Elements: Linking Users and Publications to Research Centres

Short user guide to Elements user accounts to LSHTM Research Centres and Research Groups, and then linking those users' publications to the Centres

A Matter of Distinction? A Case Study Examining the Development of a Sporting Habitus Amongst Male Sixth-Form Pupils in a Private School in the United Kingdom

This research project explores how upper-middle-class private school pupils are socialised into and through sports. Particularly around major sporting events such as the Olympics, there has often been commentary in the mass media regarding the extent to which former private school pupils tend to be overrepresented in Team GB within many elite-level sports. However, a need remains to research the experiences and underpinning processes that contribute to the sporting participation patterns of private school students. Semi-structured interviews were conducted to explore private school pupils' lived experiences and better understand how they are socialised into and through sports. Primary socialisation within the family and secondary socialisation within primary school, private school, and other external agents such as sports clubs were discussed. The research findings show that an individual’s sporting habitus is not static but changes and develops throughout their lifetime depending upon the 'fields' they are exposed to. Pierre Bourdieu's (1984) theoretical ideas relating to [(Habitus) (Capital)] + Field = Practice proved helpful in enabling the research to conceptualise and interpret how parental and family upbringing shaped this relationship and, therefore, provides the theoretical lens used to analyse this phenomenon. Participants demonstrated a robust sporting habitus, regularly engaging in sports and physical activity inside and outside school. The social class background of an individual affects the volumes of economic, social, cultural and physical capital they possess. Members of the upper-middle classes, therefore, seek to invest in developing different forms of capital for their children linked to the sporting 'tastes' and 'distinctions' of their class (Bourdieu 1984)

Development of the corpus callosum and cognition after neonatal encephalopathy

Objective: Neonatal imaging studies report corpus callosum abnormalities after neonatal hypoxic–ischaemic encephalopathy (HIE), but corpus callosum development and relation to cognition in childhood are unknown. Using magnetic resonance imaging (MRI), we examined the relationship between corpus callosum size, microstructure and cognitive and motor outcomes at early school-age children cooled for HIE (cases) without cerebral palsy compared to healthy, matched controls. A secondary aim was to examine the impact of HIE-related neonatal brain injury on corpus callosum size, microstructure and growth. Methods: Participants aged 6–8 years underwent MRI, the Movement Assessment Battery for Children Second Edition and Wechsler Intelligence Scale for Children Fourth Edition. Cross-sectional area, volume, fractional anisotropy and radial diffusivity of the corpus callosum and five subdivisions were measured. Multivariable regression was used to assess associations between total motor score, full-scale IQ (FSIQ) and imaging metrics. Results: Adjusting for age, sex and intracranial volume, cases (N = 40) compared to controls (N = 39) demonstrated reduced whole corpus callosum area (β = −26.9, 95% confidence interval [CI] = −53.17, −0.58), volume (β = −138.5, 95% CI = −267.54, −9.56), fractional anisotropy and increased radial diffusivity (P < 0.05) within segments II–V. In cases, segment V area (β = 0.18, 95% CI = 0.004, 0.35), volume (β = 0.04, 95% CI = 0.001, 0.079), whole corpus callosum fractional anisotropy (β = 13.8 95% CI = 0.6, 27.1) and radial diffusivity (β = −11.3, 95% CI = −22.22, −0.42) were associated with FSIQ. Growth of the corpus callosum was restricted in cases with a FSIQ ≤85, and volume was reduced in cases with mild neonatal multifocal injury compared to white matter injury alone. Interpretation: Following neonatal HIE, morphological and microstructural changes in the corpus callosum are associated with reduced cognitive function at early school age

Serum N-Glycosylation RPLC-FD-MS Assay to Assess Colorectal Cancer Surgical Interventions.

A newly developed analytical strategy was applied to profile the total serum N-glycome of 64 colorectal cancer (CRC) patients before and after surgical intervention. In this cohort, it was previously found that serum N-glycome alterations in CRC were associated with patient survival. Here, fluorescent labeling of serum N-glycans was applied using procainamide and followed by sialic acid derivatization specific for α2,6- and α2,3-linkage types via ethyl esterification and amidation, respectively. This strategy allowed efficient separation of specific positional isomers on reversed-phase liquid chromatography-fluorescence detection-mass spectrometry (RPLC-FD-MS) and complemented the previous glycomics data based on matrix-assisted laser desorption/ionization (MALDI)-MS that did not include such separations. The results from comparing pre-operative CRC to post-operative samples were in agreement with studies that identified a decrease in di-antennary structures with core fucosylation and an increase in sialylated tri- and tetra-antennary N-glycans in CRC patient sera. Pre-operative abundances of N-glycans showed good performance for the classification of adenocarcinoma and led to the revisit of the previous MALDI-MS dataset with regard to histological and clinical data. This strategy has the potential to monitor patient profiles before, during, and after clinical events such as treatment, therapy, or surgery and should also be further explored. </p

