Energy and environmental report. Castleland Renewal Area, Barry

This report provides a guidance of the possible routes towards improving the energy efficiency of the existing housing stock in Castleland Renewal Area, Barry. A clustering analysis focused on domestic dwellings has been developed in order to maximise the available data, creating representative groups of the larger area. Initial data has been collected and supplied by Warm Wales, thereafter complemented and expanded by the research team at the Welsh School of Architecture, where finally the information has been entered into the Energy and Environmental Prediction (EEP) model to create a database for Castleland. The analysis has been developed out of the collaborative work between Warm Wales and the Low Carbon Research Institute, at the Welsh School of Architecture (WSA), Cardiff University

Prognostic factors of poor outcomes in pneumonia in older adults: aspiration or frailty?

Purpose Little is known about the long-term and functional prognoses of older adults with pneumonia, which complicates their management. There is a common belief that aspiration is a poor prognostic factor; however, the diagnosis of aspiration pneumonia (AP) lacks consensus criteria and is mainly based on clinical characteristics typical of the frailty syndrome. Therefore, the poor prognosis of AP may also be a result of frailty rather than aspiration. This study investigated the impact of AP and other prognostic factors in older patients with pneumonia. Methods We performed a retrospective cohort study of patients aged 75 years and older, admitted with pneumonia in 2021. We divided patients according to their initial diagnosis (AP or non-AP), compared outcomes using Kaplan–Meier curves, and used logistic regression to identify independent prognostic factors. Results 803 patients were included, with a median age of 84 years and 52.7% were male. 17.3% were initially diagnosed with AP. Mortality was significantly higher in those diagnosed with AP than non-AP during admission (27.6% vs 19.0%, p = 0.024) and at 1 year (64.2% vs 53.1%, p = 0.018), with survival analysis showing a median survival time of 62 days and 274 days in AP and non-AP, respectively (χ2 = 9.2, p = 0.002). However, the initial diagnosis of AP was not an independent risk factor for poor prognosis in multivariable analysis. Old age, frailty and cardio-respiratory comorbidities were the main factors associated with death. Conclusion The greater mortality in AP may be a result of increased frailty rather than the diagnosis of aspiration itself. This supports our proposal for a paradigm shift from making predictions based on the potentially futile labelling of AP or non-AP, to considering frailty and overall condition of the patient

Embodied energy at an urban scale: A paradigm shift in calculations

Embodied energy has long been a focus of research, and improved operational energy demands in modern structures cause the proper analyses of embodied energies to be critical for full building life cycle analysis. Many different calculation techniques exist to arrive at an embodied energy value, and literature is full of the application of these values to predominantly single or small numbers of buildings. Embodied energy at an urban scale is studied in this paper, and a new software tool for estimating embodied energy impacts at the design stage is introduced. Two case studies are discussed using the software, and embodied energies are calculated and presented in context with their operational energy savings. The importance of choosing an embodied energy value calculated according to the process-based hybrid analysis method when looking at the urban scale is discussed

Embodied energy and operational energy: Case studies comparing different urban layouts

While significant progress has been made in reducing Operational Energy; Embodied Energy has been largely ignored. However, these topics are strongly linked and should be considered as a “Balance Equation”, where all factors must be carefully measured in order to avoid the excesses of both. A comparative study of urban layout and form utilising VIRVIL plugins (in Sketchup) with HTB2 (Heat Transfer in Buildings) indicates that urban layout have an impact on the Operational and Embodied Energy of buildings. The case studies analysed in this paper suggest that there is an advantage of Mid-rise type of buildings in terms of Operational Energy, however the Embodied Energy scenarios are less clear and seem to depend more on the use of the building

