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The Malaise trap is a popular device for assessing diverse terrestrial arthropod communities because it collects large samples with modest effort. A number of factors influence its collection efficiency, placement being one of them. For instance, when designing larger biotic surveys using arrays of Malaise traps we need to know the optimal distance between individual traps that maximises observable species richness and community composition. We examined the influence of spacing between Malaise traps by metabarcoding samples from two field experiments at a site in Waterloo, Ontario, Canada. For one experiment, we used two trap pairs deployed at weekly increasing distances (3 m increments from 3 to 30 m). The second experiment involved a total of 10 traps set up in a row at 3 m distance intervals for three consecutive weeks. Results show that community similarity of samples decreases over distance between traps. The amount of species shared between trap pairs drops considerably at about 18 m trap-to-trap distance. This change can be observed across all major taxonomic groups and for two different habitat types (grassland and forest). Large numbers of OTUs found only once within samples cause rather large dissimilarity between distance pairs even at close proximity. This could be caused by a large number of transient species from adjacent habitats which arrive at the trap through passive transport, as well as capture of rare taxa, which end up in different traps by chance.

Abstract Background Sexual and gender minority (SGM) persons experience substantial mental health disparities throughout the life course, including increased vulnerability to depression and suicide. Few existing studies, however, have explored how pervasive experiences of SGM-related stigma, discrimination, and trauma (i.e., minority stress) contribute to adverse mental health outcomes among diverse sub-populations of SGM adults living in rural areas of the United States. This paper describes the protocol for a prospective cohort study, “Rural Exploration and Approaches for LGBTQ + Mental Health (REALM),” that will explore minority stress in relation to mental health conditions and suicidal behaviors among rural SGM adults. Methods Online processes will be used to recruit and enroll a diverse sample of up to 2,500 SGM adults aged 18 + living in rural counties and small metropolitan areas in the United States to complete an online baseline survey. This will include: up to 1,000 cisgender sexual minority persons (up to n = 500 each cisgender women and cisgender men); and up to 1,500 gender minority persons (up to n = 500 persons who were assigned male at birth and identify as a woman, female, and/or transfeminine; up to n = 500 persons who were assigned female at birth and identify as a man, male, and/or transmasculine; and up to n = 500 persons who identify as some other gender, including non-binary, gender non-conforming, and/or agender regardless of sex assigned at birth). All enrolled participants will subsequently be followed over a 12-month period, with repeated surveys at three-month intervals. Included survey measures will focus on sociodemographic information, mental health, substance use, suicidal behaviors, minority stressors, psychological processes, and other related risk and protective factors. Discussion This study presents a critical opportunity to better understand how minority stress contributes to adverse mental health outcomes among populations that remain underrepresented in research and programs in 2024. Results will be used to create more targeted, acceptable, and impactful intervention content and strategies that mitigate stigma, promote mental health, and prevent suicidal behaviors among rural SGM adults.

Abstract Two-dimensional materials with flat electronic bands are promising for realising exotic quantum phenomena such as unconventional superconductivity and nontrivial topology. However, exploring their vast chemical space is a significant challenge. Here we introduce elf, an unsupervised convolutional autoencoder that encodes electronic band structure images into fingerprint vectors, enabling the autonomous clustering of materials by electronic properties beyond traditional chemical paradigms. Unsupervised visualisation of the fingerprint space then uncovers hidden chemical trends and identifies promising candidates based on similarities to well-studied exemplars. This approach complements high-throughput ab initio methods by rapidly screening candidates and guiding further investigations into the mechanisms underlying flat-band physics. The elf autoencoder is a powerful tool for autonomous discovery of unexplored flat-band materials, enabling unbiased identification of compounds with desirable electronic properties across the 2D chemical space.

Abstract Immunotherapy is improving the survival of patients with metastatic non-small cell lung cancer (NSCLC), yet reliable biomarkers are needed to identify responders prospectively and optimize patient care. In this study, we explore the benefits of multimodal approaches to predict immunotherapy outcome using multiple machine learning algorithms and integration strategies. We analyze baseline multimodal data from a cohort of 317 metastatic NSCLC patients treated with first-line immunotherapy, including positron emission tomography images, digitized pathological slides, bulk transcriptomic profiles, and clinical information. Testing multiple integration strategies, most of them yield multimodal models surpassing both the best unimodal models and established univariate biomarkers, such as PD-L1 expression. Additionally, several multimodal combinations demonstrate improved patient risk stratification compared to models built with routine clinical features only. Our study thus provides evidence of the superiority of multimodal over unimodal approaches, advocating for the collection of large multimodal NSCLC datasets to develop and validate robust and powerful immunotherapy biomarkers.

Abstract Background [18F] Fluorodeoxyglucose (FDG) PET-CT is a clinical imaging modality widely used in diagnosing and staging lung cancer. The clinical findings of PET-CT studies are contained within free text reports, which can currently only be categorised by experts manually reading them. Pre-trained transformer-based language models (PLMs) have shown success in extracting complex linguistic features from text. Accordingly, we developed a multi-task ‘TNMu’ classifier to classify the presence/absence of tumour, node, metastasis (‘TNM’) findings (as defined by The Eight Edition of TNM Staging for Lung Cancer). This is combined with an uncertainty classification task (‘u’) to account for studies with ambiguous TNM status. Methods 2498 reports were annotated by a nuclear medicine physician and split into train, validation, and test datasets. For additional evaluation an external dataset (n = 461 reports) was created, and annotated by two nuclear medicine physicians with agreement reached on all examples. We trained and evaluated eleven publicly available PLMs to determine which is most effective for PET-CT reports, and compared multi-task, single task and traditional machine learning approaches. Results We find that a multi-task approach with GatorTron as PLM achieves the best performance, with an overall accuracy (all four tasks correct) of 84% and a Hamming loss of 0.05 on the internal test dataset, and 79% and 0.07 on the external test dataset. Performance on the individual TNM tasks approached expert performance with macro average F1 scores of 0.91, 0.95 and 0.90 respectively on external data. For uncertainty an F1 of 0.77 is achieved. Conclusions Our ‘TNMu’ classifier successfully extracts TNM staging information from internal and external PET-CT reports. We concluded that multi-task approaches result in the best performance, and better computational efficiency over single task PLM approaches. We believe these models can improve PET-CT services by assisting in auditing, creating research cohorts, and developing decision support systems. Our approach to handling uncertainty represents a novel first step but has room for further refinement.

Abstract Ethylene glycol (EG) is a versatile molecule produced in the petrochemical industry and is widely used to manufacture plastic polymers, anti-freeze, and automotive fluids. Biotechnological production of EG from xylose, a pentose present in lignocellulose biomass hydrolysates, has been achieved by the engineering of bacteria, such as Escherichia coli and Enterobacter cloacae, and the yeast Saccharomyces cerevisiae with synthetic pathways. In the present work, the Dahms pathway was employed to construct Komagataella phaffii strains capable of producing EG from xylose. Different combinations of the four enzymes that compose the synthetic pathway, namely, xylose dehydrogenase, xylonate dehydratase, dehydro-deoxy-xylonate aldolase, and glycolaldehyde reductase, were successfully expressed in K. phaffii. Increased production of EG (1.31 g/L) was achieved by employing a newly identified xylonate dehydratase (xylD-HL). This xylonate dehydratase allowed 30% higher EG production than a previously known xylonate dehydratase (xylD-CC). Further strain engineering demonstrated that K. phaffii possesses native glycolaldehyde reduction and oxidation activities, which lead to pathway deviation from EG to glycolic acid (GA) production. Finally, cultivation conditions that favor the production of EG over GA were determined.

