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Abstract Viruses in the phylum Nucleocytoviricota are large, complex and have an exceptionally diverse metabolic repertoire. Some encode hundreds of products involved in the translation of mRNA into protein, but none was known to encode any of the proteins in ribosomes, the central engines of translation. With the discovery of the eL40 gene in FloV-SA2, we report the first example of a eukaryotic virus encoding a ribosomal protein and show that this gene is also present and expressed in other uncultivated marine giant viruses. FloV-SA2 also encodes a “group II” viral rhodopsin, a viral light-activated protein of unknown function previously only reported in metagenomes. FloV-SA2 is thus a valuable model system for investigating new mechanisms by which viruses manipulate eukaryotic cell metabolism.

Abstract Background Current evidence linking long-term exposure to fine particulate matter (PM2.5) exposure and mortality is primarily based on persons that live in the same residence, city and/or country throughout the study, with few residential moves or relocations. We propose a novel method to quantify the health impacts of PM2.5 for United States (US) diplomats who regularly relocate to international cities with different PM2.5 levels. Methods Life table methods were applied at an individual-level to US mortality statistics using the World Health Organization’s database of city-specific PM2.5 annual mean concentrations. Global Burden of Disease concentration-response (C-R) functions were used to estimate cause-specific mortality and days of life lost (DLL) for a range of illustrative 20-year diplomatic assignments for three age groups. Time lags between exposure and exposure-related mortality risks were applied. Sensitivity analysis of baseline mortality, exposure level, C-R functions and lags was conducted. The effect of mitigation measures, including the addition of air purifiers, was examined. Results DLL due to PM2.5 exposure for a standard 20-year assignment ranged from 0.3 days for diplomats’ children to 84.1 days for older diplomats. DLL decreased when assignments in high PM2.5 cities were followed by assignments in low PM2.5 cities: 162.5 DLL when spending 20 years in high PM2.5 cities compared to 62.6 DLL when spending one of every four years (5 years total) in a high PM2.5 city for older male diplomats. Use of air purifiers and improved home tightness in polluted cities may halve DLL due to PM2.5 exposure. The results were highly sensitive to lag assumptions: DLL increased by 68% without inception lags and decreased by 59% without cessation lags for older male diplomats. Conclusion We developed a model to quantify health impacts of changing PM2.5 exposure for a population with frequent relocations. Our model suggests that alternating assignments in high and low PM2.5 cities may help reduce PM2.5-related mortality burdens. Adding exposure mitigation at home may help reduce PM2.5 related mortality. Further research on outcome-specific lag structures is needed to improve the model.

This article traces the idea of domesticity through the work of Emanuele Coccia to explain his conception of happiness. Coccia argues that it is only by taking domestic concerns seriously that philosophy can begin to theorize the possibility of happiness today, claiming that rather than beginning with the polis, “philosophy must think the city from the home, and the home from the kitchen.” The article begins by situating Coccia's work in the tradition of Giorgio Agamben's critical project and then explores the idea of the home from his 2016’s The Life of Plants through 2020’s Metamorphoses to understand the reason for devoting an entire book to the topic in 2021’s Philosophy of the Home. The final sections of this article turn to Philosophy of the Home itself to explain his conception of happiness more concretely, focusing on his conceptions of love and interdependency, as well as the fundamental importance of nourishment and the kitchen.

Abstract Background Pediatric depression is a global concern that has fueled efforts for enhanced detection and treatment engagement. As one example, the US Preventive Services Task Force recommends depression screening for adolescents ages 12–18 years. While many health systems have implemented components of depression screening protocols, there is limited evidence of effective follow-up for pediatric depression. A key barrier is timely team communication and coordination across clinicians and staff within and across service areas for prompt service linkage. However, team effectiveness interventions have been shown to improve team processes and outcomes and can be applied in healthcare settings. Methods This project aims to refine and test a team communication training implementation strategy to improve implementation of an existing pediatric depression screening protocol in a large pediatric healthcare system. The team will be defined as part of the study but is expected to include medical assistants, nurses, physicians, and behavioral health clinicians within and across departments. The implementation strategy will target team mechanisms at the team-level (i.e., intra-organizational alignment and implementation climate) and team member-level (i.e., communication, coordination, psychological safety, and shared cognition). First, the project will use mixed methods to refine the team training strategy to fit the organizational context and workflows. Next, a hybrid type 3 implementation-effectiveness pilot trial will assess the initial effectiveness of the team communication training (implementation strategy) paired with the current universal depression screening protocol (clinical intervention) on implementation outcomes (i.e., feasibility, acceptability, appropriateness, workflow efficiency) and clinical/services outcomes (increased frequency of needed screening and reduced time to service linkage). Finally, the study will assess mechanisms at the team and team member levels that may affect implementation outcomes. Discussion Team communication training is hypothesized to lead to improved, efficient, and effective decision-making to increase the compliance with depression screening and timely service linkage. Findings are expected to yield better understanding and examples of how to optimize team communication to improve efficiency and effectiveness in the pediatric depression screening-to-treatment cascade. This should also culminate in improved implementation outcomes including patient engagement critical to address the youth mental health crisis. Trial registration NCT06527196. Trial Sponsor: University of California San Diego.

Abstract Marine heatwaves are becoming more frequent, widespread and severe, causing mass coral bleaching and mortality. Natural adaptation may be insufficient to keep pace with climate warming, leading to calls for selective breeding interventions to enhance the ability of corals to survive such heatwaves, i.e., their heat tolerance. However, the heritability of this trait–a prerequisite for such approaches–remains unknown. We show that selecting parent colonies for high rather than low heat tolerance increased the tolerance of adult offspring (3–4-year-olds). This result held for the response to both 1-week +3.5 °C and 1-month +2.5 °C simulated marine heatwaves. In each case, narrow-sense heritability (h 2) estimates are between 0.2 and 0.3, demonstrating a substantial genetic basis of heat tolerance. The phenotypic variability identified in this population could theoretically be leveraged to enhance heat tolerance by up to 1 °C-week within one generation. Concerningly, selective breeding for short-stress tolerance did not improve the ability of offspring to survive the long heat stress exposure. With no genetic correlation detected, these traits may be subject to independent genetic controls. Our finding on the heritability of coral heat tolerance indicates that selective breeding could be a viable tool to improve population resilience. Yet, the moderate levels of enhancement we found suggest that the effectiveness of such interventions also demands urgent climate action.

Abstract Infections with Enterobacterales (E) are increasingly difficult to treat due to antimicrobial resistance. After ceftriaxone replaced chloramphenicol (CHL) as empiric therapy for suspected sepsis in Malawi in 2004, extended-spectrum beta-lactamase (ESBL)-E rapidly emerged. Concurrently, resistance to CHL in Escherichia coli and Klebsiella spp. decreased, raising the possibility of CHL re-introduction. However, many phenotypically susceptible isolates still carry CHL acetyltransferase (cat) genes. To understand the molecular mechanisms and stability of this re-emerging CHL susceptibility we use a combination of genomics, phenotypic susceptibility assays, experimental evolution, and functional assays for CAT activity. Here, we show that of 840 Malawian E. coli and Klebsiella spp. isolates, 31% have discordant CHL susceptibility genotype–phenotype, and we select a subset of 42 isolates for in-depth analysis. Stable degradation of cat genes by insertion sequences leads to re-emergence of CHL susceptibility. Our study suggests that CHL could be reintroduced as a reserve agent for critically ill patients with ESBL-E infections in Malawi and similar settings and highlights the ongoing challenges in inferring antimicrobial resistance from sequence data.

