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Lockdowns, restrictions on people's movements and gatherings, and other COVID-19 containment measures have had economic, social, and environmental effects. The pandemic resulted in major disruption to food systems, highlighting serious weaknesses in the way such systems are currently configured. However, the pandemic also created important opportunities to develop transformative actions enabling the creation of more resilient and sustainable food systems. In this paper, we delve more deeply into the strategies developed by consumers, as key stakeholders in the food system, through an in-depth survey and statistical analysis of changes in consumers' habits during the pandemic lockdowns. We adopt a city-region food system (CRFS) approach to explore ways to enhance food system resilience to future crises.Data were collected through a telephone survey of a representative sample (600 consumers), conducted in the region of Madrid in May 2021. First, descriptive analyses allowed different consumer strategies to be identified. Differences in food preferences and behaviour changes between individuals in the sample were analysed by age, gender, income, and level of education using exponential family Principal Component Analysis (EPCA), logistic regression, and Multiple Correspondence Analysis (MCA). Lastly, Principal Component Analysis (PCA) was applied to classify the consumer strategies into four discrete profiles.The findings show significant differences in consumers' responses according to age, income, and level of education. Additionally, the results highlight increased consumption of local and organic products, and online shopping, as typical strategies employed by consumers to respond to the COVID-19 pandemic. In this context, alternative food networks were shown to play a key role in enhancing food security. Interestingly, no significant differences were found between urban and rural areas. Our discussion addresses this apparent homogeneity in consumers’ habits from a resilient CRFS approach.

Abstract The WHO guidelines for classifying central nervous system (CNS) tumours are changing considerably with each release. The classification of CNS tumours is uniquely complex among most other solid tumours as it incorporates not just morphology, but also genetic and epigenetic features. Keeping current with these changes across medical fields can be challenging, even for clinical specialists. Large language models (LLMs) have demonstrated their ability to parse and process complex medical text, but their utility in neuro‐oncology has not been systematically tested. We hypothesised that LLMs can effectively diagnose neuro‐oncology cases from free‐text histopathology reports according to the latest WHO guidelines. To test this hypothesis, we evaluated the performance of ChatGPT‐4o, Claude‐3.5‐sonnet, and Llama3 across 30 challenging neuropathology cases, which each presented a complex mix of morphological and genetic information relevant to the diagnosis. Furthermore, we integrated these models with the latest WHO guidelines through Retrieval‐Augmented Generation (RAG) and again assessed their diagnostic accuracy. Our data show that LLMs equipped with RAG, but not without RAG, can accurately diagnose the neuropathological tumour subtype in 90% of the tested cases. This study lays the groundwork for a new generation of computational tools that can assist neuropathologists in their daily reporting practice.

Abstract Understanding the spatial distribution of world cultural heritage in its present-day geographical context is the foundation for the identification of and subsequent protection from key threats and vulnerabilities, particularly those arising from anthropogenic climate change. To address this challenge, we classified 45 Spanish world cultural heritage sites (WCHS) listed in the UNESCO register (as of 2023) according to type, entry date, and creation date. To establish a basis for a detailed analysis of the specific impact of climate change on the Spanish WCHS, a spatial cartographic database was developed showing the relationships between the WCHS and key geographical and climatic variables. We then used historical climate data, combined with a review of the impact mechanism of climate conditions on cultural heritage, to quantitatively evaluate the extent to which the WCHS in Spain are affected by local climate conditions from five aspects: freeze thaw cycle, thermal stress (thermoclastism), hydrodynamic scoring, corrosion, and biodegradation. Based on the above climate condition risks, we identified the five Spanish WCHS with the greatest potential climate condition risks, including Santiago de Compostela (Old Town), Pyrénées—Mont Perdu, the Roman Walls of Lugo, the Routes of Santiago de Compostela: Camino Francés and Routes of Northern Spain, and the Tower of Hercules. Additionally, based on different shared socioeconomic pathways (SSPs), we conducted a qualitative assessment of climate risk changes for WCHS in Spain under climate change. We found that the SSP1-2.6 scenario had the lowest climate risk, emphasizing the importance of achieving carbon neutrality for the protection of the WCHS. Our work translates historical climate conditions into specific climate risk levels for cultural heritage, providing data and theoretical support for effectively assessing the climate risks to Spanish WCHS.

This study presents the development and performance evaluation of an innovative thermal energy storage (TES) system utilizing a commercially available bioderived organic phase change material (PCM) for domestic hot water production. The primary objective of this research is to enhance the efficiency and effectiveness of thermal energy storage solutions by macro-encapsulating the PCM-expanded graphite (EG) compressed modules in a multi-pass tube arrangement. A comprehensive experimental setup was employed to investigate the thermal performance of the proposed TES unit, focusing on charging and discharging cycles. Key findings reveal that conduction is the dominant mode of heat transfer, with the system achieving a significant maximum average charging power of 1440 W and a discharging power of 1990 W. The thermal energy storage capacity reached an impressive 12.6 MJ, enabling the discharge of 90 % of stored energy within 90 min. Furthermore, the exergy analysis indicated high exergy efficiencies, with charging efficiencies reaching 98 % and overall exergy efficiency at 18 %.The implications of this research are significant, demonstrating the feasibility of using bioderived organic PCM for sustainable energy applications. It highlights the potential of the modular structure of the system to integrate with heat pump and solar energy systems, thereby enhancing efficiency and sustainability in domestic hot water applications. This work significantly contributes to the advancement of sustainable thermal energy storage technologies and establishes a solid foundation for future studies aimed at optimizing TES systems for domestic hot water production.

Integrative research approaches have lost prominence in the scientific literature, and related concepts of ‘wicked problems’ and ‘post-normal science’ complement but do not adequately replace them. From a detailed examination of the foundational literature, three key principles are shown to be central to integrative research: (i) the knowledge cycle; (ii) representativeness and participation; and (iii) knowledge exchange mechanisms at the science–policy interface. As an example of the importance of the integrative research framework in the context of policy-relevant science, it is argued that the shortcomings of current climate change mitigation efforts arise from inappropriately ‘closing down’ the science–policy interface and focusing on a few narrow options acceptable to powerful stakeholders. This can lead to what is described as an ‘ascientific’ ratchet effect, where the knowledge cycle just loops endlessly between technology and capital, and science as a public good is excluded. An integrative research approach can ‘open up’ discourse to new ideas and actors and restore the iterative links between science–policy mechanisms. A theoretical framework is proposed in which the three concepts ‘wicked problems’, ‘post-normal science’ and ‘integrative research’ are nested together. Integrative research is a way to address wicked problems, sitting within the critical framing of post-normal science.

Abstract Background There are currently no data on the relationship between frailty and mortality in pleural disease. Understanding the relationship between frailty and outcomes is increasingly important for clinicians to guide decisions regarding investigation and management. This study aims to explore the relationship between all-cause mortality and frailty status in patients with pleural disease. Methods In this retrospective analysis of a prospectively collected observational cohort study, outpatients presenting to the pleural service at a tertiary centre in Bristol, UK with a radiologically confirmed, undiagnosed pleural effusion underwent comprehensive assessment and were assigned a final diagnosis at 12 months. The modified frailty index (mFI) was calculated and participants classified as frail (mFI ≥ 0.4) or not frail (mFI ≤ 0.2). Results 676 participants were included from 3rd March 2008 to 29th December 2020. The median time to mortality was 490 days (IQR 161–1595). A positive association was found between 12-month mortality and frailty (aHR = 1.72, 95% CI 1.02–2.76, p = 0.025) and age ≥ 80 (aHR = 1.80, 95% CI 1.24–2.62, p = 0.002). Subgroup analyses found a stronger association between 12-month mortality and frailty in benign disease (aHR = 4.36, 95% CI 2.17–8.77, p

Abstract Deep Learning (DL) can predict biomarkers from cancer histopathology. Several clinically approved applications use this technology. Most approaches, however, predict categorical labels, whereas biomarkers are often continuous measurements. We hypothesize that regression-based DL outperforms classification-based DL. Therefore, we develop and evaluate a self-supervised attention-based weakly supervised regression method that predicts continuous biomarkers directly from 11,671 images of patients across nine cancer types. We test our method for multiple clinically and biologically relevant biomarkers: homologous recombination deficiency score, a clinically used pan-cancer biomarker, as well as markers of key biological processes in the tumor microenvironment. Using regression significantly enhances the accuracy of biomarker prediction, while also improving the predictions’ correspondence to regions of known clinical relevance over classification. In a large cohort of colorectal cancer patients, regression-based prediction scores provide a higher prognostic value than classification-based scores. Our open-source regression approach offers a promising alternative for continuous biomarker analysis in computational pathology.

Green infrastructure (GI) is increasingly prioritised in landscape policy and planning due to its potential to benefit ecosystems and enhance wildlife conservation. However, due to the uneven distribution of protected areas (PAs) and the fragmentation of habitats more generally, multi-level policy strategies are needed to create an integrated GI network bridging national, regional and local scales. In the province of Almeria, southeastern Spain, protected areas are mainly threatened by two land use/land cover changes. On the one hand, there is the advance of intensive greenhouse agriculture, which, between 1984 and 2007, increased in surface area by more than 58%. On the other hand, there is the growth of artificial surfaces, including urban areas (+64%), construction sites (+194%) and road infrastructures (+135%). To address this challenge, we present a proposal for green infrastructure deployment in the province of Almeria. We combine Geographic Information Systems (GISs) and multi-criteria evaluation (MCE) techniques to identify and evaluate suitability for key elements to be included in GI in two key ways. First, we identify the most suitable areas to form part of the GI in order to address vulnerability to degradation and fragmentation. Second, we propose 15 ecological corridors connecting the 35 protected areas of the province that act as core areas. The proposed GI network would extend along the western coast of the province and occupy the valleys of the main rivers. The river Almanzora plays a leading role. Due to its remoteness from the coast and its climatic conditions, it has not attracted intensive greenhouse agriculture and urban development, the main drivers of the transformation and fragmentation of traditional land uses. Around 50% of the area occupied by the proposed corridors would be located in places of medium and high suitability for the movement of species between core areas.

Phase Change Material (PCM) thermal energy storage systems have emerged as a promising solution for efficient thermal energy storage from low to very high-temperature applications. This paper presents an investigation into the utilization of medium temperature range PCM-based systems for domestic hot water application, focusing on different techniques to overcome the low thermal conductivity of the PCM. Five shell and tube heat exchangers were fabricated employing different heat transfer enhancement methods including fin, expanded graphite (EG), and a combination of fin and EG. The combination of EG and circular fins exhibited the best performance in terms of charging and discharging, maintaining a uniform temperature distribution throughout the system due to extensive conductive network provided by the combination of EG and circular fins. When the PCM/EG/fin heat exchanger system is fully charged, the energy stored in the system is 109% higher than that of the PCM heat exchanger at the same elapsed time. Furthermore, the PCM/EG/fin system demonstrated a faster discharging response compared to other thermal energy storage (TES) configurations, with over 160% higher discharging power than a system without any enhancement methods. These findings emphasize the practical viability of integrating PCM/EG composite materials into thermal energy storage systems, offering a viable solution for meeting high heat demand requirements in domestic hot water applications. Furthermore, the enhanced discharging response observed in the PCM/EG/fin system has significant implications for improving energy efficiency and reducing operational costs in real-world applications.

