New technologies and disruptions related to Coronavirus disease-2019 have led to expansion of decentralized approaches to clinical trials. Remote tools and methods hold promise for increasing trial efficiency and reducing burdens and barriers by facilitating participation outside of traditional clinical settings and taking studies directly to participants. The Trial Innovation Network, established in 2016 by the National Center for Advancing Clinical and Translational Science to address critical roadblocks in clinical research and accelerate the translational research process, has consulted on over 400 research study proposals to date. Its recommendations for decentralized approaches have included eConsent, participant-informed study design, remote intervention, study task reminders, social media recruitment, and return of results for participants. Some clinical trial elements have worked well when decentralized, while others, including remote recruitment and patient monitoring, need further refinement and assessment to determine their value. Partially decentralized, or “hybrid” trials, offer a first step to optimizing remote methods. Decentralized processes demonstrate potential to improve urban-rural diversity, but their impact on inclusion of racially and ethnically marginalized populations requires further study. To optimize inclusive participation in decentralized clinical trials, efforts must be made to build trust among marginalized communities, and to ensure access to remote technology.

Clinical trials continue to face significant challenges in participant recruitment and retention. The Recruitment Innovation Center (RIC), part of the Trial Innovation Network (TIN), has been funded by the National Center for Advancing Translational Sciences of the National Institutes of Health to develop innovative strategies and technologies to enhance participant engagement in all stages of multicenter clinical trials. In collaboration with investigator teams and liaisons at Clinical and Translational Science Award institutions, the RIC is charged with the mission to design, field-test, and refine novel resources in the context of individual clinical trials. These innovations are disseminated via newsletters, publications, a virtual toolbox on the TIN website, and RIC-hosted collaboration webinars. The RIC has designed, implemented, and promised customized recruitment support for 173 studies across many diverse disease areas. This support has incorporated site feasibility assessments, community input sessions, recruitment materials recommendations, social media campaigns, and an array of study-specific suggestions. The RIC’s goal is to evaluate the efficacy of these resources and provide access to all investigating teams, so that more trials can be completed on time, within budget, with diverse participation, and with enough accrual to power statistical analyses and make substantive contributions to the advancement of healthcare.

Precise instrumental calibration is of crucial importance to 21-cm cosmology experiments. The Murchison Widefield Array’s (MWA) Phase II compact configuration offers us opportunities for both redundant calibration and sky-based calibration algorithms; using the two in tandem is a potential approach to mitigate calibration errors caused by inaccurate sky models. The MWA Epoch of Reionization (EoR) experiment targets three patches of the sky (dubbed EoR0, EoR1, and EoR2) with deep observations. Previous work in Li et al. (2018) and (2019) studied the effect of tandem calibration on the EoR0 field and found that it yielded no significant improvement in the power spectrum (PS) over sky-based calibration alone. In this work, we apply similar techniques to the EoR1 field and find a distinct result: the improvements in the PS from tandem calibration are significant. To understand this result, we analyse both the calibration solutions themselves and the effects on the PS over three nights of EoR1 observations. We conclude that the presence of the bright radio galaxy Fornax A in EoR1 degrades the performance of sky-based calibration, which in turn enables redundant calibration to have a larger impact. These results suggest that redundant calibration can indeed mitigate some level of model incompleteness error.

During pregnancy, changes occur to influence the maternal gut microbiome, and potentially the fetal microbiome. Diet has been shown to impact the gut microbiome. Little research has been conducted examining diet during pregnancy with respect to the gut microbiome. To meet inclusion criteria, dietary analyses must have been conducted as part of the primary aim. The primary outcome was the composition of the gut microbiome (infant or maternal), as assessed using culture-independent sequencing techniques. This review identified seven studies for inclusion, five examining the maternal gut microbiome and two examining the fetal gut microbiome. Microbial data were attained through analysis of stool samples by 16S ribosomal RNA gene-based microbiota assessment. Studies found an association between the maternal diet and gut microbiome. High-fat diets (% fat of total energy), fat-soluble vitamins (mg/d) and fibre (g/d) were the most significant nutrients associated with the gut microbiota composition of both neonates and mothers. High-fat diets were significantly associated with a reduction in microbial diversity. High-fat diets may reduce microbial diversity, while fibre intake may be positively associated with microbial diversity. The results of this review must be interpreted with caution. The number of studies was low, and the risk of observational bias and heterogeneity across the studies must be considered. However, these results show promise for dietary intervention and microbial manipulation in order to favour an increase of health-associated taxa in the gut of the mother and her offspring.