Abstract Background Surgical resection is integral for the treatment of neuroblastoma, the most common extracranial solid malignancy in children. Safely locating and resecting primary tumor and remote deposits of disease remains a significant challenge, resulting in high rates of complications and incomplete surgery, worsening outcomes. Intraoperative molecular imaging (IMI) uses targeted radioactive or fluorescent tracers to identify and visualize tumors intraoperatively. GD2 was selected as an IMI target, as it is highly overexpressed in neuroblastoma and minimally expressed in normal tissue. Methods GD2 expression in neuroblastoma cell lines was measured by flow cytometry. DTPA and IRDye® 800CW were conjugated to anti-GD2 antibody to generate DTPA-αGD2-IR800. Binding affinity (Kd) of the antibody and the non-radiolabeled tracer were then measured by ELISA assay. Human neuroblastoma SK-N-BE(2) cells were surgically injected into the left adrenal gland of 3.5-5-week-old nude mice and the orthotopic xenograft tumors grew for 5 weeks. 111In-αGD2-IR800 or isotype control tracer was administered via tail vein injection. After 4 and 6 days, mice were euthanized and gamma and fluorescence biodistributions were measured using a gamma counter and ImageJ analysis of acquired SPY-PHI fluorescence images of resected organs (including tumor, contralateral adrenal, kidneys, liver, muscle, blood, and others). Organ uptake was compared by one-way ANOVA (with a separate analysis for each tracer/day combination), and if significant, Sidak’s multiple comparison test was used to compare the uptake of each organ to the tumor. Handheld tools were also used to detect and visualize tumor in situ, and to assess for residual disease following non-guided resection. Results 111In-αGD2-IR800 was successfully synthesized with 0.75-2.0 DTPA and 2–3 IRDye® 800CW per antibody and retained adequate antigen-binding (Kd = 2.39 nM for aGD2 vs. 21.31 nM for DTPA-aGD2-IR800). The anti-GD2 tracer demonstrated antigen-specific uptake in mice with human neuroblastoma xenografts (gamma biodistribution tumor-to-blood ratios of 3.87 and 3.88 on days 4 and 6 with anti-GD2 tracer), while isotype control tracer did not accumulate (0.414 and 0.514 on days 4 and 6). Probe accumulation in xenografts was detected and visualized using widely available operative tools (Neoprobe® and SPY-PHI camera) and facilitated detection ofputative residual disease in the resection cavity following unguided resection. Conclusions We have developed a dual-labeled anti-GD2 antibody-based tracer that incorporates In-111 and IRDye® 800CW for radio- and fluorescence-guided surgery, respectively. The tracer adequately binds to GD2, specifically accumulates in GD2-expressing xenograft tumors, and enables tumor visualization with a hand-held NIR camera. These results encourage the development of 111In-αGD2-IR800 for future use in children with neuroblastoma, with the goal of improving patient safety, completeness of resection, and overall patient outcomes.

Abstract Autoimmune hemolytic anemia (AIHA) is an acquired condition caused by autoantibody mediated destruction of erythrocytes. AIHA is classified as warm or cold depending on whether the autoantibodies involved react optimally at or below body temperature (37°C), respectively. Mixed AIHA, with features of both, is rare and clinically more severe. We report a case of mixed AIHA that was found to be the presentation of systemic lupus erythematosus (SLE). Treatment with rituximab and prednisone resulted in good response. Although more commonly associated with warm AIHA, SLE can present with mixed AIHA.

Abstract Evidence from preclinical animal models suggests that the stress-buffering function of the endocannabinoid (eCB) system may help protect against stress-related reductions in hippocampal volume, as is documented in major depressive disorder (MDD). However, stress exposure may also lead to dysregulation of this system. Thus, pathways from marked stress histories, such as childhood maltreatment (CM), to smaller hippocampal volumes and MDD in humans may depend on dysregulated versus intact eCB functioning. We examined whether the relation between MDD and peripheral eCB concentrations would vary as a function of CM history. Further, we examined whether eCBs moderate the relation of CM/MDD and hippocampal volume. Ninety-one adults with MDD and 62 healthy comparison participants (HCs) were recruited for a study from the Canadian Biomarker Integration Network in Depression program (CAN-BIND-04). The eCBs, anandamide (AEA) and 2-arachidonylglycerol (2-AG), were assessed from blood plasma. Severe CM history was assessed retrospectively via contextual interview. MDD was associated with eCBs, though not all associations were moderated by CM or in the direction expected. Specifically, MDD was associated with higher AEA compared to HCs regardless of CM history, a difference that could be attributed to psychotropic medications. MDD was also associated with higher 2-AG, but only for participants with CM. Consistent with hypotheses, we found lower left hippocampal volume in participants with versus without CM, but only for those with lower AEA, and not moderate or high AEA. Our study presents the first evidence in humans implicating eCBs in stress-related mechanisms involving reduced hippocampal volume in MDD.

Abstract Background Despite routine echocardiographic surveillance for childhood cancer survivors, the ability to predict cardiomyopathy risk in individual patients is limited. We explored the feasibility and optimal processes for machine learning-enhanced cardiomyopathy prediction in survivors using serial echocardiograms from five centers. Methods We designed a series of deep convolutional neural networks (DCNNs) for prediction of cardiomyopathy (shortening fraction ≤ 28% or ejection fraction ≤ 50% on two occasions) for at-risk survivors ≥ 1-year post initial cancer therapy. We built DCNNs with four subsets of echocardiographic data differing in timing relative to case (survivor who developed cardiomyopathy) index diagnosis and two input formats (montages) with differing image selections. We used holdout subsets in a 10-fold cross-validation framework and standard metrics to assess model performance (e.g., F1-score, area under the precision-recall curve [AUPRC]). Performance of the input formats was compared using a combined 5 × 2 cross-validation F-test. Results The dataset included 542 pairs of montages: 171 montage pairs from 45 cases at time of cardiomyopathy diagnosis or pre-diagnosis and 371 pairs from 70 at-risk survivors who didn’t develop cardiomyopathy during follow-up (non-case). The DCNN trained to distinguish between non-case and time of cardiomyopathy diagnosis or pre-diagnosis case montages achieved an AUROC of 0.89 ± 0.02, AUPRC 0.83 ± 0.03, and F1-score: 0.76 ± 0.04. When limited to smaller subsets of case data (e.g., ≥ 1 or 2 years pre-diagnosis), performance worsened. Model input format did not impact performance accuracy across models. Conclusions This methodology is a promising first step toward development of a DCNN capable of accurately differentiating pre-diagnosis versus non-case echocardiograms to predict survivors more likely to develop cardiomyopathy. Graphical Abstract

Our paper aims to explore how doctoral EdD students in their thesis stage made use of digital technologies, social media (SM), and artificial intelligence (AI) tools. In this study, AI does not involve data on the use of the new generation of AI, which has been introduced in more recent years after this study took place. This paper refers to a 2nd stage qualitative analysis of semi-structured interviews collected from research undertaken in 2018 into student use of digital technologies in an online professional doctorate programme. The original study utilised an exploratory case study approach, an online survey (n = 28), and a series of semi-structured interviews (n = 9). This study will add further qualitative findings and perspectives to those that emerged in the previous study. This study will help to provide new insights into the interview data that was used to inform the initial paper resulting from the research in 2018. We argue that the unique characteristics of online doctoral students as both individuals and learners determine the popularity of some digital tools and that, in order to make the best use of the full range available they need to develop new skills and a better understanding of the pedagogy associated with those digital tools and the value they can add to an educational context. This can be achieved through the provision of more systematic coaching and support systems. This in turn will contribute to enhancing students’ feelings of belonging to a real academic learning community and their self-confidence and autonomy as online learners in general and in their performance in a Viva in particular.