Introduction: We performed an exposure-based Next Generation Risk Assessment case read-across study using New Approach Methodologies (NAMs) to determine the highest safe concentration of daidzein in a body lotion, based on its similarities with its structural analogue, genistein. Two assumptions were: (1) daidzein is a new chemical and its dietary intake omitted; (2) only in vitro data were used for daidzein, while in vitro and legacy in vivo data for genistein were considered.Methods: The 10-step tiered approach evaluating systemic toxicity included toxicokinetics NAMs: PBPK models and in vitro biokinetics measurements in cells used for toxicogenomics and toxicodynamic NAMs: pharmacology profiling (i.e., interaction with molecular targets), toxicogenomics and EATS assays (endocrine disruption endpoints). Whole body rat and human PBPK models were used to convert external doses of genistein to plasma concentrations and in vitro Points of Departure (PoD) to external doses. The PBPK human dermal module was refined using in vitro human skin metabolism and penetration data.Results: The most relevant endpoint for daidzein was from the ERα assay (Lowest Observed Effective Concentration was 100 ± 0.0 nM), which was converted to an in vitro PoD of 33 nM. After application of a safety factor of 3.3 for intra-individual variability, the safe concentration of daidzein was estimated to be 10 nM. This was extrapolated to an external dose of 0.5 μg/cm2 for a body lotion and face cream, equating to a concentration of 0.1%.Discussion: When in vitro PoD of 33 nM for daidzein was converted to an external oral dose in rats, the value correlated with the in vivo NOAEL. This increased confidence that the rat oral PBPK model provided accurate estimates of internal and external exposure and that the in vitro PoD was relevant in the safety assessment of both chemicals. When plasma concentrations estimated from applications of 0.1% and 0.02% daidzein were used to calculate bioactivity exposure ratios, values were >1, indicating a good margin between exposure and concentrations causing adverse effects. In conclusion, this case study highlights the use of NAMs in a 10-step tiered workflow to conclude that the highest safe concentration of daidzein in a body lotion is 0.1%.

Abstract Aberrant expansion of KRT5+ basal cells in the distal lung accompanies progressive alveolar epithelial cell loss and tissue remodelling during fibrogenesis in idiopathic pulmonary fibrosis (IPF). The mechanisms determining activity of KRT5+ cells in IPF have not been delineated. Here, we reveal a potential mechanism by which KRT5+ cells migrate within the fibrotic lung, navigating regional differences in collagen topography. In vitro, KRT5+ cell migratory characteristics and expression of remodelling genes are modulated by extracellular matrix (ECM) composition and organisation. Mass spectrometry- based proteomics revealed compositional differences in ECM components secreted by primary human lung fibroblasts (HLF) from IPF patients compared to controls. Over-expression of ECM glycoprotein, Secreted Protein Acidic and Cysteine Rich (SPARC) in the IPF HLF matrix restricts KRT5+ cell migration in vitro. Together, our findings demonstrate how changes to the ECM in IPF directly influence KRT5+ cell behaviour and function contributing to remodelling events in the fibrotic niche.

We performed an ab initio next-generation risk assessment (NGRA) for a fragrance ingredient, benzyl salicylate (BSal), to demonstrate how cosmetic ingredients can be evaluated for systemic toxicity endpoints based on non-animal approaches. New approach methodologies (NAMs) used to predict the internal exposure included skin absorption assays, hepatocyte metabolism, and physiologically based pharmacokinetic (PBPK) modeling, and potential toxicodynamic effects were assessed using pharmacology profiling, ToxProfiler cell stress assay, transcriptomics in HepG2 and MCF-7 cells, ReproTracker developmental and reproductive toxicology (DART) assays, and cytotoxicity assays in human kidney cells. The outcome of the NGRA was compared to that of the traditional risk assessment approach based on animal data. The identification of the toxicologically critical entity was a critical step that directed the workflow and the selection of chemicals for PBPK modeling and testing in bioassays. The traditional risk assessment and NGRA identified salicylic acid (SA) as the “toxdriver.” A deterministic PBPK model for a single-day application of 1.54 g face cream containing 0.5% BSal estimated the Cmax for BSal (1 nM) to be much lower than that of its major in vitro metabolite, SA (93.2 nM). Therefore, SA was tested using toxicodynamics bioassays. The lowest points of departure (PoDs) were obtained from the toxicogenomics assays. The interpretation of these results by two companies and methods were similar (SA only results in significant gene deregulation in HepG2 cells), but PoD differed (213 μM and 10.6 µM). A probabilistic PBPK model for repeated applications of the face cream estimated the highest Cmax of SA to be 630 nM. The resulting margins of internal exposure (MoIE) using the PoDs were 338 and 16, which were more conservative than those derived from external exposure and in vivo PoDs (margin of safety values were 9,705). In conclusion, both traditional and ab initio NGRA approaches concluded that the daily application of BSal in a cosmetic leave-on face cream at 0.5% is safe for humans. The processing and interpretation of toxicogenomics data can lead to different PoDs, which can subsequently affect the calculation of the MoIE. This case study supports the use of NAMs in a tiered NGRA ab initio approach.

This study explores the potential correlation between income and exposure to air pollution for the city of Madrid, Spain and its neighboring municipalities. Madrid is a well-known European air pollution hotspot with a high mortality burden attributable to nitrogen dioxide (NO2) and fine particulate matter (PM2.5). Statistical analyses were carried out using electoral district level data on gross household income (GHI), and NO2 and PM2.5 concentrations in air obtained from a mesoscale air quality model for the study area. We applied linear regression, bivariate spatial correlation analysis, spatial autoregression and geographically weighted regression to explore the relationship between contaminants and income. Three different strategies were adopted to harmonize data for analysis. While some strategies suggested a link between income and air pollution, others did not, highlighting the need for multiple different approaches where uncertainty is high. Our findings offer important lessons for future spatial geographical studies of air pollution in cities worldwide. In particular we highlight the limitations of census-scale socio-economic data and the lack of non-model derived high-resolution air quality measurement data for many cities and offers lessons for policy makers on improving the integration of these types of essential public information.

Shortwave radiation penetrating beneath an ice-sheet surface can cause internal melting and the formation of a near-surface porous layer known as the weathering crust, a dynamic hydrological system that provides home to impurities and microbial life. We develop a mathematical model, incorporating thermodynamics and population dynamics, for the evolution of such layers. The model accounts for conservation of mass and energy, for internal and surface-absorbed radiation, and for logistic growth of a microbial species mediated by nutrients that are sourced from the melting ice. It also accounts for potential melt–albedo and microbe–albedo feedbacks, through the dependence of the absorption coefficient on the porosity or microbial concentration. We investigate one-dimensional steadily melting solutions of the model, which give rise to predictions for the weathering crust depth, water content, melt rate, and microbial abundance, depending on a number of parameters. In particular, we examine how these quantities depend on the forcing energy fluxes, finding that the relative amounts of shortwave (surface-penetrating) radiation and other heat fluxes are particularly important in determining the structure of the weathering crust. The results explain why weathering crusts form and disappear under different forcing conditions and suggest a range of possible changes in behaviour in response to climate change.

