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The global COVID-19 pandemic has created, exposed and exacerbated inequalities and differences around access to—and experiences and representations of—the physical and virtual spaces of young people's leisure cultures and practices. Drawing on longstanding themes of continuity and change in youth leisure scholarship, this paper contributes to our understandings of 'liminal leisure' as experienced by some young people in the UK before and during the COVID-19 pandemic. To do this, we place primary pre-pandemic research on disadvantaged young people's leisure spaces and practices in dialogue with secondary data on lockdown and post-lockdown leisure. Subsequently, we argue that existing and emergent forms of youth 'leisure liminality' are best understood through the lens of intersectional disadvantages. Specifically, pre-existing intersectional disadvantages are being compounded by disruptions to youth leisure, as the upheaval of the pandemic continues to be differentially experienced. To understand this process, we deploy the concept of liminal leisure spaces used by Swaine et al Leisure Studies 37:4,440-451, (2018) in their ethnography of Khat-chewing among young British Somali urban youth 'on the margins'. Similarly, our focus is on young people's management and negotiation of substance use 'risks', harms and pleasures when in 'private-in-public' leisure spaces. We note that the UK government responses to the pandemic, such as national and regional lockdowns, meant that the leisure liminality of disadvantaged young people pre-pandemic became the experience of young people more generally, with for example the closure of night-time economies (NTEs). Yet despite some temporary convergence, intersectionally disadvantaged young people 'at leisure' have been subject to a particularly problematic confluence of criminalisation, exclusion and stigmatisation in COVID-19 times, which will most likely continue into the post-pandemic future.

This is the final version. Available on open access from Elsevier via the DOI in this record ; We performed shotgun genome sequencing on a total of 19 different Musa genotypes including representatives of wild banana species Musa acuminata and M. balibisiana, allopolyploid bananas and plantains, Fe'i banana, pink banana (also known as hairy banana) and abacá (also known as hemp banana). We aligned sequence reads against a previously sequenced reference genome and assessed ploidy and, in the case of allopolyploids, the contributions of the A and B genomes; this provides important quality-assurance data about the taxonomic identities of the sequenced plant material. These data will be useful for phylogenetics, crop improvement, studies of the complex story of intergenomic recombination in AAB and ABB allotriploid bananas and plantains and can be integrated into resources such as the Banana Genome Hub. ; European Union Horizon 2020 ; Gatsby Charitable Foundation

yes ; People with advanced dementia are frequently bed-bound, doubly incontinent and able to speak only a few words. Many reside in care homes and may often have complex needs requiring efficient and timely response by knowledgeable and compassionate staff. The aim of this study is to improve our understanding of health care professionals' attitudes and knowledge of the barriers to integrated care for people with advanced dementia. In-depth, interactive interviews conducted with 14 health care professionals including commissioners, care home managers, nurses and health care assistants in the UK. Barriers to care for people with advanced dementia are influenced by governmental and societal factors which contribute to challenging environments in care homes, poor morale amongst care staff and a fragmentation of health and social care at the end of life. Quality of care for people with dementia as they approach death may be improved by developing collaborative networks to foster improved relationships between health and social care services.

Particulate matter (PM) emissions from agricultural operations are an important issue for air quality and human health and a topic of interest to government regulators. PM emission rates from a dairy in the San Joaquin Valley of California were investigated during June 2008. The facility had 1,885 total animals, including 950 milking cows housed in free‐stall pens with an open‐lot exercise area, and 935 dry cows, steers, bulls, and heifers housed in open lots. Point sensors, including filter‐based aerodynamic mass samplers and optical particle counters (OPC), were deployed at select points around the facility to measure optical and aerodynamic particulate concentrations. Simultaneously, vertical PM concentration profiles were measured both upwind and downwind of the facility using lidar. The lidar was calibrated to provide mass concentration information using the OPCs and filter measurements. Emission rates were estimated over this period using both an inverse modeling technique coupled with the filter‐based measurements and a mass‐balance technique applied to lidar data. Mean emission rates calculated using inverse modeling (±95% confidence interval) were 3.8 (±3.2), 24.8 (±14.5), and 75.9 (±33.2) g d‐1 AU‐1 for PM2.5, PM10, and TSP, respectively. Mean emissions rates based on lidar data were 1.3 (±0.2), 15.1 (±2.2), and 46.4 (±7.0) g d‐1 AU‐1 for PM2.5, PM10, and TSP, respectively. The PM10 findings are roughly twice as high as those reported from other dairy studies with different climatic conditions and/or housing types, but are of similar magnitude as those from a study with similar conditions, housing, and emission rate calculation technique.

This is the final version. Available on open access from Nature Research via the DOI in this record ; Data availability; All RNA sequencing data and proteomics data is available in Supplementary Data 1–4. Exact p values, where shown on Figs. 1–5, are available in Supplementary Data 5. The source data underlying Figs. 1–5 are provided as Supplementary Data 6. Any other relevant data are available upon reasonable request. ; The interaction between a cell and its environment shapes fundamental intracellular processes such as cellular metabolism. In most cases growth rate is treated as a proximal metric for understanding the cellular metabolic status. However, changes in growth rate might not reflect metabolic variations in individuals responding to environmental fluctuations. Here we use single-cell microfluidics-microscopy combined with transcriptomics, proteomics and mathematical modelling to quantify the accumulation of glucose within Escherichia coli cells. In contrast to the current consensus, we reveal that environmental conditions which are comparatively unfavourable for growth, where both nutrients and salinity are depleted, increase glucose accumulation rates in individual bacteria and population subsets. We find that these changes in metabolic function are underpinned by variations at the translational and posttranslational level but not at the transcriptional level and are not dictated by changes in cell size. The metabolic response-characteristics identified greatly advance our fundamental understanding of the interactions between bacteria and their environment and have important ramifications when investigating cellular processes where salinity plays an important role. ; Biotechnology & Biological Sciences Research Council (BBSRC) ; Biotechnology and Biological Sciences Research Council (BBSRC) ; Medical Research Council (MRC) ; Royal Society ; QUEX Initiator grant ; European Union Horizon 2020 ; Gordon and Betty and Gordon Moore Foundation ; Wellcome Trust

International audience ; The Dementias Platform UK Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure 'lab' using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Projects are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee.

International audience ; The Dementias Platform UK Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure 'lab' using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Projects are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee.

The Dementias Platform UK Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure 'lab' using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Projects are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee.