remaining urine volume should be known for all individuals doing PD. Management should focus on preserving this as long as possible. 5. For some people who require dialysis and who are old, frail or have a poor prognosis, there may be a quality of life benefit from a reduced dialysis prescription to minimize the burden of treatment. 6. In low and lower middle-income countries, every effort should be made to conform to the framework of these statements, taking into account resource limitations. 7. The principles of prescribing and assessing delivery of high-quality PD to children are the same as for adults. In all cases, the PD prescription should be designed to meet the medical, mental health social and financial needs of the individual child and family

The regulation of nanomaterials and nanomedicines for clinical application : current and future perspectives

Abstract: The use of nanomaterials in biomedicine has increased over the past 10 years, with many different nanoparticle systems being utilised within the clinical setting. With limited emerging success in clinical trials, polymeric, metallic, and lipid based nanoparticles have all found a place in medicine, with these generally providing enhanced drug efficacy or therapeutic effect compared to the standard drug treatments. Although there is great anticipation surrounding the field of nanomedicine and its influence on the pharmaceutical industry, there is currently very little regulatory guidance in this area, despite repeated calls from the research community, something that is critical to provide legal certainty to manufacturers, policymakers, healthcare providers and the general public. This is reflected in the lack of an international definition of what these materials are, with several bodies, including the National Institute of Health, USA, the European Science Foundation and the European Technology Platform, having differing definitions, and the FDA having no clear definition at all. The uncertainty created by the lack of consistency across the board may ultimately impact funding, research and development of such products negatively thus destroying public acceptance and perception of nano-products. This review aims to discuss the use of nanomaterials within the clinical setting, why regulation of these materials is so important, and the challenges faced in regulating these materials generally, as well as the current regulation used in different nations.

British Society for Rheumatology guideline on diagnosis and treatment of giant cell arteritis

Abstract: Neuro-Ophthalmology Unit, University Hospitals Birmingham NHS Foundation Trust, Birmingham, PMR-GCA Scotland, Perth, Scotland, Department of Ophthalmology, King’s College Hospital, London, UK, Medical Centre for Rheumatology Berlin-Buch, Immanuel Hospital Berlin, Berlin, Germany, Rheumatology, Ipswich Hospital, Ipswich, UK, University of East Anglia, Ipswich, Rheumatology, Southend University NHS Foundation Trust, Westcliff-on-Sea, Essex, UK, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada, Department of

Genetic and environmental variation in educational attainment: an individual-based analysis of 28 twin cohorts.

Abstract: We investigated the heritability of educational attainment and how it differed between birth cohorts and cultural-geographic regions. A classical twin design was applied to pooled data from 28 cohorts representing 16 countries and including 193,518 twins with information on educational attainment at 25 years of age or older. Genetic factors explained the major part of individual differences in educational attainment (heritability: a2 = 0.43; 0.41-0.44), but also environmental variation shared by co-twins was substantial (c2 = 0.31; 0.30-0.33). The proportions of educational variation explained by genetic and shared environmental factors did not differ between Europe, North America and Australia, and East Asia. When restricted to twins 30 years or older to confirm finalized education, the heritability was higher in the older cohorts born in 1900-1949 (a2 = 0.44; 0.41-0.46) than in the later cohorts born in 1950-1989 (a2 = 0.38; 0.36-0.40), with a corresponding lower influence of common environmental factors (c2 = 0.31; 0.29-0.33 and c2 = 0.34; 0.32-0.36, respectively). In conclusion, both genetic and environmental factors shared by co-twins have an important influence on individual differences in educational attainment. The effect of genetic factors on educational attainment has decreased from the cohorts born before to those born after the 1950s.