Microbial fuel cells (MFCs) are a promising technology to generate electricity from wastewater and reduce the organic content. Whilst there has been a significant enhancement in MFC efficiency arising from the introduction of novel materials and cell designs, challenges remain with respect to the performance, cost, and sustainability of anode materials. This paper reports the development of single chamber MFCs with a focus on novel, cost-effective, and recycled carbon-based anode materials, including Recycled Water Filter Block/Powder (RWFB/RWFP), Recycled Chopped Carbon Fibre (RCCF), Carbon Felt (CF) and Graphite Flexible powder (GFG). Anodes prepared from GFG were shown to provide high power density (342.8 mW/m2), followed by RCCF, CF, RWFP, RWFB and CF (77.6, 71.8, 59.0 and 57.9 mW/m2, respectively). Chemical Oxygen Demand (COD) reduction was measured initially and at day 30, with GFG anodes observed to remove 83% of the initial load, compared to RCCF, RWFB, RWFP and CF anodes, where COD reductions of 69%, 61%, 65% and 73% were observed, respectively. Electrochemical analysis and biofilm imaging confirmed recycled materials were colonised by microorganisms and performed to high standards. GFG offers significant promise as an anode material, with excellent performance supported by a reduction in capital cost of up to 90% in comparison to CF. The use of recycled carbon material as MFC anodes shows promise, but requires additional work to improve the stability and durability of systems to permit scale-up.

Abstract Background Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease that affects 3 million people worldwide. Senescence and small extracellular vesicles (sEVs) have been implicated in the pathogenesis of IPF, although how sEVs promote disease remains unclear. Here, we profile sEVs from bronchial epithelial cells and determine small RNA (smRNA) content. Methods Conditioned media was collected and sEVs were isolated from normal human bronchial epithelial cells (NHBEs) and IPF-diseased human bronchial epithelial cells (DHBEs). Results Increased sEV release from DHBEs compared to NHBEs (n = 4; p

The effect of increasing surface melt on annual discharge is unknown for the Greenland Ice Sheet. Here, the authors find that Greenland’s largest single-glacier contributor to sea-level rise accommodates basal floods following supraglacial lake-drainage events with limited impact on ice flow.

It is commonly asserted that there are two distinct classes of glacier surges: slow, long-duration ‘Svalbard-type’ surges, triggered by a transition from cold- to warm-based conditions (thermal switching), and fast, shorter-duration ‘Alaska-type’ surges triggered by a reorganisation of the basal drainage system (hydraulic switching). This classification, however, reflects neither the diversity of surges in Svalbard and Alaska (and other regions), nor the fundamental dynamic processes underlying all surges. We argue that enthalpy balance theory offers a framework for understanding the spectrum of glacier surging behaviours while emphasising their essential dynamic unity. In this paper, we summarise enthalpy balance theory, illustrate its potential to explain so-called ‘Svalbard-type’ and ‘Alaska-type’ surges using a single set of principles, and show examples of a much wider range of glacier surge behaviour than previously observed. We then identify some future directions for research, including strategies for testing predictions of the theory against field and remote sensing data, and priorities for numerical model development.

As researchers and ultimately deployers of energy decarbonisation solutions, we collectively see significant but often siloed efforts that in isolation may appear as an appropriate solution to an aspect of energy decarbonisation. However, when systemwide thinking is applied, a former attractive solution may become more challenging and, likewise, a less attractive silo may become more appropriate as part of an energy systemwide approach. Thus, the aim of this paper is to combine proposed energy decarbonisation concepts, e.g., electrification, hydrogen, biogas etc., with the status of the system in which they intend to operate, and then highlight the barriers, opportunities, and alternatives that may come into play when the whole system is taken into account. This is a hypothetical study using the city of Belfast, Northern Ireland, UK as an example and reflects, in part, the city’s desire to decarbonise while enhancing its economic prosperity. The “system” is defined as the region boundaries, i.e., Northern Ireland will supply the energy (all or in part) to the city of Belfast. The methodology deployed here therefore is a framework of energy thinking that is the basis of such energy decarbonisation plans at a city-wide level.

All cosmetic ingredients registered in Europe must be evaluated for their safety using non-animal methods. Microphysiological systems (MPS) offer a more complex higher tier model to evaluate chemicals. Having established a skin and liver HUMIMIC Chip2 model demonstrating how dosing scenarios impact the kinetics of chemicals, we investigated whether thyroid follicles could be incorporated to evaluate the potential of topically applied chemicals to cause endocrine disruption. This combination of models in the HUMIMIC Chip3 is new; therefore, we describe here how it was optimized using two chemicals known to inhibit thyroid production, daidzein and genistein. The MPS was comprised of Phenion® Full Thickness skin, liver spheroids and thyroid follicles co-cultured in the TissUse HUMIMIC Chip3. Endocrine disruption effects were determined according to changes in thyroid hormones, thyroxine (T4) and 3,3’,5-triiodothyronine (T3). A main part of the Chip3 model optimization was the replacement of freshly isolated thyroid follicles with thyrocyte-derived follicles. These were used in static incubations to demonstrate the inhibition of T4 and T3 production by genistein and daidzein over 4 days. Daidzein exhibited a lower inhibitory activity than genistein and both inhibitory activities were decreased after a 24 h preincubation with liver spheroids, indicating metabolism was via detoxification pathways. The skin-liver-thyroid Chip3 model was used to determine a consumer-relevant exposure to daidzein present in a body lotion based on thyroid effects. A “safe dose” of 0.235 μg/cm2 i.e., 0.047% applied in 0.5 mg/cm2 of body lotion was the highest concentration of daidzein which does not result in changes in T3 and T4 levels. This concentration correlated well with the value considered safe by regulators. In conclusion, the Chip3 model enabled the incorporation of the relevant exposure route (dermal), metabolism in the skin and liver, and the bioactivity endpoint (assessment of hormonal balance i.e., thyroid effects) into a single model. These conditions are closer to those in vivo than 2D cell/tissue assays lacking metabolic function. Importantly, it also allowed the assessment of repeated doses of chemical and a direct comparison of systemic and tissue concentrations with toxicodynamic effects over time, which is more realistic and relevant for safety assessment.