Abstract This article describes a Patient and Public Involvement (PPI) led creative workshop space held within a clinical trial of a talking therapy for distressing voices (AVATAR2). PPI adds significant value to clinical research and ensures the work is meaningful to patients and their supporters. However, known issues include tokenism, a common power imbalance between PPI colleagues and researchers and a lack of opportunity for PPI to shape the research. PPI has played a key role at all stages of the AVATAR2 trial, including design, recruitment of staff and participants, data collection, analysis, and dissemination. An active and creative group of people was established, with over 30 members flexibly involved across all four sites. PPI group members were from diverse backgrounds, with lived experience of mental health conditions and recovery, and including carers. During this work, PPI colleagues identified that they would value a creative space which would help to promote the study but extend beyond an exclusive focus on trial deliverables. A regular creative workshop was established to support PPI colleagues in their creative work, including material such as poetry, blogs, art and podcasts. PPI colleagues and trial staff have cowritten a reflective piece to share their experiences on the impact of the creative workshops, organised into four themes. We found the workshops to be a powerful tool for forging relationships among trial staff and PPI colleagues, while also fostering personal development. We reflected on how the workshops built up the confidence of attendees and supported demanding trial activities such as public speaking. Finally, we discussed the impact of the workshops on wider trial culture, by upholding the values of the team and challenging the status quo.

Abstract Background As the impact of the SARS-CoV-2 pandemic extends into 2023 and beyond, the treatment and outcomes of infected patients continues to evolve. Unlike earlier in the pandemic there are now further infectious disease pressures placed on hospitals, which influence patient care and triage decisions. Methods The manuscript uses individual patient records linked with associated hospital management information of system pressure characteristics to attribute COVID-19 hospitalisation fatality risks (HFR) to patients and hospitals, using generalised additive mixed effects models. Results Between 01 September 2022 and 09 October 2023, the COVID-19 hospitalisation fatality risk in England was estimated as 12.71% (95% confidence interval (CI) 12.53%, 12.88%). Staff absences had an adjusted odds ratio of 1.038 (95% CI 1.017, 1.060) associated with the HFR when accounting for patient and hospital characteristics. Interpretation This observational research presents evidence that a range of local hospital effects can have a meaningful impact on the risk of death from COVID-19 once hospitalised and should be accounted for when reporting estimates. We show that both the patient case mix and hospital pressures impact estimates of patient outcomes.

Abstract Background The management of acute type A aortic dissection (ATAAD) using the Ascyrus Medical Dissection Stent (AMDS) can lead to complications due to the persistence of the false lumen (FL). This case report presents two instances of failed AMDS treatment for ATAAD, highlighting the novel use of a trifurcated hybrid prosthesis for redo aortic arch repair using a minimally invasive frozen elephant trunk (FET) technique. Case Presentation Case 1: A 57-year-old male, previously treated with AMDS for ATAAD, presented with an enlarging aortic arch and persistent FL two years post-surgery caused by re-entry in the distal aortic arch. Redo surgery using the FET technique with an E-vita OPEN NEO Trifurcated hybrid prosthesis resulted in successful repair and partial FL thrombosis. Case 2: A 51-year-old male with prior AMDS treatment for ATAAD presented with severe aortic valve regurgitation and a maintained FL perfusion due to a residual re-entry in the proximal region of the descending aorta. Redo surgery using the FET technique with the same hybrid prosthesis led to successful repair and good recovery, confirmed by follow-up imaging. Conclusions The use of the E-vita OPEN NEO Trifurcated hybrid prosthesis in the FET technique offers a promising solution for redo aortic arch repair in cases of failed AMDS treatment for ATAAD. This approach can improve patient outcomes by addressing complications associated with persistent FL and enhancing long-term survival.

OBJECTIVES: Physicians have been shown to have lower mortality compared to the general population, particularly regarding lifestyle-associated causes of death. Prior literature is divided on whether this is due to higher socioeconomic position (SEP), healthier lifestyle, or other specific occupational characteristics. This study analyzed the mortality of Austrian physicians compared to the general population and other (health) professionals with a similar SEP, and investigated patterns of lifestyle-associated mortality among physicians. METHODS: Data from professional associations and cause-of-death statistics were collated to determine causes of death for all occupational groups. Gender-specific age-standardized mortality rates (ASMR) and standardized rate ratios (SRR) were calculated to compare main causes of death [cancer, cardiovascular disease (CVD), external causes] among physicians to other (health) professionals and the general population. Standardized mortality ratios (SMR) were calculated for more detailed causes of death in physicians compared to the general population. RESULTS: Physicians had lower all-cause mortality than the general population [SRR 0.45, 95% confidence interval (CI) 0.41–0.49 for males and SRR 0.60, 95% CI 0.54–0.66 for females] and health professionals (SRR 0.72, 95% CI 0.60–0.88 for males and SRR 0.77, 95% CI 0.63–0.93 for females), mostly due to low CVD and cancer mortality. SMR for detailed causes of death among physicians exhibited a pattern of particularly low mortality in lifestyle-associated causes of death and an increased SMR for suicide among female physicians (SMR 1.58, 95% CI 1.22–2.02). CONCLUSIONS: This study confirmed lower mortality among physicians compared to the general population and compared to other (health) professionals. Low physician mortality can be primarily explained by lifestyle-associated causes of death.

Abstract Mitral regurgitation (MR) is associated with morphological and functional alterations of left atrium (LA) and ventricle (LV), possibly inducing LA–LV misalignment. We aimed to: (1) characterize angulation between LA and mitral annulus from conventional cine MRI data and feature-tracking (FT) contours, (2) assess their associations with functional capacity in MR patients, as assessed by oxygen consumption (peak-VO2) and minute ventilation to carbon dioxide production (VE/VCO2) slope, in comparison with MRI LA/LV strain indices. Thirty-two asymptomatic primary MR patients (56 [40; 66] years, 12 women) underwent cardiac MRI resulting in LA/LV conventional FT-derived strain indices. Then, end-diastolic angles were derived from FT LA contours: (1) α, centered on the LA centre of mass and defined by mitral valve extremities, (2) γ, centered on the mitral ring anterior/lateral side, and defined by LA centre and the other extremity of the mitral ring. Cardiopulmonary exercise testing with simultaneous echocardiography were also performed; peak-VO2 and VE/VCO2 slope were measured. While peak-VO2 and VE/VCO2 slope were not correlated to LA/LV strains, they were significantly associated with angles (α: r = 0.50, p = 0.003 and r = − 0.52, p = 0.003; γ: r = − 0.53, p = 0.002 and r = 0.52, p = 0.003; respectively), independently of age and gender (R2 ≥ 0.29, p ≤ 0.03). In primary MR, the new LA/mitral annulus angles, computed directly from standard-of-care MRI, are better correlated to exercise tolerance than conventional LA/LV strain.

The mesenteric extension of small neuroendocrine tumors is the surgical limiting factor because of the risk of postoperative short bowel syndrome due to superior mesenteric artery involvement. Recent pathological studies have shown that this vascular involvement is due to mesenteric tumor deposits, differentiated from lymph node metastases. The aim of this study was to evaluate the performances of computed tomography (CT) for the surgical planning of small intestine neuroendocrine tumors. This was a retrospective observational study, and all patients undergoing surgery for small intestine neuroendocrine tumor between January 2014 and March 2019 were included. Preoperative CTs were reviewed, blinded from surgical and pathological data, by two radiologists. Diagnostic accuracy and interobserver reliability analysis were performed. We included 45 patients (mean age: 61 years (28–84 years); 23 men). The CT sensitivity to identify the mesenteric mass was 97% (37/38) with a ĸ of 0.73. The positive predictive value of CT to anticipate a right colic resection was 86% (18/21). The negative predictive value of CT was high (97% (34/35) to 100% (35/35)) for duodenal resection (ĸ = 0.78). Regarding retropancreatic lymph node invasion, the CT sensitivity was poor (24%, 4/17), with a high ĸ (0.88). The level of involvement by the mesenteric mass was correlated with the length and the percentage of the remaining small bowel. CT is essential for the surgical planning of small intestine neuroendocrine tumors, being accurate in defining the mesenteric tumor deposits, allowing one to anticipate, with a good reproducibility, the length and percentage of the remaining small bowel and the necessity for a right colectomy.

