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Citrulline malate (CM) has been touted as a nutritional ergogenic aid for sports performance, with purported mechanisms of increased muscle blood flow, ammonia clearance, and adenosine triphosphate resynthesis. Combined, these physiological benefits may be best applied to whole-body endurance exercises, such as swimming, though this postulate has not yet been explored. In a double-blind, randomised, and crossover design, 11 national-level swimmers (age: 17 ± 3 years, height: 1.71 ± 0.05 m, body mass: 60.6 ± 8.3 kg) from a high-performance swimming club ingested either 15 g CM or a placebo (PLA) 60 min before six × 300 m freestyle bouts (at 4.5 min intervals). Blood lactate, blood pressure, and ratings of perceived exertion were measured at baseline, 60 min post-ingestion, and immediately post-exercise. Neither mean 300 m swimming time (CM: 212.0 ± 9.6 vs. PLA: 212.8 ± 7.7 s, p = 0.683, g = 0.09) nor any individual swimming bouts (p = 0.679, Pŋ2 = 0.02) were improved with CM ingestion. Moreover, no differences in any physiological or subjective measures were identified between conditions (all p > 0.05). Whether the proposed CM mechanisms were active was unclear as more direct physiological measures (i.e., plasma NO, ammonia) may have been required. Resultantly, these observations do not support an ergogenic effect of acute CM ingestion in highly trained swimmers.

Abstract Aim To investigate the potential of embedded research in bridging the gap between research evidence and its implementation in public health practice. Methods Using a case study methodology, semi-structured interviews were conducted with 4 embedded researchers, 9 public health practitioners, and 4 other stakeholders (2 teachers and 2 students) across four case study sites. Sites and individuals were purposively selected. Sites included two local authorities, one secondary school, and one sports organisation. Thematic data analysis was adopted to analyse the qualitative data. Results Four themes were identified: (1) building and maintaining relationships, (2) working with stakeholders, (3) informing practice, and (4) critical reflection. Conclusions Embedded researchers build and maintain relationships with practitioners and other stakeholders to produce research. Evidence from the co-produced research informs future practice and research to improve service and delivery rendered to the public. Thus, embedded researchers use their role to bridge the research evidence - implementation gap in public health practice.

Background and hypothesisChildren exposed to socioenvironmental adversities (eg, urbanicity, pollution, neighborhood deprivation, crime, and family disadvantage) are more likely to subsequently develop subclinical psychotic experiences during adolescence (eg, hearing voices, paranoia). However, the pathways through which this occurs have not been previously investigated. We hypothesized that cognitive ability and inflammation would partly explain this association.Study designData were utilized from the Environmental-Risk Longitudinal Twin Study, a cohort of 2232 children born in 1994-1995 in England and Wales and followed to age 18. Socioenvironmental adversities were measured from birth to age 10 and classified into physical risk (defined by high urbanicity and air pollution) and socioeconomic risk (defined by high neighborhood deprivation, neighborhood disorder, and family disadvantage). Cognitive abilities (overall, crystallized, fluid, and working memory) were assessed at age 12; and inflammatory markers (C-reactive protein, interleukin-6, soluble urokinase plasminogen activator receptor) were measured at age 18 from blood samples. Participants were interviewed at age 18 regarding psychotic experiences.Study resultsHigher physical risk and socioeconomic risk were associated with increased odds of psychotic experiences in adolescence. The largest mediation pathways were from socioeconomic risk via overall cognitive ability and crystallized ability, which accounted for ~11% and ~19% of the association with psychotic experiences, respectively. No statistically significant pathways were found via inflammatory markers in exploratory (partially cross-sectional) analyses.ConclusionsCognitive ability, especially crystallized ability, may partly explain the association between childhood socioenvironmental adversity and adolescent psychotic experiences. Interventions to support cognitive development among children living in disadvantaged settings could buffer them against developing subclinical psychotic phenomena.