For the authorization of plant protection products, a quantitative non-dietary exposure risk assessment relies on established dermal exposure models, measured mainly using passive dosimetry. Exposure to the hands is determined via hand washing or using cotton gloves as a surrogate for skin. This study compared both methods using operator exposure data available from the Agricultural Operator Exposure Model (AOEM) project report. These data indicate that hand exposure determined using cotton gloves resulted in markedly higher exposure values for all exposure scenarios compared to those determined by hand washes. One explanation for this is that dermal uptake of the residues reduces the amount of residue that can be recovered by hand washing. Uncertainty due to dermal uptake can be addressed by either default assumptions or by specific dermal absorption data. However, this cannot solely account for the large difference observed between the values and is mainly likely to be due to the higher capacity of the cotton gloves vs. human skin to retain residues. The results further indicate that the variability between hand wash samples and cotton glove samples differs between the exposure scenarios. Hence, the level of conservatism related to the use of cotton gloves as surrogate skin remains unknown. In conclusion, this evaluation of the AOEM data indicates that the cotton glove method results in much higher levels of measured hand exposure than the hand wash method. It cannot be excluded that dermal uptake has contributed to that result. However, the findings suggest the higher retention capacity of cotton gloves vs. human skin to be the main impact parameter. The cotton glove method does not provide the results with regards to the protection level that can be expected from the use of protective gloves. Therefore, we believe that the application of the hand wash method is a more accurate measure of exposure levels, if either specific dermal absorption data or, in its absence, default assumptions are applied as adjustment factor.

Summary: The airway epithelium is a protective barrier that is maintained by the self-renewal and differentiation of basal stem cells. Increasing age is a principle risk factor for chronic lung diseases, but few studies have explored age-related molecular or functional changes in the airway epithelium. We retrieved epithelial biopsies from histologically normal tracheobronchial sites from pediatric and adult donors and compared their cellular composition and gene expression profile (in laser capture-microdissected whole epithelium, fluorescence-activated cell-sorted basal cells, and basal cells in cell culture). Histologically, pediatric and adult tracheobronchial epithelium was similar in composition. We observed age-associated changes in RNA sequencing studies, including higher interferon-associated gene expression in pediatric epithelium. In cell culture, pediatric cells had higher colony formation ability, sustained in vitro growth, and outcompeted adult cells in a direct competitive proliferation assay. Our results demonstrate cell-intrinsic differences between airway epithelial cells from children and adults in both homeostatic and proliferative states.

Ammonium nitrate is a major aerosol constituent over many land regions and contributes to air pollution episodes, ecosystem destruction, regional haze, and aerosol-induced climate forcing. Many climate models that represent ammonium nitrate assume that the ammonium–sulfate–nitrate chemistry reaches thermodynamic equilibrium instantaneously without considering kinetic limitations on condensation rates. The Met Office's Unified Model (UM) is employed to investigate the sensitivity of ammonium nitrate concentrations to the nitric acid uptake coefficient (γ) in a newly developed nitrate scheme in which first-order condensation theory is utilised to limit the rate at which thermodynamic equilibrium is attained. Two values of γ representing fast (γ=0.193) and slow (γ=0.001) uptake rates are tested in 20-year global UM integrations. The global burden of nitrate associated with ammonium in the “fast” simulation (0.11 Tg[N]) is twice as great as in the “slow” simulation (0.05 Tg[N]), while the top-of-the-atmosphere radiative impact of representing nitrate is −0.19 W m−2 in the fast simulation and −0.07 W m−2 in the slow simulation. In general, the fast simulation exhibits better spatial correlation with observed nitrate concentrations, while the slow simulation better resolves the magnitude of concentrations. Local near-surface nitrate concentrations are found to be highly correlated with seasonal ammonia emissions, suggesting that ammonia is the predominant limiting factor controlling nitrate prevalence. This study highlights the high sensitivity of ammonium nitrate concentrations to nitric acid uptake rates and provides a novel mechanism for reducing nitrate concentration biases in climate model simulations. The new UM nitrate scheme represents a step change in aerosol modelling capability in the UK across weather and climate timescales.

Abstract Advanced therapeutic medicinal products (ATMPs) have emerged as novel therapies for untreatable diseases, generating the need for large volumes of high‐quality, clinically‐compliant GMP cells to replace costly, high‐risk and limited scale manual expansion processes. We present the design of a fully automated, robot‐assisted platform incorporating the use of multiliter stirred tank bioreactors for scalable production of adherent human stem cells. The design addresses a needle‐to‐needle closed process incorporating automated bone marrow collection, cell isolation, expansion, and collection into cryovials for patient delivery. AUTOSTEM, a modular, adaptable, fully closed system ensures no direct operator interaction with biological material; all commands are performed through a graphic interface. Seeding of source material, process monitoring, feeding, sampling, harvesting and cryopreservation are automated within the closed platform, comprising two clean room levels enabling both open and closed processes. A bioprocess based on human MSCs expanded on microcarriers was used for proof of concept. Utilizing equivalent culture parameters, the AUTOSTEM robot‐assisted platform successfully performed cell expansion at the liter scale, generating results comparable to manual production, while maintaining cell quality postprocessing.

Melting at the base of the Greenland Ice Sheet is often disregarded as a source of quantifiable mass loss. In this study, the authors find the basal mass loss is equivalent to 8% of the ice sheet’s present imbalance, and that the loss of mass from basal melt is likely to increase in the future.