Play Performance class at the English Language Education Study Program of Sanata Dharma University is designed to introduce students to fundamental concepts of drama and elaborate underlying principles of drama performance that come into play. In this course, not only do students learn about drama aspects, but they are also actively encouraged to practice and perform their soft skills in dealing with various challenges in preparing the performances. The researchers focused on finding out students’ academic self-efficacy in dealing with diverse challenges in this class. The researchers analyzed 29 students’ progress test 1, progress test 2, and final test reflection to investigate the students’ academic self-efficacy developments and factors contributing to the academic self-efficacy. The results showed that most students considered themselves not having self-efficacy at the beginning of the class. However, after facing several challenges, students’ academic self-efficacy was growing. This study illuminates the positive impact of giving students challenges to foster self-efficacy while practicing their English skills. The findings imply that educators should provide students enough opportunities to grow from both successes and failures in the context of academic journey and provide adequate supports during the period.

Abstract Available evidence suggests that various medical/rehabilitation treatments evoke multiple effects on blood hemostasis. It was therefore the aim of our study to examine whether fascial manipulation, vibration exercise, motor imagery, or neuro‐muscular electrical stimulation can activate the coagulation system, and, thereby, expose patients to thrombotic risk. Ten healthy young subject were enrolled in the study. Blood samples were obtained pre and posttreatment. Besides standard laboratory methods, calibrated automated thrombography (CAT) and thrombelastometry (TEM) were used allowing sensitive detection of hyper‐ and hypocoagulable states. Application of fascial manipulation, motor imagery, or neuro‐muscular electrical stimulation had vitually no effect whereas a single bout of vibration exercise caused significant coagulation activation. For example, TEM‐derived coagulation times were significantly shortened (209 ± 34 vs. 187 ± 41 s, p = 0.0098) and CAT‐derived thrombin peaks were significantly higher (235 ± 88 vs. 268 ± 82 nM, p = 0.0020) in post compared with preexercise samples. Moreover, vibration exercise, motor imagery, and neuro‐muscular electrical stimulation caused significant plasma expansion (6.15%, 7.53%, and 3.88% plasma volume changes, respectively). We conclude that vibrational exercise apparently represents a potential procoagulant stimulus, and ongoing studies have to clarify whether VE should be applied particularly to patients with an elevated risk for thrombosis.

Polysorbates, in particular polysorbate (PS) 20 and 80, are the most commonly used surfactants for stabilising biotherapeutics produced by biotechnological processes. PSs are derived from ethoxylated sorbitan (a derivative of sorbitol) esterified with fatty acids of varying chain length and degree of saturation. In the past, these surfactants have been reported to have specific liabilities. Chemical (oxidations and hydrolyses) and enzymatic degradations have been reported to affect the stability of PS in drug products. Specifically, the presence of trace amounts (sub-ppm) of certain host cell proteins (HCPs) can induce enzymatic PS degradation, which can lead to the release of free fatty acids during storage over time. Enzymatic polysorbate degradation may impair the functionality of the surfactant in stabilising therapeutic proteins, leading to the formation of visible and/or sub-visible particles in biopharmaceutical drug products. This review summarises the enzymes currently known to be involved in the degradation of polysorbate in mammalian biotechnological processes for therapeutic proteins. In recent years, advanced analytical methods have been developed to qualify and quantify the PS-degrading enzymes. Most of these assays are based on mass spectrometry with a preceding HCP enrichment approach. Efforts were made to measure the enzyme activity and correlate it with observed PS degradation. The impact on drug product quality attributes, including fatty acid solubility and phase separation, up to the formation of visible particles, and the potential induction of protein and protein/fatty acid mixed particles as well as the sensitivity of specific PS quality towards enzymatic degradation, was considered. Various drug substance (DS) mitigation strategies related to the occurrence of PS degrading enzymes are discussed as amongst them the generation of stable HCP knockout cell lines, which are also carefully analysed. The underlying opinion article reflects the undergoing discussions related to PS degrading enzymes and focusses on (i) impact on drug product, (ii) analytics for identification/quantification (characterisation) of the PS degrading enzymes, (iii) enzyme activity (iv) currently identified enzymes, and (v) potential mitigation strategies to avoid enzymatic PS degradation during DS manufacturing.

Objectives: Influenza-like-illness (ILI) is a commonly used symptom categorization in seasonal disease surveillance focusing on influenza in community and clinical settings. However, SARS-CoV-2 often causes presentation with a similar symptom profile. We explore how SARS-CoV-2-positive individuals can influence surveillance trends for the World Health Organization, the United States Centre for Disease Control, and the European Centre for Disease Control (ECDC) ILI criteria. Methods: Harnessing the Winter COVID-19 Infection Study in England, a cohort study, the prevalence of different ILI definitions is modeled using multilevel regression and poststratification using age and spatial stratifications with temporal smoothing. Trends over time across stratifications were compared for SARS-CoV-2 positive and negative individuals to understand differences in ILI trends. Symptom presentation across positive and negative SARS-CoV-2 cases were compared. Results: SARS-CoV-2 symptom profiles are shown to overlap with the ILI case definitions, particularly for “cough” and “fever”, causing SARS-CoV-2 positive individuals to be frequently detected as ILI cases. The trend of SARS-CoV-2 positives is a substantial component of the ILI-modeled trend, driving an earlier perceived peak in prevalence. The ECDC symptom definition was most influenced by SARS-CoV-2 positive individuals. Conclusions: Using a large community cohort we show how SARS-CoV-2 can impact ILI surveillance trends. SARS-CoV-2 makes up a substantial part of the community ILI burden and public health messaging should reflect this when discussing ILI. We show ILI is no longer a strong proxy for influenza activity alone.

Background The use of immune checkpoint inhibitors (CPIs) has become a dominant regimen in modern cancer therapy, however immune resistance induced by tumor-associated macrophages (TAMs) with immune suppressive and evasion properties limits responses. Therefore, the rational design of immune modulators that can control the immune suppressive properties of TAMs and polarize them, as well as dendritic cells (DCs), toward a more proinflammatory phenotype is a principal objective in cancer immunotherapy.Methods Here, using a protein engineering approach to enhance cytokine residence in the tumor microenvironment, we examined combined stimulation of the myeloid compartment via tumor stroma-binding granulocyte–macrophage colony-stimulating factor (GM-CSF) to enhance responses in both DCs and T cells via stroma-binding interleukin-12 (IL-12). We evaluated tumor responses at the levels of outcome, cellular responses, and cytokine responses in both the tumors and the tumor-draining lymph nodes. We further investigated the potentiation of DC response to IL-12 by GM-CSF stimulation ex vivo.Results Engineered GM-CSF restored an antitumorigenic tumor myeloid microenvironment otherwise suppressed by TAMs, while engineered IL-12 provided effector signals to T cells, thereby boosting both tumor-resident antitumor macrophage and CD8+ T cell populations. Furthermore, engineered GM-CSF potentiated DC response to IL-12, upregulating DC expression of IL-12 receptor and enhancing their expression of proinflammatory cytokines and chemokines on IL-12 exposure. This resulted in remarkable synergistic efficacy in multiple solid tumor models treated with the dual cytokine combination. The combination therapy also improved the efficacy of CPI in a CPI-resistant genetically-engineered melanoma model and exhibited synergistic antitumor efficacy in a pulmonary metastasis model.Conclusion Our strategy provides a rational design for combination immunotherapy targeting both myeloid and lymphoid compartments through complementary mechanisms.

