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Abstract The proton light yield of liquid scintillators is an important property in the context of their use in large-scale neutrino experiments, with direct implications for neutrino-proton scattering measurements and the discrimination of fast neutrons from inverse $$\beta $$ β -decay coincidence signals. This work presents the first measurement of the proton light yield of a water-based liquid scintillator (WbLS) formulated from 5% linear alkyl benzene (LAB), at energies below 20 MeV, as well as a measurement of the proton light yield of a pure LAB + 2 g/L 2,5-diphenyloxazole (PPO) mixture (LABPPO). The measurements were performed using a double time-of-flight method and a pulsed neutron beam from the 88-Inch Cyclotron at Lawrence Berkeley National Laboratory. The proton light yields were measured relative to that of a 477 keV electron. The relative proton light yield of WbLS was approximately 3.8% lower than that of LABPPO, itself exhibiting a relative proton light yield 15–20% higher than previous measurements of an analogous anoxic sample. The observed quenching is not compatible with the Birks model for either material, but is well described with the addition of Chou’s bimolecular quenching term.

Adolescents who have been diagnosed with disabilities constitute a significant portion of the school population in the United States. For example, the National Survey of Children's Health identified one in four children ages 12 to 17 as having special healthcare needs in 2019 (Data Resource Center for Child and Adolescent Health, n.d.). In the school setting, adolescents with disabilities often have an individualized educational program (IEP). Mandated by the Individuals with Disabilities Educational Act (IDEA) of 2004, an IEP is an educational document that describes a child's disability, along with specific supports a child will receive in school to help achieve optimum educational and developmental success (Individuals with Disabilities Education Act, 2004). Adolescents with disabilities demonstrate a higher risk for emotional distress compared to age-matched peers (Barnes et al., 2010; Emerson et al., 2007; Gilmore et al., 2013; Stein et al., 2011; Rockett, 2021; Lal et al., 2022). A large body of research has investigated the role of protective factors in decreasing the level of emotional distress among adolescents (Bernat et al., 2006; Resnick et al., 1997). Many protective factors have been identified, including protective home environments, adequate sleep (So et al., 2021), strong parental or other adult relationships (Sieving et al., 2017), and involvement in organized activities, such as sports (Brosnahan et al., 2004; Johnson & Taliaferro, 2011; Boelens et al., 2021). Although a higher risk of co-occurring mental health conditions among adolescents with disabilities and a positive benefit of activity involvement are both well-recognized in the literature, few studies have evaluated the possible overlap between these two areas. The goal of the current study, therefore, is to examine the associations between having an IEP and emotional distress among adolescents and the potential protective association of organized activity involvement on emotional distress symptoms among adolescents with an IEP.

Abstract Segmentation, or the classification of pixels (grid cells) in imagery, is ubiquitously applied in the natural sciences. Manual methods are often prohibitively time‐consuming, especially those images consisting of small objects and/or significant spatial heterogeneity of colors or textures. Labeling complicated regions of transition that in Earth surface imagery are represented by collections of mixed‐pixels, ‐textures, and ‐spectral signatures, can be especially error‐prone because it is difficult to reliably unmix, identify and delineate consistently. However, the success of supervised machine learning (ML) approaches is entirely dependent on good label data. We describe a fast, semi‐automated, method for interactive segmentation of N‐dimensional (x, y, N) images into two‐dimensional (x, y) label images. It uses human‐in‐the‐loop ML to achieve consensus between the labeler and a model in an iterative workflow. The technique is reproducible; the sequence of decisions made by human labeler and ML algorithms can be encoded to file, so the entire process can be played back and new outputs generated with alternative decisions and/or algorithms. We illustrate the scientific potential of segmentation of imagery of diverse settings and image types using six case studies from river, estuarine, and open coast environments. These photographic and non‐photographic imagery consist of 1‐ and 3‐bands on regular and irregular grids ranging from centimeters to tens of meters. We demonstrate high levels of agreement in label images generated by several labelers on the same imagery, and make suggestions to achieve consensus and measure uncertainty, ideal for widespread application in training supervised ML for image segmentation.

Abstract Background Argonaute-2 (Ago2) is an essential component of microRNA biogenesis implicated in tumourigenesis. However Ago2 expression and localisation in breast cancer remains undetermined. The aim was to define Ago2 expression (mRNA and protein) and localisation in breast cancer, and investigate associations with clinicopathological details. Methods Ago2 protein was stained in breast cancer cell lines and tissue microarrays (TMAs), with intensity and localization assessed. Staining intensity was correlated with clinicopathological details. Using independent databases, Ago2 mRNA expression and gene alterations in breast cancer were investigated. Results In the breast cancer TMAs, 4 distinct staining intensities were observed (Negative, Weak, Moderate, Strong), with 64.2% of samples stained weak or negatively for Ago2 protein. An association was found between strong Ago2 staining and, the Her2 positive or basal subtypes, and between Ago2 intensity and receptor status (Estrogen or Progesterone). In tumours Ago2 mRNA expression correlated with reduced relapse free survival. Conversely, Ago2 mRNA was expressed significantly lower in SK-BR-3 (HER2 positive) and BT-20 (Basal/Triple negative) cell lines. Interestingly, high levels of Ago2 gene amplification (10–27%) were observed in breast cancer across multiple patient datasets. Importantly, knowledge of Ago2 expression improves predictions of breast cancer subtype by 20%, ER status by 15.7% and PR status by 17.5%. Conclusions Quantification of Ago2 improves the stratification of breast cancer and suggests a differential role for Ago2 in breast cancer subtypes, based on levels and cellular localisation. Further investigation of the mechanisms affecting Ago2 dysregulation will reveal insights into the molecular differences underpinning breast cancer subtypes.