Abstract Background There is growing interest in the use of routine patient-reported outcome measures (PROMs) to influence the care of individual patients with stroke. However, there are significant gaps in our understanding as to how PROMs influence post-stroke patient care and clinical practice. This is due to factors including the number of purported uses for PROMs and that PROMs are complex interventions, which attempt to stimulate varied actions or behaviours. Therefore, the objective of this realist synthesis is to offer theory-based explanations as to how PROMs influence post-stroke clinical practice and patient care. Methods This is a protocol for a realist synthesis, which involves three distinct phases: theory building (phase 1), theory testing and refinement (phase 2) and synthesis (phase 3). Phase 1 will develop initial rough programme theories (IRPTs), through literature searches (from January 2000 onwards) of MEDLINE, EMBASE, PsycINFO, CINAHL, Cochrane Library and the grey literature. Only secondary sources will be included that contribute to the development of IRPTs. Only two IRPTs, prioritised by the stakeholder group, will be taken forward to be tested and refined during phase 2. Further novel searches will be employed in phase 2, utilising the same criteria as phase 1; however, phase 2 searches will not utilise grey literature searches, and only primary research studies that contribute to the refinement of programme theories under investigation will be included. Two independent reviewers will screen and select all returned results. The reviewers will code and annotate relevant sources, resulting in ‘fragments’ to be extracted and graded based on the richness of their contribution to explanation and causal insight. Further, these fragments will be organised into ‘Context-Mechanism-Outcome’ configurations. Phase 3 of the review will involve the synthesis of context-mechanism-outcome configurations to form middle-range theory-based explanations and developed logic models for stakeholders to understand how PROMs in post-stroke clinical practice and patient care work for whom, how and under what circumstances. Discussion The resulting realist synthesis will provide guidance on the implementation of PROMs within routine post-stroke clinical practice and patient care and act as a touchstone for further testing and refinement of PROMs programmes. Systematic review registration PROSPERO CRD42020138649 .

Billions of litres of wastewater are produced daily from domestic and industrial areas, and whilst wastewater is often perceived as a problem, it has the potential to be viewed as a rich source for resources and energy. Wastewater contains between four and five times more energy than is required to treat it, and is a potential source of bio-hydrogen—a clean energy vector, a feedstock chemical and a fuel, widely recognised to have a role in the decarbonisation of the future energy system. This paper investigates sustainable, low-energy intensive routes for hydrogen production from wastewater, critically analysing five technologies, namely photo-fermentation, dark fermentation, photocatalysis, microbial photo electrochemical processes and microbial electrolysis cells (MECs). The paper compares key parameters influencing H2 production yield, such as pH, temperature and reactor design, summarises the state of the art in each area, and highlights the scale-up technical challenges. In addition to H2 production, these processes can be used for partial wastewater remediation, providing at least 45% reduction in chemical oxygen demand (COD), and are suitable for integration into existing wastewater treatment plants. Key advancements in lab-based research are included, highlighting the potential for each technology to contribute to the development of clean energy. Whilst there have been efforts to scale dark fermentation, electro and photo chemical technologies are still at the early stages of development (Technology Readiness Levels below 4); therefore, pilot plants and demonstrators sited at wastewater treatment facilities are needed to assess commercial viability. As such, a multidisciplinary approach is needed to overcome the current barriers to implementation, integrating expertise in engineering, chemistry and microbiology with the commercial experience of both water and energy sectors. The review concludes by highlighting MECs as a promising technology, due to excellent system modularity, good hydrogen yield (3.6–7.9 L/L/d from synthetic wastewater) and the potential to remove up to 80% COD from influent streams.

Spray drift is an inescapable consequence of agricultural plant protection operation, which has always been one of the major concerns in the spray application industry. Spray drift evaluation is essential to provide a basis for the rational selection of spray technique and working surroundings. Nowadays, conventional sampling methods with passive collectors used in drift evaluation are complex, time-consuming, and labor-intensive. The aim of this paper is to present a method to evaluate spray drift based on 3D LiDAR sensor and to test the feasibility of alternatives to passive collectors. Firstly, a drift measurement algorithm was established based on point clouds data of 3D LiDAR. Wind tunnel tests included three types of agricultural nozzles, three pressure settings, and five wind speed settings were conducted. LiDAR sensor and passive collectors (polyethylene lines) were placed downwind from the nozzle to measure drift droplets in a vertical plane. Drift deposition volume on each line and the number of LiDAR droplet points in the corresponding height of the collecting line were calculated, and the influencing factors of this new method were analyzed. The results show that 3D LiDAR measurements provide a rich spatial information, such as the height and width of the drift droplet distribution, etc. High coefficients of determination (R2 > 0.75) were observed for drift points measured by 3D LiDAR compared to the deposition volume captured by passive collectors, and the anti-drift IDK12002 nozzle at 0.2 MPa spray pressure has the largest R2 value, which is 0.9583. Drift assessment with 3D LiDAR is sensitive to droplet density or drift mass in space and nozzle initial droplet spectrum; in general, larger droplet density or drift mass and smaller droplet size are not conducive to LiDAR detection, while the appropriate threshold range still needs further study. This study demonstrates that 3D LiDAR has the potential to be used as an alternative tool for rapid assessment of spray drift.

Acute anemia induces rapid expansion of erythroid precursors and accelerated differentiation to replenish erythrocytes. Paracrine signals—involving cooperation between stem cell factor (SCF)/Kit signaling and other signaling inputs—are required for the increased erythroid precursor activity in anemia. Our prior work revealed that the sterile alpha motif (SAM) domain 14 (Samd14) gene increases the regenerative capacity of the erythroid system in a mouse genetic model and promotes stress-dependent Kit signaling. However, the mechanism underlying Samd14’s role in stress erythropoiesis is unknown. We identified a protein-protein interaction between Samd14 and the α- and β-heterodimers of the F-actin capping protein (CP) complex. Knockdown of the CP β subunit increased erythroid maturation in murine ex vivo cultures and decreased colony forming potential of stress erythroid precursors. In a genetic complementation assay for Samd14 activity, our results revealed that the Samd14-CP interaction is a determinant of erythroid precursor cell levels and function. Samd14-CP promotes SCF/Kit signaling in CD71med spleen erythroid precursors. Given the roles of Kit signaling in hematopoiesis and Samd14 in Kit pathway activation, this mechanism may have pathological implications in acute/chronic anemia.

