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BackgroundAcute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are important causes of morbidity and mortality in critically ill patients. Gastric contents aspiration is one of the most common causes of ALI/ARDS. To date, there are still no specific and effective pharmacological treatments for ALI/ARDS. Polyvinylalcohol-carbazate (PVAC), a polymer that can bind endogenous aldehydes, neutralize oxidative stress and inhibit inflammatory factors, may be a potential treatment for ALI/ARDS.MethodsA hydrochloric acid (HCl) induced mouse model was employed to assess the effect of PVAC. The changes of lung mechanics, pulmonary edema, histology and immune cells, cytokines, and lipid mediators in bronchioalveolar lavage fluid (BALF) were investigated in HCl-challenged mice.ResultsIn the HCl model, PVAC administration alleviated airway hyperresponsiveness and improved pulmonary edema and damage. In addition, it decreased the recruitment of neutrophils to the lung, and inhibited the increase of IL-6, TNF-α and leukotriene B4.ConclusionThese data indicates that PVAC is a potential candidate for the treatment of ALI/ARDS induced by aspiration of gastric acid or for the control of “asthma-like” symptoms in patients with gastroesophageal reflux.

Objectives To understand how we can better initiate and run international collaborations to deliver tangible and impactful findings using population-wide linked health and education data. Approach Representatives from 14 countries (America, Australia, Canada, Chile, Denmark, England, Finland, Germany, New Zealand, Northern Ireland, Norway, Scotland, Sweden, Wales) summarised the potential for research using their linked administrative health and education data. The scope for collaboration and comparison of research findings across countries was explored. Results Several substantive research themes emerged, including the quantifying of differences in educational outcomes by health conditions and other early life factors, using health data to better identify and explore the special educational needs identified in educational records, using linked health and education data to identify and explore reasons for absenteeism from school. Conclusions The workshop showcased the primary themes for research and the data assets available within each country for comparative work. Further work is required to more robustly document the available detail within these datasets, collaboratively develop protocol templates for comparative studies, and develop pilot, proof of concept, studies.

Introduction First steps for knee osteoarthritis (OA) is a cluster randomised implementation trial examining the effect of an educational reminder message included in knee X-ray reports on the proportion of people subsequently referred to exercise professionals for their knee OA. Evaluating the processes supporting the completion of the study and the efficacy of the reminder message is essential to interpreting the outcomes of the study and aiding translation into practice.Methods and analysis We will conduct a concurrent process evaluation throughout the current study using a previously published framework for examining cluster randomised trials. This framework divides processes into those occurring at the cluster level and those at the target population level. For the current study, the cluster level is within radiology clinics. The target population is people with newly diagnosed radiologically evident, structural knee OA. A mixed methods design, incorporating survey data, administrative records, field notes and semi-structured interviews with representatives from radiology clinics and people with knee OA, will evaluate these processes. The focus of the evaluation will be recruitment and response processes of the radiology clinics and delivery and response processes for the people with knee OA. We will also describe the context and explore how the nudge theory of behavioural change influences the outcome of the study.Ethics and dissemination The study protocol, inclusive of the process evaluation, was approved by Macquarie University Human Research Ethics Committee (#520221190343842). Findings will be disseminated through national and international conferences, national industry stakeholders and patient advocacy groups to reach all levels of healthcare. Staff at radiology clinics and people with knee OA involved in interviews provide written, informed consent to participate in the process evaluation. Specific findings will be incorporated into training modules aimed at radiology clinics and will be developed by our industry partners.Trial registration Prospectively registered with the Australian New Zealand Clinical Trials Registry (ACTRN12622001414707p). Registration occurred in December 2022