Abstract Background The ineffective implementation of evidence based practice guidelines can mean that the best health outcomes are not achieved. This study examined the barriers and enablers to the uptake and implementation of the new bi-national (Australia and New Zealand) antenatal corticosteroid clinical practice guidelines among health professionals, using the Theoretical Domains Framework. Methods Semi-structured interviews or online questionnaires were conducted across four health professional groups and three district health boards in Auckland, New Zealand. The questions were constructed to reflect the 14 behavioural domains from the Theoretical Domains Framework. Relevant domains were identified by the presence of conflicting beliefs within a domain; the frequency of beliefs; and the likely strength of the impact of a belief on the behaviour using thematic analysis. The influence of health professional group and organisation on the different barriers and enablers identified were explored. Results Seventy-three health professionals completed either a semi-structured interview (n = 35) or on-line questionnaire (n = 38). Seven behavioural domains were identified as overarching enablers: belief about consequences; knowledge; social influences; environmental context and resource; belief about capabilities; social professional role and identity; and behavioural regulation. Five behavioural domains were identified as overarching barriers: environmental context and resources; knowledge; social influences; belief about consequences; and social professional role and identity. Differences in beliefs between individual health professional groups were identified within the domains: belief about consequences; social professional role and identity; and emotion. Organisational differences were identified within the domains: belief about consequences; social influences; and belief about capabilities. Conclusion This study has identified some of the enablers and barriers to implementation of the New Zealand and Australian Antenatal Corticosteroid Clinical Practice Guidelines using the validated Theoretical Domains Framework, as perceived by health professionals. We have identified differences between individual health professional groups and organisations. The identification of these behavioural determinants can be used to enhance an implementation strategy, assist in the design of interventions to achieve improved implementation and facilitate process evaluations to understand why or how change interventions are effective.

The endemic Pyrenean Desman (Galemys pyrenaicus) is an elusive, rare, and vulnerable species declining over its entire and narrow range (Spain, Portugal, France, and Andorra). The principal set of conservation measures in France is a 5-years National Action Plan based on 25 conservation actions. Priority is given to update its present distribution and develop tools for predictive distribution models. We aim at building the first species distribution model and map for the northern edge of the range of the Desman and confronting the outputs of the model to target conservation efforts in the context of environmental change. Contrasting to former comparable studies, we derive a simpler model emphasizing the importance of factors linked to precipitation and not to the temperature. If temperature is one of the climate change key factors, depicted shrinkage in Desman distribution could be lower or null at the northern (French) edge suggesting thus a major role for this northern population in terms of conservation of the species. Finally, we question the applied issue of temporal and spatial transferability for such environmental favourability models when it is made at the edge of the distribution range.

Abstract We present 109 near full-length HIV genomes amplified from blood serum samples obtained during early 1986 from across Uganda, which to our knowledge is the earliest and largest population sample from the initial phase of the HIV epidemic in Africa. Consensus sequences were made from paired-end Illumina reads with a target-capture approach to amplify HIV material following poor success with standard approaches. In comparisons with a smaller ‘intermediate’ genome dataset from 1998 to 1999 and a ‘modern’ genome dataset from 2007 to 2016, the proportion of subtype D was significantly higher initially, dropping from 67% (73/109), to 57% (26/46) to 17% (82/465) respectively (p

High-resolution gridded datasets of meteorological variables are needed in order to resolve fine-scale hydrological gradients in complex mountainous terrain. Across the United States, the highest available spatial resolution of gridded datasets of daily meteorological records is approximately 800 m. This work presents gridded datasets of daily precipitation and mean temperature for the East–Taylor subbasin (in the western United States) covering a 12-year period (2008–2019) at a high spatial resolution (400 m). The datasets are generated using a downscaling framework that uses data-driven models to learn relationships between climate variables and topography. We observe that downscaled datasets of precipitation and mean temperature exhibit smoother spatial gradients (while preserving the spatial variability) when compared to their coarser counterparts. Additionally, we also observe that when downscaled datasets are upscaled to the original resolution (800 m), the mean residual error is almost zero, ensuring no bias when compared with the original data. Furthermore, the downscaled datasets are observed to be linearly related to elevation, which is consistent with the methodology underlying the original 800 m product. Finally, we validate the spatial patterns exhibited by downscaled datasets via an example use case that models lidar-derived estimates of snowpack. The presented dataset constitutes a valuable resource to resolve fine-scale hydrological gradients in the mountainous terrain of the East–Taylor subbasin, which is an important study area in the context of water security for the southwestern United States and Mexico. The dataset is publicly available at https://doi.org/10.15485/1822259 (Mital et al., 2021).

Here the authors observe transcription dynamics in real-time throughout erythropoiesis by combining PP7 tagging of α-globin RNA transcripts and “on-microscope” cell staging. They show how the pattern of transcriptional bursting changes during differentiation, with variability in individual cells significantly reduced at the peak period of gene expression.