Abstract Aims Inflammation has emerged as a potential key pathophysiological mechanism in heart failure (HF) in general and acute HF (AHF) specifically, with inflammatory biomarkers shown to be highly predictive of adverse outcomes in these patients. The CORTAHF study builds on both these data and the fact that steroid burst therapy has been shown to be effective in the treatment of respiratory diseases and COVID‐19. Our hypothesis is that in patients with AHF and elevated C‐reactive protein (CRP) levels without symptoms or signs of infection, a 7‐day course of steroid therapy will lead to reduced inflammation and short‐term improvement in quality of life and a reduced risk of worsening HF (WHF) events. Methods and results The study, which is currently ongoing, will include 100 patients with AHF ages 18–85, regardless of ejection fraction, screened within 12 h of presentation. Patients will be included who have NT‐proBNP > 1500 pg/mL and CRP > 20 mg/L at screening. Exclusion criteria include haemodynamic instability and symptoms and signs of infection. After signed consent, eligible patients will be randomized according to a central randomization scheme stratified by centre 1:1 to either treatment once daily for 7 days with 40 mg prednisone orally or to standard care. Patients will be assessed at study day 2, day 4 or at discharge if earlier, and at days 7 and 31 at the hospital; and at day 91 through a telephone follow‐up. The primary endpoint is the change in CRP level from baseline to day 7, estimated from a mixed model for repeated measures (MMRM) including all measured timepoints, in patients without a major protocol violation. Secondary endpoints include the time to the first event of WHF adverse event, readmission for HF, or death through day 91; and changes to day 7 in EQ‐5D visual analogue scale score and utility index. Additional clinical and laboratory measures will be assessed. Conclusions The results of the study will add to the knowledge of the role of inflammation in AHF and potentially inform the design of larger studies with possibly longer duration of anti‐inflammatory therapies in AHF.

Abstract Introduction Patients with alopecia areata (AA) may have received several therapies for management of AA during their lives. In the ALLEGRO phase 2b/3 (NCT03732807) study, the oral JAK3/TEC family kinase inhibitor ritlecitinib demonstrated efficacy and an acceptable safety profile in patients aged ≥ 12 years with AA and ≥ 50% scalp hair loss. This post hoc analysis investigated associations between prior use of AA therapies and Severity of Alopecia Tool (SALT) responses in patients receiving ritlecitinib for AA. Methods Patients receiving ritlecitinib 30 mg or 50 mg once daily with or without an initial 4-week 200-mg daily loading dose were grouped by previous exposure to AA treatments, including topicals, intralesional corticosteroids (ILCS), topical immunotherapy, and systemic immunosuppressants or any prior AA treatment. Multivariable logistic regression analyses evaluated the association between response based on a SALT score of ≤ 20 and any prior treatment for AA at weeks 24 and 48. Results Of 522 patients, 360 (69.0%) had previous exposure to any AA treatment. At Week 24, SALT ≤ 20 response was positively associated with prior use of ILCS (odds ratio [OR], 2.12; 95% confidence interval [CI], 1.23–3.65; P 0.05). Previous exposure to any AA therapy was not associated with SALT ≤ 20 response at weeks 24 or 48 (all P > 0.05). Conclusions Prior AA treatment history had no effect on longer-term treatment response to ritlecitinib. Trial Registration Number NCT03732807. Graphical Abstract

Abstract We use the worldline formalism to derive Bern-Kosower type Master Formulae for the tree-level scattering of a charged particle and an arbitrary number of photons on impulsive PP-waves, where the coupling of the PP-wave to matter is treated fully non-perturbatively. We show that, in a certain kinematic regime characterised by a semi-classical positive energy condition, both off-shell currents and scattering amplitudes exhibit two novel factorisation structures. First, they may be written as currents in vacuum but with a single additional photon, averaged over the momentum of that photon. This converts the all-orders interaction with the PP-wave into a single effective interaction. Second, the currents and amplitudes may be written as a weighted average of the corresponding quantities in an impulsive plane wave background, with the average taken over all possible field strengths of the plane wave. This generalises a known single-photon result to arbitrary multiplicity.

Abstract Background A decade ago paper questionnaires were more common in epidemiology than those administered online, but increasing Internet access may have changed this. Researchers planning to use a self-administered questionnaire should know whether response rates to questionnaires administered electronically differ to those of questionnaires administered by post. We analysed trials included in a recently updated Cochrane Review to answer this question. Methods We exported data of randomised controlled trials included in three comparisons in the Cochrane Review that had evaluated hypotheses relevant to our research objective and imported them into Stata for a series of meta-analyses not conducted in the Cochrane review. We pooled odds ratios for response using random effects meta-analyses. We explored causes of heterogeneity among study results using subgroups. We assessed evidence for reporting bias using Harbord’s modified test for small-study effects. Results Twenty-seven trials (66,118 participants) evaluated the effect on response of an electronic questionnaire compared with postal. Results were heterogeneous (I-squared = 98%). There was evidence for biased (greater) effect estimates in studies at high risk of bias; A synthesis of studies at low risk of bias indicates that response was increased (OR = 1.43; 95% CI 1.08–1.89) using postal questionnaires. Ten trials (39,523 participants) evaluated the effect of providing a choice of mode (postal or electronic) compared to an electronic questionnaire only. Response was increased with a choice of mode (OR = 1.63; 95% CI 1.18–2.26). Eight trials (20,909 participants) evaluated the effect of a choice of mode (electronic or postal) compared to a postal questionnaire only. There was no evidence for an effect on response of a choice of mode compared with postal only (OR = 0.94; 95% CI 0.86–1.02). Conclusions Postal questionnaires should be used in preference to, or offered in addition to, electronic modes.

Abstract Background Epithelial ovarian cancer (EOC) is the deadliest gynaecological cancer with high mortality rates driven by the common development of resistance to chemotherapy. EOC frequently invades the omentum, an adipocyte-rich organ of the peritoneum and omental adipocytes have been implicated in promoting disease progression, metastasis and chemoresistance. The signalling mechanisms underpinning EOC omentum tropism have yet to be elucidated. Methods Three-dimensional co-culture models were used to explore adipocyte-EOC interactions. The impact of adipocytes on EOC proliferation, response to therapy and invasive capacity was assessed. Primary adipocytes and omental tissue were isolated from patients with ovarian malignancies and benign ovarian neoplasms. Exosomes were isolated from omentum tissue conditioned media and the effect of omentum-derived exosomes on EOC evaluated. Exosomal microRNA (miRNA) sequencing was used to identify miRNAs abundant in omental exosomes and EOC cells were transfected with highly abundant miRNAs miR-21, let-7b, miR-16 and miR-92a. Results We demonstrate the capacity of adipocytes to induce an invasive phenotype in EOC populations through driving epithelial-to-mesenchymal transition (EMT). Exosomes secreted by omental tissue of ovarian cancer patients, as well as patients without malignancies, induced proliferation, upregulated EMT markers and reduced response to paclitaxel therapy in EOC cell lines and HGSOC patient samples. Analysis of the omentum-derived exosomes from cancer patients revealed highly abundant miRNAs that included miR-21, let-7b, miR-16 and miR-92a that promoted cancer cell proliferation and protection from chemotherapy when transfected in ovarian cancer cells. Conclusions These observations highlight the capacity of omental adipocytes to generate a pro-tumorigenic and chemoprotective microenvironment in ovarian cancer and other adipose-related malignancies.

Abstract The cumulative impacts of future climatic and socioeconomic change threaten the ability of freshwater catchments to provide essential ecosystem services. Stakeholders who manage freshwaters require decision-support tools that increase their understanding of catchment system resilience and support the appraisal of adaptive management options to inform decision-making. Our research aims to test the ability of a Bayesian Network model to identify adaptive management scenarios and test their effectiveness across future pathways to 2050. Using the predominantly arable river Eden catchment (320 km2) in eastern Scotland as a case study, we invited stakeholders from multiple sectors to participate in a series of workshops aimed at addressing water quality issues and achieving good ecological status in the catchment both now and in the future. Our participatory methods helped stakeholders overcome multiple layers of complexity and uncertainty associated with future-focused water management. Outputs of a Bayesian Network model simulated both current and future catchment resilience to inform the identification of six management scenarios. The effectiveness of each management scenario was tested using the Bayesian Network model. Two adaptive management scenarios increased catchment resilience and helped achieve good ecological status; a ‘Best Available Technology’ scenario, including aerobic granular sludge treatment, and a management scenario focused on ‘Resource Centre’, including phosphorus recovery from wastewater treatment works and constructed lagoons for crop irrigation. Stakeholders were interested in a 'Nature Based' management scenario including options such as wetland wastewater treatment methods and rural sustainable drainage systems, which improved water quality in the catchment, but had lower certainty in achieving desired outcome. Findings led to a recognition that innovative and collaborative action was required to improve current and future freshwater conditions.