Purpose: Understanding relationships between blood flow and muscle inflexibility in the lower leg can support improved healthcare competency. Sports medicine practitioners might use the reference ranges and knowledge of relationships among these variables to support effective health screenings among their competitive runners. These variables have been linked in other areas of the body where inflexibility in the pectoralis minor and scalene muscles have been associated with diminished blood flow to the upper limb. No studies, however, have examined the relationship between vascular and mobility characteristics in the lower legs of runners. Therefore, the purpose of this study was to examine the relationship between blood flow in the posterior tibial artery and ankle range of motion (ROM) among competitive runners. Methods: Blood flow in the posterior tibial artery and ankle ROM were measured bilaterally on twenty-five, asymptomatic collegiate track athletes (15 males, 10 females, age = 20.0±1.2 years, height = 171.5±10.2 cm, mass = 66.7±13.7 kg) using diagnostic ultrasound and standard goniometry, respectively. Pearson correlation analysis was used to analyze the relationship between blood flow in the posterior tibial artery and ROM of the ankle joint. Results: Findings revealed no significant relationship between blood flow in the dominant leg’s posterior tibial artery and dorsiflexion (r=.14, P=.52, CI95% = -0.27 – 0.51) or plantarflexion (r=-.32, P=.12, CI95% = -0.63 – 0.09) and no significant relationship between blood flow in the non-dominant leg’s posterior tibial artery and dorsiflexion (r=-.02, P=.93; CI95% = -0.41 – 0.38) or plantarflexion (r=-.02, P=.92; CI95% = -0.41 – 0.38). Conclusion: While muscle inflexibility is associated with compromised blood flow in other body regions, findings of this study demonstrated no relationship between the variables within the lower legs of a sample of competitive runners. Sports medicine practitioners should consider these findings in their efforts to predict, prevent, and manage potential vascular and musculoskeletal adaptations among clients/patients who are competitive runners.

Alcohol dependence (AD) and gambling disorder (GD) are common addiction disorders with significant physical and mental health consequences. AD and GD are associated with dysregulated responses to reward which could be due to a common mechanism of dysregulated endogenous opioid signalling. We explored associations between reward anticipation responses, using the Monetary Incentive Delay (MID) functional magnetic resonance imaging (fMRI) task, and mu-opioid receptor (MOR) availability and endogenous opioid release capacity using [11C]carfentanil positron emission tomography (PET), in 13 AD, 15 GD and 14 heathy control (HC) participants. We also examined differences in MID task reward anticipation responses between AD, GD and HC participants. These were secondary exploratory analysis of data collected to examine differences in MOR PET in addiction. We did not find significant differences in MID win > neutral anticipation BOLD responses compared between participant groups in a priori ROIs (ventral striatum, putamen, caudate) or whole brain analyses. We found no significant correlations between MID win > neutral anticipation BOLD responses and [11C]carfentanil PET measures, except for limited negative correlations between putamen MOR availability and MID win > neutral anticipation BOLD response in AD participants. Previous research has suggested a limited role of endogenous opioid signalling on MID task reward anticipation responses in AD and HCs as these responses are not modulated by opioid receptor blockade and this may explain our lack of significant correlations in HC and AD or GD participants. Our results, particularly the lack of differences in MID win > neutral anticipation BOLD responses across participants groups, may be limited due to only including AD or GD participants who are abstinent or in active treatment.

Background Living with a family member who has a long-term health condition (HC) is associated with poorer health and well-being outcomes, but the number and socio-demographics of people and families impacted by a family member who has an HC is unknown. Methods Using the Integrated Data Infrastructure (IDI), a collection of linked administrative datasets for the full New Zealand (NZ) population, we identified n= 1,043,172 families using 2013 NZ Census data, and used health data over the previous 5-years to ascertain whether people in these families (n=3,137,517) had cancer, chronic obstructive pulmonary disease, coronary health disease, diabetes, dementia, gout, stroke, traumatic brain injury (TBI) or a mental health/behavioural condition (MHBC). Results Over 60% of families included at least one person with a HC. The most common HCs were MHBCs (39.4% of families), diabetes (16.0%), and TBI (13.9%). A high proportion of multi-generation families (73.9%) included a member with a HC. Two-thirds (67.7%) of Pacific Peoples either had a HC themselves or were living with a family member who had a HC, compared with 62.3% of Europeans and 62.5% of Māori (the indigenous peoples of NZ). At the highest level of socioeconomic deprivation, 57.6% of children lived with a family member who had a HC. Conclusions Three in five NZ families were living with a HC, with differences in the proportion affected according to family composition, socio-economic status and an individuals’ ethnicity. This suggests that there are a substantial number of people at risk of the associated poor outcomes.