Abstract Background The COVID-19 pandemic has placed significant pressure on health and social care. Survivors of COVID-19 may be left with substantial functional deficits requiring ongoing care. We aimed to determine whether pre-admission frailty was associated with increased care needs at discharge for patients admitted to hospital with COVID-19. Methods Patients were included if aged over 18 years old and admitted to hospital with COVID-19 between 27 February and 10 June 2020. The Clinical Frailty Scale (CFS) was used to assess pre-admission frailty status. Admission and discharge care levels were recorded. Data were analysed using a mixed-effects logistic regression adjusted for age, sex, smoking status, comorbidities, and admission CRP as a marker of severity of disease. Results Thirteen hospitals included patients: 1671 patients were screened, and 840 were excluded including, 521 patients who died before discharge (31.1%). Of the 831 patients who were discharged, the median age was 71 years (IQR, 58–81 years) and 369 (44.4%) were women. The median length of hospital stay was 12 days (IQR 6–24). Using the CFS, 438 (47.0%) were living with frailty (≥ CFS 5), and 193 (23.2%) required an increase in the level of care provided. Multivariable analysis showed that frailty was associated with an increase in care needs compared to patients without frailty (CFS 1–3). The adjusted odds ratios (aOR) were as follows: CFS 4, 1.99 (0.97–4.11); CFS 5, 3.77 (1.94–7.32); CFS 6, 4.04 (2.09–7.82); CFS 7, 2.16 (1.12–4.20); and CFS 8, 3.19 (1.06–9.56). Conclusions Around a quarter of patients admitted with COVID-19 had increased care needs at discharge. Pre-admission frailty was strongly associated with the need for an increased level of care at discharge. Our results have implications for service planning and public health policy as well as a person's functional outcome, suggesting that frailty screening should be utilised for predictive modelling and early individualised discharge planning.

Abstract Background Post-operative delirium is an important, yet under-researched complication of surgery. Patients undergoing urological surgery may be at especially high risk of POD, as they are often older, and interventions can be associated with conditions that trigger delirium. The main aim of this systematic review was to evaluate the available evidence for risk factors in this patient group. Methods Five databases were searched (MEDLINE, Web of Science, EMBASE, CINAHL and PsychInfo) between January 1987 and June 2019. The Newcastle–Ottawa Scale was used to assess for risk of bias. Pooled odds ratio or mean difference (MD) for individual risk factors were estimated using the Mantel–Haenzel and inverse variance methods. Results Seven articles met the inclusion criteria, giving a total population of 1937. The incidence of POD ranged from 5 to 29%. Three studies were deemed low risk of bias and four at a high risk of bias. Nine risk factors were suitable for meta-analysis, with age (MD 4.314 95% CI 1.597, 7.032 p = 0.002) and the clock drawing test (MD − 2.443 95% CI − 3.029, − 1.857 p

The study was conducted at the University of Nebraska Pesticide Application and Technology Laboratory in North Platte, Nebraska in July 2015. Two application volume rates (100 and 200 l · ha−1) and three nozzle types (XR, AIXR, TTI) were selected at two flow rates (0.8 and 1.6 l · min−1) and at a single application speed of 7.7 km · h−1. Each collector type [Mylar washed (MW), Mylar image analysis (MIA), water-sensitive paper (WSP), and Kromekote (KK)] was arranged in a randomized complete block design. Each nozzle treatment was replicated twice, providing six cards of each collector type for each nozzle treatment. A water + 0.4% v/v Rhodamine WT spray solution was applied, given the fluorescent and visible qualities of Rhodamine, which allows it to be applied over all the collector types. MW had the highest coverage at 18.3% across nozzle type, followed by WSP at 18%, KK at 12% and lastly by MIA at 4%. MW resulted in a 58% increase in coverage, WSP in a 56% increase, and KK only an increase of 39% when the volume rate was doubled from 100 l · ha−1 to 200 l · ha−1 across nozzle type. MW coverage was similar to KK for half of the nozzles (XR 11002, XR 11004, AIXR 11002). Droplet number density fixed effects were all significant for nozzle type and collector type (p < 0.001) as was the interaction of nozzle type and collector type (p < 0.001). Results from this study suggest a strong correlation to data produced with WSP and MW collectors, as there was full agreement between both types except for the TTI 11004. Using both collector types in the same study would allow for a visual understanding of the distribution of the spray, while also giving an idea of the concentration of that distribution.

Here we present a description of the UKCA StratTrop chemical mechanism, which is used in the UKESM1 Earth system model for CMIP6. The StratTrop chemical mechanism is a merger of previously well-evaluated tropospheric and stratospheric mechanisms, and we provide results from a series of bespoke integrations to assess the overall performance of the model. We find that the StratTrop scheme performs well when compared to a wide array of observations. The analysis we present here focuses on key components of atmospheric composition, namely the performance of the model to simulate ozone in the stratosphere and troposphere and constituents that are important for ozone in these regions. We find that the results obtained for tropospheric ozone and its budget terms from the use of the StratTrop mechanism are sensitive to the host model; simulations with the same chemical mechanism run in an earlier version of the MetUM host model show a range of sensitivity to emissions that the current model does not fall within. Whilst the general model performance is suitable for use in the UKESM1 CMIP6 integrations, we note some shortcomings in the scheme that future targeted studies will address.

Background Fibrotic interstitial lung disease (fILD) has previously been associated with the presence of autoantibody. While studies have focused on systemic autoimmunity, the role of local autoantibodies in the airways remains unknown. We therefore extensively characterised the airway and peripheral autoantibody profiles in patients with fILD, and assessed association with disease severity and outcome. Methods Bronchoalveolar lavage (BAL) fluid was collected from a cohort of fILD patients and total BAL antibody concentrations were quantified. An autoantigen microarray was used to measure IgG and IgA autoantibodies against 122 autoantigens in BAL from 40 idiopathic pulmonary fibrosis (IPF), 20 chronic hypersensitivity pneumonitis (CHP), 20 connective tissue disease-associated ILD (CTD-ILD) patients and 20 controls. Results A subset of patients with fILD but not healthy controls had a local autoimmune signature in their BAL that was not present systemically, regardless of disease. The proportion of patients with IPF with a local autoantibody signature was comparable to that of CTD-ILD, which has a known autoimmune pathology, identifying a potentially novel subset of patients. The presence of an airway autoimmune signature was not associated with reduced survival probability or changes in lung function in the cohort as a whole. Patients with IPF had increased BAL total IgA and IgG1 while subjects with CHP had increased BAL IgA, IgG1 and IgG4. In patients with CHP, increased BAL total IgA was associated with reduced survival probability. Conclusion Airway autoantibodies that are not present systemically identify a group of patients with fILD and the mechanisms by which these autoantibodies contribute to disease requires further investigation.