Abstract There is growing evidence that pesticides may be among the causes of worldwide bee declines, which has resulted in repeated calls for their increased scrutiny in regulatory assessments. One recurring concern is that the current frameworks may be biased towards assessing risks to the honey bee. This paradigm requires extrapolating toxicity information across bee species. Most research effort has therefore focused on quantifying differences in sensitivity across species. However, our understanding of how responses to pesticides may vary within a species is still very poor. Here we take the first steps towards filling this knowledge gap by comparing acute, lethal hazards in sexes and castes of the eusocial bee Bombus terrestris and in sexes of the solitary bee Osmia bicornis after oral and contact exposure to the pesticides sulfoxaflor, Amistar (azoxystrobin) and glyphosate. We show that sensitivity towards pesticides varies significantly both within and across species. Bee weight was a meaningful predictor of pesticide susceptibility. However, weight could not fully explain the observed differences, which suggests the existence of unexplored mechanisms regulating pesticide sensitivity across bee sexes and castes. Our data show that intra-specific responses are an overlooked yet important aspect of the risk assessment of pesticides in bees.

Abstract Background This review has been developed following a panel discussion with an international group of experts in the care of patients with obesity in the critical care setting and focuses on current best practices in malnutrition screening and assessment, estimation of energy needs for patients with obesity, the risks and management of sarcopenic obesity, the value of tailored nutrition recommendations, and the emerging role of immunonutrition. Patients admitted to the intensive care unit (ICU) increasingly present with overweight and obesity that require individualized nutrition considerations due to underlying comorbidities, immunological factors such as inflammation, and changes in energy expenditure and other aspects of metabolism. While research continues to accumulate, important knowledge gaps persist in recognizing and managing the complex nutritional needs in ICU patients with obesity. Available malnutrition screening and assessment tools are limited in patients with obesity due to a lack of validation and heterogeneous factors impacting nutrition status in this population. Estimations of energy and protein demands are also complex in patients with obesity and may include estimations based upon ideal, actual, or adjusted body weight. Evidence is still sparse on the role of immunonutrition in patients with obesity, but the presence of inflammation that impacts immune function may suggest a role for these nutrients in hemodynamically stable ICU patients. Educational efforts are needed for all clinicians who care for complex cases of critically ill patients with obesity, with a focus on strategies for optimal nutrition and the consideration of issues such as weight stigma and bias impacting the delivery of care. Conclusions Current nutritional strategies for these patients should be undertaken with a focus on individualized care that considers the whole person, including the possibility of preexisting comorbidities, altered metabolism, and chronic stigma, which may impact the provision of nutritional care. Additional research should focus on the applicability of current guidelines and evidence for nutrition therapy in populations with obesity, especially in the setting of critical illness.

Abstract Current breast tumor margin detection methods are destructive, time-consuming, and result in significant reoperative rates. Dual-modality photoacoustic tomography (PAT) and ultrasound has the potential to enhance breast margin characterization by providing clinically relevant compositional information with high sensitivity and tissue penetration. However, quantitative methods that rigorously compare volumetric PAT and ultrasound images with gold-standard histology are lacking, thus limiting clinical validation and translation. Here, we present a quantitative multimodality workflow that uses inverted Selective Plane Illumination Microscopy (iSPIM) to facilitate image co-registration between volumetric PAT-ultrasound datasets with histology in human invasive ductal carcinoma breast tissue samples. Our ultrasound-PAT system consisted of a tunable Nd:YAG laser coupled with a 40 MHz central frequency ultrasound transducer. A linear stepper motor was used to acquire volumetric PAT and ultrasound breast biopsy datasets using 1100 nm light to identify hemoglobin-rich regions and 1210 nm light to identify lipid-rich regions. Our iSPIM system used 488 nm and 647 nm laser excitation combined with Eosin and DRAQ5, a cell-permeant nucleic acid binding dye, to produce high-resolution volumetric datasets comparable to histology. Image thresholding was applied to PAT and iSPIM images to extract, quantify, and topologically visualize breast biopsy lipid, stroma, hemoglobin, and nuclei distribution. Our lipid-weighted PAT and iSPIM images suggest that low lipid regions strongly correlate with malignant breast tissue. Hemoglobin-weighted PAT images, however, correlated poorly with cancerous regions determined by histology and interpreted by a board-certified pathologist. Nuclei-weighted iSPIM images revealed similar cellular content in cancerous and non-cancerous tissues, suggesting malignant cell migration from the breast ducts to the surrounding tissues. We demonstrate the utility of our nondestructive, volumetric, region-based quantitative method for comprehensive validation of 3D tomographic imaging methods suitable for bedside tumor margin detection.