Background In 2021 we launched the BronchStart study, which collected information on 17,899 presentations in children with serious respiratory tract infections following the release of lockdown restrictions. Our study informed the Joint Committee on Vaccination and Immunisation’s decision to recommend the introduction maternal respiratory syncytial virus (RSV) vaccination, which was introduced in the United Kingdom in August/September 2024. Study question We modified our original protocol to conduct a United Kingdom-wide assessment of maternal vaccination against RSV. Methods and likely impact We will conduct a multi-centre study, utilising the PERUKI network used in the original BronchStart study, to assess the effectiveness of maternal vaccination using a test-negative study design. We will gather detailed clinical information on children admitted with bronchiolitis in the post-RSV vaccination era, and understand possible reasons for incomplete vaccine uptake.

Adhesion at the interface between dissimilar materials in the semiconductor industry is an important topic, but reliable quantitative methods for strongly adhesive or highly plastic layers are hardly available. This study aims to investigate the suitability of the cross-sectional nanoindentation (CSN) method for determination of the critical energy release rate of thin film stacks in the presence of a polyimide layer as a representative structure for such a case. For this purpose, the adhesion of a deliberately weakened Si/SiOx interface in a Si/SiOx/Al/SixNy/polyimide stack is examined by systematic variation of the experimental parameters. This allows for a limitation of the plastic energy dissipated in the polyimide layer during delamination, while still investigating its influences on the overall delamination behavior. The results and evaluability of individual experiments were strongly affected by the geometry of the indenter tip and the distance of indentation to the interface, while other internal control parameters of the nanoindenter were more relevant for ease of the experimental procedure. An optimized choice of the mentioned parameters, 8 μm distance from the deposited layers for the cube-corner tip geometry, and 10 μm for the Berkovich geometry, led to 30 % of evaluable results, considered as high for quantitative adhesion testing of thin films. A multi-stage finite element analysis was developed to consider the effect of plasticity in the polyimide layer. Using this, the critical energy release rates (Gc) of the Si/SiOx interface was determined to be 9.61 J/m2 and 10.85 J/m2 for the cube-corner and Berkovich tip geometries, respectively. This work presents a novel promising way to extend the application fields of the CSN method for the determination of the energy release rate of systems containing layers with a high plasticity.

BackgroundPoststroke irritability (PSI) is common among stroke survivors and can lead to a poor quality of life, difficulties in social interactions, criticism from caregivers, and caregiver stress. The planned study will evaluate the clinical, neuropsychological, and magnetic resonance imaging (MRI) correlates of PSI in a cohort of stroke survivors. In addition, the study will examine the 15-month progression of PSI.MethodsThis will be a prospective cohort study that will recruit 285 participants. Participants and their caregivers will undergo detailed assessments at a research clinic at 3, 9, and 15 months after stroke onset (T1/T2/T3). The irritability/lability subscale of the Chinese version of the Neuropsychiatric Inventory (CNPI) will be completed by caregivers. Potential covariates will also be measured. Patients will undergo MRI, including diffusion-weighted imaging, within 1 week of stroke onset. A stepwise logistic regression will be performed to evaluate the importance of lesions in the regions of interest (ROIs) along with other significant variables identified in univariate analyses. These analyses will be repeated for patients with and without PSI at T2 and T3. Repeated measures analysis of covariance (ANCOVA) will be used to assess changes in CNPI scores for the entire sample. In ANCOVA analyses, the frequency of infarcts in the ROIs will be treated as the predictor.DiscussionThis will be the first MRI study on PSI in stroke survivors. The findings will provide insights into the association of the orbitofrontal cortex, anterior cingulate cortex, anterior temporal lobe, insula, amygdala, thalamus, and basal ganglia lesions with the risk of PSI.

ABSTRACT Ethyl acetate is at present exclusively produced from fossil resources. Microbial synthesis of this ester from sugar‐rich waste as an alternative is an aerobic process. Ethyl acetate is highly volatile and therefore stripped with the exhaust gas from the bioreactor which enables in situ product recovery. Previous research on microbial formation of ethyl acetate has focused on the kinetics of ester synthesis and in part on the ester stripping, while the separation of the ester from the exhaust gas has hardly been investigated. A mixed matrix membrane was developed consisting of Silikalite‐1 embedded in polydimethylsiloxane which was installed in a radial–symmetrical membrane module. Evaluation of the separation of ethyl acetate was based on the analysis of the composition of the feed and retentate gas by mass spectrometry. The separation efficiency of the membrane was first tested with varied flows of artificial exhaust gas, containing defined amounts of ethyl acetate. A model for describing the separation process was parametrized by the measured data and used to design a real separation experiment. Ethyl acetate produced from delactosed whey permeate by Kluyveromyces marxianus DSM 5422 in a stirred bioreactor gassed with 0.5 vvm air was successfully separated from the exhaust gas by membranes; 93.6% of the stripped ester was separated. Liquid ethyl acetate was recovered by cooling the permeate gas to ‒78°C, whereby 99.75% of the condensed organic compounds were ethyl acetate. This study demonstrates for the first time that microbially produced and stripped ethyl acetate can be effectively separated from the exhaust gas of bioreactors by membrane technology to obtain the ester in high yield and purity.

Summary: Background: Between 1% and 4% of febrile infants, aged from birth to 90 days of age, presenting to hospital will be diagnosed with an invasive bacterial infection (IBI). Traditional teaching has advocated a treat all approach but more recently a number of clinical decision aids (CDA) have been developed to classify febrile infants into lower and higher risk cohorts, with lower risk infants suitable for management without immediate parenteral antibiotics and lumbar puncture. The aim of this study was to apply these CDA to a UK and Irish cohort. Methods: This was a prospective multicentre cohort study of febrile infants presenting to 35 Paediatric Emergency Research in the UK and Ireland (PERUKI) sites between the 6th July 2022 and the 31st August 2023. All infants received standard care as per local policy. IBI was defined as growth of bacterial pathogen in blood or cerebrospinal fluid. The performance of the following CDAs were assessed, National Institute for Health and Care Excellence (NICE) guidelines NG143 (Fever under 5 years), British Society Antimicrobial Chemotherapy (BSAC), Aronson rule and American Academy of Pediatrics (AAP) CDA. A cost comparison of each CDA against a treat all approach was conducted. Trial registration: NCT05259683. Findings: 1821 were included in the final analysis. The median age was 46 days (IQR: 30–64 days), with 1108 (61%) being male. Of the 1821 infants, 67 (3.7%) had IBI. The AAP and BSAC CDAs were the most sensitive at 0.99 (95% CI 0.92–1.0) for both with specificities of 0.23 (95% CI 0.21–0.25) and 0.20 (95% CI 0.18–0.22) respectively. The NICE NG143 and Aronson CDA were the most specific CDAs with values of 0.27 (95% CI 0.25–0.30) and 0.30 (95% CI 0.28–0.32) respectively, but their sensitivity was lower. The AAP CDA performed equally well with either procalcitonin (PCT) or C-reactive protein (CRP) as the biomarker of choice. Of the 1821 infants, 77% were admitted, 14% were discharged and 9% were ambulated. All CDAs were cost saving for hospital services when compared to a treat all approach, with the lowest mean cost per patient estimated for Aronson (£1171; bootstrap 95% CI £1129–£1214) and NICE NG143 CDA (£1218; bootstrap 95% CI £1174–£1263). Interpretation: The AAP and BSAC CDAs are highly sensitive at excluding IBI, with a cost saving to hospital services when compared to a treat all approach. The substitution of CRP for PCT made no difference to the performance of the AAP CDA in this cohort and was more costly. Funding: The Febrile Infant Diagnostic Assessment and Outcome (FIDO) study is funded by Royal College of Emergency Medicine Doctoral Fellowship (RCEM 02/03/2021). Procalcitonin analysis was supported by the Public Health Agency Northen Ireland Grant (HSC R&D-COM/5745/22). The funders played no part in the conception or design of this study.