Introduction Globally, 55 million individuals have dementia, with an increasing annual incident of 10 million. Enabling the development of new multi-modal models can improve the current diagnostic pathways and potentially contribute to early diagnosis and treatment of dementia. Here, we report how multi-modal resources is achieved within the successful Trusted Research Environment (TRE). Objectives We aimed to identify the challenges of the storage, distribution and analysis of neuroimaging data and how we could implement a comprehensive infrastructure to deal with these. The problems we specifically aimed to address were how to: anonymise scans, store large amounts of data, standardise datasets to a common format, extract metadata, provision the data, and allow for analysis. Methods We document various stages and capacities required for multi-modal neuroimaging analysis for dementia and conclude that achieving research ready assets to enable neuroimaging analysis for dementia from existing resources requires an engineered process to facilitate multiple aspects of curation, provisioning and large-scale analysis. Results We developed an ingest pipeline for neuroimaging data to meet the requirements set out in the objectives. This involved standardising all datasets to the Brain Imaging Data Structure, defacing scans and anonymising data, using MinIO for data storage and extracting metadata from header information for data discovery and provisioning. Conclusion The neuroimaging ingest pipeline developed has allowed for the distribution of imaging datasets within DPUK which has facilitated multi-modal research on anonymised and standardised data and enabled linkage with phenotypic and genomic data.

Purpose: Young people with developmental language disorder (DLD) have poorer mental health than those without DLD. However, not all young people with DLD are equally affected; some have more mental health difficulties than others. What explains these differences remains unclear. Method: Data from a community cohort study, the Avon Longitudinal Study of Parents and Children, were analyzed to investigate genetic and environmental influences on the development of mental health difficulties at five time points from childhood (7 years) to adolescence (16 years) in 6,387 young people (8.7% with DLD). Regression and latent class models were fitted to the data. Results: Polygenic scores (PGSs), indices of genetic risk, for common psychiatric disorders (major depressive disorder, anxiety disorder, and attention deficit hyperactivity disorder) predicted mental health difficulties in both groups (with and without DLD). The presence of DLD, in some instances, amplified mental health difficulties for those with high genetic risk for common psychiatric disorders. Subgroups of children with similar developmental trajectories of mental health difficulties were identified. Young people with DLD were more likely than those without DLD to follow mental health subgroups characterized by consistently high levels of difficulties during development. PGSs, socioeconomic status, and the early home environment distinguished subgroups with low mental health difficulties from those characterized by high levels of difficulties, but these effects did not differ based on DLD status. Conclusions: These findings suggest that, for the most part, both genetic and environmental risk affect the development of mental health difficulties in a cumulative way for young people with DLD (and those without). Some analysis did, however, suggest that genetic risk for common psychiatric disorders might manifest more strongly in those with DLD compared with those without DLD.

Background Intracranial hemorrhage is a critical finding on computed tomography (CT) of the head. This study compared the accuracy of an artificial intelligence (AI) model (Annalise Enterprise CTB Triage Trauma) to consensus neuroradiologist interpretations in detecting 4 hemorrhage subtypes: acute subdural/epidural hematoma, acute subarachnoid hemorrhage, intra‐axial hemorrhage, and intraventricular hemorrhage. Methods A retrospective stand‐alone performance assessment was conducted on data sets of cases of noncontrast CT of the head acquired between 2016 and 2022 at 5 hospitals in the United States for each hemorrhage subtype. The cases were obtained from patients aged ≥18 years. The positive cases were selected on the basis of the original clinical reports using natural language processing and manual confirmation. The negative cases were selected by taking the next negative case acquired from the same CT scanner after positive cases. Each case was interpreted independently by up to 3 neuroradiologists to establish consensus interpretations. Each case was then interpreted by the AI model for the presence of the relevant hemorrhage subtype. The neuroradiologists were provided with the entire CT study. The AI model separately received thin (≤1.5 mm) and thick (>1.5 and ≤5 mm) axial series as available. Results The 4 cohorts included 571 cases of acute subdural/epidural hematoma, 310 cases of acute subarachnoid hemorrhage, 926 cases of intra‐axial hemorrhage, and 199 cases of intraventricular hemorrhage. The AI model identified acute subdural/epidural hematoma with area under the curve of 0.973 (95% CI, 0.958–0.984) on thin series and 0.942 (95% CI, 0.921–0.959) on thick series; acute subarachnoid hemorrhage with area under the curve 0.993 (95% CI, 0.984–0.998) on thin series and 0.966 (95% CI, 0.945–0.983) on thick series; intraaxial hemorrhage with area under the curve of 0.969 (95% CI, 0.956–0.980) on thin series and 0.966 (95% CI, 0.953–0.976) on thick series; and intraventricular hemorrhage with area under the curve of 0.987 (95% CI, 0.969–0.997) on thin series and 0.983 (95% CI, 0.968–0.994) on thick series. Each finding had at least 1 operating point with sensitivity and specificity >80%. Conclusion The assessed AI model accurately identified intracranial hemorrhage subtypes in this CT data set. Its use could assist the clinical workflow, especially through enabling triage of abnormal CTs.