Gliding motility of Plasmodium merozoites

Plasmodium malaria parasites are obligate intracellular protozoans that use a unique form of locomotion, termed gliding motility, to move through host tissues and invade cells. The process is substrate dependent and powered by an actomyosin motor that drives the posterior translocation of extracellular adhesins which, in turn, propel the parasite forward. Gliding motility is essential for tissue translocation in the sporozoite and ookinete stages; however, the short-lived erythrocyte-invading merozoite stage has never been observed to undergo gliding movement. Here we show Plasmodium merozoites possess the ability to undergo gliding motility in vitro and that this mechanism is likely an important precursor step for successful parasite invasion. We demonstrate that two human infective species, Plasmodium falciparum and Plasmodium knowlesi, have distinct merozoite motility profiles which may reflect distinct invasion strategies. Additionally, we develop and validate a higher throughput assay to evaluate the effects of genetic and pharmacological perturbations on both the molecular motor and the complex signaling cascade that regulates motility in merozoites. The discovery of merozoite motility provides a model to study the glideosome and adds a dimension for work aiming to develop treatments targeting the blood stage invasion pathways

Gliding motility of Plasmodium merozoites.

Plasmodium malaria parasites are obligate intracellular protozoans that use a unique form of locomotion, termed gliding motility, to move through host tissues and invade cells. The process is substrate dependent and powered by an actomyosin motor that drives the posterior translocation of extracellular adhesins which, in turn, propel the parasite forward. Gliding motility is essential for tissue translocation in the sporozoite and ookinete stages; however, the short-lived erythrocyte-invading merozoite stage has never been observed to undergo gliding movement. Here we show Plasmodium merozoites possess the ability to undergo gliding motility in vitro and that this mechanism is likely an important precursor step for successful parasite invasion. We demonstrate that two human infective species, Plasmodium falciparum and Plasmodium knowlesi, have distinct merozoite motility profiles which may reflect distinct invasion strategies. Additionally, we develop and validate a higher throughput assay to evaluate the effects of genetic and pharmacological perturbations on both the molecular motor and the complex signaling cascade that regulates motility in merozoites. The discovery of merozoite motility provides a model to study the glideosome and adds a dimension for work aiming to develop treatments targeting the blood stage invasion pathways

Community prevalence of SARS-CoV-2 in England from April to November, 2020: results from the ONS Coronavirus Infection Survey

Background: Decisions about the continued need for control measures to contain the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rely on accurate and up-to-date information about the number of people testing positive for SARS-CoV-2 and risk factors for testing positive. Existing surveillance systems are generally not based on population samples and are not longitudinal in design. Methods: Samples were collected from individuals aged 2 years and older living in private households in England that were randomly selected from address lists and previous Office for National Statistics surveys in repeated cross-sectional household surveys with additional serial sampling and longitudinal follow-up. Participants completed a questionnaire and did nose and throat self-swabs. The percentage of individuals testing positive for SARS-CoV-2 RNA was estimated over time by use of dynamic multilevel regression and poststratification, to account for potential residual non-representativeness. Potential changes in risk factors for testing positive over time were also assessed. The study is registered with the ISRCTN Registry, ISRCTN21086382. Findings: Between April 26 and Nov 1, 2020, results were available from 1 191 170 samples from 280 327 individuals; 5231 samples were positive overall, from 3923 individuals. The percentage of people testing positive for SARS-CoV-2 changed substantially over time, with an initial decrease between April 26 and June 28, 2020, from 0·40% (95% credible interval 0·29–0·54) to 0·06% (0·04–0·07), followed by low levels during July and August, 2020, before substantial increases at the end of August, 2020, with percentages testing positive above 1% from the end of October, 2020. Having a patient-facing role and working outside your home were important risk factors for testing positive for SARS-CoV-2 at the end of the first wave (April 26 to June 28, 2020), but not in the second wave (from the end of August to Nov 1, 2020). Age (young adults, particularly those aged 17–24 years) was an important initial driver of increased positivity rates in the second wave. For example, the estimated percentage of individuals testing positive was more than six times higher in those aged 17–24 years than in those aged 70 years or older at the end of September, 2020. A substantial proportion of infections were in individuals not reporting symptoms around their positive test (45–68%, dependent on calendar time. Interpretation: Important risk factors for testing positive for SARS-CoV-2 varied substantially between the part of the first wave that was captured by the study (April to June, 2020) and the first part of the second wave of increased positivity rates (end of August to Nov 1, 2020), and a substantial proportion of infections were in individuals not reporting symptoms, indicating that continued monitoring for SARS-CoV-2 in the community will be important for managing the COVID-19 pandemic moving forwards. Funding: Department of Health and Social Care