Abstract Background Derivative profiling is a novel approach to identify differential signals from dynamic omics data sets. This approach applies variable step-size differentiation to time dynamic omics data. This work assumes that there is a general omics derivative that is a useful and descriptive feature of dynamic omics experiments. We assert that this omics derivative, or omics flux, is a valuable descriptor that can be used instead of, or with, fold change calculations. Results The results of derivative profiling are compared to established methods such as Multivariate Adaptive Regression Splines, significance versus fold change analysis (Volcano), and an adjusted ratio over intensity (M/A) analysis to find that there is a statistically significant similarity between the results. This comparison is repeated for transcriptomic and phosphoproteomic expression profiles previously characterized in Aspergillus nidulans. This method has been packaged in an open-source, GUI-based MATLAB app, the Derivative Profiling omics Package (DPoP). Gene Ontology (GO) term enrichment has been included in the app so that a user can automatically/programmatically describe the over/under-represented GO terms in the derivative profiling results using domain specific knowledge found in their organism’s specific GO database file. The advantage of the DPoP analysis is that it is computationally inexpensive, it does not require fold change calculations, it describes both instantaneous as well as overall behavior, and it achieves statistical confidence with signal trajectories of a single bio-replicate over four or more points. Conclusions While we apply this method to time dynamic transcriptomic and phosphoproteomic datasets, it is a numerically generalizable technique that can be applied to any organism and any field interested in time series data analysis. The app described in this work enables omics researchers with no computer science background to apply derivative profiling to their data sets, while also allowing multidisciplined users to build on the nascent idea of profiling derivatives in omics.

The field of cardio-oncology is an expanding frontier within cardiovascular medicine, and the need for evidence-based guidelines is apparent. One of the emerging focuses within cardio-oncology is the concomitant use of medications for cardioprotection in the setting of chemotherapy regimens that have known cardiovascular toxicity. While clinical trials focusing on cardioprotection during chemotherapy are sparse, an inaugural trial exploring the prophylactic potential of Sodium-Glucose Cotransporter-2 inhibitors (SGLT2is) for anthracycline (ANT)-induced cardiotoxicity has recently commenced. Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, though less studied in this oncology demographic, have exhibited promise in preclinical studies for conferring cardiac protection during non-ischemic toxic insults. While primarily used to reduce low-density lipoprotein, PCSK9 inhibitors exhibit pleiotropic effects, including the attenuation of inflammation, reactive oxygen species, and endothelial dysfunction. In ANT-induced cardiotoxicity, these same processes are accelerated, resulting in premature termination of treatment, chronic cardiovascular sequelae, heart failure, and/or death. This review serves a dual purpose: firstly, to provide a concise overview of the mechanisms implicated in ANT-induced cardiotoxicity, and, finally, to summarize the existing preclinical data supporting the theoretical possibility of the cardioprotective effects of PCSK9 inhibition in ANT-induced cardiotoxicity.

Abstract Open Science Partnerships (OSPs) are gaining attention as alternatives to university–industry collaborations with restrictive IPR and knowledge sharing policies. OSPs have different expected outcomes and deploy varying means to reach them. Appreciating these differences is crucial to understanding their scientific and socio-economic impact, and yet these differences have never been systematically investigated. This exploratory study draws on qualitative case studies of five biomedical OSPs involving academic partners and pharmaceutical companies. It identifies key elements—purpose, activities and structure—that can be used to describe how OSPs are designed. We identify two key aspects of purpose—predominant intent and research aims—which we argue affect the activities and structure of an OSP. Based on these two aspects, we propose four ideal types of OSPs that are designed to provide a starting point for researchers who explore the nature and impact of OSPs and for practitioners who are developing OSPs and wish to ensure that they deploy appropriate means to meet the intended outcomes of their partnership.

Abstract Background Trauma systems are crucial for enhancing survival and quality of life for trauma patients. Understanding trauma triage and patient outcomes is essential for optimizing resource allocation and trauma care. Aims The aim was to explore prehospital trauma triage in Region Zealand, Denmark. Specifically, characteristics for patients who were either primarily admitted or secondarily transferred to major trauma centers were described. Methods A retrospective descriptive study of severely injured trauma patients was conducted from January 2017 to December 2021. Results The study comprised 744 patients including 55.6% primary and 44.4% secondary patients. Overall, men accounted for 70.2% of patients, and 66.1% were aged 18–65 years. The secondary patients included more women—34.2% versus 26.3% and a higher proportion of Injury Severity Score of ≥ 15—59.6% versus 47.8%, compared to primary patients. 30-day survival was higher for secondary patients—92.7% versus 87%. Medical dispatchers assessed urgency as Emergency level A for 98.1% of primary patients and 86.3% for secondary patients. Physician-staffed prehospital units attended primary patients first more frequently—17.1% versus 3.5%. Response times were similar, but time at scene was longer for primary patients whereas time from injury to arrival at a major trauma center was longer for secondary patients. Conclusions Secondary trauma patients had higher Injury Severity Scores and better survival rates. They were considered less urgent by medical dispatchers and less frequently assessed by physician-staffed units. Prospective quality data are needed for further investigation of optimal triage and continuous quality improvement in trauma care.

Abstract Background Natural language processing (NLP) is increasingly being used to extract structured information from unstructured text to assist clinical decision-making and aid healthcare research. The availability of expert-annotated documents for the development and validation of NLP applications is limited. We created synthetic clinical documents to address this, and to validate the Extraction of Epilepsy Clinical Text version 2 (ExECTv2) NLP pipeline. Methods We created 200 synthetic clinic letters based on hospital outpatient consultations with epilepsy specialists. The letters were double annotated by trained clinicians and researchers according to agreed guidelines. We used the annotation tool, Markup, with an epilepsy concept list based on the Unified Medical Language System ontology. All annotations were reviewed, and a gold standard set of annotations was agreed and used to validate the performance of ExECTv2. Results The overall inter-annotator agreement (IAA) between the two sets of annotations produced a per item F1 score of 0.73. Validating ExECTv2 using the gold standard gave an overall F1 score of 0.87 per item, and 0.90 per letter. Conclusion The synthetic letters, annotations, and annotation guidelines have been made freely available. To our knowledge, this is the first publicly available set of annotated epilepsy clinic letters and guidelines that can be used for NLP researchers with minimum epilepsy knowledge. The IAA results show that clinical text annotation tasks are difficult and require a gold standard to be arranged by researcher consensus. The results for ExECTv2, our automated epilepsy NLP pipeline, extracted detailed epilepsy information from unstructured epilepsy letters with more accuracy than human annotators, further confirming the utility of NLP for clinical and research applications.

Objectives To describe the development, implementation, and results of a training course designed to equip health professionals from the Pan American Health Organization region with the knowledge and tools needed to adapt health systems to current climate realities Methods The Pan American climate resilient health systems course was a 9-week live-virtual course in MarchApril 2023, which was delivered through Zoom and offered in English, Spanish, and French. All lectures were delivered by local and regional climate and health experts. The curricular foundation of this initiative was the Global Consortium on Climate and Health Education core competencies for health professionals. Participants completed pre- and post-course surveys Results A total of 1212 participants attended at least one of the nine sessions and 489 (from 66 countries) attended at least six sessions. Of these, 291 participants completed both the pre- and post-course surveys which were used in the analysis. Longitudinal survey results suggested an improvement in participants climate and health communication, an increased frequency of incorporating climate knowledge in professional practice, and improved confidence in engaging in climate initiatives. At the same time, many participants expressed a need for additional training Conclusions The results indicate that live-virtual courses have the potential to empower health professionals to contribute to climate resilience efforts by: increasing their communication skills; changing their professional practice; increasing their ability to lead climate and health activities; and preparing them to assess vulnerability and adaptation in health systems, measure and monitor environmental sustainability, and apply a health equity lens.