Abstract As mobile genetic elements, plasmids are central for our understanding of antimicrobial resistance spread in microbial communities. Plasmids can have varying fitness effects on their host bacteria, which will markedly impact their role as antimicrobial resistance vectors. Using a plasmid population model, we first show that beneficial plasmids interact with a higher number of hosts than costly plasmids when embedded in a community with multiple hosts and plasmids. We then analyse the network of a natural host-plasmid wastewater community from a Hi-C metagenomics dataset. As predicted by the model, we find that antimicrobial resistance encoding plasmids, which are likely to have positive fitness effects on their hosts in wastewater, interact with more bacterial taxa than non-antimicrobial resistance plasmids and are disproportionally important for connecting the entire network compared to non- antimicrobial resistance plasmids. This highlights the role of antimicrobials in restructuring host-plasmid networks by increasing the benefits of antimicrobial resistance carrying plasmids, which can have consequences for the spread of antimicrobial resistance genes through microbial networks. Furthermore, that antimicrobial resistance encoding plasmids are associated with a broader range of hosts implies that they will be more robust to turnover of bacterial strains.

Determination of trace gas emissions from sources is critical for understanding and regulating air quality and climate change. Here, we demonstrate a method for rapid quantification of the emission rate of multiple gases from simple and complex sources using a mass balance approach with a spatially scannable open-path sensor – in this case, an open-path dual-comb spectrometer. The open-path spectrometer measures the total column density of gases between the spectrometer and a retroreflector mounted on an uncrewed aerial vehicle (UAV). By measuring slant columns at multiple UAV altitudes downwind of a source (or sink), the total emission rate can be rapidly determined without the need for an atmospheric dispersion model. Here, we demonstrate this technique using controlled releases of CH4 and C2H2. We show an emission rate determination to within 56 % of the known flux with a single 10 min flight and within 15 % of the known flux after 12 flights. Furthermore, we estimate the detection limit for CH4 emissions to be 0.03 g CH4 s−1. This detection limit is approximately the same as the emissions from 25 head of beef cattle and is less than the average emissions from a small oil field pneumatic controller. Other gases including CO2, NH3, HDO, ethane, formaldehyde (HCHO), CO, and N2O can be measured by simply changing the dual-comb spectrometer.