The Australian Community Climate and Earth System Simulator (ACCESS) has contributed to the World Climate Research Programme’s Coupled Model Intercomparison Project Phase 6 (CMIP6) using two fully coupled model versions (ACCESS-CM2 and ACCESS-ESM1.5) and two ocean–sea-ice model versions (1° and 0.25° resolution versions of ACCESS-OM2). The fully coupled models differ primarily in the configuration and version of their atmosphere components (including the aerosol scheme), with smaller differences in their sea-ice and land model versions. Additionally, ACCESS-ESM1.5 includes biogeochemistry in the land and ocean components and can be run with an interactive carbon cycle. CMIP6 comprises core experiments and associated thematic Model Intercomparison Projects (MIPs). This paper provides an overview of the CMIP6 submission, including the methods used for the preparation of input forcing datasets and the post-processing of model output, along with a comprehensive list of experiments performed, detailing their initialisation, duration, ensemble number and computational cost. A small selection of model output is presented, focusing on idealised experiments and their variants at global scale. Differences in the climate simulation of the two coupled models are highlighted. ACCESS-CM2 produces a larger equilibrium climate sensitivity (4.7°C) than ACCESS-ESM1.5 (3.9°C), likely a result of updated atmospheric parameterisation in recent versions of the atmospheric component of ACCESS-CM2. The idealised experiments run with ACCESS-ESM1.5 show that land and ocean carbon fluxes respond to both changing atmospheric CO2 and to changing temperature. ACCESS data submitted to CMIP6 are available from the Earth System Grid Federation (https://doi.org/10.22033/ESGF/CMIP6.2281 and https://doi.org/10.22033/ESGF/CMIP6.2288). The information provided in this paper should facilitate easier use of these significant datasets by the broader climate community.

The increasing availability of high-quality remote sensing data and advanced technologies has spurred land cover mapping to characterize land change from local to global scales. However, most land change datasets either span multiple decades at a local scale or cover limited time over a larger geographic extent. Here, we present a new land cover and land surface change dataset created by the Land Change Monitoring, Assessment, and Projection (LCMAP) program over the conterminous United States (CONUS). The LCMAP land cover change dataset consists of annual land cover and land cover change products over the period 1985–2017 at a 30 m resolution using Landsat and other ancillary data via the Continuous Change Detection and Classification (CCDC) algorithm. In this paper, we describe our novel approach to implement the CCDC algorithm to produce the LCMAP product suite composed of five land cover products and five products related to land surface change. The LCMAP land cover products were validated using a collection of ∼25 000 reference samples collected independently across CONUS. The overall agreement for all years of the LCMAP primary land cover product reached 82.5 %. The LCMAP products are produced through the LCMAP Information Warehouse and Data Store (IW+DS) and shared Mesos cluster systems that can process, store, and deliver all datasets for public access. To our knowledge, this is the first set of published 30 m annual land change datasets that include land cover, land cover change, and spectral change spanning from the 1980s to the present for the United States. The LCMAP product suite provides useful information for land resource management and facilitates studies to improve the understanding of terrestrial ecosystems and the complex dynamics of the Earth system. The LCMAP system could be implemented to produce global land change products in the future. The LCMAP products introduced in this paper are freely available at https://doi.org/10.5066/P9W1TO6E (LCMAP, 2021).

Abstract Pollinators, particularly wild bees, are suffering declines across the globe, and pesticides are thought to be drivers of these declines. Research into, and regulation of pesticides has focused on the active ingredients, and their impact on bee health. In contrast, the additional components in pesticide formulations have been overlooked as potential threats. By testing an acute oral dose of the fungicide product Amistar, and equivalent doses of each individual co-formulant, we were able to measure the toxicity of the formulation and identify the ingredient responsible. We found that a co-formulant, alcohol ethoxylates, caused a range of damage to bumble bee health. Exposure to alcohol ethoxylates caused 30% mortality and a range of sublethal effects. Alcohol ethoxylates treated bees consumed half as much sucrose as negative control bees over the course of the experiment and lost weight. Alcohol ethoxylates treated bees had significant melanisation of their midguts, evidence of gut damage. We suggest that this gut damage explains the reduction in appetite, weight loss and mortality, with bees dying from energy depletion. Our results demonstrate that sublethal impacts of pesticide formulations need to be considered during regulatory consideration, and that co-formulants can be more toxic than active ingredients.

Abstract Background Host population structure is a key determinant of pathogen and infectious disease transmission patterns. Pathogen phylogenetic trees are useful tools to reveal the population structure underlying an epidemic. Determining whether a population is structured or not is useful in informing the type of phylogenetic methods to be used in a given study. We employ tree statistics derived from phylogenetic trees and machine learning classification techniques to reveal an underlying population structure. Results In this paper, we simulate phylogenetic trees from both structured and non-structured host populations. We compute eight statistics for the simulated trees, which are: the number of cherries; Sackin, Colless and total cophenetic indices; ladder length; maximum depth; maximum width, and width-to-depth ratio. Based on the estimated tree statistics, we classify the simulated trees as from either a non-structured or a structured population using the decision tree (DT), K-nearest neighbor (KNN) and support vector machine (SVM). We incorporate the basic reproductive number ( $$R_0$$ R 0 ) in our tree simulation procedure. Sensitivity analysis is done to investigate whether the classifiers are robust to different choice of model parameters and to size of trees. Cross-validated results for area under the curve (AUC) for receiver operating characteristic (ROC) curves yield mean values of over 0.9 for most of the classification models. Conclusions Our classification procedure distinguishes well between trees from structured and non-structured populations using the classifiers, the two-sample Kolmogorov-Smirnov, Cucconi and Podgor-Gastwirth tests and the box plots. SVM models were more robust to changes in model parameters and tree size compared to KNN and DT classifiers. Our classification procedure was applied to real -world data and the structured population was revealed with high accuracy of $$92.3\%$$ 92.3 % using SVM-polynomial classifier.