Summary: Background: Prompt antibiotic administration for febrile neutropenia (FN) is standard of care, and targets of time to antibiotics (TTA)

Abstract Robust diagnostic tools and surveillance are crucial for malaria control and elimination efforts. Malaria caused by neglected Plasmodium parasites is often underestimated due to the lack of rapid diagnostic tools that can accurately detect these species. While nucleic-acid amplification technologies stand out as the most sensitive methods for detecting and confirming Plasmodium species, their implementation in resource-constrained settings poses significant challenges. Here, we present a Pan Plasmodium recombinase polymerase amplification lateral flow (RPA–LF) assay, capable of detecting all six human infecting Plasmodium species in low resource settings. The Pan Plasmodium RPA-LF assay successfully detected low density clinical infections with a preliminary limit of detection between 10–100 fg/µl for P. falciparum. When combined with crude nucleic acid extraction, the assay can serve as a point-of-need tool for molecular xenomonitoring. This utility was demonstrated by screening laboratory-reared Anopheles stephensi mosquitoes fed with Plasmodium-infected blood, as well as field samples of An. funestus s.l. and An. gambiae s.l. collected from central Africa. Overall, our proof-of-concept Pan Plasmodium diagnostic tool has the potential to be applied for clinical and xenomonitoring field surveillance, and after further evaluation, could become an essential tool to assist malaria control and elimination.

Abstract The mpox epidemic in the UK began in May 2022, with rates of new cases unexpectedly and rapidly declining during August 2022. Interpreting trends in infection requires disentangling the underlying growth rate of cases from the delay from symptom onset to presenting to healthcare. We developed a nowcasting Bayesian method which incorporates time-varying delays (EpiLine) to quantify the changes in the delay from symptom onset to healthcare presentation and the underlying mpox growth rate over the period May-August 2022 in the UK. We show that the mean delay between symptom onset and healthcare presentation for mpox in the UK decreased from 22 days in early May 2022 to 10 days by early June and 8 days in August 2022. When we account for these dynamic delays, the time-varying growth rate declined gradually and continuously in the UK during the May-August 2022 period. Not accounting for varying time delays would have incorrectly characterised the growth rate by a sharp increase followed by a rapid decline in mpox cases. Our results highlight the importance of correctly quantifying the delay between symptom onset to healthcare presentation when characterising the epidemic growth of mpox in the UK. The gradual reduction in the rate of epidemic spread, which pre-dated the vaccine roll-out, is consistent with gradual risk reduction or acquired immunity amongst the highest risk individuals. Our study highlights the need for public health agencies to record the delays from symptom onset to healthcare presentation early in an outbreak.

Background: Multisystem inflammatory syndrome in children (MIS-C) occurs after SARS-CoV-2 infection, with gastrointestinal symptoms a prominent feature. This syndrome has been proposed to be triggered by persistent SARS-CoV-2 antigenemia due to increased intestinal epithelial permeability. We obtained evidence for this in this study. Methods: In a single-centre study, we recruited 83 children and analysed blood samples to quantify the circulating markers of increased intestinal permeability following SARS-CoV-2 infection. Publicly available proteomics MIS-C datasets were also accessed to assess the evidence for increased intestinal permeability. We further quantified SARS-CoV-2 antigenemia and the humoral response to SARS-CoV-2 spike protein. Results: Following SARS-CoV-2 infection, healthy children demonstrated no dysregulation of the intestinal epithelial barrier. In MIS-C, considerable increases in markers of epithelial dysfunction were observed, with similar increases noted in febrile controls. Furthermore, we found little evidence of persistent SARS-CoV-2 antigenemia in MIS-C. Conclusions: Our results suggest that although increased intestinal epithelial permeability is a feature of MIS-C, it is not unique to the condition, and persistent SARS-CoV-2 antigenemia does not occur.

Abstract Recent progress in image-based spatial RNA profiling enables to spatially resolve tens to hundreds of distinct RNA species with high spatial resolution. It presents new avenues for comprehending tissue organization. In this context, the ability to assign detected RNA transcripts to individual cells is crucial for downstream analyses, such as in-situ cell type calling. Yet, accurate cell segmentation can be challenging in tissue data, in particular in the absence of a high-quality membrane marker. To address this issue, we introduce ComSeg, a segmentation algorithm that operates directly on single RNA positions and that does not come with implicit or explicit priors on cell shape. ComSeg is applicable in complex tissues with arbitrary cell shapes. Through comprehensive evaluations on simulated and experimental datasets, we show that ComSeg outperforms existing state-of-the-art methods for in-situ single-cell RNA profiling and in-situ cell type calling. ComSeg is available as a documented and open source pip package at https://github.com/fish-quant/ComSeg .

Abstract Aims Inherited cardiomyopathies are relatively rare but carry a high risk of cardiac maternal morbidity and mortality during pregnancy and postpartum. However, data for risk stratification are scarce. The new CARPREG II score improves prediction of prognosis in pregnancies associated with heart disease, though its role in inherited cardiomyopathies is unclear. We aim to describe characteristics and cardiac maternal outcomes in patients with inherited cardiomyopathy during pregnancy, and to evaluate the interest of the CARPREG II risk score in this population. Methods and results In this retrospective single‐centre study, 90 consecutive pregnancies in 74 patients were included (mean age 32 ± 5 years), including 28 cases of dilated cardiomyopathy (DCM), 46 of hypertrophic cardiomyopathy, 11 of arrhythmogenic right ventricular cardiomyopathy and 5 of left ventricular noncompaction, excluding peripartum cardiomyopathy. The discriminatory power of several risk scores was assessed by the area under the receiver‐operating characteristic curve (AUC). Median CARPREG II score was 2 [0;3] and was higher in the DCM subgroup. A severe cardiac maternal complication was observed in 18 (20%) pregnancies, mainly driven by arrhythmia and heart failure (each event in 10 pregnancies), with 3 cardiovascular deaths. Forty‐three pregnancies (48%) presented foetal/neonatal complications (18 premature delivery, 3 foetal/neonatal death). CARPREG II was significantly associated with cardiac maternal complications (P

Abstract Background Anomalous left coronary artery originating from the pulmonary artery (ALCAPA), is a unique congenital anomaly, comprising only 0.24–0.46% of all congenital cardiac anomalies. Late presentations, ranging from asymptomatic cases to sudden cardiac arrest, are exceptionally rare. This unique case highlights the complexity of managing ALCAPA in adulthood and underscores the necessity of a comprehensive surgical approach addressing both coronary and valvular issues. Presentation A 34-year-old female patient, who had been diagnosed with ALPACA in her early childhood, suffered sudden cardiac arrest at work, followed by out-of-hospital resuscitation. The patient had been followed-up regularly until adolescence, however, she had refused surgery. In the diagnostic work-up following successful resuscitation severe mitral valve regurgitation was additionally revealed. Subsequently, the patient underwent surgery, involving coronary artery bypass grafting (CABG), using bilateral internal mammary arteries, and mitral valve repair, with an excellent postsurgical result. At 16-month follow-up, the patient was asymptomatic and quality of life had significantly improved. Conclusion This rare case initially presented as silent myocardial ischemia, resulting in reduced left ventricular function and secondary mitral incompetence. Surgical treatment of ALCAPA in adults poses greater challenges and a higher risk than in children. CABG procedure offers an excellent prognostic therapeutic strategy, since this procedure is a routine in adult cardiac surgery.