Inconsistent swimming performances are often observed following sodium bicarbonate (NaHCO3) ingestion, possibly because the time taken to reach peak blood buffering capacity is highly variable between individuals. Personalising NaHCO3 ingestion based on time-to-peak blood bicarbonate (HCO3−) could be a solution; however, this strategy is yet to be explored in swimming, or adequately compared to standardised NaHCO3 approaches. Therefore, six highly trained female swimmers ingested 0.3 g·kg BM−1 NaHCO3 in capsules to pre-determine their individual time-to-peak blood HCO3−. They then participated in three experimental trials, consisting of a 6 × 75 m repeated sprint swimming test, followed by a 200 m maximal time trial effort after 30 min active recovery. These experiments were conducted consuming a supplement at three different timings: individualised NaHCO3 (IND: 105–195 min pre-exercise); standardised NaHCO3 (STND: 150 min pre-exercise); and placebo (PLA: 90 min pre-exercise). Both NaHCO3 strategies produced similar increases in blood HCO3− prior to exercise (IND: +6.8 vs. STND: +6.1 mmol·L−1, p < 0.05 vs. PLA) and fully recovered blood HCO3− during active recovery (IND: +6.0 vs. STND: +6.3 mmol·L−1 vs. PLA, p < 0.05). However, there were no improvements in the mean 75 m swimming time (IND: 48.2 ± 4.8 vs. STND: 48.9 ± 5.8 vs. PLA: 49.1 ± 5.1 s, p = 0.302) nor 200 m maximal swimming (IND: 133.6 ± 5.0 vs. STND: 133.6 ± 4.7 vs. PLA: 133.3 ± 4.4 s, p = 0.746). Regardless of the ingestion strategy, NaHCO3 does not appear to improve exercise performance in highly trained female swimmers.

BackgroundAssociations of socioenvironmental features like urbanicity and neighborhood deprivation with psychosis are well-established. An enduring question, however, is whether these associations are causal. Genetic confounding could occur due to downward mobility of individuals at high genetic risk for psychiatric problems into disadvantaged environments.MethodsWe examined correlations of five indices of genetic risk [polygenic risk scores (PRS) for schizophrenia and depression, maternal psychotic symptoms, family psychiatric history, and zygosity-based latent genetic risk] with multiple area-, neighborhood-, and family-level risks during upbringing. Data were from the Environmental Risk (E-Risk) Longitudinal Twin Study, a nationally-representative cohort of 2232 British twins born in 1994-1995 and followed to age 18 (93% retention). Socioenvironmental risks included urbanicity, air pollution, neighborhood deprivation, neighborhood crime, neighborhood disorder, social cohesion, residential mobility, family poverty, and a cumulative environmental risk scale. At age 18, participants were privately interviewed about psychotic experiences.ResultsHigher genetic risk on all indices was associated with riskier environments during upbringing. For example, participants with higher schizophrenia PRS (OR = 1.19, 95% CI = 1.06-1.33), depression PRS (OR = 1.20, 95% CI = 1.08-1.34), family history (OR = 1.25, 95% CI = 1.11-1.40), and latent genetic risk (OR = 1.21, 95% CI = 1.07-1.38) had accumulated more socioenvironmental risks for schizophrenia by age 18. However, associations between socioenvironmental risks and psychotic experiences mostly remained significant after covariate adjustment for genetic risk.ConclusionGenetic risk is correlated with socioenvironmental risk for schizophrenia during upbringing, but the associations between socioenvironmental risk and adolescent psychotic experiences appear, at present, to exist above and beyond this gene-environment correlation.

Handedness has been studied for association with language-related disorders because of its link with language hemispheric dominance. No clear pattern has emerged, possibly because of small samples, publication bias, and heterogeneous criteria across studies. Non-right-handedness (NRH) frequency was assessed in N = 2503 cases with reading and/or language impairment and N = 4316 sex-matched controls identified from 10 distinct cohorts (age range 6-19 years old; European ethnicity) using a priori set criteria. A meta-analysis (N[subscript cases] = 1994) showed elevated NRH % in individuals with language/reading impairment compared with controls (OR = 1.21, CI = 1.06-1.39, p = 0.01). The association between reading/language impairments and NRH could result from shared pathways underlying brain lateralization, handedness, and cognitive functions.