Validation of a multifactorial risk factor model used for predicting future caries risk with nevada adolescents

<p>Abstract</p> <p>Background</p> <p>The objective of this study was to measure the validity and reliability of a multifactorial Risk Factor Model developed for use in predicting future caries risk in Nevada adolescents in a public health setting.</p> <p>Methods</p> <p>This study examined retrospective data from an oral health surveillance initiative that screened over 51,000 students 13-18 years of age, attending public/private schools in Nevada across six academic years (2002/2003-2007/2008). The Risk Factor Model included ten demographic variables: exposure to fluoridation in the municipal water supply, environmental smoke exposure, race, age, locale (metropolitan vs. rural), tobacco use, Body Mass Index, insurance status, sex, and sealant application. Multiple regression was used in a previous study to establish which significantly contributed to caries risk. Follow-up logistic regression ascertained the weight of contribution and odds ratios of the ten variables. Researchers in this study computed sensitivity, specificity, positive predictive value (PVP), negative predictive value (PVN), and prevalence across all six years of screening to assess the validity of the Risk Factor Model.</p> <p>Results</p> <p>Subjects' overall mean caries prevalence across all six years was 66%. Average sensitivity across all six years was 79%; average specificity was 81%; average PVP was 89% and average PVN was 67%.</p> <p>Conclusions</p> <p>Overall, the Risk Factor Model provided a relatively constant, valid measure of caries that could be used in conjunction with a comprehensive risk assessment in population-based screenings by school nurses/nurse practitioners, health educators, and physicians to guide them in assessing potential future caries risk for use in prevention and referral practices.</p

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170.

We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER(+) or ER(-)) and human ERBB2 (HER2(+) or HER2(-)) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER(-) tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.352

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Basic science232. Certolizumab pegol prevents pro-inflammatory alterations in endothelial cell function

Background: Cardiovascular disease is a major comorbidity of rheumatoid arthritis (RA) and a leading cause of death. Chronic systemic inflammation involving tumour necrosis factor alpha (TNF) could contribute to endothelial activation and atherogenesis. A number of anti-TNF therapies are in current use for the treatment of RA, including certolizumab pegol (CZP), (Cimzia ®; UCB, Belgium). Anti-TNF therapy has been associated with reduced clinical cardiovascular disease risk and ameliorated vascular function in RA patients. However, the specific effects of TNF inhibitors on endothelial cell function are largely unknown. Our aim was to investigate the mechanisms underpinning CZP effects on TNF-activated human endothelial cells. Methods: Human aortic endothelial cells (HAoECs) were cultured in vitro and exposed to a) TNF alone, b) TNF plus CZP, or c) neither agent. Microarray analysis was used to examine the transcriptional profile of cells treated for 6 hrs and quantitative polymerase chain reaction (qPCR) analysed gene expression at 1, 3, 6 and 24 hrs. NF-κB localization and IκB degradation were investigated using immunocytochemistry, high content analysis and western blotting. Flow cytometry was conducted to detect microparticle release from HAoECs. Results: Transcriptional profiling revealed that while TNF alone had strong effects on endothelial gene expression, TNF and CZP in combination produced a global gene expression pattern similar to untreated control. The two most highly up-regulated genes in response to TNF treatment were adhesion molecules E-selectin and VCAM-1 (q 0.2 compared to control; p > 0.05 compared to TNF alone). The NF-κB pathway was confirmed as a downstream target of TNF-induced HAoEC activation, via nuclear translocation of NF-κB and degradation of IκB, effects which were abolished by treatment with CZP. In addition, flow cytometry detected an increased production of endothelial microparticles in TNF-activated HAoECs, which was prevented by treatment with CZP. Conclusions: We have found at a cellular level that a clinically available TNF inhibitor, CZP reduces the expression of adhesion molecule expression, and prevents TNF-induced activation of the NF-κB pathway. Furthermore, CZP prevents the production of microparticles by activated endothelial cells. This could be central to the prevention of inflammatory environments underlying these conditions and measurement of microparticles has potential as a novel prognostic marker for future cardiovascular events in this patient group. Disclosure statement: Y.A. received a research grant from UCB. I.B. received a research grant from UCB. S.H. received a research grant from UCB. All other authors have declared no conflicts of interes