Heat stress events in dairy cows are associated with behavioral and physiological changes such as seeking shade, increased respiration rate and body temperature, reduced milk production, and psychological distress. Knowledge of the relationship between weather and animal responses to heat stress enables automated alerts using forecast weather, aiding early provision of shade or other mitigation practices. While numerous heat stress indices for cattle have been developed, these have limitations for cows exposed to wind and solar radiation (i.e., predominantly grazing outdoors or managed on pasture). To develop a predictive model for heat stress events in pasture-based dairy systems, rumen temperature data from smaXtec (smaXtec animal care GmbH, Graz, Austria) rumen boluses in 443 cows on 3 dairy farms in Northland, New Zealand, were used to identify heat stress events and these were matched with automated weather station data collected on or near the farm. Heat stress rate (HSR) was defined as the percentage of cows within an age-breed group having a rumen temperature greater than 3 standard deviations above an individual cow's mean and heat stress events were defined as HSR >25%. Single and multiple linear regression models, including published heat stress indices, were generally able to predict a high proportion of heat stress events (sensitivity 34%–68%), but were insufficiently discriminating, predicting also a high number of false positives (precision only 9%–27%). A machine learning algorithm, cubist, was the best performing model, predicting 79% of heat stress events with a precision of 52% for this dataset. Our proof-of-concept study demonstrates the potential of this approach, using climate data to predict and forecast heat stress events in pasture-based dairy systems. Further work should test the cubist model using independent data, refine dataset construction, investigate the value of including known animal variables such as cow age or breed, and incorporate other measures of heat stress such as respiration rate.

This study aimed to compare grazing behavior of dairy cows with highly contrasting pasture allocation frequencies. The study ran from September 9, 2022, to December 2, 2022 (12 wk), during a time when daily pasture growth was expected to exceed daily herd intake. Three pasture allocation frequencies were compared, each with 11 spring-calving cows grazing a 4-ha farmlet. The allocations were high frequency rotational grazing (HFRG; 32.5 m2/cow per allocation and 4 allocations/d), rotational grazing with weekly allocations (7RG; 909 m2/cow per allocation and each allocated area continuously grazed over 7 d), and continuous grazing (CG; 1,818 m2/cow per allocation). Animal behavior was monitored using IceQube accelerometers (Peacock Technology) and CowManager ear tags (Agis Automatisering BV). Milk yield and composition were measured and pasture cover was estimated. Daily eating time was highest for CG animals, whereas lying time, lying bouts, and ruminating time were lowest, with no differences between HFRG and 7RG. There were no differences in fat- and protein-corrected milk yield between farmlets; however, estimated accumulated pasture yield was greater with more frequent allocations. Although milk production did not differ between treatment groups, this appeared to be achieved through greater eating times when allocated pasture less frequently, at the expense of time spent lying.

Abstract Due to variable and complex work environments, nonlinearities, uncertainty and disturbances are inevitable in multi‐agent systems. Approximation‐free control can address these issues without involving approximators, such as fuzzy logic systems and neural networks. However, some issues like the singularity problem caused by the signals exceeding the preset boundary in changing work conditions still remain. This paper proposes an adaptive and reliable approximation‐free control, which comprises a novel singularity compensator and a modified transforming function. The proposed control scheme performs better in terms of convergence rate and overshoot, avoids issues relating to singularity, and has added flexibility in terms of parameter choice. The proposed control law adapts to changes in operating conditions and nonlinearities—the efficacy of which is demonstrated using simulations.

Abstract Preeclampsia, a pregnancy complication characterized by hypertension after 20 gestational weeks, is a major cause of maternal and neonatal morbidity and mortality. Mechanisms leading to preeclampsia are unclear; however, there is evidence of high heritability. We evaluated the association of polygenic scores (PGS) for blood pressure traits and preeclampsia to assess whether there is shared genetic architecture. Non-Hispanic Black and White reproductive age females with pregnancy indications and genotypes were obtained from Vanderbilt University’s BioVU, Electronic Medical Records and Genomics network, and Penn Medicine Biobank. Preeclampsia was defined by ICD codes. Summary statistics for diastolic blood pressure (DBP), systolic blood pressure (SBP), and pulse pressure (PP) PGS were acquired from Giri et al. Associations between preeclampsia and each PGS were evaluated separately by race and data source before subsequent meta-analysis. Ten-fold cross validation was used for prediction modeling. In 3504 Black and 5009 White included individuals, the rate of preeclampsia was 15.49%. In cross-ancestry meta-analysis, all PGSs were associated with preeclampsia (ORDBP = 1.10, 95% CI 1.02–1.17, p = 7.68 × 10−3; ORSBP = 1.16, 95% CI 1.09–1.23, p = 2.23 × 10−6; ORPP = 1.14, 95% CI 1.07–1.27, p = 9.86 × 10−5). Addition of PGSs to clinical prediction models did not improve predictive performance. Genetic factors contributing to blood pressure regulation in the general population also predispose to preeclampsia.

Medical stents are vital for treating vascular complications and restoring blood flow in millions of patients. Despite its widespread effectiveness, restenosis, driven by the complex interplay of cellular responses, remains a concern. This study investigated the reactions of vascular cells to nano/microscale wrinkle (nano-W and micro-W) patterns created on laser-textured nitinol (NiTi) surfaces by adjusting laser processing parameters, such as spot overlap ratio and line overlap ratio. Evaluation of topographical effects on endothelial and smooth muscle cells (SMCs) revealed diverse morphologies, proliferation rates, and gene expressions. Notably, microscale wrinkle patterns exhibited reduced monocyte adhesion and inflammation-related gene expression, demonstrating their potential applications in mitigating vascular complications after stent insertion. Additionally, an ex vivo metatarsal assay was utilized to bridge the gap between in vitro and in vivo studies, demonstrating enhanced angiogenesis on laser-textured NiTi surfaces. Laser-textured NiTi exhibits a guided formation process, emphasizing their potential to promote swift endothelialization. These findings underscore the efficacy of laser texturing for tailored cellular interactions on metallic surfaces and offer valuable insights into optimizing biocompatibility and controlling cellular responses, which may pave the way for innovative advances in vascular care and contribute to the ongoing improvement of stent insertion.

Following nearly a decade of unabated growth in the digitally disruptive short-term rental (STR) sector, the onset of the COVID-19 pandemic in 2020 caused a relatively abrupt two-year industry contraction characterised by substantial reductions in participating properties and booking activities. Given the sudden opportunity to rethink how STR markets fit alongside more traditional accommodation arrangements, this unanticipated Black Swan event catalysed much debate about the role that STRs play, and how they are regulated and managed. As the STR market rebounds toward a ‘new normal’, a timely opportunity exists to understand and theorise how and where the industry evolves. In this paper, we apply regression modelling and descriptive statistics to compare STR property utilisation across four regional markets in Australia both before and after the pandemic. We observe a sharp reduction yet strong intensification in available properties after the COVID-19 pandemic, with 27% fewer properties that were booked 26% more often across the nation. This was led by a significant geographical shift from capital cities to high-amenity, tourist-focused regions. Our findings suggest that this pivot is driven by spatial market segmentation, in which urban STRs are operated professionally, whereas regional markets are distinguished by their amenity value, both at the regional and property scales. Combined, the results of this study point to a more professionalised STR hosting landscape in which properties are more intensively used. Any potential policy reform should consider this evolution in the STR accommodation sector.