Objective: To report how improvements on a Brazilian language intervention for early childhood education settings (PROLIN) were made and evaluated. Study Design: In the first phase, the programme layout and materials were improved. This involved redesigning the guidelines for the programme, adding videos (using a learning management system) and creating an observation checklist to monitor the fidelity of implementation. The second phase was a two-week pilot study (a seven-session intervention) involving two teachers and 22 students. Checklists and video footage were analysed to investigate implementation. Results: Quality of implementation was generally good, but we identified additional areas for improvement. Teachers had some difficulties with aspects related to session dynamics, implementation of activities and use of techniques that reinforce learning. Conclusions: The pilot study was instrumental in identifying obstacles for a scaled-up, high-quality implementation. The design of these materials took into consideration ways of guiding and supporting teachers to: (1) offer students adequate participation time; (2) help include children who are shy or have behaviour problems; (3) use teaching strategies properly; (4) bring sessions to a close; and (5) reach the objectives of each session. Further modification is still needed, especially in the manual, videos and supplementary materials.

Background: Previous studies have explored the size and word type composition (nouns, predicates, etc.) of expressive vocabularies of preschool children with Down syndrome, both spoken and signed. Separately, overall preferences for modality of expression have also been explored. Aims: To extend previous findings by describing the relationships between expressive vocabulary size and both word type and modality of expression in the preschool period including changes to modality preference over time. Methods & Procedures: Mothers of 35 children with Down syndrome, aged 36-66 months and attending the same early intervention programme, completed a version -- with both spoken word and sign options -- of the New Zealand MacArthur-Bates Communicative Development Inventory (CDI): Words and Sentences. Most mothers completed the CDI on multiple occasions across the duration of the study. Completions (n = 114) were analysed cross-sectionally and longitudinally in terms of (1) word type relative to vocabulary size, (2) modality of expression relative to word type and vocabulary size, and (3) individual trajectories in vocabulary size and modality of expression. Outcomes & Results: (1) Word type relative to vocabulary size was similar to previous studies with a greater proportion of the SOCIAL words being present in the children's vocabularies throughout, followed by NOUNS, PREDICATES and CLOSED class words, with proportions converging as vocabulary sizes increase. (2) An initial spoken word preference for SOCIAL and CLOSED class words and sign preference for NOUNS and PREDICATES was found, with more spoken words in larger vocabularies overall. (3) Individual trajectories were highly variable and also revealed temporary points of regression in overall expressive vocabulary size in some children. Children who shifted from reliance on sign to predominantly spoken word expression did so at different ages and at different vocabulary sizes. At school entry, while most of the children used both modalities, some children continued to rely on sign for most vocabulary items whereas others used only spoken words. Conclusions & Implications: An appreciation of both the general trends and potential for individual variation in vocabulary structure, modality of expression and change over time will better position clinicians and education specialists to provide individually tailored support to both preschool and school-aged children with Down syndrome.

Research in the UK suggests that multi-componential interventions focusing on language and pre-literacy skills can improve children's reading and language skills. However, simple translations of such programmes may not produce equivalent effects in diverse communities. The reasons for this are multi-faceted and include factors beyond the rationale and content of the intervention programmes themselves. Understanding these factors is critical for creating programmes that will generalise across settings. In this review, we reflect upon challenges encountered in two reading and language intervention programmes in South America to identify community and cultural contextual factors that can influence the implementation and scalability of educational programmes. We use our findings to develop an education-specific framework to guide the development and implementation of high-quality evidence-based approaches to language and literacy intervention. Our model guides implementation practices in diverse contexts and stresses the importance of the evidence-base and communication.