Effective planter downforce is crucial for optimizing seed placement and improving crop emergence and growth. This study explores the impact of different downforce settings on soil compaction, seeding depth, and crop performance for corn and cotton. Two field experiments were implemented using a John Deere 6145R tractor and a 6-row John Deere planter equipped with a DeltaForce® hydraulic downforce system in Shorter, Alabama, during the 2020 growing season. Multiple planter's downforce levels (0, 550, 1100, and 1800 N) were tested in both static and dynamic modes across two fields with distinct soil types (clay loam and sandy loam). Results indicated that the dynamic downforce mode provided more accurate and consistent load distribution compared to the static mode, which often exceeded target loads. Increased downforce led to deeper seeding depths, particularly with the dynamic mode, and higher loads in the static mode resulted in greater variability. For corn in clay loam soil, higher static downforce improved seed-to-soil contact, enhancing emergence and plant height. Conversely, cotton in sandy loam soil showed no significant differences in emergence or plant height, likely due to soil moisture conditions and target depth. The study concludes that dynamic downforce systems offer superior load control and uniformity, enhancing corn emergence and growth in heavier soils, while further research is recommended to optimize settings for various crops and soil conditions.

Among the key figures of global housing inequality is the average living space per person. Thus, it comes as no surprise that during the past decade, tiny houses have become an attractive option for some who want to set an example in an affluent society of the global north: free-standing, two-storey building with a total floor space of less than 30 m2. At the same time, in many countries of the global south, people are confined to a similar floorspace – not out of choice but out of need. In bringing together these two very different contexts, I am arguing that from a perspective of capability justice, the concept of home is more than just the need for shelter. In order to enable people to participate in societal life, housing solutions require processes of urban transformation, as well as careful planning and design for social housing. Even in a situation of hardship, living in a small-scale house can be a step towards a realisation of concepts of the good life within the given circumstances. Taking up Charles Taylor’s concept of social imaginaries and presenting architectural examples from the Mexican context (Apan housing laboratory and work done by Tatiana Bilbao), I am drawing some unlikely parallels between the effects that tiny houses, on the one hand, and suggestions for social housing, on the other hand, might have within their respective societies. In this, the concept of social imaginaries helps to see parallels between architecture as a medium of the social and the role of religion. Intradisciplinary and/or interdisciplinary implications: The article argues that in questions of housing justice, architectural solutions can fruitfully supplement considerations of justice.

In cities worldwide, housing is precarious. Local socio-economic environments can exacerbate existing social differences and exclusions, but can also contribute to alleviate these differences, and to foster high levels of social inclusion. This article introduces a special collection of articles asking how theology should contribute theologically to address the challenges of housing and human settlements. It derives from an assertion that theology and reflection on the built environment should engage each other, made concrete in this collection through exploring issues of housing justice. We explore the question of housing justice with reference to four related questions: (1) How can urban planning interventions enhance affordable, sustainable and aesthetically appealing housing for all? (2) What are the political, economic and legal conditions impacting on housing justice, and how can theologians engage in these spaces? (3) How can exclusionary or precarious conditions be addressed architecturally to contribute to ecological sustainability, aesthetics and affordability? (4) What are the dominant social imaginaries that mediate housing and settlement development, and how can theologians help foster inclusive and just social imaginaries? Examples from different countries, cities and socio-cultural contexts are introduced and reflected upon, seeking to identify conditions that enable affordable, sustainable and aesthetically attractive housing in an unequal and precarious world. Intradisciplinary and/or interdisciplinary implications: The article points out the relevance of a theological perspective on the housing problem. At the same time, the implications for architecture, urban planning and politics are addressed.

BackgroundLoss of empathy (LoE) is common among stroke survivors, yet often undiagnosed and thus untreated. LoE is related to the loss of a caring marital relationship, higher care burden and poorer quality of life in carers. The present study will evaluate the clinical and MRI correlates of LoE in a cohort of stroke survivors. The secondary objective is to describe the 12-month course of LoE.MethodsThe current study is a prospective cohort study. We will recruit 246 subjects. Subjects and carers will receive a detailed assessment at a research clinic at 3, 9, and 15 months after stroke onset (T1/T2/T3). The Chinese version of the Interpersonal Reactivity Index (IRI), a 28-item personality assessment tool, will be completed by a carer for each subject. LoE is defined as an IRI total score of 39 or less. Patients will be examined by MRI including diffusion weighted imaging (DWI) within 1 week after the onset of stroke. A stepwise logistic regression will be performed to assess the importance of lesions in the regions of interest. To examine the predictors of LoE remission, the demographic, clinical and MRI variables of remitters and non-remitters at T2/T3 will be examined by logistic regression.DiscussionThis project will be the first longitudinal study on LoE in stroke survivors. The results will shed light on the association between prefrontal cortex and subcortical lesions and LoE risk, symptom severity and outcome. The findings will provide data to advance our understanding of the pathogenesis and clinical course of LoE in stroke as well as other neurological conditions. They are thus likely to be applicable to the large population of neurological patients at risk of LoE and should also stimulate further research in this field.

Abstract In the field of material informatics, artificial neural networks (ANNs) contribute to the investigation of the processing‐structure‐properties‐performance relationship of materials. This inspires us to leverage the capabilities of ANNs to decode properties of hydrogels, thereby customizing these active materials for sensors or actuators. In the current work, we introduce an approach to predict discrete swelling states of temperature‐responsive hydrogels, especially PNIPAAm, based on their synthesis parameters, utilizing ANN models. To build the database, we analyze literature on temperature‐responsive hydrogels and compile essential synthesis parameters. The corresponding data points related to these synthesis parameters are then extracted. We propose different variants of ANN models and compare their accuracy on the acquired dataset. The selected model can predict the swelling states of hydrogel samples within the test dataset with relative prediction error of 0.11. This approach is applied to predict the expected properties. Subsequently, the hydrogels can be synthesized, and their properties can be experimentally verified. Our approach can be extended to other types of hydrogels and in the prediction of additional properties. The identified synthesis parameters serve as a valuable foundation for the expansion of the database with further literature resources. An enriched database will enhance the performance of the data‐driven model, thereby improving its predictive capabilities.

Introduction Febrile infants under 3 months of age are at risk of invasive bacterial infection (IBI). It is currently unclear if testing for respiratory viruses may have a role in IBI risk stratification. If found to be associated with the likelihood of IBI, respiratory viral point-of-care testing may improve patient and caregiver experience, reduce costs and enhance antimicrobial stewardship.Methods and analysis This is a study protocol for a systematic review and meta-analysis that aims to answer the following question: In young febrile infants presenting to emergency care settings does a positive respiratory viral test for RSV, Influenza or SARS-CoV2 (relative to a negative test) add value to current risk stratification pathways for the exclusion of invasive bacterial infection, subsequently enabling safe de-escalation of investigation and treatment?A search strategy will include MEDLINE, EMBASE, Web of Science, The Cochrane Library and grey literature. Abstracts and then full texts will be independently screened for selection. Data extraction and quality assessment will be completed by two independent authors.The primary objective is to analyse the ability of a positive respiratory viral test to identify the overall risk of IBI. The secondary objective is to perform a subgroup analysis to investigate how the risk stratification alters based on other variables including virus type, patient characteristics and the presence of an identified source of fever.Bivariate random-effects meta-analysis will be undertaken. Diagnostic odds ratios (OR), sensitivity, specificity and positive and negative likelihood ratios will be calculated. The degree of heterogeneity and publication bias will be investigated and presented.Ethics and dissemination Ethical approval is not required. We will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to disseminate the study results through publication and conference presentations.PROSPERO registration number This protocol is registered in PROSPERO—ID number: CRD42023433716.