Meta-analysis of whole genome sequencing/whole exome sequencing (WGS/WES) studies provides an attractive solution to the problem of collecting large sample sizes for discovering rare variants associated with complex phenotypes. Existing rare variant meta-analysis approaches are not scalable to biobank-scale WGS data. Here we present MetaSTAAR, a powerful and resource-efficient rare variant meta-analysis framework for large-scale WGS/WES studies. MetaSTAAR accounts for relatedness and population structure, can analyze both quantitative and dichotomous traits and boosts the power of rare variant tests by incorporating multiple variant functional annotations. Through meta-analysis of four lipid traits in 30,138 ancestrally diverse samples from 14 studies of the Trans Omics for Precision Medicine (TOPMed) Program, we show that MetaSTAAR performs rare variant meta-analysis at scale and produces results comparable to using pooled data. Additionally, we identified several conditionally significant rare variant associations with lipid traits. We further demonstrate that MetaSTAAR is scalable to biobank-scale cohorts through meta-analysis of TOPMed WGS data and UK Biobank WES data of ~200,000 samples.

IntroductionAfrican Americans are at increased risk for type 2 diabetes.ObjectivesThis work aimed to examine metabolomic signature of glucose homeostasis in African Americans.MethodsWe used an untargeted liquid chromatography-mass spectrometry metabolomic approach to comprehensively profile 727 plasma metabolites among 571 African Americans from the Insulin Resistance Atherosclerosis Family Study (IRAS-FS) and investigate the associations between these metabolites and both the dynamic (SI, insulin sensitivity; AIR, acute insulin response; DI, disposition index; and SG, glucose effectiveness) and basal (HOMA-IR and HOMA-B) measures of glucose homeostasis using univariate and regularized regression models. We also compared the results with our previous findings in the IRAS-FS Mexican Americans.ResultsWe confirmed increased plasma metabolite levels of branched-chain amino acids and their metabolic derivatives, 2-aminoadipate, 2-hydroxybutyrate, glutamate, arginine and its metabolic derivatives, carbohydrate metabolites, and medium- and long-chain fatty acids were associated with insulin resistance, while increased plasma metabolite levels in the glycine, serine and threonine metabolic pathway were associated with insulin sensitivity. We also observed a differential ancestral effect of glutamate on glucose homeostasis with significantly stronger effects observed in African Americans than those previously observed in Mexican Americans.ConclusionWe extended the observations that metabolites are useful biomarkers in the identification of prediabetes in individuals at risk of type 2 diabetes in African Americans. We revealed, for the first time, differential ancestral effect of certain metabolites (i.e., glutamate) on glucose homeostasis traits. Our study highlights the need for additional comprehensive metabolomic studies in well-characterized multiethnic cohorts.

Liquid organic hydrogen carriers will likely be a key element of a future hydrogen economy by enabling the storage and transport of large quantities of hydrogen. Ethanol is a liquid organic hydrogen carrier that is readily available from biological resources, which undergoes a reversible reaction to yield hydrogen and ethyl acetate. The objective of the present study is to obtain a better understanding of the thermodynamic and environmental suitability of the ethanol–ethyl acetate cycle for hydrogen storage applications. The analysis covers three aspects: thermodynamics of the chemical reaction, energy balance of the process, and a first-order assessment of greenhouse gas emissions. Thermodynamics of the reaction are characterized by a standard Gibbs energy of reaction close to zero which allows the reaction to be shifted between hydrogenation and dehydrogenation within a moderate window of temperature and pressure conditions. The energy demand for dehydrogenation is comparatively small, resulting in an overall system efficiency of 88%. A life cycle greenhouse gas analysis over a 20-year storage system lifetime gives a carbon intensity of 7.0 kg-CO2eq/kg-H2 delivered. These results indicate that the ethanol–ethyl acetate system has considerable promise as a hydrogen carrier and should be the subject of further research.