Background: Increasing evidence suggests that air pollution exposure contributes to the development of mental health problems, including psychosis and depression. However, little is known about the importance of early-life exposure, nor the potential role of noise pollution, a correlate of air pollution. We examined the association of exposure to air and noise pollution from pregnancy to age 12 years with three mental health problems assessed at ages 12, 18, and 24 years. Methods: Data were from the Avon Longitudinal Study of Parents and Children (ALSPAC), which tracks the development of about 14 000 babies who had expected delivery dates between April 1, 1991, and Dec 31, 1992, in Avon, UK. This was linked with novel data on nitrogen dioxide, PM2·5, and noise pollution in pregnancy, childhood (ages 1–9 years), and adolescence (ages 10–12 years). Psychotic experiences, depression, and anxiety were measured at ages 12, 18, and 24 years. Logistic regression models were controlled for individual-level, family-level, and area-level confounders, and e-values were calculated to estimate residual confounding. Findings: Participants exposed to higher PM2.5, particularly during pregnancy, had greater odds for psychotic experiences (adjusted odds ratio 1·17 [95% CI 1·05–1·30]) and depression (1·11 [1·01–1·22]). There was little evidence associating nitrogen dioxide or noise pollution with psychotic experiences or depression. Conversely, higher nitrogen dioxide (but not PM2·5) exposure in pregnancy (1·16 [1·01–1·33]), and higher noise pollution in childhood (1·20 [1·06-1·37]) and adolescence (1·17 [1·02-1·35]), were associated with greater odds for anxiety. Interpretation: Our study builds on evidence linking air pollution to psychosis and depression and provides rare longitudinal evidence linking noise pollution to anxiety. Our findings indicate that air pollution exposure earlier in development (eg, during pregnancy) might be particularly important, and suggest a degree of specificity in terms of pollutant-outcome associations. If causal, our findings suggest that interventions to reduce air pollution would improve global mental health. Funding: Wellcome Trust, UK Medical Research Council–Wellcome, and University of Bristol.

The control of gene expression is a fundamental process essential for correct development and to maintain homeostasis. Many post-transcriptional mechanisms exist to maintain the correct levels of each RNA transcript within the cell. Controlled and targeted cytoplasmic RNA degradation is one such mechanism with the 5′-3′ exoribonuclease Pacman (XRN1) and the 3′-5′ exoribonuclease Dis3L2 playing crucial roles. Loss of function mutations in either Pacman or Dis3L2 have been demonstrated to result in distinct phenotypes, and both have been implicated in human disease. One mechanism by which gene expression is controlled is through the function of miRNAs which have been shown to be crucial for the control of almost all cellular processes. Although the biogenesis and mechanisms of action of miRNAs have been comprehensively studied, the mechanisms regulating their own turnover are not well understood. Here we characterise the miRNA landscape in a natural developing tissue, the Drosophila melanogaster wing imaginal disc, and assess the importance of Pacman and Dis3L2 on the abundance of miRNAs. We reveal a complex landscape of miRNA expression and show that whilst a null mutation in dis3L2 has a minimal effect on the miRNA expression profile, loss of Pacman has a profound effect with a third of all detected miRNAs demonstrating Pacman sensitivity. We also reveal a role for Pacman in regulating the highly conserved let-7 cluster (containing miR-100, let-7 and miR-125) and present a genetic model outlining a positive feedback loop regulated by Pacman which enhances our understanding of the apoptotic phenotype observed in Pacman mutants.

Abstract Background The ticks Ixodes ricinus and Dermacentor reticulatus are two of the most important vectors in Europe. Climate niche modelling has been used in many studies to attempt to explain their distribution and to predict changes under a range of climate change scenarios. The aim of this study was to assess the ability of different climate niche modelling approaches to explain the known distribution of I. ricinus and D. reticulatus in Europe. Methods A series of climate niche models, using different combinations of input data, were constructed and assessed. Species occurrence records obtained from systematic literature searches and Global Biodiversity Information Facility data were thinned to different degrees to remove sampling spatial bias. Four sources of climate data were used: bioclimatic variables, WorldClim, TerraClimate and MODIS satellite-derived data. Eight different model training extents were examined and three modelling frameworks were used: maximum entropy, generalised additive models and random forest models. The results were validated through internal cross-validation, comparison with an external independent dataset and expert opinion. Results The performance metrics and predictive ability of the different modelling approaches varied significantly within and between each species. Different combinations were better able to define the distribution of each of the two species. However, no single approach was considered fully able to capture the known distribution of the species. When considering the mean of the performance metrics of internal and external validation, 24 models for I. ricinus and 11 models for D. reticulatus of the 96 constructed were considered adequate according to the following criteria: area under the receiver-operating characteristic curve > 0.7; true skill statistic > 0.4; Miller’s calibration slope 0.25 above or below 1; Boyce index > 0.9; omission rate