A core component of nearly all bacteria, the cell wall is an ideal target for broad spectrum antibiotics. Many bacteria have evolved strategies to sense and respond to antibiotics targeting cell wall synthesis, especially in the soil where antibiotic-producing bacteria compete with one another. Here we show that cell wall stress caused by both chemical and genetic inhibition of the essential, bifunctional penicillin-binding protein PBP1a prevents microcolony formation and activates the canonical host-invasion two-component system ChvG-ChvI in Agrobacterium tumefaciens. Using RNA-seq, we show that depletion of PBP1a for 6 hours results in a downregulation in transcription of flagellum-dependent motility genes and an upregulation in transcription of type VI secretion and succinoglycan biosynthesis genes, a hallmark of the ChvG-ChvI regulon. Depletion of PBP1a for 16 hours, results in differential expression of many additional genes and may promote a stress response, resembling those of sigma factors in other bacteria. Remarkably, the overproduction of succinoglycan causes cell spreading and deletion of the succinoglycan biosynthesis gene exoA restores microcolony formation. Treatment with cefsulodin phenocopies depletion of PBP1a and we correspondingly find that chvG and chvI mutants are hypersensitive to cefsulodin. This hypersensitivity only occurs in response to treatment with β-lactam antibiotics, suggesting that the ChvG-ChvI pathway may play a key role in resistance to antibiotics targeting cell wall synthesis. Finally, we provide evidence that ChvG-ChvI likely has a conserved role in conferring resistance to cell wall stress within the Alphaproteobacteria that is independent of the ChvG-ChvI repressor ExoR.

ABSTRACT Candida albicans exists as a commensal of mucosal surfaces and the gastrointestinal tract without causing pathology. However, this fungus is also a common cause of mucosal and systemic infections when antifungal immune defenses become compromised. The activation of antifungal host defenses depends on the recognition of fungal pathogen-associated molecular patterns (PAMPs), such as β-1,3-glucan. In C. albicans, most β-1,3-glucan is present in the inner cell wall, concealed by the outer mannan layer, but some β-1,3-glucan becomes exposed at the cell surface. In response to host signals, such as lactate, C. albicans induces the Xog1 exoglucanase, which shaves exposed β-1,3-glucan from the cell surface, thereby reducing phagocytic recognition. We show here that β-1,3-glucan is exposed at bud scars and punctate foci on the lateral wall of yeast cells, that this exposed β-1,3-glucan is targeted during phagocytic attack, and that lactate-induced masking reduces β-1,3-glucan exposure at bud scars and at punctate foci. β-1,3-Glucan masking depends upon protein kinase A (PKA) signaling. We reveal that inactivating PKA, or its conserved downstream effectors, Sin3 and Mig1/Mig2, affects the amounts of the Xog1 and Eng1 glucanases in the C. albicans secretome and modulates β-1,3-glucan exposure. Furthermore, perturbing PKA, Sin3, or Mig1/Mig2 attenuates the virulence of lactate-exposed C. albicans cells in Galleria. Taken together, the data are consistent with the idea that β-1,3-glucan masking contributes to Candida pathogenicity. IMPORTANCE Microbes that coexist with humans have evolved ways of avoiding or evading our immunological defenses. These include the masking by these microbes of their “pathogen-associated molecular patterns” (PAMPs), which are recognized as “foreign” and used to activate protective immunity. The commensal fungus Candida albicans masks the proinflammatory PAMP β-1,3-glucan, which is an essential component of its cell wall. Most of this β-1,3-glucan is hidden beneath an outer layer of the cell wall on these microbes, but some can become exposed at the fungal cell surface. Using high-resolution confocal microscopy, we examine the nature of the exposed β-1,3-glucan at C. albicans bud scars and at punctate foci on the lateral cell wall, and we show that these features are targeted by innate immune cells. We also reveal that downstream effectors of protein kinase A (Mig1/Mig2, Sin3) regulate the secretion of major glucanases, modulate the levels of β-1,3-glucan exposure, and influence the virulence of C. albicans in an invertebrate model of systemic infection. Our data support the view that β-1,3-glucan masking contributes to immune evasion and the virulence of a major fungal pathogen of humans.

In this study, acetylcholine release is shown to reorganise hippocampal CA1 inhibitory networks resulting in prioritisation of entorhinal input over CA3 input. This is achieved by activation of a combination of M3 and M4 muscarinic receptors.

Abstract Aryl polyenes (APEs) are specialized polyunsaturated carboxylic acids that were identified in silico as the product of the most widespread family of bacterial biosynthetic gene clusters (BGCs). They are present in several Gram-negative host-associated bacteria, including multidrug-resistant human pathogens. Here, we characterize a biological function of APEs, focusing on the BGC from a uropathogenic Escherichia coli (UPEC) strain. We first perform a genetic deletion analysis to identify the essential genes required for APE biosynthesis. Next, we show that APEs function as fitness factors that increase protection from oxidative stress and contribute to biofilm formation. Together, our study highlights key steps in the APE biosynthesis pathway that can be explored as potential drug targets for complementary strategies to reduce fitness and prevent biofilm formation of multi-drug resistant pathogens.