Background In 2021 we launched the BronchStart study, which collected information on 17,899 presentations in children with serious respiratory tract infections following the release of lockdown restrictions. Our study informed the Joint Committee on Vaccination and Immunisation’s decision to recommend the introduction maternal respiratory syncytial virus (RSV) vaccination, which was introduced in the United Kingdom in August/September 2024. Study question We modified our original protocol to conduct a United Kingdom-wide assessment of maternal vaccination against RSV. Methods and likely impact We will conduct a multi-centre study, utilising the PERUKI network used in the original BronchStart study, to assess the effectiveness of maternal vaccination using a test-negative study design. We will gather detailed clinical information on children admitted with bronchiolitis in the post-RSV vaccination era, and understand possible reasons for incomplete vaccine uptake.

Preclinical high-field magnetic resonance imaging (MRI) systems offer a diverse array of MRI techniques, providing rich multiparametric MRI (mpMRI) platforms for studying numerous biological parameters. mpMRI platforms prove particularly indispensable when investigating tumors that exhibit profound intratumoral heterogeneity, such as breast cancer. A thoughtful comprehension of the origins of intratumoral heterogeneity is imperative for the judicious assessment of new targeted therapies and treatment interventions. Furthermore, when data from mpMRI are complemented with data from other in vivo imaging modalities, such as positron emission tomography (PET), and correlated with data from ex vivo modalities, such as matrix-assisted laser desorption imaging mass spectrometry (MALDI IMS), the in vivo parameters can be further elucidated at a molecular level and microscopic scale. Nevertheless, extracting meaningful scientific insights from such complex datasets necessitates the utilization of machine learning (ML) approaches to discern region-specific radiomic features. The development of correlative, multimodal imaging (CMI) workflows, such as one incorporating MRI, PET and MALDI IMS, is inherently challenging, given the many technological and methodological challenges related to multimodal data acquisition as well as the physiological limitations of the laboratory mice of the investigation. Standardization efforts in image acquisition and processing are required to increase the reproducibility and translatability of CMI data. To address the challenges of developing standardized CMI workflows and stimulate dialog regarding this area of need, we present a practical workflow to investigate tumor heterogeneity in breast cancer xenografts across various spatial scales. Our workflow entails simultaneous functional MRI and PET acquisitions in living mice, followed by correlation with post-imaging MALDI IMS and histologic data. Additionally, we propose data preprocessing steps for potential ML applications. We illustrate the feasibility of this workflow through two examples, showcasing its effectiveness in comparing in vivo and ex vivo images to evaluate tumor metabolism and hypoxia in mice with breast cancer xenografts.

Epidemiological delays are key quantities that inform public health policy and clinical practice. They are used as inputs for mathematical and statistical models, which in turn can guide control strategies. In recent work, we found that censoring, right truncation, and dynamical bias were rarely addressed correctly when estimating delays and that these biases were large enough to have knock-on impacts across a large number of use cases. Here, we formulate a checklist of best practices for estimating and reporting epidemiological delays. We also provide a flowchart to guide practitioners based on their data. Our examples are focused on the incubation period and serial interval due to their importance in outbreak response and modeling, but our recommendations are applicable to other delays. The recommendations, which are based on the literature and our experience estimating epidemiological delay distributions during outbreak responses, can help improve the robustness and utility of reported estimates and provide guidance for the evaluation of estimates for downstream use in transmission models or other analyses.

Abstract Levees aim to provide protection during floods, however, these structures can breach, causing significant damage. Flood maps that include levee breaching are often limited to deterministic methods. Where probabilistic breaching is done, it often requires computationally expensive Monte Carlo simulations and an understanding of the geotechnical levee properties that are often limited. In this paper, we combine existing fragility curves and empirical breaching equations with a framework for automating levee breaching in catchments with limited geotechnical information. This method can be adapted and applied to existing 2D flood models to determine the probability of inundation, given that a breach occurs. This ultimately allows for greater emergency responses and land use planning to reduce the flood risk faced by our communities. The method was applied to four case study catchments. The results showed that including levee breaching in one catchment led to an average increase in the inundated area by 48.2% and a tripling in the potentially exposed area. However, breaching in some locations reduced the inundation extent by 12%, illustrating the potential for fuse plug levees and floodways as a flood mitigation strategy. This strategy has seen successful usage internationally. Further investigation is recommended to consider whether these mitigation strategies should be enacted.

Aquaporin-0 (AQP0) tetramers form square arrays in lens membranes through a yet unknown mechanism, but lens membranes are enriched in sphingomyelin and cholesterol. Here, we determined electron crystallographic structures of AQP0 in sphingomyelin/cholesterol membranes and performed molecular dynamics (MD) simulations to establish that the observed cholesterol positions represent those seen around an isolated AQP0 tetramer and that the AQP0 tetramer largely defines the location and orientation of most of its associated cholesterol molecules. At a high concentration, cholesterol increases the hydrophobic thickness of the annular lipid shell around AQP0 tetramers, which may thus cluster to mitigate the resulting hydrophobic mismatch. Moreover, neighboring AQP0 tetramers sandwich a cholesterol deep in the center of the membrane. MD simulations show that the association of two AQP0 tetramers is necessary to maintain the deep cholesterol in its position and that the deep cholesterol increases the force required to laterally detach two AQP0 tetramers, not only due to protein–protein contacts but also due to increased lipid–protein complementarity. Since each tetramer interacts with four such ‘glue’ cholesterols, avidity effects may stabilize larger arrays. The principles proposed to drive AQP0 array formation could also underlie protein clustering in lipid rafts.

INTRODUCTION The benefits of theatre and arts-based initiatives for enhancing the health and wellbeing of adults, regardless of mental health status, are well-documented. Theatre methodologies offer a platform for co-produced experiential learning, promoting perspective-taking and effective communication among staff and service users. This project aimed to bring together service users and mental health professionals through workshops conducted by an experiential theatre company, focusing on themes such as relationship dynamics, co-production, empowerment and perspective-taking. Notably, the sessions were conducted online due to the COVID-19 pandemic. METHODS The study sought to explore the experiences, learning outcomes and work-related wellbeing benefits of participating in this innovative project. Methods involved inviting East London Foundation Trust members to eight weekly online workshops, culminating in a co-created filmed performance. Interviews conducted 9 months to a year later with participants and facilitators were thematically analysed. RESULTS Results revealed four key themes: (1) personal and collective growth through storytelling and embodied acting experiences; (2) the importance of workshop structure for experiential learning; (3) challenging traditional role definitions through diminished hierarchy; and (4) sustained impacts on time management at work and in personal lives. CONCLUSIONS In conclusion, participants valued their involvement, indicating that theatre-based co-produced learning enhances communication and interpersonal skills in mental healthcare settings. These findings suggest the potential for integrating such approaches into healthcare education and training programs.

Coastal flood damage is primarily the result of extreme sea levels. Climate change is expected to drive an increase in these extremes. While proper estimation of changes in storm surges is essential to estimate changes in extreme sea levels, there remains low confidence in future trends of surge contribution to extreme sea levels. Alerting local populations of imminent extreme sea levels is also critical to protecting coastal populations. Both predicting and projecting extreme sea levels require reliable numerical prediction systems. The SurgeMIP (surge model intercomparison) community has been established to tackle such challenges. Efforts to intercompare storm surge prediction systems and coordinate the community's prediction and projection efforts are introduced. An overview of past and recent advances in storm surge science such as physical processes to consider and the recent development of global forecasting systems are briefly introduced. Selected historical events and drivers behind fast increasing service and knowledge requirements for emergency response to adaptation considerations are also discussed. The community's initial plans and recent progress are introduced. These include the establishment of an intercomparison project, the identification of research and development gaps, and the introduction of efforts to coordinate projections that span multiple climate scenarios.