Ethical and legal considerations have led to increased use of non-animal methods to evaluate the safety of chemicals for human use. We describe the development and qualification of a physiologically-based kinetics (PBK) model for the cosmetic UV filter ingredient, homosalate, to support its safety without the need of generating further animal data. The intravenous (IV) rat PBK model, using PK-Sim®, was developed and validated using legacy in vivo data generated prior to the 2013 EU animal-testing ban. Input data included literature or predicted physicochemical and pharmacokinetic properties. The refined IV rat PBK model was subject to sensitivity analysis to identify homosalate-specific sensitive parameters impacting the prediction of Cmax (more sensitive than AUC(0-∞)). These were then considered, together with population modeling, to calculate the confidence interval (CI) 95% Cmax and AUC(0-∞). Final model parameters were established by visual inspection of the simulations and biological plausibility. The IV rat model was extrapolated to oral administration, and used to estimate internal exposures to doses tested in an oral repeated dose toxicity study. Next, a human PBK dermal model was developed using measured human in vitro ADME data and a module to represent the dermal route. Model performance was confirmed by comparing predicted and measured values from a US-FDA clinical trial (Identifier: NCT03582215, https://clinicaltrials.gov/). Final exposure estimations were obtained in a virtual population and considering the in vitro and input parameter uncertainty. This model was then used to estimate the Cmax and AUC(0–24 h) of homosalate according to consumer use in a sunscreen. The developed rat and human PBK models had a good biological basis and reproduced in vivo legacy rat and human clinical kinetics data. They also complied with the most recent WHO and OECD recommendations for assessing the confidence level. In conclusion, we have developed a PBK model which predicted reasonably well the internal exposure of homosalate according to different exposure scenarios with a medium to high level of confidence. In the absence of in vivo data, such human PBK models will be the heart of future completely non-animal risk assessments; therefore, valid approaches will be key in gaining their regulatory acceptance.Clinical Trial Registration: https://clinicaltrials.gov/, identifier, NCT03582215

Electric Vehicles (EVs) replace fossil fuel vehicles in effort towards having more sustainable transport systems. The battery of an EV is recharged at a charging point using electricity. While some recharging will be required at locations where vehicles are normally parked, other recharging could be necessary at strategic locations of vehicular travel. Certain locations are suitable for EV charging station deployment, others are not. A multi-stage decision analysis methodology for selecting suitable locations for installing EV charging station is presented. The multi-stage approach makes it possible to select critical criteria with respect to any defined objectives of the EV charging station and techno-physio-socio-economic factors without which the EV charging station could not be deployed or would not serve its designated purpose. In a case, the type of charging station is specified, and a purpose is defined: rapid EV charging stations intended for public use within and across border regions. Applied in siting real EV charging stations at optimal locations, stages in the methodology present additional techno-physio-socio-economic factors in deploying the type of EV charging stations at optimal locations and keep the EV charging stations operating within acceptable standards. Some locations were dropped at the critical analysis stage; others were dropped at the site-specific analysis stage and replacement sites were required in certain instances. Final locations included most optimal, less optimal, least optimal, and strategic or special need locations. The average distances between contiguous recharging locations were less than 60 miles. Using any specified separation standard, the number of additional EV charging stations required between EV charging stations were determinable with the Pool Box. The Overall Charging Station Availability quadrants suggest that the overall user experience could get worse as less-standardized additional EV charging stations are deployed.

Spatial planning systems at local and regional levels are often not well-adapted to the growth of small-scale and local social innovations in renewable energy. Participatory decision support tools have been developed to support the implementation of many areas of environmental policy, but are less common in energy contexts. In response to this knowledge gap, we discuss, compare and contrast the participatory development of two different types of digital support tools for the cases of Spain and the Netherlands, leading to insights into the characteristics that local-level stakeholders find particularly desirable. We adopt an integrative approach, hybridizing implementation theory and action research for, respectively, analysis of implementation characteristics of key actors, and knowledge co-construction with participant stakeholders. The tools developed represent two extremes of the spatial decision support tool spectrum, a simple touchscreen application on the one hand (COLLAGE) and a more complicated spatial model on the other (APoLUS). COLLAGE was used and well-liked by stakeholders, whereas APoLUS was not adopted by the participant group, who nevertheless contributed much essential information to its development. We identify eight key differences between the two tools which shed light on the nature of bottom-up energy transition processes: 1: Target users; 2: Target scale of action; 3: Relevance to users’ needs; 4: Interactive quality; 5: Key emphasis; 6: Level of complexity; 7: Ease of communication of tool rationale; 8: Cost. The differences between these tools also relate to a recognized dichotomy in sustainability transition research, with complex spatial support systems like APoLUS tending towards descriptive-analytical modes of sustainability science and simpler tools like COLLAGE being more clearly related to transformational modes. Approaches to supporting local-scale energy transitions that are able to span both modes are likely to become increasingly relevant as the climate crisis evolves. We also identify a research gap between support tools for implementation of established policy and support tools for transformative actions at local scales, and suggest the study of digital “transition support tools” as a promising avenue for future research.

Abstract We document the development of the first version of the U.K. Earth System Model UKESM1. The model represents a major advance on its predecessor HadGEM2‐ES, with enhancements to all component models and new feedback mechanisms. These include a new core physical model with a well‐resolved stratosphere; terrestrial biogeochemistry with coupled carbon and nitrogen cycles and enhanced land management; tropospheric‐stratospheric chemistry allowing the holistic simulation of radiative forcing from ozone, methane, and nitrous oxide; two‐moment, five‐species, modal aerosol; and ocean biogeochemistry with two‐way coupling to the carbon cycle and atmospheric aerosols. The complexity of coupling between the ocean, land, and atmosphere physical climate and biogeochemical cycles in UKESM1 is unprecedented for an Earth system model. We describe in detail the process by which the coupled model was developed and tuned to achieve acceptable performance in key physical and Earth system quantities and discuss the challenges involved in mitigating biases in a model with complex connections between its components. Overall, the model performs well, with a stable pre‐industrial state and good agreement with observations in the latter period of its historical simulations. However, global mean surface temperature exhibits stronger‐than‐observed cooling from 1950 to 1970, followed by rapid warming from 1980 to 2014. Metrics from idealized simulations show a high climate sensitivity relative to previous generations of models: Equilibrium climate sensitivity is 5.4 K, transient climate response ranges from 2.68 to 2.85 K, and transient climate response to cumulative emissions is 2.49 to 2.66 K TtC−1.