Abstract Coastal communities and infrastructure need protection from flooding and wave overtopping events. Assessment of hazard prediction methods, used in sea defence design, defence performance inspections and forecasting services, requires observations at the land-sea interface but these are rarely collected. Here we show how a database of hindcast overtopping events, and the conditions that cause them, can be built using qualitative overtopping information obtained from social media. We develop a database for a case study site at Crosby in the Northwest of England, use it to test the standard methods applied in operational flood forecasting services and new defence design, and suggest improvements to these methods. This novel approach will become increasingly important to deliver long-term, cost-effective coastal management solutions as sea-levels rise and coastal populations grow. At sites with limited, or no, monitoring or forecasting services, this approach, especially if combined with citizen science initiatives, could underpin the development of simplified early warning systems.

Background In cancer therapy, higher-resolution tumor-agnostic biomarkers that predict response to immune checkpoint inhibitor (ICI) therapy are needed. Mutation signatures reflect underlying oncogenic processes that can affect tumor immunogenicity, and thus potentially delineate ICI treatment response among tumor types.Methods Based on mutational signature analysis, we developed a stratification for all solid tumors in The Cancer Genome Atlas (TCGA). Subsequently, we developed a new software (Genomic Subtyping and Predictive Response Analysis for Cancer Tumor ICi Efficacy, GS-PRACTICE) to classify new tumors submitted to whole-exome sequencing. Using existing data from 973 pan-cancer ICI-treated cases with outcomes, we evaluated the subtype-response predictive performance.Results Systematic analysis on TCGA samples identified eight tumor genomic subtypes, which were characterized by features represented by smoking exposure, ultraviolet light exposure, APOBEC enzyme activity, POLE mutation, mismatch repair deficiency, homologous recombination deficiency, genomic stability, and aging. The former five subtypes were presumed to form an immune-responsive group acting as candidates for ICI therapy because of their high expression of immune-related genes and enrichment in cancer types with FDA approval for ICI monotherapy. In the validation cohort, the samples assigned by GS-PRACTICE to the immune-reactive subtypes were significantly associated with ICI response independent of cancer type and TMB high or low status.Conclusions The new tumor subtyping method can serve as a tumor-agnostic biomarker for ICI response prediction and will improve decision making in cancer treatment.

Advanced liver diseases account for approximately 2 million deaths annually worldwide. Roughly, half of liver disease-associated deaths arise from complications of cirrhosis and the other half driven by viral hepatitis and hepatocellular carcinoma. Unfortunately, the development of therapeutic strategies to treat subjects with advanced liver disease has been hampered by a lack of mechanistic understanding of liver disease progression and a lack of human-relevant animal models. An important advance has been made within the past several years, as several genome-wide association studies have discovered that an SNP near the gene encoding membrane-bound O-acyltransferase 7 (MBOAT7) is associated with severe liver diseases. This common MBOAT7 variant (rs641738, C>T), which reduces MBOAT7 expression, confers increased susceptibility to nonalcoholic fatty liver disease, alcohol-associated liver disease, and liver fibrosis in patients chronically infected with viral hepatitis. Recent studies in mice also show that Mboat7 loss of function can promote hepatic steatosis, inflammation, and fibrosis, causally linking this phosphatidylinositol remodeling enzyme to liver health in both rodents and humans. Herein, we review recent insights into the mechanisms by which MBOAT7-driven phosphatidylinositol remodeling influences liver disease progression and discuss how rapid progress in this area could inform drug discovery moving forward.

Abstract Based on our previous phase II clinical trial of anti-programmed death-1 (PD-1) antibody nivolumab for platinum-resistant ovarian cancer (n = 19, UMIN000005714), we aimed to identify the biomarkers predictive of response. Tumor gene expression was evaluated by proliferative, mesenchymal, differentiated, and immunoreactive gene signatures derived from high-grade serous carcinomas and a signature established prior for ovarian clear cell carcinoma. Resulting signature scores were statistically assessed with both univariate and multivariate approaches for correlation to clinical response. Analyses were performed to identify pathways differentially expressed by either the complete response (CR) or progressive disease (PD) patient groups. The clear cell gene signature was scored significantly higher in the CR group, and the proliferative gene signature had significantly higher scores in the PD group where nivolumab was not effective (respective p values 0.005 and 0.026). Combinations of gene signatures improved correlation with response, where a visual projection of immunoreactive, proliferative, and clear cell signatures differentiated clinical response. An applicable clinical response prediction formula was derived. Ovarian cancer-specific gene signatures and related pathway scores provide a robust preliminary indicator for ovarian cancer patients prior to anti-PD-1 therapy decisions.