De novo mutations in GRIN1 cause extensive bilateral polymicrogyria

Polymicrogyria is a malformation of cortical development. The aetiology of polymicrogyria remains poorly understood. Using whole-exome sequencing we found de novo heterozygous missense GRIN1 mutations in 2 of 57 parent-offspring trios with polymicrogyria. We found nine further de novo missense GRIN1 mutations in additional cortical malformation patients. Shared features in the patients were extensive bilateral polymicrogyria associated with severe developmental delay, postnatal microcephaly, cortical visual impairment and intractable epilepsy. GRIN1 encodes GluN1, the essential subunit of the N-methyl-d-aspartate receptor. The polymicrogyria-associated GRIN1 mutations tended to cluster in the S2 region (part of the ligand-binding domain of GluN1) or the adjacent M3 helix. These regions are rarely mutated in the normal population or in GRIN1 patients without polymicrogyria. Using two-electrode and whole-cell voltage-clamp analysis, we showed that the polymicrogyria-associated GRIN1 mutations significantly alter the in vitro activity of the receptor. Three of the mutations increased agonist potency while one reduced proton inhibition of the receptor. These results are striking because previous GRIN1 mutations have generally caused loss of function, and because N-methyl-d-aspartate receptor agonists have been used for many years to generate animal models of polymicrogyria. Overall, our results expand the phenotypic spectrum associated with GRIN1 mutations and highlight the important role of N-methyl-d-aspartate receptor signalling in the pathogenesis of polymicrogyria

Community prevalence of SARS-CoV-2 in England from April to November, 2020: results from the ONS Coronavirus Infection Survey

Background: Decisions about the continued need for control measures to contain the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rely on accurate and up-to-date information about the number of people testing positive for SARS-CoV-2 and risk factors for testing positive. Existing surveillance systems are generally not based on population samples and are not longitudinal in design. Methods: Samples were collected from individuals aged 2 years and older living in private households in England that were randomly selected from address lists and previous Office for National Statistics surveys in repeated crosssectional household surveys with additional serial sampling and longitudinal follow-up. Participants completed a questionnaire and did nose and throat self-swabs. The percentage of individuals testing positive for SARS-CoV-2 RNA was estimated over time by use of dynamic multilevel regression and poststratification, to account for potential residual non-representativeness. Potential changes in risk factors for testing positive over time were also assessed. The study is registered with the ISRCTN Registry, ISRCTN21086382. Findings: Between April 26 and Nov 1, 2020, results were available from 1 191 170 samples from 280327 individuals; 5231 samples were positive overall, from 3923 individuals. The percentage of people testing positive for SARS-CoV-2 changed substantially over time, with an initial decrease between April 26 and June 28, 2020, from 0·40% (95% credible interval 0·29–0·54) to 0·06% (0·04–0·07), followed by low levels during July and August, 2020, before substantial increases at the end of August, 2020, with percentages testing positive above 1% from the end of October, 2020. Having a patient facing role and working outside your home were important risk factors for testing positive for SARS-CoV-2 at the end of the first wave (April 26 to June 28, 2020), but not in the second wave (from the end of August to Nov 1, 2020). Age (young adults, particularly those aged 17–24 years) was an important initial driver of increased positivity rates in the second wave. For example, the estimated percentage of individuals testing positive was more than six times higher in those aged 17–24 years than in those aged 70 years or older at the end of September, 2020. A substantial proportion of infections were in individuals not reporting symptoms around their positive test (45–68%, dependent on calendar time. Interpretation: Important risk factors for testing positive for SARS-CoV-2 varied substantially between the part of the first wave that was captured by the study (April to June, 2020) and the first part of the second wave of increased positivity rates (end of August to Nov 1, 2020), and a substantial proportion of infections were in individuals not reporting symptoms, indicating that continued monitoring for SARS-CoV-2 in the community will be important for managing the COVID-19 pandemic moving forwards