We apply two methods to estimate the 21-cm bispectrum from data taken within the Epoch of Reionisation (EoR) project of the Murchison Widefield Array (MWA). Using data acquired with the Phase II compact array allows a direct bispectrum estimate to be undertaken on the multiple redundantly spaced triangles of antenna tiles, as well as an estimate based on data gridded to the uv-plane. The direct and gridded bispectrum estimators are applied to 21 h of high-band (167–197 MHz; z = 6.2–7.5) data from the 2016 and 2017 observing seasons. Analytic predictions for the bispectrum bias and variance for point-source foregrounds are derived. We compare the output of these approaches, the foreground contribution to the signal, and future prospects for measuring the bispectra with redundant and non-redundant arrays. We find that some triangle configurations yield bispectrum estimates that are consistent with the expected noise level after 10 h, while equilateral configurations are strongly foreground-dominated. Careful choice of triangle configurations may be made to reduce foreground bias that hinders power spectrum estimators, and the 21-cm bispectrum may be accessible in less time than the 21-cm power spectrum for some wave modes, with detections in hundreds of hours.

A national need is to prepare for and respond to accidental or intentional disasters categorized as chemical, biological, radiological, nuclear, or explosive (CBRNE). These incidents require specific subject-matter expertise, yet have commonalities. We identify 7 core elements comprising CBRNE science that require integration for effective preparedness planning and public health and medical response and recovery. These core elements are (1) basic and clinical sciences, (2) modeling and systems management, (3) planning, (4) response and incident management, (5) recovery and resilience, (6) lessons learned, and (7) continuous improvement. A key feature is the ability of relevant subject matter experts to integrate information into response operations. We propose the CBRNE medical operations science support expert as a professional who (1) understands that CBRNE incidents require an integrated systems approach, (2) understands the key functions and contributions of CBRNE science practitioners, (3) helps direct strategic and tactical CBRNE planning and responses through first-hand experience, and (4) provides advice to senior decision-makers managing response activities. Recognition of both CBRNE science as a distinct competency and the establishment of the CBRNE medical operations science support expert informs the public of the enormous progress made, broadcasts opportunities for new talent, and enhances the sophistication and analytic expertise of senior managers planning for and responding to CBRNE incidents.

Shiga toxin-producing Escherichia coli (STEC) infection can cause serious illness including haemolytic uraemic syndrome. The role of socio-economic status (SES) in differential clinical presentation and exposure to potential risk factors amongst STEC cases has not previously been reported in England. We conducted an observational study using a dataset of all STEC cases identified in England, 2010–2015. Odds ratios for clinical characteristics of cases and foodborne, waterborne and environmental risk factors were estimated using logistic regression, stratified by SES, adjusting for baseline demographic factors. Incidence was higher in the highest SES group compared to the lowest (RR 1.54, 95% CI 1.19–2.00). Odds of Accident and Emergency attendance (OR 1.35, 95% CI 1.10–1.75) and hospitalisation (OR 1.71, 95% CI 1.36–2.15) because of illness were higher in the most disadvantaged compared to the least, suggesting potential lower ascertainment of milder cases or delayed care-seeking behaviour in disadvantaged groups. Advantaged individuals were significantly more likely to report salad/fruit/vegetable/herb consumption (OR 1.59, 95% CI 1.16–2.17), non-UK or UK travel (OR 1.76, 95% CI 1.40–2.27; OR 1.85, 95% CI 1.35–2.56) and environmental exposures (walking in a paddock, OR 1.82, 95% CI 1.22–2.70; soil contact, OR 1.52, 95% CI 2.13–1.09) suggesting other unmeasured risks, such as person-to-person transmission, could be more important in the most disadvantaged group.

Tissue engineering aims to grow artificial tissues in vitro to replace those in the body that have been damaged through age, trauma or disease. A recent approach to engineer artificial cartilage involves seeding cells within a scaffold consisting of an interconnected 3D-printed lattice of polymer fibres combined with a cast or printed hydrogel, and subjecting the construct (cell-seeded scaffold) to an applied load in a bioreactor. A key question is to understand how the applied load is distributed throughout the construct. To address this, we employ homogenisation theory to derive equations governing the effective macroscale material properties of a periodic, elastic–poroelastic composite. We treat the fibres as a linear elastic material and the hydrogel as a poroelastic material, and exploit the disparate length scales (small inter-fibre spacing compared with construct dimensions) to derive macroscale equations governing the response of the composite to an applied load. This homogenised description reflects the orthotropic nature of the composite. To validate the model, solutions from finite element simulations of the macroscale, homogenised equations are compared to experimental data describing the unconfined compression of the fibre-reinforced hydrogels. The model is used to derive the bulk mechanical properties of a cylindrical construct of the composite material for a range of fibre spacings and to determine the local mechanical environment experienced by cells embedded within the construct.

This study assessed variation in coverage of maternal pertussis vaccination, introduced in England in October 2012 in response to a national outbreak, and a new infant rotavirus vaccination programme, implemented in July 2013. Vaccine eligible patients were included from national vaccine coverage datasets and covered April 2014 to March 2015 for pertussis and January 2014 to June 2016 for rotavirus. Vaccine coverage (%) was calculated overall and by NHS England Local Team (LT), ethnicity and Index of Multiple Deprivation (IMD) quintile, and compared using binomial regression. Compared with white-British infants, the largest differences in rotavirus coverage were in ‘other’, white-Irish and black-Caribbean infants (−13·9%, −12·1% and −10·7%, respectively), after adjusting for IMD and LT. The largest differences in maternal pertussis coverage were in black-other and black-Caribbean women (−16·3% and −15·4%, respectively). Coverage was lowest in London LT for both programmes. Coverage decreased with increasing deprivation and was 14·0% lower in the most deprived quintile compared with the least deprived for the pertussis programme and 4·4% lower for rotavirus. Patients’ ethnicity and deprivation were therefore predictors of coverage which contributed to, but did not wholly account for, geographical variation in coverage in England.

Conventionally perennial ryegrass evaluations are conducted under simulated grazing studies to identify varieties with the best phenotypic performance. However, cut-plot environments differ greatly to those experienced on commercial farms as varieties are not exposed to the same stress levels in test environments. It could be argued that plot-based testing regimes provide little direction to plant breeders in the development of advanced varieties. Varietal phenotypic performance needs to be quantified in ‘commercial’ situations. The objective of the current study was to evaluate the phenotypic performance of a range of perennial ryegrass varieties under commercial farm conditions. Monocultures of 11 Irish Recommended List perennial ryegrass varieties were sown on 66 commercial farms throughout Ireland where performance was evaluated over a 3-year period from 2013 to 2015, inclusive. A linear mixed model was used to quantify variety effects on grassland phenotypic performance characteristics. No significant variety effect was estimated for total, seasonal or silage herbage production. Despite the lack of variety effects, pairwise comparisons found significant performance differences between individual varieties. Grazed herbage yield is of primary importance and was shown to be correlated strongly with total production (0.71); Grazed herbage yield differed significantly by variety, with a range of 1927 kg dry matter (DM)/ha between the highest and lowest performing varieties. Sward quality (dry matter digestibility [DMD]) and density were influenced by variety with a range of 44 g/kg DM for DMD and 0.7 ground score units between the highest and lowest performing varieties. Results of the current study show that on-farm evaluation is effective in identifying the most suitable varieties for intensive grazing regimes, and the phenotypic variance identified among varieties performance for many traits should allow for improved genetic gain in areas such as DM production, persistence and grazing efficiency.