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1-4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.

Flexible high-deflection strain gauges have been demonstrated to be cost-effective and accessible sensors for capturing human biomechanical deformations. However, the interpretation of these sensors is notably more complex compared to conventional strain gauges, particularly during dynamic motion. In addition to the non-linear viscoelastic behavior of the strain gauge material itself, the dynamic response of the sensors is even more difficult to capture due to spikes in the resistance during strain path changes. Hence, models for extracting strain from resistance measurements of the gauges most often only work well under quasi-static conditions. The present work develops a novel model that captures the complete dynamic strain–resistance relationship of the sensors, including resistance spikes, during cyclical movements. The forward model, which converts strain to resistance, comprises the following four parts to accurately capture the different aspects of the sensor response: a quasi-static linear model, a spike magnitude model, a long-term creep decay model, and a short-term decay model. The resulting sensor-specific model accurately predicted the resistance output, with an R-squared value of 0.90. Additionally, an inverse model which predicts the strain vs. time data that would result in the observed resistance data was created. The inverse model was calibrated for a particular sensor from a small amount of cyclic data during a single test. The inverse model accurately predicted key strain characteristics with a percent error as low as 0.5%. Together, the models provide new functionality for interpreting high-deflection strain sensors during dynamic strain measurement applications, including wearables sensors used for biomechanical modeling and analysis.

Common genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this 'missing heritability'. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability ([Formula: see text]) was estimated from 0.13 to 0.28 (s.e., 0.10-0.13) in European ancestries, with 35-74% of it attributable to rare variants with minor allele frequencies between 0.01% and 1%. These heritability estimates are 1.5-4 times higher than past estimates based on common variants alone and accounted for 60% to 100% of our pedigree-based estimates of narrow-sense heritability ([Formula: see text], 0.18-0.34). In the African ancestry samples, [Formula: see text] was estimated from 0.03 to 0.33 (s.e., 0.09-0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking.

This mixed-methods study describes a framework for conducting cost analyses of school-based programs leveraging fidelity data and applying the ingredients method. We illustrate this approach by applying it to Positive Behavioral Interventions and Supports (PBIS), drawing on multiple sources of data from a sample of U.S. 77 schools that were trained in PBIS. We concluded that the average per school cost of PBIS was US$53,216.00 (median = US$36,698), with an average per-pupil cost of US$90.00 (median = US$58.00), which is considerably less than other school-based prevention models. The cost did, however, differ by implementation level, such that high-fidelity implementation tended to cost more than low-fidelity implementation. We provide a case illustration to elucidate some of the cost drivers of PBIS implementation. Specifically, these data highlight the variability in the amount of training and coaching by the specific evidence-based program implemented within the tiered PBIS framework. Through this case illustration, we demonstrate the utility of tracking costs of school-based program within the context of fidelity data collection. The findings also suggest the potential cost savings of PBIS, both when compared with other evidence-based interventions as well as the known costs of negative school outcomes like dropout.

This exploratory study evaluated the impact of a Spanish second language (L2) domestic immersion (DI) program that was developed expediently at a large university in the United States in response to widespread study abroad (SA) program closures due to COVID-19. Spanish language learners (n = 14) participated in an intensive, six-week summer immersion program for a total of 96 contact hours over the duration of the program. L2 development was evaluated via a conceptual replication of Issa et al. (2020), which recently provided compelling evidence of the benefits of short-term SA programs. L2 gains were measured using an acceptability judgment task, a lexical decision task, and an elicited imitation task. Results showed that DI learners had significant L2 gains in some of the same areas as the SA students, including subject-verb agreement and scores on the elicited imitation task. Implications for creating and maintaining DI programs in the current educational landscape are discussed.