We consider state and parameter estimation for compartmental models having both time-varying and time-invariant parameters. In this manuscript, we first detail a general Bayesian computational framework as a continuation of our previous work. Subsequently, this framework is specifically tailored to the susceptible-infectious-removed (SIR) model which describes a basic mechanism for the spread of infectious diseases through a system of coupled nonlinear differential equations. The SIR model consists of three states, namely, the susceptible, infectious, and removed compartments. The coupling among these states is controlled by two parameters, the infection rate and the recovery rate. The simplicity of the SIR model and similar compartmental models make them applicable to many classes of infectious diseases. However, the combined assumption of a deterministic model and time-invariance among the model parameters are two significant impediments which critically limit their use for long-term predictions. The tendency of certain model parameters to vary in time due to seasonal trends, non-pharmaceutical interventions, and other random effects necessitates a model that structurally permits the incorporation of such time-varying effects. Complementary to this, is the need for a robust mechanism for the estimation of the parameters of the resulting model from data. To this end, we consider an augmented state vector, which appends the time-varying parameters to the original system states whereby the time evolution of the time-varying parameters are driven by an artificial noise process in a standard manner. Distinguishing between time-varying and time-invariant parameters in this fashion limits the introduction of artificial dynamics into the system, and provides a robust, fully Bayesian approach for estimating the time-invariant system parameters as well as the elements of the process noise covariance matrix. This computational framework is implemented by leveraging the robustness of the Markov chain Monte Carlo algorithm permits the estimation of time-invariant parameters while nested nonlinear filters concurrently perform the joint estimation of the system states and time-varying parameters. We demonstrate performance of the framework by first considering a series of examples using synthetic data, followed by an exposition on public health data collected in the province of Ontario.

Recent discoveries of massive galaxies existing in the early universe, as well as apparent anomalies in Ωm and H0 at high redshift, have raised sharp new concerns for the ΛCDM model of cosmology. Here, we address these problems by using new solutions for the Einstein field equations of relativistic compact objects originally found by Ni. Applied to the universe, the new solutions imply that the universe’s mass is relatively concentrated in a thick outer shell. The interior space would not have a flat, Minkowski metric, but rather a repulsive gravitational field centered on the origin. This field would induce a gravitational redshift in light waves moving inward from the cosmic shell and a corresponding blueshift in waves approaching the shell. Assuming the Milky Way lies near the origin, within the KBC Void, this redshift would make H0 appear to diminish at high redshifts and could thus relieve the Hubble tension. The Ni redshift could also reduce or eliminate the requirement for dark energy in the ΛCDM model. The relative dimness of distant objects would instead arise because the Ni redshift makes them appear closer to us than they really are. To account for the CMB temperature–redshift relation and for the absence of a systematic blueshift in stars closer to the origin than the Milky Way, it is proposed that the Ni redshift and blueshift involve exchanges of photon energy with a photonic spacetime. These exchanges in turn form the basis for a cosmic CMB cycle, which gives rise to gravity and an Einsteinian cosmological constant, Λ. Black holes are suggested to have analogous Ni structures and gravity/Λ cycles.

The dynamic behaviour of a spring-mounted symmetrical NACA0012 wing in a freestream flow of air is studied in the pre-stall region, over 0° to 12° angles of incidence. The primary aim of this work is for use within the automotive sector to reduce drag and fuel emissions. However, this work will also be of interest in the motorsport sector to improve performance, and also have some applications within the aerospace and renewable energy sectors. The general operation of the concept has previously been verified at these low angles in the pre-stall region with that of a theoretical estimation using finite and infinite wings. This paper provides a numerical solution of the same problem and is compared with the previous experimentation. At these low angles, the computations yield a dynamic response settling into a static equilibrium. The stable solutions match the start of a steady regime well, when compared with the experiment. The trends are also comparable with the experiment, but the velocities at which they occur are underestimated in the computation. The computations demonstrate a drag reduction of 59% when compared to a fixed wing, whereas the lift remains stable at a near constant value with increasing wind speed. Thence, downforce is maintained whilst drag is reduced, which will facilitate higher speeds on the straight whilst maintaining vehicle direction stability. Limitations to this proof-of-concept work are highlighted and future development work is suggested to achieve even further increases in performance.

Abstract Background Opioids kill more people than any other class of drug. Naloxone is an opioid antagonist which can be distributed in kits for peer administration. We assessed the feasibility of implementing a Take-home Naloxone (THN) intervention in emergency settings, as part of designing a definitive randomised controlled trial (RCT). Methods We undertook a clustered RCT on sites pairing UK Emergency Departments (ED) and ambulance services. At intervention sites, we recruited emergency healthcare practitioners to supply THN to patients presenting with opioid overdose or related condition, with recruitment across 2019–2021. We assessed feasibility of intervention implementation against four predetermined progression criteria covering site sign up and staff training; identification of eligible patients; issue of THN kits and Serious Adverse Events. Results At two intervention sites, randomly selected from 4, 299/687 (43.5%) clinical staff were trained (ED1 = 107, AS1 = 121, ED2 = 25, AS2 = 46). Sixty THN kits were supplied to eligible patients (21.7%) (n: ED1 = 36, AS1 = 4, ED2 = 16, AS2 = 4). Across sites, kits were not issued to eligible patients on a further 164 occasions, with reasons reported including: staff forgot (n = 136), staff too busy (n = 15), and suspected intentional overdose (n = 3), no kit available (n = 2), already given by drugs nurse (n = 4), other (n = 4). Staff recorded 626 other patients as ineligible but considered for inclusion, with reasons listed as: patient admitted to hospital (n = 194), patient absconded (n = 161) already recruited (n = 64), uncooperative or abusive (n = 55), staff not trained (n = 43), reduced consciousness level (n = 41), lack of capacity (n = 35), patient in custody (n = 21), other (n = 12). No adverse events were reported. Conclusion Staff and patient recruitment were low and varied widely by site. This feasibility study did not meet progression criteria; a fully powered RCT is not planned. Trial Registration ISRCTN13232859 (Registered 16/02/2018).

Abstract Non-coding RNAs (ncRNAs) are frequently documented RNA modification substrates. Nanopore Technologies enables the direct sequencing of RNAs and the detection of modified nucleobases. Ordinarily, direct RNA sequencing uses polyadenylation selection, studying primarily mRNA gene expression. Here, we present NERD-seq, which enables detection of multiple non-coding RNAs, excluded by the standard approach, alongside natively polyadenylated transcripts. Using neural tissues as a proof of principle, we show that NERD-seq expands representation of frequently modified non-coding RNAs, such as snoRNAs, snRNAs, scRNAs, srpRNAs, tRNAs, and rRFs. NERD-seq represents an RNA-seq approach to simultaneously study mRNA and ncRNA epitranscriptomes in brain tissues and beyond.

Abstract There are two main families of G protein-coupled receptors that detect odours in humans, the odorant receptors (ORs) and the trace amine-associated receptors (TAARs). Their amino acid sequences are distinct, with the TAARs being most similar to the aminergic receptors such as those activated by adrenaline, serotonin, dopamine and histamine. To elucidate the structural determinants of ligand recognition by TAARs, we have determined the cryo-EM structure of a murine receptor, mTAAR7f, coupled to the heterotrimeric G protein Gs and bound to the odorant N,N-dimethylcyclohexylamine (DMCHA) to an overall resolution of 2.9 Å. DMCHA is bound in a hydrophobic orthosteric binding site primarily through van der Waals interactions and a strong charge-charge interaction between the tertiary amine of the ligand and an aspartic acid residue. This site is distinct and non-overlapping with the binding site for the odorant propionate in the odorant receptor OR51E2. The structure, in combination with mutagenesis data and molecular dynamics simulations suggests that the activation of the receptor follows a similar pathway to that of the β-adrenoceptors, with the significant difference that DMCHA interacts directly with one of the main activation microswitch residues, Trp6.48.