Abstract Glioblastoma (GBM) displays marked cellular and metabolic heterogeneity that varies among cellular microenvironments within a tumor. Metabolic targeting has long been advocated as a therapy against many tumors including GBM, but how lipid metabolism is altered to suit different microenvironmental conditions and whether cancer stem cells (CSCs) have altered lipid metabolism are outstanding questions in the field. We interrogated gene expression in separate microenvironments of GBM organoid models that mimic the transition between nutrient-rich and nutrient-poor pseudopalisading/perinecrotic tumor zones using spatial-capture RNA-sequencing. We revealed a striking difference in lipid processing gene expression and total lipid content between diverse cell populations from the same patient, with lipid enrichment in hypoxic organoid cores and also in perinecrotic and pseudopalisading regions of primary patient tumors. This was accompanied by regionally restricted upregulation of hypoxia-inducible lipid droplet-associated (HILPDA) gene expression in organoid cores and pseudopalisading regions of clinical GBM specimens, but not lower-grade brain tumors. CSCs have low lipid droplet accumulation compared to non-CSCs in organoid models and xenograft tumors, and prospectively sorted lipid-low GBM cells are functionally enriched for stem cell activity. Targeted lipidomic analysis of multiple patient-derived models revealed a significant shift in lipid metabolism between GBM CSCs and non-CSCs, suggesting that lipid levels may not be simply a product of the microenvironment but also may be a reflection of cellular state. CSCs had decreased levels of major classes of neutral lipids compared to non-CSCs, but had significantly increased polyunsaturated fatty acid production due to high fatty acid desaturase (FADS1/2) expression which was essential to maintain CSC viability and self-renewal. Our data demonstrate spatially and hierarchically distinct lipid metabolism phenotypes occur clinically in the majority of patients, can be recapitulated in laboratory models, and may represent therapeutic targets for GBM.

Abstract Periodontitis is characterized by subgingival biofilm dysbiosis, inflammation and tissue destruction. Current treatment involves mechanical biofilm disruption known as non-surgical periodontal therapy (NSPT). This study sought to characterise the impact of treatment on microbial diversity and overall community, and the parallel impact on host inflammation in the oral cavity. Fourty-two periodontitis patients were included in this study, with periodontal clinical parameters, subgingival plaque and saliva samples collected at baseline and 90 days after treatment. Salivary cytokines were quantified, and subgingival plaque was analysed using 16S rRNA sequencing. After treatment, there were marked health-associated alterations in microbial composition and diversity, including differential abundance of 42 genera and 61 species. These changes were accompanied by substantial clinical improvement (pockets ≥ 5 mm, 27.50% to 9.00%, p

Gamma photons used in positron emission tomography are predicted to be produced in an entangled state. Here, the authors simulate the effects of entanglement and test them through comparison with experimental data from a PET demonstrator apparatus, showing the potential gains in background suppression.

Abstract The in vitro growth (IVG) of human follicles is a potential fertility option for women for whom cryopreserved ovarian tissues cannot be transplanted due to the risk of cancer cell reintroduction; however, there is currently no established method. Furthermore, optimal IVG conditions may differ between the follicles of adult and pre-pubertal females due to molecular differences suggested by basic research. To systematically identify differences between the secondary follicles of adult and pre-pubertal females, a comparative transcriptomic study using mice was conducted herein. Among differentially expressed genes (DEGs), Figla was up-regulated in mature mice. We successfully down-regulated Figla expression in secondary follicle oocytes by a Figla siRNA microinjection, and the subsequent IVG of follicles showed that the diameter of these follicles was smaller than those of controls in mature mice, whereas no significant difference was observed in premature mice. The canonical pathways of DEGs between control and Figla-reduced secondary follicles suggest that Figla up-regulates VDR/RXR activation and down-regulates stem cell pluripotency as well as estrogen signaling. We demonstrated for the first time that folliculogenesis of the secondary follicles of premature and mature mice may be regulated by different factors, such as Figla with its possible target genes, providing insights into optimal IVG conditions for adult and pre-pubertal females, respectively.

Abstract Background Patient-reported outcomes (PROs) are used in clinical trials to assess the effectiveness and tolerability of interventions. Inclusion of participants from different ethnic backgrounds is essential for generalisability of cancer trial results. PRO data collection should include appropriately translated patient-reported outcome measures (PROMs) to minimise missing data and sample attrition. Methods Protocols and/or publications from cancer clinical trials using a PRO endpoint and registered on the National Institute for Health Research Portfolio were systematically reviewed for information on recruitment, inclusion of ethnicity data, and use of appropriately translated PROMs. Semi-structured interviews were conducted with key stakeholders to explore barriers and facilitators for optimal PRO trial design, diverse recruitment and reporting, and use of appropriately translated PROMs. Results Eighty-four trials met the inclusion criteria, only 14 (17%) (n = 4754) reported ethnic group data, and ethnic group recruitment was low, 611 (13%). Although 8 (57%) studies were multi-centred and multi-national, none reported using translated PROMs, although available for 7 (88%) of the studies. Interviews with 44 international stakeholders identified a number of perceived barriers to ethnically diverse recruitment including diverse participant engagement, relevance of ethnicity to research question, prominence of PROs, and need to minimise investigator burden. Stakeholders had differing opinions on the use of translated PROMs, the impact of trial designs, and recruitment strategies on diverse recruitment. Facilitators of inclusive research were described and examples of good practice identified. Conclusions Greater transparency is required when PROs are used as primary or secondary outcomes in clinical trials. Protocols and publications should demonstrate that recruitment was accessible to diverse populations and facilitated by trial design, recruitment strategies, and appropriate PROM usage. The use of translated PROMs should be made explicit when used in cancer clinical trials.