The extraction of individual events from continuous time series is a common challenge in many extreme value studies. In the field of environmental science, various methods and algorithms for event identification (de-clustering) have been applied in the past. The distinctive features of extreme events, such as their temporal evolutions, durations, and inter-arrival times, vary significantly from one location to another making it difficult to identify independent events in the series. In this study, we propose a new automated approach to detect independent events from time series, by identifying the standard event duration across locations using event correlations. To account for the inherent variability at a given site, we incorporate the standard deviation of the event duration through a soft-margin approach. We apply the method to 1 485 tide gauge records from across the global coast to gain new insights into the typical durations of independent storm surges along different coastline stretches. The results highlight the effects of both local characteristics at a given tide gauge and seasonality on the derived storm durations. Additionally, we compare the results obtained with other commonly used de-clustering techniques showing that these methods are more sensitive to the chosen threshold.

BackgroundEarly identification of high-risk individuals for weight problems in children and adolescents is crucial for implementing timely preventive measures. While machine learning (ML) techniques have shown promise in addressing this complex challenge with high-dimensional data, feature selection is vital for identifying the key predictors that can facilitate effective and targeted interventions. This study aims to utilize feature selection process to identify a robust and minimal set of predictors that can aid in the early prediction of short- and long-term weight problems in children and adolescents.MethodsWe utilized demographic, physical, and psychological wellbeing predictors to model weight status (normal, underweight, overweight, and obese) for 1-, 3-, and 5-year periods. To select the most influential features, we employed four feature selection methods: (1) Chi-Square test; (2) Information Gain; (3) Random Forest; (4) eXtreme Gradient Boosting (XGBoost) with six ML approaches. The stability of the feature selection methods was assessed by Jaccard's index, Spearman's rank correlation and Pearson's correlation. Model evaluation was performed by various accuracy metrics.ResultsWith 3,862,820 million student-visits were included in this population-based study, the mean age of 11.6 (SD = 3.64) for the training set and 10.8 years (SD = 3.50) for the temporal test set. From the initial set of 38 predictors, we identified 6, 9, and 13 features for 1-, 3-, and 5-year predictions, respectively, by the best performed feature selection method of Chi-Square test in XGBoost models. These feature sets demonstrated excellent stability and achieved prediction accuracies of 0.82, 0.73, and 0.70; macro-AUCs of 0.94, 0.86, and 0.83; micro-AUCs of 0.96, 0.93, and 0.92 for different prediction windows, respectively. Weight, height, sex, total score of self-esteem, and age were consistently the most influential predictors across all prediction windows. Additionally, several psychological and social wellbeing predictors showed relatively high importance in long-term weight status prediction.ConclusionsWe demonstrate the potential of ML in identifying key predictors of weight status in children and adolescents. While traditional anthropometric measures remain important, psychological and social wellbeing factors also emerge as crucial predictors, potentially informing targeted interventions to address childhood and adolescence weight problems.

Abstract Background Hyperkalemia (HK) is frequently present in chronic kidney disease (CKD). Risk factors for HK among CKD patients include comorbidities and renin–angiotensin–aldosterone system inhibitor (RAASi) treatment. Current standard of care (SoC) often necessitates RAASi down-titration or discontinuation, resulting in poorer cardiorenal outcomes, hospitalization and mortality. This study evaluates the cost-effectiveness of patiromer for HK in CKD patients with and without heart failure (HF) in an Italian setting. Methods A lifetime Markov cohort model was developed based on OPAL-HK to assess the health economic impact of patiromer therapy in comparison to SoC after accounting for the effects of HK and RAASi use on clinical events. Outcomes included accumulated clinical events, number needed to treat (NNT) and the incremental cost-effectiveness ratio (ICER). Subgroup analysis was conducted in CKD patients with and without HF. Results Patiromer was associated with an incremental discounted cost of €4,660 and 0.194 quality adjusted life years (QALYs), yielding an ICER of €24,004. Per 1000 patients, patiromer treatment prevented 275 moderate/severe HK events, 54 major adverse cardiovascular event, 246 RAASi discontinuation and 213 RAASi up-titration/restart. Subgroup analysis showed patiromer was more effective in preventing clinical events in CKD patients with HF compared to those without; QALY gains were greater in CKD patients without HF versus those with HF (0.267 versus 0.092, respectively). Scenario analysis and sensitivity analysis results support base-case conclusions. Conclusion Patiromer is associated with QALY gains in CKD patients with and without HF compared to SoC in Italy. Patiromer prevented HK events, enabled RAASi therapy maintenance and reduced cardiovascular event risk.

Abstract Background Adolescent weight problems have become a growing public health concern, making early prediction of non-normal weight status crucial for effective prevention. However, few temporal prediction tools for adolescent four weight status have been developed. This study aimed to predict the short- and long-term weight status of Hong Kong adolescents and assess the importance of predictors. Methods A population-based retrospective cohort study of adolescents was conducted using data from a territory-wide voluntary annual health assessment service provided by the Department of Health in Hong Kong. Using diet habits, physical activity, psychological well-being, and demographics, we generated six prediction models for successive weight status (normal, overweight, obese and underweight) using multiclass Decision Tree, Random Forest, k-Nearest Neighbor, eXtreme gradient boosting, support vector machine, logistic regression. Model performance was evaluated by multiple standard classifier metrics and the overall accuracy. Predictors’ importance was assessed using Shapley values. Results 442,898 Primary 4 (P4, Grade 4 in the US) and 344,186 in Primary 6 (P6, Grade 6 in the US) students, with followed up until their Secondary 6 (Grade 12 in the US) during the academic years 1995/96 to 2014/15 were included. The XG Boosts model consistently outperformed all other model in predicting the long-term weight status at S6 from P4 or P6. It achieved an overall accuracy of 0.72 or 0.74, a micro-averaging AUC of 0.92 or 0.93, and a macro-averaging AUC of 0.83 or 0.86, respectively. XG Boost also demonstrated accurate predictions for each predicted weight status, surpassing the AUC values obtained by other models. Weight, height, sex, age, frequency and hours of aerobic exercise were consistently the most important predictors for both cohorts. Conclusions The machine learning approaches accurately predict adolescent weight status in both short- and long-term. The developed multiclass model that utilizing easy-assessed variables enables accurate long-term prediction on weight status, which can be used by adolescents and parents for self-prediction when applied in health care system. The interpretable models may help to provide the early and individualized interventions suggestions for adolescents with weight problems particularly.

Abstract The COVID-19 pandemic led to 231,841 deaths and 940,243 hospitalisations in England, by the end of March 2023. This paper calculates the real-time infection hospitalisation risk (IHR) and infection fatality risk (IFR) using the Office for National Statistics Coronavirus Infection Survey (ONS CIS) and the Real-time Assessment of Community Transmission Survey between November 2020 to March 2023. The IHR and the IFR in England peaked in January 2021 at 3.39% (95% Credible Intervals (CrI): 2.79, 3.97) and 0.97% (95% CrI: 0.62, 1.36), respectively. After this time, there was a rapid decline in the severity from infection, with the lowest estimated IHR of 0.32% (95% CrI: 0.27, 0.39) in December 2022 and IFR of 0.06% (95% CrI: 0.04, 0.08) in April 2022. We found infection severity to vary more markedly between regions early in the pandemic however, the absolute heterogeneity has since reduced. The risk from infection of SARS-CoV-2 has changed substantially throughout the COVID-19 pandemic with a decline of 86.03% (80.86, 89.35) and 89.67% (80.18, 93.93) in the IHR and IFR, respectively, since early 2021. From April 2022 until March 2023, the end of the ONS CIS study, we found fluctuating patterns in the severity of infection with the resumption of more normative mixing, resurgent epidemic waves, patterns of waning immunity, and emerging variants that have shown signs of convergent evolution.