Abstract Background Patients with rheumatoid arthritis (RA) have an increased risk of developing serious infections (SIs) vs. individuals without RA; efforts to predict SIs in this patient group are ongoing. We assessed the ability of different machine learning modeling approaches to predict SIs using baseline data from the tofacitinib RA clinical trials program. Methods This analysis included data from 19 clinical trials (phase 2, n = 10; phase 3, n = 6; phase 3b/4, n = 3). Patients with RA receiving tofacitinib 5 or 10 mg twice daily (BID) were included in the analysis; patients receiving tofacitinib 11 mg once daily were considered as tofacitinib 5 mg BID. All available patient-level baseline variables were extracted. Statistical and machine learning methods (logistic regression, support vector machines with linear kernel, random forest, extreme gradient boosting trees, and boosted trees) were implemented to assess the association of baseline variables with SI (logistic regression only), and to predict SI using selected baseline variables using 5-fold cross-validation. Missing values were handled individually per prediction model. Results A total of 8404 patients with RA treated with tofacitinib were eligible for inclusion (15,310 patient-years of total follow-up) of which 473 patients reported SIs. Amongst other baseline factors, age, previous infection, and corticosteroid use were significantly associated with SI. When applying prediction modeling for SI across data from all studies, the area under the receiver operating characteristic (AUROC) curve ranged from 0.656 to 0.739. AUROC values ranged from 0.599 to 0.730 in data from phase 3 and 3b/4 studies, and from 0.563 to 0.643 in data from ORAL Surveillance only. Conclusions Baseline factors associated with SIs in the tofacitinib RA clinical trial program were similar to established SI risk factors associated with advanced treatments for RA. Furthermore, while model performance in predicting SI was similar to other published models, this did not meet the threshold for accurate prediction (AUROC > 0.85). Thus, predicting the occurrence of SIs at baseline remains challenging and may be complicated by the changing disease course of RA over time. Inclusion of other patient-associated and healthcare delivery-related factors and harmonization of the duration of studies included in the models may be required to improve prediction. Trial registration ClinicalTrials.gov: NCT00147498; NCT00413660; NCT00550446; NCT00603512; NCT00687193; NCT01164579; NCT00976599; NCT01059864; NCT01359150; NCT02147587; NCT00960440; NCT00847613; NCT00814307; NCT00856544; NCT00853385; NCT01039688; NCT02187055; NCT02831855; NCT02092467.

Abstract Background Covid 19 was declared as a public health emergency by the World Health Organisation (WHO) due to its rapid spread and catastrophic effects on health. It affected around 119 M people with mortality rate of 0.27% worldwide, including South-Asians. This review aims to understand the risk perceptions, cultural religious beliefs and the coping mechanisms of South Asians during the Covid 19 pandemic. Methods We conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The following search engines were used: Medline, Cochrane Library, PsycINFO, CINAHL, and Web of Science. Included studies investigated perceptions and opinions of individuals on knowledge, risk and protective factors, native faith based practices, and attitudes towards the COVID-19 pandemic. Results The database search produced 282 articles to screen. The final narrative synthesis included five studies comprising of 13,476 participants from Pakistan, India, Nepal, and Bangladesh. Ten studies, comprising 7,893 participants, were eligible and included for meta-analysis. The overall pooled prevalence with maximum heterogeneity for correct knowledge of symptoms, hand washing or use of sanitizers, face masking use of herbal or traditional remedies and physical distancing or avoidance of contact was reported through meta-analysis. Conclusion The review brings forth a useful comparison of individual and cultural differences in KAP, risk perceptions and coping strategies. This review highlights the need for and importance of tailored information dissemination, culturally sensitive risk communication, targeted educational interventions, community engagement and empowerment, policy, and infrastructure improvements, as well as continued research and data collection. By addressing these implications, efforts to mitigate the impact of COVID-19 can be more effective and equitable across diverse populations. Prospero registration CRD42021246475.

Abstract We present an exploration of the unpolarized isovector proton generalized parton distributions (GPDs) H u−d (x, ξ, t) and E u−d (x, ξ, t) in the pseudo-distribution formalism using distillation. Taking advantage of the large kinematic coverage made possible by this approach, we present results on the moments of GPDs up to the order x 3 — including their skewness dependence — at a pion mass m π = 358 MeV and a lattice spacing a = 0.094 fm.

Abstract The QUANT study represents the most extensive open-access evaluation of commercial air quality sensor systems to date. This comprehensive study assessed 49 systems from 14 manufacturers across three urban sites in the UK over a three-year period. The resulting open-access dataset captures high time-resolution measurements of a variety of gasses (NO, NO2, O3, CO, CO2), particulate matter (PM1, PM2.5, PM10), and key meteorological parameters (humidity, temperature, atmospheric pressure). The quality and scope of the dataset is enhanced by reference monitors’ data and calibrated products from sensor manufacturers across the three sites. This publicly accessible dataset serves as a robust and transparent resource that details the methods used for data collection and procedures to ensure dataset integrity. It provides a valuable tool for a wide range of stakeholders to analyze the performance of air quality sensors in real-world settings. Policymakers can leverage this data to refine sensor deployment guidelines and develop standardized protocols, while manufacturers can utilize it as a benchmark for technological innovation and product certification. Moreover, the dataset has supported the development of a UK code of practice, and the certification of one of the participating companies, underscoring the dataset’s utility and reliability.

Abstract Background Pregnant women with obesity face heightened focus on weight during pregnancy due to greater risk of medical complications. Closer follow-up in maternety care may contribute to reduce risk and promote health in these women. The aim of this study was to gain a deeper insight in how pregnant women with obesity experience encounters with healthcare providers in maternity care. How is the received maternity care affected by their weight, and how do they describe the way healthcare providers express attitudes towards obesity in pregnancy? Methods We conducted in-depth interviews with 14 women in Trøndelag county in Norway with pre-pregnancy BMI of ≥ 30 kg/m2, between 3 and 12 months postpartum. The study sample was strategic regarding age, relationship status, education level, obesity class, and parity. Themes were developed using reflexive thematic analysis. The analysis was informed by contextual information from a prior study, describing the same participants’ weight history from childhood to motherhood along with their perceptions of childhood quality. Results This study comprised of an overarching theme supported by three main themes. The overarching theme, Being pregnant with a high BMI: a vulnerable condition, reflected the challenge of entering maternity care with obesity, especially for women unprepared to be seen as “outside the norm”. Women who had grown up with body criticism and childhood bullying were more prepared to have their weight addressed in maternity care. The first theme, Loaded conversations: a balancing act, emphasizes how pregnant women with a history of body criticism or obesity-related otherness proactively protect their integrity against weight bias, stigma and shame. The women also described how some healthcare providers balance or avoid weight and risk conversations for the same reasons. Dehumanization: an unintended drawback of standardized care makes apparent the pitfalls of prioritizing standardization over person-centered care. Finally, the third theme, The ambivalence of discussing weight and lifestyle, represent women’s underlying ambivalence towards current weight practices in maternity care. Conclusions Our findings indicate that standardized weight and risk monitoring, along with lifestyle guidance in maternity care, can place the pregnant women with obesity in a vulnerable position, contrasting with the emotionally supportive care that women with obesity report needing. Learning from these women’s experiences and their urge for an unloaded communication to protect their integrity highlights the importance of focusing on patient-centered practices instead of standardized care to create a safe space for health promotion.

Abstract The sympathetic nervous system controls bodily functions including vascular tone, cardiac rhythm, and the “fight-or-flight response”. Sympathetic chain ganglia develop in parallel with preganglionic motor nerves extending from the neural tube, raising the question of whether axon targeting contributes to sympathetic chain formation. Using nerve-selective genetic ablations and lineage tracing in mouse, we reveal that motor nerve-associated Schwann cell precursors (SCPs) contribute sympathetic neurons and satellite glia after the initial seeding of sympathetic ganglia by neural crest. Motor nerve ablation causes mispositioning of SCP-derived sympathoblasts as well as sympathetic chain hypoplasia and fragmentation. Sympathetic neurons in motor-ablated embryos project precociously and abnormally towards dorsal root ganglia, eventually resulting in fusion of sympathetic and sensory ganglia. Cell interaction analysis identifies semaphorins as potential motor nerve-derived signaling molecules regulating sympathoblast positioning and outgrowth. Overall, central innervation functions both as infrastructure and regulatory niche to ensure the integrity of peripheral ganglia morphogenesis.