A primary mercury gas standard was developed at Van Swinden Laboratory (VSL) to establish an International System of Units (SI)-traceable reference point for mercury concentrations at emission and background levels in the atmosphere. The majority of mercury concentration measurements are currently made traceable to the empirically determined vapour pressure of mercury. The primary mercury gas standard can be used for the accurate and precise calibration of analytical systems used for measuring mercury concentrations in air. It has been especially developed to support measurements related to ambient air monitoring (1–2 ng m−3), indoor and workplace-related mercury concentration levels according to health standards (from 50 ng m−3 upwards) as well as stationary source emissions (from 1 µg m−3 upwards). The primary mercury gas standard is based on diffusion according to ISO 6154-8. Calibration gas mixtures are obtained by combining calibrated mass flows of nitrogen and air through a generator holding diffusion cells containing elemental mercury. In this paper, we present the results of comparisons between the primary gas standard and mercury calibration methods maintained by NPL (National Physical Laboratory in the United Kingdom), a National Metrology Institute (NMI), and the Jozef Stefan Institute (JSI), a Designated Institute (DI). The calibration methods currently used at NPL and JSI are based on the bell-jar calibration apparatus in combination with the Dumarey equation or a NIST (National Institute of Standards and Technology in the United States) reference material. For the comparisons, mercury was sampled on sorbent traps to obtain transfer standards with levels between 2 and 1000 ng with an expanded uncertainty not exceeding 3 % (k=2). The comparisons performed show that the results for the primary gas standard and the NIST reference material are comparable, whereas a difference of −8 % exists between results traceable to the primary gas standard and the Dumarey equation.

Abstract Background Associations between kidney disease and periodontal disease are not well documented among Aboriginal people of Australia. The purpose of this investigation was to report and compare demographic, oral health, anthropometric and systemic health status of Aboriginal Australians with kidney disease and to compare against relevant Aboriginal Australians and Australian population estimates. This provides much needed evidence to inform dental health service provision policies for Aboriginal Australians with kidney disease. Methods Sample frequencies and means were assessed in adults represented in six datasets including: (1) 102 Aboriginal Australians with kidney disease residing in Central Australia who participated in a detailed oral health assessment; (2) 312 Aboriginal participants of the Northern Territory’s PerioCardio study; (3) weighted estimates from 4775 participants from Australia’s National Survey of Adult Oral Health (NSAOH); (4) Australian 2016 Census (all Australians); (5) National Health Survey 2017–2018 (all Australians) and; (6) Australian Health Survey: Biomedical Results for Chronic Diseases, 2011–2012 (all Australians). Oral health status was described by periodontal disease and experience of dental caries (tooth decay). Statistically significant differences were determined via non-overlapping 95% confidence intervals. Results Aboriginal Australians with kidney disease were significantly older, less likely to have a tertiary qualification or be employed compared with both PerioCardio study counterparts and NSAOH participants. Severe periodontitis was found in 54.3% of Aboriginal Australians with kidney disease, almost 20 times the 2.8% reported in NSAOH. A higher proportion of Aboriginal Australians with kidney disease had teeth with untreated caries and fewer dental restorations when compared to NSAOH participants. The extent of periodontal attachment loss and periodontal pocketing among Aboriginal Australians with kidney disease (51.0%, 21.4% respectively) was several magnitudes greater than PerioCardio study (22.0%, 12.3% respectively) and NSAOH (5.4%, 1.3% respectively) estimates. Conclusions Aboriginal Australians with kidney disease exhibited more indicators of poorer oral health than both the general Australian population and a general Aboriginal population from Australia’s Northern Territory. It is imperative that management of oral health among Aboriginal Australians with kidney disease be included as part of their ongoing medical care.

Abstract Background Emergence of Candida glabrata, which causes potential life-threatening invasive candidiasis, has been widely associated with high morbidity and mortality. In order to cause disease in vivo, a robust and highly efficient metabolic adaptation is crucial for the survival of this fungal pathogen in human host. In fact, reprogramming of the carbon metabolism is believed to be indispensable for phagocytosed C. glabrata within glucose deprivation condition during infection. Methods In this study, the metabolic responses of C. glabrata under acetate growth condition was explored using high-throughput transcriptomic and proteomic approaches. Results Collectively, a total of 1482 transcripts (26.96%) and 242 proteins (24.69%) were significantly up- or down-regulated. Both transcriptome and proteome data revealed that the regulation of alternative carbon metabolism in C. glabrata resembled other fungal pathogens such as Candida albicans and Cryptococcus neoformans, with up-regulation of many proteins and transcripts from the glyoxylate cycle and gluconeogenesis, namely isocitrate lyase (ICL1), malate synthase (MLS1), phosphoenolpyruvate carboxykinase (PCK1) and fructose 1,6-biphosphatase (FBP1). In the absence of glucose, C. glabrata shifted its metabolism from glucose catabolism to anabolism of glucose intermediates from the available carbon source. This observation essentially suggests that the glyoxylate cycle and gluconeogenesis are potentially critical for the survival of phagocytosed C. glabrata within the glucose-deficient macrophages. Conclusion Here, we presented the first global metabolic responses of C. glabrata to alternative carbon source using transcriptomic and proteomic approaches. These findings implicated that reprogramming of the alternative carbon metabolism during glucose deprivation could enhance the survival and persistence of C. glabrata within the host.