Abstract Objective To assess the cost-effectiveness of using cheaper-but-noisier outcome measures, such as a short questionnaire, for large simple clinical trials. Background To detect associations reliably, trials must avoid bias and random error. To reduce random error, we can increase the size of the trial and increase the accuracy of the outcome measurement process. However, with fixed resources, there is a trade-off between the number of participants a trial can enrol and the amount of information that can be collected on each participant during data collection. Methods To consider the effect on measurement error of using outcome scales with varying numbers of categories, we define and calculate the variance from categorisation that would be expected from using a category midpoint; define the analytic conditions under which such a measure is cost-effective; use meta-regression to estimate the impact of participant burden, defined as questionnaire length, on response rates; and develop an interactive web-app to allow researchers to explore the cost-effectiveness of using such a measure under plausible assumptions. Results An outcome scale with only a few categories greatly reduced the variance of non-measurement. For example, a scale with five categories reduced the variance of non-measurement by 96% for a uniform distribution. We show that a simple measure will be more cost-effective than a gold-standard measure if the relative increase in variance due to using it is less than the relative increase in cost from the gold standard, assuming it does not introduce bias in the measurement. We found an inverse power law relationship between participant burden and response rates such that a doubling the burden on participants reduces the response rate by around one third. Finally, we created an interactive web-app ( https://benjiwoolf.shinyapps.io/cheapbutnoisymeasures/ ) to allow exploration of when using a cheap-but-noisy measure will be more cost-effective using realistic parameters. Conclusion Cheaper-but-noisier questionnaires containing just a few questions can be a cost-effective way of maximising power. However, their use requires a judgement on the trade-off between the potential increase in risk of information bias and the reduction in the potential of selection bias due to the expected higher response rates.

The Geostationary Environment Monitoring Spectrometer (GEMS) over Asia is the first geostationary Earth orbit instrument in the virtual constellation of sensors for atmospheric chemistry and composition air quality research and applications. For the first time, the hourly observations enable studies of diurnal variation in several important trace gas and aerosol pollutants including nitrogen dioxide (NO2), which is the focus of this work. NO2 is a regulated pollutant and an indicator of anthropogenic emissions in addition to being involved in tropospheric ozone chemistry and particulate matter formation. We present new quantitative measures of NO2 tropospheric column diurnal variation which can be greater than 50 % of the column amount, especially in polluted environments. The NO2 distribution is seen to change hourly and can be quite different from what would be seen by a once-a-day low-Earth-orbit satellite observation. We use GEMS data in combination with TROPOspheric Monitoring Instrument (TROPOMI) satellite and Pandora ground-based remote sensing measurements and Multi-Scale Infrastructure for Chemistry and Aerosols (Version 0, MUSICAv0) 3D chemical transport model analysis to examine the NO2 diurnal variation in January and June 2023 over Northeast Asia and Seoul, South Korea, study regions to distinguish the different emissions, chemistry, and meteorological processes that drive the variation. Understanding the relative importance of these processes will be key to including pollutant diurnal variation in models aimed at determining true pollutant exposure levels for air quality studies. The work presented here also provides a path for investigating similar NO2 diurnal cycles in the new Earth Venture Instrument-1 Tropospheric Emissions: Monitoring Pollution (TEMPO) data over North America, and later over Europe with Sentinel-4.

Abstract Dengue is a global health concern, and the host-viral interactions that regulate disease severity are largely unknown. Detrimental effects of neutrophils in this disease have been reported, but the precise mechanisms and functional properties of dengue-activated neutrophils are not fully characterised. Here, we measured the effects of dengue virus serotype 3 (DV3) on neutrophil lifespan and functions. We show that DV3 extends neutrophil survival with a significant proportion of cells surviving for 72 h post-incubation. These effects on neutrophil survival were greater than those observed by adding GM-CSF and TNF-α alone, but these cytokines enhanced survival induced by the virus. Enhanced reactive oxygen species (ROS) generation was observed following incubation with DV3 activation and this ROS production was enhanced by co-incubation with priming agents. In addition, DV triggered the enhanced IL-8 expression by the majority of neutrophils and a low percentage of cells were activated to express MCP-1 (CCL2). A low number of neutrophils showed increased co-expression of the migratory markers, CCR7 and CXCR4 which could promote their migration towards lymph nodes. DV3 significantly upregulated the BCL-XL gene at 3, 12, and 24 h, and the Mcl-1 gene at 12 h, following treatment. We also show that DV3 induces the Mcl-1 protein stabilization similar to GM-CSF. This report sheds new light on the mechanisms by which neutrophils may contribute to the pathology of dengue disease via delayed apoptosis and generation of pro-inflammatory molecules, and raises the possibility that dengue-activated neutrophils may play a role in activating cells of adaptive immunity.

Abstract Purpose Accurate assessment of chronic pain and functional disability in children and adolescents is imperative for guiding pain management interventions. Parents have multifaceted roles in their child’s pain experience and frequently provide parent-proxy reports of pain-related functioning. However, cross-informant variance is often observed with limited understanding of contributing factors. This study aims to examine the degree of alignment between child and parent-proxy reports for Patient-Reported Outcomes Measurement Information System (PROMIS) pain interference domain among children with chronic pain and to identify factors associated with improved child-parent agreement. Methods This study includes a sample of 127 youth (66.1% female) with mixed etiology chronic pain, ranging in age from 8 to 17 (M = 12.24; SD = 1.598), and their parent. Data was collected at an interdisciplinary pediatric pain clinic and online peer support groups. Measures of demographic, pain intensity, and functioning were collected. Results Means of parent-proxy reports were significantly lower than child self-reports on the PROMIS (p

Abstract The common bean (Phaseolus vulgaris L.) is a crucial legume crop and an ideal evolutionary model to study adaptive diversity in wild and domesticated populations. Here, we present a common bean pan-genome based on five high-quality genomes and whole-genome reads representing 339 genotypes. It reveals ~234 Mb of additional sequences containing 6,905 protein-coding genes missing from the reference, constituting 49% of all presence/absence variants (PAVs). More non-synonymous mutations are found in PAVs than core genes, probably reflecting the lower effective population size of PAVs and fitness advantages due to the purging effect of gene loss. Our results suggest pan-genome shrinkage occurred during wild range expansion. Selection signatures provide evidence that partial or complete gene loss was a key adaptive genetic change in common bean populations with major implications for plant adaptation. The pan-genome is a valuable resource for food legume research and breeding for climate change mitigation and sustainable agriculture.

Abstract The ability to image early treatment response to radiotherapy in head and neck squamous cell carcinoma (HNSCC) will enable the identification of radioresistant tumor volumes suitable for treatment intensification. Here, we propose the system xc − radiotracer (4S)-4-(3-[18F]fluoropropyl)-L-glutamate ([18F]FSPG) as a non-invasive method to monitor radiation response in HNSCC. We assessed temporal changes in cell death, antioxidant status, and [18F]FSPG retention following a single dose of 10 Gy irradiation in FaDU HNSCC cells. Next, using a fractionated course of radiotherapy, we assessed tumor volume changes and performed [18F]FSPG-PET imaging in FaDU-bearing mouse xenografts, followed by ex vivo response assessment. In cells, 10 Gy irradiation reduced [18F]FSPG retention, coinciding with the induction of apoptosis and the production of reactive oxygen species. In vivo, [18F]FSPG tumor retention was halved seven days after the start of treatment, which preceded radiotherapy-induced tumor shrinkage, thereby confirming [18F]FSPG-PET as an early and sensitive marker of radiation response.